ChatGPT answers, unedited

Yes. For non-English SEO, the key is to research in the target language and market, rather than translating English keyword lists. Long-tail queries are especially valuable because local phrasing, slang, spelling variants, and question patterns can differ substantially.

Best methods

1. Start with native-language seed terms

Build a small list of 10–30 concepts in the language your customers actually use.

Don't just translate an English seed literally. For example, if your topic is “running shoes,” collect:

• The formal/local term
• Colloquial terms
• Regional variants
• Singular/plural variations
• Common misspellings
• Product/problem terminology
• Words people use when asking questions

Then feed those seeds into keyword tools.

2. Use a multilingual keyword database

Two particularly useful options are:

• Ahrefs Keywords Explorer — supports hundreds of country/language combinations. Its current documentation lists markets ranging from Spanish, French and German to Arabic, Japanese, Korean, Vietnamese, Thai, Turkish and many others. Data depth varies by market, so smaller languages deserve extra validation. Ahrefs Help Center Ahrefs
• Semrush Keyword Magic Tool — supports language/market filtering, related terms, questions, intent, difficulty, SERP features and word-count filtering. Semrush Semrush

For long-tail discovery specifically, look for Questions, Related, Phrase Match, and semantically related terms rather than just high-volume head keywords.

3. Mine Google autocomplete and related searches

This is one of the best ways to discover how people naturally phrase things.

Search your seed in the target language and collect:

• Autocomplete suggestions
• “People also ask” questions
• Related searches at the bottom of the SERP
• Suggested searches after modifying the query
• Search variations with how/why/what/which/where/when equivalents in that language

This can reveal long-tail queries that aren't obvious from English-language keyword databases.

4. Use Google Trends for local language behavior

trends.google.com is particularly useful for multilingual SEO because you can change the country/region and compare terms in different languages. Google also distinguishes between individual search terms and broader Topics, where a topic can encompass equivalent concepts across languages. Google Help Google Help

For example, don't assume that the most literal translation of an English keyword is what people search. Compare several native expressions in the target country and look at:

• Relative popularity
• Seasonality
• Regional differences
• Rising queries
• Related searches

5. Mine your own Google Search Console data

If the site already has traffic, this is arguably your most valuable source because the queries are actual searches that already produced impressions for your site.

Export the queries and look for:

• 4–8+ word queries
• Question structures
• Queries where you're ranking positions ~5–20
• Queries with impressions but few clicks
• Variations you haven't explicitly targeted
• Different terminology for the same topic

For question discovery, you can filter queries using the question words appropriate to the language. Ahrefs also recommends this approach for uncovering longer, conversational queries in Search Console. Ahrefs

6. Research competitors in the target market

Put 5–10 genuinely local competitors into Ahrefs/Semrush and export the keywords they're ranking for.

This is important: a competitor in the US, UK or another English-speaking market isn't necessarily a useful competitor for a Spanish-, German-, Japanese-, etc. site.

Look specifically for:

• Keywords where several competitors rank
• Keywords where only one competitor ranks
• Low-volume queries with multiple ranking pages
• Question queries
• Informational queries surrounding commercial pages
• Queries your competitors rank for but you don't

Semrush's Keyword Gap, for example, is designed to compare competitors' organic keyword portfolios. Semrush

For questions, use a separate research process

I'd build a question database, rather than relying entirely on keyword volume.

Search your topic with the local equivalents of:

Then cluster the questions by search intent, not merely by words.

For example, 15 different questions might actually represent one content topic and should potentially be answered on a single page.

A useful evaluation framework

Don't select long-tail keywords solely because they have low difficulty.

I'd score each candidate internally on:

Opportunity = relevance × business value × evidence of demand × ranking feasibility

Look at:

1. Search intent — does the query match something your site should answer?
2. SERP fit — are the current results actually pages like yours?
3. Search demand — volume is useful, but don't reject a query simply because the reported volume is 10–20.
4. Competition — examine the actual SERP rather than trusting KD alone.
5. Traffic potential — one page can rank for dozens/hundreds of related long-tail queries.
6. Business value — informational traffic isn't automatically valuable.
7. Localization — does the wording correspond to the actual market's language?
8. Content gap — can you answer something that existing results don't answer well?

This last point is particularly important in smaller-language markets where keyword-volume estimates can be thin. Ahrefs explicitly notes that data depth varies considerably between non-English markets. Ahrefs

One workflow I'd recommend

For each major topic:

Native seeds → autocomplete → Google Trends → Ahrefs/Semrush → competitor keywords → Search Console → SERP inspection → clustering → content mapping

For example:

20 native seed terms
↓
500–2,000 keyword/question candidates
↓
Remove irrelevant terms
↓
Group by search intent/topic
↓
Inspect actual SERPs for promising clusters
↓
Identify 20–50 content opportunities
↓
Map each cluster to an existing or new page

The important distinction is that translation is an input, not a keyword-research strategy. Native search behavior should ultimately determine the phrases you target.

If you tell me the language + country + your site's topic, I can also give you a concrete research workflow (including which tools to use, what filters to apply, and how I'd evaluate the long-tail opportunities).

One workflow I'd recommend

For each major topic:

For non-English SEO, research the language people actually use rather than translating English keywords.

• Ahrefs — country/language-specific keyword data, questions, autocomplete, SERPs, and long-tail discovery. Ahrefs Ahrefs Help Center
• Semrush Keyword Magic Tool — multilingual databases, question filters, intent, difficulty, and topical grouping. Semrush Semrush
• Google Search Console — mine your own impressions/clicks for real local-language queries, especially low-volume long tails.
• Google autocomplete / “People also ask” — excellent for discovering natural questions and phrasing that keyword databases may miss.
• Native speakers — particularly important for slang, regional wording, informal questions, and terms that literal translation gets wrong. Semrush

Practical workflow: native-language seed terms → Ahrefs/Semrush expansion → autocomplete/PAA question mining → filter by country + intent → manually inspect the local SERP → cluster synonymous queries into pages.

For smaller languages/markets, treat volume estimates cautiously; database coverage can vary substantially by country and language. Ahrefs

Yes. For a non-English site, the key is not to simply translate English keywords. You want to discover the phrases people actually use in that language, including colloquialisms, regional wording, misspellings, and question formats.

A practical multilingual keyword-research stack

1. Start with Google Search Console — if you already have traffic

This is often the highest-value source because it gives you real queries that people have already used to find your site.

In Search Console, segment by:

• Country
• Queries
• Pages
• Date range

Look especially for queries with impressions but few clicks and queries where you're ranking around positions 5–30. Those can reveal long-tail topics that Google already associates with your site. Search Console supports query and country dimensions and lets you compare performance between countries. Google Help Google Help

search.google.com

2. Use Google autocomplete in the target language

This is excellent for finding natural-language questions.

Take a seed topic and try modifiers equivalent to:

• how
• why
• what
• when
• where
• which
• can
• should
• is it
• does
• alternatives
• price/cost
• problems
• reviews
• comparison

But don't translate the modifiers mechanically. Search them natively in the target language and look at Google's suggestions.

Also try incomplete queries:

[topic] + "how..."
[topic] + "why..."
[topic] + "can..."
[topic] + "best..."
[topic] + "without..."

The autocomplete suggestions often expose conversational phrasing that conventional keyword databases miss.

3. Google Trends is particularly useful for multilingual research

You can compare terms across languages

Yes. For non-English SEO, the key is not to simply translate an English keyword list. You want to discover the way people in that language and market actually phrase problems, questions, products, and comparisons.

Best methods

1. Start with native-language seed terms

Build a small seed list in the site's actual language, then expand each seed using keyword tools.

For example, if you're targeting Spanish speakers searching for accounting software, don't start with the English keyword accounting software and translate it. Start with several native concepts such as:

• software de contabilidad
• programa de contabilidad
• cómo llevar la contabilidad
• contabilidad para pequeñas empresas
• programa para facturar y llevar cuentas

Then expand those separately. This catches differences in terminology that literal translation misses.

2. Use keyword tools with country/language targeting

Ahrefs Keywords Explorer is particularly useful because you can select the target country and it supports a large number of language/country combinations. Its Questions report can isolate question-style queries, while Terms match and related-keyword reports are useful for discovering variations. Ahrefs Help Center Ahrefs Help Center

ahrefs.com

Semrush Keyword Magic Tool is another strong option. It groups related keywords into subtopics and has a questions-only filter, which is useful for finding informational long tails. Semrush

semrush.com

Don't blindly trust the reported volume, though. Data quality varies substantially between markets; even Ahrefs notes that some smaller-language markets have thinner keyword datasets. Ahrefs

3. Mine Google itself

This is one of my favorite approaches for smaller languages.

Search your native-language seed and collect:

• autocomplete suggestions
• "People also ask"
• related searches
• question variations
• modifiers such as how, why, which, where, best, price, alternatives, etc.

The important insight is that the modifiers themselves are language-specific. Build a list of native question words and commercial modifiers rather than translating an English modifier list.

4. Use Google Trends for language-specific demand

trends.google.com is excellent for validating whether a long-tail phrase actually has traction.

Its related searches include both "Top" and "Rising" queries, so you can find emerging language-specific wording. Google Help

There's also an important distinction:

• Search term = the exact wording people type.
• Topic = Google's broader conceptual grouping, potentially incorporating searches across languages.

For keyword research, use search terms when you care about the exact local wording; use topics when you want to understand broader demand. Google Help Google Help

5. Mine your own Search Console data

If the site already has traffic, this can be more valuable than third-party keyword databases.

Export queries from Google Search Console and look for:

• queries with 4+ words
• questions
• queries with impressions but low CTR
• queries ranking positions 5–20
• unexpected synonyms
• colloquial wording
• queries in regional variants of the language
• queries you aren't explicitly targeting

Google itself recommends using Search Console to identify queries in other languages and countries where your site is already getting visibility. Google for Developers

6. Look outside traditional SEO tools

For genuine questions, communities can be better keyword research sources than keyword databases.

Depending on the language, mine:

• Reddit
• regional forums
• Quora equivalents
• Facebook groups
• YouTube comments
• TikTok/YouTube search suggestions
• product reviews
• customer-support tickets
• your site's internal search
• competitor FAQ pages

The wording people use in these places often resembles conversational long-tail searches much more closely than a keyword database does. Video titles and transcripts can also expose natural-language questions. Ahrefs

A particularly effective workflow

I'd use this pipeline:

Native seeds → Google autocomplete/PAA → Ahrefs/Semrush expansion → Google Trends → competitor SERPs → Search Console → community questions → clustering → SERP validation

Then score each candidate on something like:

One important warning

Don't translate your English keyword list and assume you've localized it.

A native speaker might use completely different:

• synonyms
• word order
• singular/plural forms
• abbreviations
• informal terminology
• regional vocabulary
• question constructions
• commercial modifiers

For example, two Spanish-speaking markets may use different words for the same product, and German, Japanese, Arabic, etc. can have much larger differences in how a search intent is expressed.

For a genuinely multilingual site, I'd therefore create a separate keyword universe for each language × country combination, rather than one master English list translated into 10 languages.

If you tell me the language + country + your site's niche, I can give you a concrete long-tail/question research process and the exact tools and filters I'd use for that market.

One important warning

Don't translate your English keyword list and assume you've localized it.

A native speaker might use completely different:

• synonyms
• word order
• singular/plural forms
• abbreviations
• informal terminology
• regional vocabulary
• question constructions
• commercial modifiers

For example, two Spanish-speaking markets may use different words for the same product, and German, Japanese, Arabic, etc. can have much larger differences in how a search intent is expressed.

For a genuinely multilingual site, I'd therefore create a separate keyword universe for each language × country combination, rather than one master English list translated into 10 languages.

If you tell me the language + country + your site's niche, I can give you a concrete long-tail/question research process and the exact tools and filters I'd use for that market.

Yes. For a non-English site, I’d avoid simply translating an English keyword list. The best long-tail keywords are usually discovered from how native speakers actually search, including local phrasing, slang, misspellings, and question formats.

A strong multilingual keyword-research workflow

1. Start with Google Search Console — if the site already has traffic

search.google.com is particularly valuable because it gives you real queries people used to find your site, rather than estimated keywords.

Look at:

• Queries with lots of impressions but few clicks
• Queries where you're ranking around positions 5–20
• Unexpected queries your pages already appear for
• Very specific multi-word queries
• Question-like queries
• Queries by country
• Queries associated with individual URLs

Search Console lets you filter by query, page, country, device, etc., and Google explicitly recommends examining queries with high impressions and low CTR for optimization opportunities. Google Help Google Help

For multilingual sites, country + query is especially useful because the same language can have very different search vocabulary in different markets.

2. Use Ahrefs or Semrush for actual keyword discovery

Two of the better options are:

• ahrefs.com — particularly useful for finding matching terms, questions, related topics and long-tail variations.
• semrush.com — useful for filtering by language, intent, volume, difficulty and other attributes.

Ahrefs' Keywords Explorer supports a large number of language/locale combinations, while Semrush's Keyword Magic Tool allows language filtering within supported country databases. Ahrefs Help Center Semrush

For example, instead of researching only:

running shoes

also investigate the local equivalents of:

best running shoes for flat feet
running shoes for beginners
running shoes that don't hurt knees
how should running shoes fit
can I run every day with these shoes?

The question and modifier patterns are often more useful than the head keyword itself.

3. Mine Google's autocomplete and SERPs in the target language

This is one of the most underrated methods.

Search the seed topic in the actual target language and country, then collect:

• Google autocomplete suggestions
• "People also ask"
• Related searches
• Suggested refinements
• Search-result titles
• Featured snippets
• Forums appearing in the SERPs

Don't just translate your English query and stop there. Google adjusts results according to language and region, and searches can surface results from other languages when Google considers them relevant. Google Help

For example, if your market is Mexican Spanish, research in Mexican Spanish, rather than assuming European Spanish terminology will reflect the same search behavior.

4. Mine native-language communities

This is excellent for finding question-shaped long tails that conventional keyword databases miss.

Look at:

• Reddit
• Quora
• Local forums
• Facebook groups
• YouTube comments
• TikTok comments
• Product reviews
• Local Q&A sites
• Community sites specific to your country

You're looking for questions such as:

¿Por qué...?
¿Cómo puedo...?
¿Cuál es mejor...?
¿Cuánto cuesta...?
¿Vale la pena...?
¿Qué pasa si...?
¿Dónde puedo...?

The important thing isn't necessarily the exact wording. Extract the underlying problem/question, then validate whether people actually search for it.

Ahrefs similarly recommends Q&A sites and community discussions as sources of long-tail ideas, and notes that conversational language from videos and discussions can reveal natural query patterns. Ahrefs Ahrefs

5. Use local competitors as a keyword dataset

This is especially powerful for non-English SEO.

Take 5–20 sites that rank well in your target country/language and run them through:

• Ahrefs Site Explorer
• Semrush Organic Research
• Similarweb, where useful
• Google manually

Look for keywords where competitors rank but you don't.

Then filter those terms by:

Relevance → intent → search demand → competition → business value

Don't blindly copy competitor keywords. You're trying to identify topics and questions that the local market already demonstrates demand for.

6. Use native-language question modifiers

Build a modifier library for each language.

For example, conceptually:

But don't translate these mechanically. Have a native speaker or native-language SERP research establish the natural versions.

That distinction matters because searchers don't necessarily phrase questions the way a literal translation would.

7. Evaluate long tails by more than search volume

This is where multilingual keyword research gets interesting.

I'd score candidates on something like:

Opportunity = relevance × intent × achievable ranking × business value

Specifically look at:

• Search demand — volume is useful, but don't reject a keyword because volume is tiny.
• Search intent — can you actually satisfy the query?
• SERP competition — who currently ranks?
• Content quality — are the existing results genuinely good?
• Topical fit — does it belong naturally on your site?
• Conversion potential — could the searcher become a customer?
• Localization — is the wording genuinely used in your market?
• SERP features — PAA, snippets, shopping, video, etc.
• Existing visibility — are you already getting impressions?

For long tails, zero/low reported volume doesn't necessarily mean zero demand. Many highly specific queries have demand fragmented across hundreds of variations.

8. Use your own Search Console data to discover "hidden" questions

This is probably my favorite technique for an established site.

Export your queries and look for words equivalent to:

• how
• why
• what
• which
• where
• when
• can
• should
• does
• is
• price/cost
• problem
• alternative
• difference
• review

Then cluster them by question/topic, rather than treating every keyword as a separate article.

For example:

how to choose X
which X is best
X for beginners
how much X costs
is X worth it

might all belong to one useful content cluster.

Search Console has an important limitation: it doesn't expose every query, because some queries are anonymized and the displayed tables are truncated. Google Help

9. Use AI for clustering, not as your primary source of demand

LLMs are excellent for taking a large pile of native-language queries and turning it into structure.

For example, give an LLM 2,000 queries and ask it to:

1. Detect the language/dialect.
2. Normalize spelling variants.
3. Identify duplicate intent.
4. Cluster queries by underlying question.
5. Label search intent.
6. Identify modifiers.
7. Separate informational/commercial/local queries.
8. Flag queries that appear unnatural or machine-translated.
9. Suggest missing questions within an existing topic cluster.

But don't treat AI-generated keywords as evidence of search demand.

Use AI to organize real search/community/competitor data, then validate the resulting candidates with keyword tools and SERPs.

My preferred tool stack

The key principle

For multilingual SEO, I'd use this pipeline:

Native-language seed topics → local SERPs → autocomplete/PAA → competitors → communities → keyword database → Search Console → clustering → intent/SERP evaluation

rather than:

English keywords → machine translation → publish

The first approach tends to uncover the actual language of the market, which is where many of the best long-tail opportunities are hiding.

If you tell me the language + country and your site's niche, I can also give you a concrete multilingual keyword-research process (including the exact tools, filters, regex patterns, and a spreadsheet structure) for that market.

• how
• why
• what
• which
• where
• when
• can
• should
• does
• is
• price/cost
• problem
• alternative
• difference
• review

Then cluster them by question/topic, rather than treating every keyword as a separate article.

For example:

how to choose X
which X is best
X for beginners
how much X costs
is X worth it

might all belong to one useful content cluster.

Search Console has an important limitation: it doesn't expose every query, because some queries are anonymized and the displayed tables are truncated.

For a non-English site, the biggest mistake is treating keyword research as “translate my English keywords.” Search behavior, wording, and intent often change by country and culture, so the goal is to discover what people actually type in that language, then evaluate whether those queries are worth targeting. BeTranslated Crisol Translation Services

A practical workflow:

1. Start with native-language keyword discovery

Use Google autocomplete and question sources

These are often the best sources for long-tail phrases because they reflect real user wording.

• Google autocomplete (set the target country/language)
• Google “People Also Ask”
• Related searches at the bottom of SERPs
• YouTube autocomplete (especially for tutorials/how-to niches)
• Reddit, forums, Q&A sites, and local communities

For example, instead of translating “best accounting software,” a Spanish audience might search around a different concept such as “programa para llevar la contabilidad de autónomos” (software for freelancers’ accounting). The opportunity is in discovering the local phrasing.

2. Use multilingual keyword tools

Useful options:

• Semrush — strong for country databases, competitor keyword gaps, and intent analysis. The Sharp Digital
• Ahrefs — useful for seeing what local competitors rank for and finding long-tail variations/questions. Ahrefs
• Google Keyword Planner — free and useful when you correctly set country + language filters. BrightKeyword
• Keyword Tool — helpful for autocomplete-based long-tail discovery across different platforms and countries. keyword.io
• Authoritas — has international keyword research and question discovery features. Authoritas

For smaller sites, a combination of Google autocomplete + Keyword Planner + competitor research is often enough.

3. Find questions specifically

Question keywords are often excellent long-tail targets:

Examples of modifiers to collect in your language:

• “how to…”
• “why does…”
• “which…”
• “best…”
• “difference between…”
• “can I…”
• “is it worth…”

Tools:

• Google People Also Ask extraction tools
• AlsoAsked (question maps)
• Ahrefs/Semrush question filters
• Local forums and communities

4. Analyze competitors in the target language

This is usually more reliable than translating your own ideas.

Process:

1. Find 5–10 sites ranking in the target market.
2. Export their organic keywords.
3. Filter for: - low difficulty
4. informational intent
5. keywords where they rank positions 5–30
6. question formats
7. Build content around gaps they have not covered.

Competitor keywords reveal vocabulary choices that native users already accept.

5. Evaluate keywords beyond search volume

For long-tail keywords, volume alone can mislead. Score each keyword on:

A keyword with 50 searches/month and strong buying intent may be more valuable than one with 5,000 searches/month from casual browsers.

6. Use native speakers for final validation

Machine translation is useful for brainstorming, but before publishing:

• Check whether the phrase sounds natural.
• Check regional differences.
• Check whether people use formal or informal wording.
• Check whether the term means what you think it means.

A native reviewer can often find better variants in minutes.

A simple repeatable process

1. Pick a topic in your niche.
2. Collect 100–500 phrases from autocomplete, competitors, and keyword tools.
3. Remove literal translations that nobody searches.
4. Group by intent: - informational
5. comparison
6. transactional
7. local
8. Validate volume and competition.
9. Create pages targeting clusters, not single keywords.

If you tell me the language, country, and niche of your site, I can suggest a more specific keyword research stack and workflow.

6. Use native speakers for final validation

Machine translation is useful for brainstorming, but before publishing:

• Check whether the phrase sounds natural.
• Check regional differences.
• Check whether people use formal or informal wording.
• Check whether the term means what you think it means.

A native reviewer can often find better variants in minutes.

A simple repeatable process

1. Pick a topic in your niche.
2. Collect 100–500 phrases from autocomplete, competitors, and keyword tools.
3. Remove literal translations that nobody searches.
4. Group by intent: - informational
5. comparison
6. transactional
7. local
8. Validate volume and competition.
9. Create pages targeting clusters, not single keywords.

If you tell me the language, country, and niche of your site, I can suggest a more specific keyword research stack and workflow.

Yes. For a non-English site, the biggest mistake is to translate English keywords and assume they represent how people actually search. Long-tail research works much better when you research the target language and market directly.

A strong multilingual keyword-research workflow

1. Start with native-language seed terms

Create 20–50 seed concepts in the site's actual language, rather than translating an English keyword list.

For each seed, expand it into modifiers such as:

• Questions: why, how, when, where, which, can I, is it worth it
• Problems: not working, causes, symptoms, alternatives, mistakes
• Comparisons: X vs Y, best X for Y, X or Y
• Buying intent: price, cheap, reviews, discount, near me
• Audience: for beginners, for students, for small businesses, for children
• Situations: after…, before…, without…, during…, in [country/city]

This is particularly important because people often express the same underlying intent differently across languages.

2. Use Google Keyword Planner by language + country

ads.google.com is one of the best starting points because you can specify both a language and geographic location when generating keyword ideas. Google Help Google Help

For example, don't just research:

"best accounting software"

Instead, set the target country and language and investigate the native-language equivalents, then look at related suggestions.

I'd run separate research sets for each market. A Spanish site targeting Spain and one targeting Mexico shouldn't necessarily use the same keyword list.

3. Mine Google autocomplete and SERPs

This is especially useful for long-tail questions.

Take a native-language seed and examine:

• Google autocomplete
• "People also ask"
• Related searches
• Question-style titles in the SERPs
• Forums and community discussions
• Competitors' headings and FAQ sections

The goal isn't merely to collect keywords. You're looking for recurring ways that native speakers describe the problem.

For example, you may discover that the literal translation of "how to fix X" isn't how people actually formulate the question in your target market.

4. Use your own Google Search Console data

Once the site has traffic, search.google.com becomes one of your best sources of real long-tail queries.

The Performance report shows the actual queries that caused your pages to appear, along with impressions, clicks, CTR and position. Google Help Google Help

You can also filter/compare by country, which is very useful for multilingual SEO. Google Help Google Help

Look particularly for:

• Queries with high impressions + low CTR
• Queries ranking around positions 5–20
• Unexpected question queries
• Queries for which you rank with the "wrong" page
• Several related long-tails pointing to the same URL
• Queries appearing in one country but not another

Those often reveal your next content opportunities better than generic keyword-volume databases.

5. Use specialist SEO databases for discovery

Tools such as:

• ahrefs.com
• semrush.com
• sistrix.com
• keywordtool.io

can be useful for expanding seeds, identifying competitors' keywords and estimating demand.

But for non-English markets, I'd treat their volume estimates as directional rather than absolute truth. A keyword with "20 searches/month" can still be commercially valuable, particularly when hundreds of related long-tail searches exist.

6. Find questions, not just keywords

For question research, build a database of native-language interrogatives.

For example, if your language were German, you might create buckets around:

• wie — how
• warum — why
• wann — when
• welche/welcher — which
• kann man — can you
• ist es — is it
• was tun wenn — what to do if
• lohnt sich — is it worth it

Then combine them with your seed topics.

This approach is powerful because many long-tail questions have too little individual volume for traditional keyword tools to surface them reliably.

7. Check local-language communities

For genuine question discovery, communities can be better than SEO tools.

Depending on the language/market, investigate:

• Reddit
• Quora
• local forums
• Facebook groups
• YouTube comments
• product reviews
• app-store reviews
• marketplace reviews
• industry-specific communities

You're looking for phrases people repeatedly use when describing their problem in their own words.

Those phrases can become article titles, H2s, FAQs and supporting sections.

How I'd evaluate a long-tail keyword

Don't rank opportunities solely by search volume. I'd use something like:

I'd give particular weight to SERP fit + business value + localization.

A keyword with 100 searches/month where the search results are dominated by huge sites isn't necessarily better than a 20-search/month query where you can provide exactly what the searcher wants.

One particularly useful technique: keyword clustering

Don't create one article for every tiny variation.

Suppose you discover 30 native-language queries around the same underlying question. Group them according to search intent, not merely linguistic similarity.

For example:

Topic
├── "how to X"
├── "how can I X"
├── "X step by step"
├── "X for beginners"
└── "X without Y"

If Google returns essentially the same type of pages for all five, they probably belong to one content cluster/page.

If the SERPs differ substantially, they may deserve separate pages.

This prevents the classic multilingual-SEO problem of producing hundreds of thin pages targeting microscopic keyword variations.

My preferred tool stack

For most non-English sites, I'd use:

Discovery
→ Google autocomplete + local communities + competitor research

Keyword expansion
→ Google Keyword Planner + Ahrefs/Semrush/KeywordTool

Real-world validation
→ Google Search Console

Trend validation
→ trends.google.com

SERP/competition analysis
→ Google itself + Ahrefs/Semrush/SISTRIX

Organization
→ Spreadsheet/database with keyword, language, country, intent, volume, difficulty, SERP type, business value and target URL

The important part is that the SEO tool is only one layer. For multilingual long-tail research, the combination of native-language phrasing + actual SERPs + Search Console + local communities is usually much more revealing than relying on a keyword database alone.

If you tell me the language, country/market, and your site's niche, I can also give you a concrete multilingual keyword-research process—including which tools are strongest for that particular language and how I'd find hundreds of question/long-tail opportunities.

Yes. For non-English SEO, the biggest mistake is translating English keywords and assuming search behavior is equivalent. You’ll generally get better long-tail keywords by combining native-language SERP research, keyword databases, question mining, and actual search-query data.

Best methods

• Google Search + autocomplete — Search your topic in the target language and collect autocomplete suggestions, “People also ask,” related searches, and variations in wording. This is especially useful for conversational questions.
• Google Search Console — If the site already gets traffic, your own impressions/query data is one of the best sources of real long-tail terms in the target language.
• Google Keyword Planner — Set the language and target country/region explicitly. Useful for search volume and discovering variations, though long-tail coverage can be limited.
• Semrush — Good for multilingual keyword databases, keyword variations, questions, SERP analysis, and competitor research.
• Ahrefs — Particularly useful for competitor keyword research and filtering for low-volume/low-competition queries. Check that your target country/language has sufficient database coverage.
• Google Trends — Excellent for comparing synonymous terms and discovering regional differences. A literal translation may be much less popular than the phrase native speakers actually use.
• AlsoAsked — Useful for finding question relationships and building question/topic clusters; coverage varies by language and location.
• AnswerThePublic — Can surface question/preposition-based queries in multiple languages, although I'd validate the results against actual SERPs.
• Reddit, forums, Quora, YouTube, TikTok, and local communities — Often better than SEO tools for discovering the exact language people use. Search these in the target language and mine recurring questions, slang, abbreviations, and problem descriptions.

A strong multilingual workflow

I'd use this sequence:

1. Start with native-language seed topics

Don't start with:

English keyword → machine translation → target keyword

Instead, get 20–50 seed concepts from someone who understands the target market, existing customer language, local forums, product terminology, etc.

2. Expand them in the actual search engine

For each seed, search in the target language and collect:

• Autocomplete suggestions
• PAA questions
• Related searches
• Search-result titles/headings
• Featured snippets
• Forum/community questions
• Competitor pages ranking for the topic

This gives you linguistic variants, not merely translations.

3. Mine competitor keywords

Put several locally successful competitors into Ahrefs/Semrush and look for queries where:

• Their page ranks in positions ~3–20
• Search volume is modest
• The query is highly specific
• The SERP doesn't contain many authoritative competitors
• The query clearly expresses a problem or intent

Those are often excellent long-tail opportunities.

4. Build question modifiers

Different languages have different natural question patterns. For example, instead of simply translating:

how to + [topic]

look for native equivalents of patterns such as:

• how to…
• why does…
• what is…
• which… is best
• can I…
• is it possible to…
• how much…
• how long…
• where can I…
• [topic] vs [topic]
• [topic] for [specific audience]
• [topic] without [constraint]
• [topic] near [location]
• [topic] in [year]

Then discover the language-specific versions people actually search.

5. Evaluate the SERP, not just keyword volume

For long-tail queries, a keyword with 20 searches/month can be more valuable than one with 1,000 if the intent matches your business.

I'd score each candidate on:

One particularly important technique

Compare several countries that speak the same language.

For example, Spanish searches in Spain, Mexico, Argentina, and Colombia can use noticeably different vocabulary. The same is true for Portuguese in Brazil vs. Portugal, French in France vs. Canada, and German across different markets.

So don't just configure a tool to:

Language = Spanish

Also configure:

Country = Mexico

and separately:

Country = Spain

Then compare the resulting keyword sets and SERPs.

Tools I'd prioritize

If you're building a serious multilingual keyword process, my shortlist would be:

1. Google Search + Search Console — actual language/search behavior
2. Ahrefs or Semrush — scalable keyword + competitor research
3. Google Trends — regional terminology and demand comparisons
4. AlsoAsked — question discovery
5. Local-language communities — finding the long-tail wording SEO databases miss
6. A native speaker/translator — validation of whether the query sounds natural

The last one is surprisingly important: a keyword can have measurable search volume and still be an unnatural phrase that nobody would use in normal local language.

If you tell me the language(s), target country, and your site's topic, I can also give you a concrete multilingual long-tail research workflow—including which tools have the best coverage for that particular language.

Yes. For a non-English site, I’d use a mix of native-language keyword data, search-result analysis, and question-mining, rather than simply translating English keywords.

Best methods

• Google Keyword Planner — Set the target country/language and collect local search volumes. Useful for finding variants that English-language tools often miss.
• Google Search Console — Once you have traffic, filter queries by country/page and look for low-volume, specific queries that already generate impressions.
• Google autocomplete + “People also ask” — Search important topics in the target language. This is particularly useful for discovering natural questions and conversational long tails.
• Google Trends — Compare terminology, regional variations, and seasonality in the actual target language.
• Ahrefs / Semrush — Both have substantial international keyword databases. Look specifically for country/language-specific volume, keyword difficulty, SERP features, and related questions rather than relying on their English databases.
• AlsoAsked — Good for mapping question relationships around a topic; check whether the target language/country is supported before relying on the data.
• AnswerThePublic — Useful for question and modifier discovery across languages, although coverage and data quality vary considerably by market.
• Reddit, forums, YouTube, TikTok, Quora, and local communities — Excellent for finding the way native speakers actually phrase problems. These often produce long-tail topics that conventional keyword databases don't capture.
• Google/Bing SERPs in the target market — One of the most important steps. Search from the target country and inspect titles, related searches, PAA questions, forums, and autocomplete.

A particularly effective workflow

For each important topic:

1. Start with a native-language seed term, not an English keyword translated literally.
2. Put that term into Google in the target country.
3. Collect: - autocomplete suggestions
4. PAA questions
5. related searches
6. suggested refinements
7. forum/community questions
8. Put the resulting terms into Ahrefs/Semrush/Keyword Planner to obtain volume and competition estimates.
9. Cluster variations by search intent, not just by similar words.
10. Manually inspect the SERP for the highest-value clusters.
11. Prioritize queries where: - the intent is clear,
12. the SERP contains weak/irrelevant results,
13. competitors aren't comprehensively answering the question,
14. and your site can provide a genuinely better answer.

Don't overlook language-specific differences

A major trap is assuming that a direct translation has the same search behavior.

For example, English speakers might search:

“best laptop for college students”

But a Spanish-speaking market might use a completely different combination of terms, regional vocabulary, abbreviations, or sentence structure. Even spelling and formal vs. informal language can change the keyword landscape.

I'd therefore distinguish:

Translation → “What is the translated version of this keyword?”
Localization → “What would someone in this market actually type into Google?”

For long-tail SEO, localization is much more valuable.

If you tell me the language + target country + type of site/business, I can suggest a concrete keyword-research stack and workflow for that particular market.

For non-English sites, long-tail keyword research works best when you combine native-language data sources, search-engine-specific tools, and question mining. Translation alone usually misses the way real users search.

1. Use local search data first (best signal)

Google tools

• ads.google.com

• Set the target country and language.
• Use local keyword variations, not English seed terms.
• Good for search volume, competition, and keyword grouping.
• search.google.com

• If your site already has traffic, this is often the best source.
• Export queries that already generate impressions but rank poorly.
• Look for: - 4–8 word queries
• question phrases
• synonyms you did not target
• regional wording differences

Regional search engines

Depending on your audience:

• China: ziyuan.baidu.com
• Russia: webmaster.yandex.com
• South Korea: searchadvisor.naver.com

These often reveal queries Google tools miss.

2. Use keyword tools that support multiple languages

semrush.com

Useful for:

• competitor keyword discovery
• keyword difficulty
• SERP analysis
• country-specific databases

ahrefs.com

Strong for:

• finding competitor pages ranking for long-tail terms
• seeing estimated traffic by country
• analyzing content gaps

mangools.com

Often easier for:

• smaller-language markets
• long-tail discovery
• localized SERP checking

keywordtool.io

Useful for pulling autocomplete suggestions from:

• Google
• YouTube
• Bing
• Amazon
• other platforms

3. Mine questions directly

Long-tail keywords are frequently questions. Useful sources:

Search suggestions

Collect autocomplete data from:

• Google
• YouTube
• Bing
• local search engines

Examples:

• “how to…” equivalents in your language
• “best…”
• “near me”
• “price of…”
• “difference between…”
• “is it worth…”

answerthepublic.com

Good for:

• question clusters
• prepositions
• comparison searches

alsoasked.com

Useful for mapping:

• “People also ask” questions
• related search journeys

4. Use native-language competitor analysis

This is especially important for smaller languages.

Find competitors ranking in the target language and analyze:

• Their top pages
• Page titles
• H1/H2 headings
• FAQ sections
• Blog categories
• User comments/reviews

Tools:

• Ahrefs Content Gap
• Semrush Keyword Gap
• Google site searches: - site:competitor-domain.com keyword
• "phrase in your language"

5. Use community sources for real wording

Search behavior often appears first in communities.

Depending on the language:

• Forums
• Reddit communities
• Facebook groups
• Quora equivalents
• Local Q&A sites
• Product reviews
• App store reviews

Look for:

• repeated complaints
• beginner questions
• exact phrases people use
• alternative names for products/services

6. Use AI carefully for expansion

AI is useful for generating variations, but validate everything with search data.

Good workflow:

1. Start with 20–50 real keywords.
2. Ask AI to generate: - synonyms
3. regional variants
4. question forms
5. beginner wording
6. comparison phrases
7. Validate in: - Keyword Planner
8. Ahrefs/Semrush
9. Google autocomplete
10. Search Console

Avoid:

• translating English keywords directly
• assuming search intent transfers between languages
• creating pages for AI-generated phrases with no search demand

7. Evaluate long-tail keywords in other languages

Look at:

For multilingual SEO, SERP analysis matters more than raw volume. A keyword with 200 searches/month can outperform one with 5,000 searches/month if the intent is highly specific.

A practical workflow

1. Pick 5–10 seed topics in the target language.
2. Pull autocomplete suggestions.
3. Export questions from AnswerThePublic/AlsoAsked.
4. Check volume and competition in Keyword Planner/Ahrefs/Semrush.
5. Analyze the top 10 SERP results in that language.
6. Group keywords by intent: - learn
7. compare
8. buy
9. solve a problem
10. Build content around clusters, not single keywords.

If you tell me the language, country/market, and type of site (ecommerce, SaaS, blog, local business, etc.), I can suggest a more specific keyword research stack and workflow.

7. Evaluate long-tail keywords in other languages

Look at:

For multilingual SEO, SERP analysis matters more than raw volume. A keyword with 200 searches/month can outperform one with 5,000 searches/month if the intent is highly specific.

A practical workflow

Yes. For a non-English site, the best approach is usually not to translate an English keyword list. You want to discover the phrases people actually search for in the target language, including local wording, spelling variations, and question formats.

Useful methods

• Google Search + autocomplete — Search your core topics in the target language and collect autocomplete suggestions, related searches, and “People also ask” questions. This is particularly useful for discovering natural-language long tails.
• Google Keyword Planner — Set the target country and language. Use it for search-volume ranges, competition, and keyword expansion rather than treating its volumes as exact.
• Google Trends — Compare synonymous terms and regional variations. This is especially valuable when the same concept is expressed differently across countries or dialects.
• Search Console — Once you have traffic, this is one of your best sources of real long-tail queries. Look at queries with impressions but low clicks/CTR and queries where you're ranking around positions 5–30.
• Ahrefs / Semrush — Both can be useful for multilingual keyword databases, SERP analysis, keyword difficulty, competitor keywords, and question-based terms. Coverage varies considerably by language and country, so validate their data against actual SERPs.
• AlsoAsked — Useful for mapping question relationships around a topic. Check whether your target language/country is supported well before relying on it.
• AnswerThePublic — Good for generating question/phrase patterns, although coverage and usefulness vary by language.
• Google/YouTube/Reddit/forum searches in the target language — Excellent for discovering the vocabulary people actually use. Forums can reveal questions that conventional keyword tools don't surface.
• LLMs — Useful for expanding a seed set into semantic variations, colloquial terminology, question formulations, and topic clusters. Treat generated keywords as hypotheses; validate them with search/SERP data rather than assuming they have demand.

A particularly effective multilingual workflow

Suppose your site is about home coffee equipment in Spanish.

Start with a few concepts rather than translated keywords:

espresso machine, grinder, cleaning, coffee extraction

Then search the Spanish market and collect:

1. Exact queries

• cómo limpiar una cafetera espresso
• qué molino necesito para espresso
• Long-tail modifiers

• para principiantes
• barato
• en casa
• sin cápsulas
• para café de especialidad
• Question patterns

• cómo...
• qué...
• cuál...
• por qué...
• merece la pena...
• se puede...
• cuánto...
• Local language differences

• Spain vs. Mexico vs. Argentina, etc.
• formal vs. conversational terminology
• regional names for the same product/concept
• SERP validation

Search the actual phrase in Google using the target country's settings. Look at:

• autocomplete
• PAA questions
• related searches
• titles/H1s of ranking pages
• forums and Q&A results
• whether Google is returning results for the same intent

Then put the candidates into a spreadsheet with columns such as:

Don't overlook "zero-volume" keywords

For multilingual SEO, third-party tools can substantially under-report demand in smaller languages. A keyword showing 0–10 searches/month doesn't necessarily mean nobody searches it.

If the phrase is clearly natural, matches your audience, has strong intent, and you can create a genuinely useful page around it, it can still be worth targeting—particularly when dozens of similar long-tail queries can be covered by one page.

Tools I'd choose by purpose

• Best overall SEO research: Ahrefs or Semrush
• Free/first-party data: Google Keyword Planner + Search Console + Trends
• Question discovery: Google PAA + AlsoAsked
• Real-world language discovery: Reddit, forums, YouTube, autocomplete
• Large-scale keyword expansion: Ahrefs/Semrush + an LLM
• Small/less-supported languages: Google SERPs, Trends, local forums, Search Console, and native-speaker validation become much more important

The key distinction is keyword translation vs. keyword localization. For multilingual SEO, localization wins: what would a person in that language and market actually type into Google?

For non-English SEO, long-tail keyword research is often more challenging because search behavior, spelling variations, idioms, and available SEO data differ by language. A good approach combines native-language sources, multilingual keyword tools, and SERP analysis.

1. Use multilingual keyword research tools

ads.google.com

• Supports many languages and countries.
• Useful for: - search volume estimates
• keyword variants
• location-specific searches
• discovering related terms
• Tip: set both the country and language correctly. Search behavior in Spanish in Spain vs. Mexico, for example, can differ significantly.

ahrefs.com

Good for international SEO because it provides:

• keyword difficulty by country
• SERP analysis
• questions people search
• competitor keyword discovery

Useful workflows:

• Enter a competitor’s non-English URL → see keywords bringing traffic.
• Filter keywords by: - low difficulty
• question modifiers
• low-volume but highly specific terms

semrush.com

Helpful for:

• multilingual competitor research
• keyword gap analysis
• country-specific databases
• topic discovery

moz.com

Useful for:

• keyword suggestions
• difficulty estimates
• SERP features

2. Mine real questions from native-language sources

Long-tail keywords are often phrased as questions. Look beyond traditional keyword tools.

Search engines

Use Google/Bing autocomplete:

Examples:

• [topic] how to
• [topic] why
• [topic] best
• [topic] vs
• [topic] price
• [topic] near me

Translate the modifiers into the target language rather than translating literally.

For example, instead of translating:

"best running shoes for beginners"

look for how native speakers actually search:

• French: "meilleures chaussures running débutant"
• German: "beste Laufschuhe für Anfänger"
• Japanese: "初心者 ランニングシューズ おすすめ"

The natural search phrase matters more than the literal translation.

3. Use question databases

answerthepublic.com

Useful for finding:

• question formats
• comparisons
• prepositions
• "why/how/when" searches

Availability varies by language, so verify results with native SERPs.

alsoasked.com

Great for:

• "People also ask" question trees
• discovering related search intent

trends.google.com

Use it to compare:

• regional vocabulary
• seasonal terms
• local phrasing differences

4. Analyze local-language SERPs

This is one of the highest-value methods.

For each candidate keyword:

1. Search it in the target language.
2. Check: - autocomplete suggestions
3. "People also ask"
4. related searches
5. top-ranking pages
6. featured snippets

Look for:

• weak competitors
• outdated content
• unanswered questions
• forums ranking on page one

A keyword with only 50 searches/month can be valuable if it represents strong purchase intent.

5. Use local keyword sources

Depending on the language, local platforms can reveal queries that English tools miss.

Examples:

• Chinese:

• index.baidu.com
• Zhihu discussions
• Korean:

• searchad.naver.com
• Naver Knowledge iN
• Japanese:

• Yahoo! Japan suggestions
• Japanese Q&A communities
• Russian:

• wordstat.yandex.com
• German:

• German-language forums, Reddit communities, and local marketplaces

6. Extract keywords from competitors

A strong multilingual tactic:

1. Find the top sites in your target language.
2. Export their ranking keywords.
3. Filter for: - positions 5–30 (easy opportunities)
4. long phrases (4+ words)
5. question terms
6. low difficulty

Tools:

• Ahrefs Site Explorer
• Semrush Organic Research
• similarweb.com

7. Use AI carefully for expansion

AI can help generate keyword variations, but validate them.

Good prompts:

"Generate native search queries in [language] that people would type when looking for [topic]. Include informal phrases, questions, and buying-intent searches."

Then verify with:

• Google autocomplete
• Keyword Planner
• SERP results
• native speakers

Avoid relying on direct translation. AI often produces grammatically correct phrases that nobody searches.

8. Evaluate long-tail keywords by intent, not just volume

For multilingual sites, prioritize:

Examples of valuable long-tail patterns:

• "[product] for [specific user]"
• "how to fix [specific problem]"
• "is [product] worth it"
• "[service] cost in [city]"
• "difference between [A] and [B]"

A practical workflow

1. Pick 5–10 core topics.
2. Collect: - Google autocomplete suggestions
3. PAA questions
4. competitor keywords
5. forum discussions
6. Expand with Ahrefs/Semrush/Keyword Planner.
7. Remove unnatural translations.
8. Group by search intent.
9. Create pages that answer the exact questions.

For a non-English site, native SERP research usually beats translated keyword lists. The biggest opportunities often come from phrases that English-focused tools underestimate.

For multilingual sites, prioritize:

Examples of valuable long-tail patterns:

• "[product] for [specific user]"
• "how to fix [specific problem]"
• "is [product] worth it"
• "[service] cost in [city]"
• "difference between [A] and [B]"

A practical workflow

Yes. For a non-English site, the best approach is usually native-language keyword research + question mining + SERP validation, rather than simply translating English keyword lists.

Useful methods

• Google Search / autocomplete — Search in the target language and collect autocomplete suggestions, “People also ask,” related searches, and query variations. This is especially useful for discovering natural phrasing.
• Google Keyword Planner — Set the target country and language. Useful for search-volume estimates and keyword variants, although long-tail queries can have sparse volume.
• Google Trends — Compare synonymous terms, regional vocabulary, and seasonal demand in the target language. It can reveal that a literal translation isn't how people actually search.
• Search Console — If the site already gets traffic, this is one of the highest-value sources. Filter queries by country/language patterns and look for impressions with low clicks or pages ranking around positions 5–30.
• Ahrefs / Semrush — Both can surface keyword variations, related terms, questions, SERP data, and competitor keywords across many countries and languages. Their coverage varies considerably by language and country.
• AlsoAsked — Useful for mapping question chains around a topic, particularly when Google exposes substantial “People also ask” data for the target market.
• AnswerThePublic — Good for generating question-style queries from a seed topic, though you should validate whether the resulting phrases are actually used by native speakers.
• Reddit, forums, Quora, local social platforms, and review sites — Excellent for finding how people describe their problems, which often produces better long-tail ideas than conventional keyword tools.
• Native-language SERP analysis — Search the actual phrase and examine the pages ranking. This helps determine whether the query represents informational, commercial, transactional, or navigational intent.

For questions specifically

I'd build a question-mining workflow rather than relying on a single tool:

1. Start with 10–20 core topics in the target language.
2. Pull questions from Google PAA/autocomplete, keyword tools, forums, Reddit/local communities, and your Search Console.
3. Normalize spelling, synonyms, singular/plural forms, and regional terminology.
4. Group questions by search intent and underlying problem, not just by matching words.
5. Check each cluster against the actual SERP.
6. Prioritize questions where you see: - clear search intent,
7. weak/outdated competing content,
8. multiple related queries,
9. reasonable impressions or trend growth,
10. and a strong connection to something your site can answer or sell.

One important caveat

Don't translate English long-tail keywords and assume they're valid keywords in another language. A phrase can be grammatically correct but almost never searched that way. Native speakers may use completely different terminology, word order, abbreviations, or colloquial expressions.

For example, you'd want to discover the equivalent of “how much does X cost?” from actual searches in the target market rather than mechanically translating that sentence. Regional differences can matter too—even between countries sharing the same language.

If you tell me the language/country and your site's topic, I can suggest a specific keyword + question research stack and workflow for that market.

Yes. For non-English SEO, the biggest mistake is simply translating English keyword lists. Long-tail searches often differ by wording, intent, local terminology, and how people phrase questions.

Best methods

• Native-language keyword research: Start with seed topics in the target language, then expand using local search suggestions and related searches. Look for conversational variations rather than literal translations.
• Google autocomplete + “People also ask”: Search the target-language terms while using the target country/region. This is especially useful for question-style long tails.
• Competitor mining: Find sites that rank in the target language and extract their titles, headings, category pages, FAQs, and recurring terminology.
• Search Console: If the site already gets traffic, this is one of the best sources of real long-tail queries. Export queries by country/language and look for low-volume queries with impressions but weak CTR/rankings.
• Forums and communities: Reddit, Quora equivalents, local forums, Facebook groups, and review sites can reveal questions people actually ask rather than questions invented by keyword tools.
• SERP analysis: Search the target-language query and examine the pages Google considers relevant. Compare intent, terminology, content depth, and whether the SERP favors articles, products, forums, videos, local businesses, etc.

Tools worth considering

For languages other than English, I'd use this workflow

1. Build native seeds → 2. Expand from local SERPs/autocomplete → 3. Collect questions → 4. Validate volume/demand → 5. Cluster by intent → 6. Check the actual SERP → 7. Prioritize.

For example, don't take:

“best hiking shoes for wide feet”

and mechanically translate it.

Instead, investigate how speakers of the target language naturally express:

• best/recommended
• hiking vs trekking vs walking
• wide feet vs wide-fit shoes
• questions about sizing
• comparisons
• use cases
• local product terminology

You may discover that the highest-value long tails don't resemble the English query at all.

A particularly effective approach: question mining

For each core topic, collect questions from:

1. Google autocomplete
2. People Also Ask
3. Related searches
4. Reddit/local forums
5. Competitor FAQs
6. Search Console
7. Keyword databases

Then normalize them and cluster questions such as:

• How: “How do I…?”
• Which: “Which X is best for…?”
• Can: “Can X be used for…?”
• Why: “Why does X…?”
• Comparison: “X vs Y”
• Problem: “X not working…”
• Cost: “How much does X cost?”
• Local: “X near me / in [location]”
• Compatibility: “Does X work with Y?”

This gives you a much better content map than a flat list of keywords.

Don't rely on search volume alone

For long-tail keywords in smaller languages, reported volume can be very low or even absent despite genuine demand. I'd score opportunities using something like:

Opportunity = relevance × intent × SERP weakness × business value × evidence of demand

Search volume is just one signal.

For example, a query with 20 reported searches/month can be more valuable than one with 500 if the 20 searches have strong commercial intent and your site can realistically rank #1.

If you tell me the language/country your site targets and your site's topic, I can suggest a specific multilingual keyword-research stack and workflow—including which tools have the best coverage for that particular language.

Absolutely. For a non-English site, the biggest opportunity is often not translating English keyword lists, but discovering how people actually search and ask questions in the target language.

Here are the strongest methods and tools:

1. Use native-language keyword databases

• Google Keyword Planner — Good baseline for search volume, competition, and keyword ideas in specific countries/languages.
• Semrush — Useful for multilingual keyword research, keyword variations, SERP analysis, and competitor discovery.
• Ahrefs — Particularly useful for finding long-tail terms from competitors' pages and analyzing international SERPs.
• SISTRIX — Strong option for European markets and country-specific SERP/keyword data.
• Mangools — A simpler option for country/language-specific keyword research.

The important setting is country + language, not simply language. Search behavior for Spanish in Mexico, Spain, Argentina, and Colombia can be substantially different.

2. Mine Google autocomplete and "People Also Ask"

Search your important topics in the target language and collect:

• Autocomplete suggestions
• People Also Ask questions
• Related searches
• Search-result titles/headings
• Featured snippets
• Forums and Q&A results

This is particularly good for long-tail questions because Google's suggestions reflect actual search behavior rather than translations of English queries.

You can also vary the query structure:

[topic] cómo...
[topic] qué...
[topic] cuándo...
[topic] por qué...
[topic] vale la pena...
[topic] vs...

Obviously, use the equivalent question words and natural constructions for your target language.

3. Use Reddit, forums, and local communities

For questions rather than just keywords, community sites can be extremely valuable.

Search the target language for phrases such as:

• "¿cómo puedo...?"
• "¿alguien sabe...?"
• "mejor forma de..."
• "problema con..."
• "recomiendan...?"
• "qué hacer si..."

Then look for recurring problems and vocabulary.

The valuable part isn't necessarily the exact phrase someone posted. It's identifying the underlying question and the language people naturally use to describe the problem.

4. Analyze competitors in the target market

This is one of my favorite approaches for multilingual SEO.

Find 5–20 sites that already rank in the target country, then use Ahrefs/Semrush/SISTRIX to extract:

• Keywords they're ranking for
• Pages generating organic traffic
• Question-based queries
• Low-volume keywords
• Keywords where they're ranking positions 4–20
• Multiple related keywords ranking for the same page

You can then identify "keyword clusters" rather than creating one page for every tiny variation.

5. Use Google Search Console once you have traffic

For an established site, GSC is arguably more valuable than generic keyword tools.

Export queries and look for:

• Queries with impressions but few clicks
• Unexpected long-tail queries
• Question phrases
• Queries where your page ranks 5–20
• Different wording than the terminology you used on the page

That last category is especially interesting for multilingual sites: your visitors can teach you the vocabulary your keyword research tool missed.

6. Use local-language SERPs as a research tool

Don't assume that translating an English keyword produces the right keyword.

For example, an English concept may have several natural ways of expressing it in another language. Search each candidate phrase and compare:

• Search intent
• SERP results
• Number/type of ads
• Featured snippets
• Forums
• Commercial vs informational results
• Whether Google treats the phrases as synonyms

If completely different pages appear, they're probably different search intents—and potentially different content opportunities.

7. Mine questions from "question" sites

Depending on your language/market, investigate local equivalents of:

• Reddit
• Quora
• Stack Exchange
• Facebook groups
• YouTube comments
• Product reviews
• Local forums
• Q&A websites
• Blog comments

YouTube is particularly underrated. Search the topic in the target language and inspect video titles/comments. Comments often contain very specific questions that have no dedicated search result yet.

8. Use Google Trends for regional/language differences

trends.google.com is useful for comparing terminology.

For example, compare:

term A vs term B vs term C

Then change the country/region.

This can reveal that one term dominates in one country while another is much more common elsewhere.

9. Use AI—but as a discovery layer, not your source of truth

LLMs are excellent for expanding a seed topic into possible natural questions in the target language.

A useful workflow is:

Seed topic → AI expansion → native-language SERP validation → keyword-volume validation → clustering → content

Ask the model to generate questions from different perspectives:

• Beginner
• Expert
• Buyer
• Troubleshooting
• Comparison
• Cost
• Local/regional
• "Is it worth it?"
• "How do I..."
• "What happens if..."
• "Why does..."
• "Alternatives to..."

Then validate those questions against actual search results.

A particularly effective multilingual workflow

I'd combine the tools like this:

One important caveat

For non-English SEO, I'd be very cautious about relying on translated keyword lists.

Machine translation can produce phrases that are grammatically correct but that nobody actually searches. Conversely, colloquial expressions, regional terminology, misspellings, abbreviations, and mixed-language searches can generate valuable queries that a translation-based workflow completely misses.

If you tell me the language and country you're targeting (e.g. German/Germany, Spanish/Mexico, French/Canada, Japanese/Japan), I can give you a more specific research workflow and recommend the best tools/data sources for that market.

Seed topic → AI expansion → native-language SERP validation → keyword-volume validation → clustering → content

Ask the model to generate questions from different perspectives:

• Beginner
• Expert
• Buyer
• Troubleshooting
• Comparison
• Cost
• Local/regional
• "Is it worth it?"
• "How do I..."
• "What happens if..."
• "Why does..."
• "Alternatives to..."

Then validate those questions against actual search results.

A particularly effective multilingual workflow

I'd combine the tools like this:

One important caveat

For non-English SEO, I'd be very cautious about relying on translated keyword lists.

Machine translation can produce phrases that are grammatically correct but that nobody actually searches. Conversely, colloquial expressions, regional terminology, misspellings, abbreviations, and mixed-language searches can generate valuable queries that a translation-based workflow completely misses.

Yes. For a non-English site, you’ll generally get better results by combining native-language keyword data + question research + SERP analysis + your own Search Console data rather than simply translating English keyword lists.

Best methods

• Google Keyword Planner — Set the target country/language and use native-language seed terms. Useful for search volume, competition, and discovering variations.
• Google Search Console — Once you have traffic, this is one of the best sources of real long-tail queries in your target language. Export queries with impressions but low clicks/positions around 5–30.
• Google autocomplete & “People also ask” — Search your core topics in the target language. Look for complete questions, modifiers, comparisons, problems, and conversational phrasing.
• Google Trends — Compare synonymous terms in the actual language and country. This can reveal regional vocabulary that translation tools miss.
• Ahrefs / Semrush — Both can discover long-tail variations, related questions, SERP difficulty, and competitor keywords across many countries/languages. Their databases vary significantly by language, so check coverage for your market.
• AnswerThePublic — Particularly useful for question-oriented keyword discovery. It can surface questions and modifiers around a native-language seed.
• AlsoAsked — Good for mapping the question relationships around a topic, especially when you want to build topic clusters/FAQ content.
• KeywordTool.io — Useful for harvesting autocomplete suggestions from Google and other platforms in different languages.
• Reddit, forums, Quora, local communities, and social platforms — Excellent for finding the actual wording people use. This is particularly valuable in languages where conventional SEO databases have weak coverage.

For long-tail keywords specifically

I’d use a workflow like:

Native-language seed → autocomplete → questions → SERP mining → keyword database → clustering → validation

For example, don't start with an English keyword such as:

“best running shoes for flat feet”

and simply translate it.

Instead, search the equivalent concept natively and collect variations such as:

• “best shoes for flat feet”
• “shoes for flat feet women”
• “running shoes if you have flat feet”
• “why do my feet hurt when running”
• “can you run with flat feet”
• “flat feet running shoes vs normal”
• local/regional ways of describing flat feet or running shoes

The wording people actually search can differ considerably from a literal translation.

Evaluate the keywords

For each candidate, I'd score at least:

The last two are especially important for multilingual SEO. A keyword can have decent volume but be a phrase that native speakers rarely use.

A particularly effective technique

Take your top 20–50 competitors in the target language, export their ranking keywords, and then filter for:

• 3+ word queries
• question queries
• low-to-medium difficulty
• positions 5–30
• keywords where the competitor's page isn't an especially good answer
• queries with clear commercial or problem-solving intent

Then manually inspect the SERPs.

That often produces much better opportunities than simply sorting a keyword database by volume.

If you tell me the language + country + what your site sells/covers, I can suggest a specific tool stack and a step-by-step process for finding long-tail keywords and question queries in that language.

Yes. For a non-English site, I’d use a localized keyword-research stack, rather than simply translating English keywords. Search behavior, wording, intent, and even what counts as a “long-tail” query can differ substantially by language and country.

Best methods

• Google Search Console — Your best source of actual queries in the target language. Export queries, filter by country/page, and look for low-impression, low-ranking, highly specific queries. These often reveal long-tail opportunities that keyword databases miss.
• Google Keyword Planner — Set both the language and target country/region. Use seed terms in the native language and examine related searches, not just translated English terms.
• Google autocomplete + People Also Ask — Search native-language seed terms manually. Record autocomplete suggestions, PAA questions, related searches, and variations in spelling/word order.
• Native-language SERP analysis — Search the query as a local user would. Examine titles, snippets, forums, Reddit-like communities, Q&A sites, and the types of pages Google ranks. This is especially important for determining intent.
• Ahrefs / Semrush — Useful for search volume, keyword difficulty, SERP analysis, related terms, and question keywords in supported markets. Treat their volume estimates as directional rather than absolute, particularly for smaller languages.
• Google Trends — Compare synonymous terms, regional vocabulary, seasonality, and emerging questions in the target country.
• Forums and social communities — Mine recurring questions and the exact language people use. These are excellent for discovering long-tail phrasing before it becomes visible in conventional keyword tools.
• Answer/question databases — Tools such as AlsoAsked can help uncover question relationships and query hierarchies where the target language is supported.
• LLMs + native-language validation — An LLM can expand a seed keyword into hundreds of possible questions, but use it primarily for ideation and clustering. Have a native speaker or actual SERP data validate whether the phrasing sounds natural.

A particularly effective workflow

Suppose your site is in Spanish and your broad topic is jardinería.

Instead of translating:

“how to grow tomatoes in pots”

into Spanish and stopping there, start with native-language seeds such as:

cultivar tomates en maceta

Then collect variations from actual Spanish SERPs:

• cómo cultivar tomates en maceta
• cómo cultivar tomates cherry en maceta
• qué tamaño de maceta necesita un tomate
• cada cuánto regar tomates en maceta
• por qué se ponen amarillas las hojas del tomate
• tomates en maceta necesitan sol directo
• cómo cultivar tomates en maceta en un balcón

Now evaluate each query on several dimensions:

Don't overlook localization

This is one of the biggest differences from English SEO.

A literal translation might be grammatically correct but not how people search. For example, Spanish speakers in Spain and Latin America can use different vocabulary; German searches may combine words differently; Japanese queries may omit things an English query explicitly states.

I'd therefore research at the level of:

language → country → audience → topic → query

rather than simply:

English keyword → translation

If you tell me the language/country of your site and your niche, I can give you a concrete tool stack and a step-by-step process for finding hundreds of long-tail keywords and questions in that language.

Yes. For a non-English site, you’ll usually get better results by combining native-language keyword data + question research + SERP analysis, rather than translating English keyword lists.

Best methods

• Google Search Console — Your best source for actual queries already bringing impressions/clicks. Export queries, then cluster them by intent and topic in the target language.
• Google Keyword Planner — Set the target country/language explicitly. Useful for search volume and related terms, although long-tail coverage can be limited.
• Google Trends — Excellent for comparing terminology, regional variations, seasonality, and the wording people actually use in a particular country.
• Google autocomplete + People Also Ask — Search in the target language and collect autocomplete suggestions, related searches, and PAA questions. These often surface conversational long-tail queries that conventional keyword tools miss.
• Ahrefs — Its Keywords Explorer supports many countries/languages and is particularly useful for filtering by low volume, matching terms, questions, and ranking difficulty.
• Semrush — Useful for multilingual keyword research, competitor keyword gaps, SERP analysis, and question/related-keyword discovery across different databases.
• AlsoAsked — Particularly useful for mapping question relationships (“why,” “how,” “what,” “can I,” etc.) and building content clusters. Coverage varies considerably by language/market.
• AnswerThePublic — Can generate question/preposition-based ideas in multiple languages, though I'd treat its data as idea generation rather than authoritative search-volume data.
• Keywordtool.io — Useful for mining Google/YouTube/Bing autocomplete suggestions in different countries and languages.
• Reddit, forums, Quora, Facebook groups, and local communities — Extremely valuable for discovering the natural vocabulary people use. This is especially important in languages where formal terminology differs from everyday speech.

The important part: don't just translate English keywords

For example, suppose you're targeting Spanish.

An English keyword such as:

"best hiking shoes for wide feet"

shouldn't simply become a translated keyword.

You may discover that Spanish speakers use several genuinely different formulations:

• mejores zapatillas para senderismo y pie ancho
• botas de montaña para pies anchos
• calzado trekking pie ancho
• zapatillas trekking horma ancha
• qué botas usar si tengo el pie ancho
• mejores botas de montaña para pies anchos

Those aren't merely translations—they can represent different search behaviors and intents.

I'd therefore start with native-language seed topics, then expand them using the search behavior of the target market.

How I'd evaluate a long-tail keyword

Don't judge it solely by search volume. For each candidate, score:

A particularly useful workflow

1. Pick 5–20 native-language seed topics.
2. Put them into Keyword Planner, Ahrefs/Semrush, Keywordtool.io, etc.
3. Export thousands of related keywords.
4. Filter for questions + low-volume terms + longer phrases.
5. Search the most promising terms manually in the target country.
6. Record the actual SERP intent and competing pages.
7. Look at PAA, autocomplete, related searches, forums, and discussions.
8. Cluster synonymous questions together.
9. Create one excellent page capable of answering a group of closely related long-tail queries.
10. Feed the resulting data back into Search Console once the content starts ranking.

One important trick: use the target country's Google domain/interface when doing manual research, not just the language. Spanish in Spain, Mexico, Argentina, and Colombia, for example, can produce noticeably different vocabulary and search intent.

If you tell me the language + target country + what your site is about, I can give you a concrete multilingual long-tail research workflow and recommend the best tools/data sources for that particular market.

For non-English websites, long-tail keyword research works best when you combine native-language data sources, search-engine-specific tools, and human language validation. Many SEO tools are English-first, so you often need a broader workflow.

1. Use keyword tools that support multiple languages

General SEO platforms

• semrush.com

• Supports many countries and languages.
• Useful for: - Keyword Magic Tool
• Keyword difficulty estimates
• SERP analysis by country
• Competitor keyword discovery
• ahrefs.com

• Strong for international SEO.
• Useful for: - Finding keywords competitors rank for
• Questions from "Also rank for" data
• Country-specific SERP analysis
• moz.com

• Offers keyword suggestions and difficulty metrics across multiple markets.

Free or lower-cost options

• ads.google.com

• Select the target country and language.
• Good for search volume ranges and related queries.
• trends.google.com

• Excellent for: - Regional wording differences
• Seasonal searches
• Comparing synonyms in different languages
• answerthepublic.com

• Useful for question-based keywords in supported languages.

2. Mine questions directly from search engines

Long-tail keywords often appear as natural questions.

Google search features

Search in the target language and collect:

• "People also ask"
• Autocomplete suggestions
• Related searches
• Featured snippets

Example:

Instead of searching only:

"coffee machine"

Try:

• "which coffee machine is best for a small apartment"
• "how to clean a coffee machine without vinegar"
• "why does my coffee machine leak water"

Do the same in the target language, because translations often produce unnatural keywords.

3. Use local search engines and platforms

Different markets have different search behaviour.

Examples:

Local platforms often reveal wording that global SEO tools miss.

4. Use native-language question databases

Good sources for question keywords:

• reddit.com — search relevant communities in the target language.
• quora.com — useful in some languages.
• Local forums and discussion boards.
• YouTube comments in the target language.
• Product reviews and marketplaces.

These reveal:

• real customer phrasing
• pain points
• comparison searches
• "how do I..." queries

5. Use AI carefully for keyword expansion

AI can help generate variations, but validate everything against search data.

Useful prompts:

"Generate 200 long-tail search queries in [language] that people might use when looking for [topic]. Include informational, comparison, and buying-intent searches."

Then check those ideas with:

• Google Keyword Planner
• Semrush/Ahrefs
• Google autocomplete
• actual SERPs

A common mistake is using machine-translated keywords. A native speaker might search differently.

Example:

English:

"best budget laptop for students"

Literal translation may not match local searches.

Actual searches might use:

• "cheap student laptop"
• "laptop for university"
• "affordable notebook for studying"

6. Evaluate long-tail keywords in the target market

Don't judge keywords only by English SEO metrics. Evaluate:

Search intent

Classify each keyword:

• Informational: - "how to..."
• "what is..."
• Commercial investigation: - "best..."
• "vs..."
• "reviews..."
• Transactional: - "buy..."
• "price..."
• "near me..."

SERP competition

Check:

• Are results dominated by major brands?
• Are forums ranking?
• Are small sites ranking?
• Are there weak pages you can beat?

Local relevance

Ask:

• Does the phrase sound natural to native speakers?
• Is it used in that country?
• Does the product/service exist locally?
• Are spelling variants different?

7. Build a multilingual keyword workflow

A practical process:

1. Pick a topic.
2. Generate seed terms in the native language.
3. Expand using: - autocomplete
4. keyword tools
5. forums
6. competitor pages
7. Remove unnatural translations.
8. Group by search intent.
9. Check SERPs in the target country.
10. Create content around clusters, not individual keywords.

8. Tools specifically useful for international SEO

• sistrix.com — strong in European markets.
• mangools.com — beginner-friendly and supports many locations.
• keywordinsights.ai — helps cluster keywords by intent.
• lowfruits.io — useful for finding low-competition long-tail opportunities.

A strong approach for non-English SEO is usually:

Local autocomplete + competitor research + native forums + keyword database validation

rather than simply translating English keywords. The best long-tail opportunities are often phrases that native users type naturally but that global SEO tools have limited data for.

Yes. For a non-English site, the best approach is to combine native-language keyword data + SERP/question research + competitor mining, rather than simply translating English keywords.

Useful methods

• Google Keyword Planner — Set the target country/language and look for search-volume and competition data. Good baseline, but it can underrepresent very specific long-tail queries.
• Google Search Console — If the site already gets traffic, this is one of the best sources. Filter queries by country/page and look for longer, low-impression queries that already generate impressions.
• Google autocomplete + People Also Ask — Search in the target language and collect autocomplete suggestions, related searches, and PAA questions. This is particularly useful for discovering natural-language questions.
• Semrush / Ahrefs — Both support keyword research in many non-English markets. Look specifically at keyword variations, matching terms, questions, SERP results, and competitor keywords rather than relying only on volume.
• Google Trends — Compare local terminology, spelling variants, and seasonal demand. This is especially valuable because the phrase people actually use may differ substantially from a literal translation.
• AnswerThePublic — Useful for question discovery in supported languages, particularly when you're looking for informational long tails.
• AlsoAsked — Good for mapping the relationships between questions appearing in Google's People Also Ask results.
• KeywordTool.io — Useful for harvesting autocomplete suggestions from Google and other platforms across different languages.
• Reddit, forums, Quora, local communities, YouTube comments, and social platforms — Often the best source of how native speakers actually phrase problems. Mine these for recurring questions and vocabulary, then validate them with search data.

A particularly effective workflow

For each target language:

1. Start with 10–20 seed topics in the site's subject area.
2. Put the native-language versions into Keyword Planner, Ahrefs/Semrush, and Google.
3. Expand them using autocomplete, PAA, related searches, and question tools.
4. Search forums/Reddit/local communities to find phrases people use conversationally.
5. Group the resulting keywords by search intent, not just by linguistic similarity.
6. Check the actual SERP for each promising cluster.
7. Prioritize queries where you see: - Low-to-moderate competition
8. Clear informational or commercial intent
9. Specific problems/questions
10. Weak or outdated results
11. Forums, Reddit, PDFs, or thin pages ranking highly
12. A realistic opportunity for your site to provide a better answer

Don't translate English keywords mechanically

This is probably the biggest issue with multilingual keyword research.

For example, an English search such as:

"best running shoes for flat feet"

might have several natural equivalents in another language, with differences in word order, terminology, singular/plural forms, and even the way people describe the problem.

I'd therefore treat translation as one source of seed keywords, not as the keyword-research method itself.

A better process is:

English concept → native-speaker phrasing → autocomplete/PAA → local SERP → keyword database → competitor analysis

How I'd evaluate a long-tail keyword

Don't focus exclusively on search volume. I'd score each candidate on something like:

One important trick: look for low-volume keywords with high intent. A question with only 20–50 searches/month can be considerably more valuable than a 5,000-search generic term if the searcher has a very specific problem and your page can answer it exceptionally well.

If you tell me the language and country your site targets (e.g. German/Germany, Spanish/Mexico, French/France), I can give you a specific tool stack and workflow for finding long-tail keywords + question clusters in that language, including which tools are strongest for that market.

For non-English SEO, the biggest challenge is that keyword tools often have weaker coverage outside English, and literal translations usually miss how people actually search. A good approach combines native-language data sources, search behavior tools, and SERP analysis.

1. Use local-language keyword research tools

Many global tools support multiple languages, but coverage varies:

• ahrefs.com — Good for keyword difficulty, related terms, questions, and competitor analysis across many countries/languages.
• semrush.com — Useful for multilingual keyword databases, competitor keywords, and SERP features.
• ads.google.com — Free and often one of the best sources because it uses Google search data by country and language.
• trends.google.com — Helps identify local phrasing, seasonal demand, and regional differences.

For smaller languages, Google tools often outperform commercial databases because they have more direct search data.

2. Mine questions people ask in that language

Long-tail keywords are frequently questions. Sources:

• google.com autocomplete:

• Start typing a phrase in the target language.
• Record autocomplete suggestions.
• Repeat with question words (equivalents of “how,” “why,” “which,” “best,” “where,” etc.).
• Google “People also ask” boxes:

• Search target-language phrases.
• Collect related questions.
• Group them by topic.
• answerthepublic.com — Generates question-style keyword ideas in supported languages.
• Forums and communities:

• Local Reddit communities
• Regional forums
• Facebook groups
• Quora versions in that language
• Industry-specific communities

These often reveal wording that keyword tools miss.

3. Analyze competitors in the target language

Instead of translating English keywords:

1. Find the top-ranking local sites for your topic.
2. Export their ranking keywords.
3. Look for: - phrases with 3–8 words
4. question formats
5. comparison searches
6. “near me” variations
7. problem-based searches

Tools:

• ahrefs.com
• semrush.com
• moz.com

4. Use native speakers or language models for query expansion

Machine translation is usually insufficient because search intent differs.

A better workflow:

1. Take a seed topic.
2. Ask a native speaker or language model: - “How would a person in [country] search for this problem?”
3. “What informal phrases would they use?”
4. “What questions would beginners ask?”
5. Validate those phrases using search volume and SERPs.

For example, English:

“cheap flights to Japan”

might become several different searches in another language:

• a formal travel phrase
• a conversational phrase
• a phrase used by younger travelers
• a local abbreviation

5. Evaluate keywords beyond search volume

For long-tail terms, prioritize:

Search intent

Classify each keyword:

• Informational:

• “how to…”
• “why does…”
• “what is…”
• Commercial investigation:

• “best…”
• “reviews of…”
• “comparison…”
• Transactional:

• “buy…”
• “price…”
• “near me…”

SERP competition

Check:

• Are ranking pages weak?
• Are forums ranking?
• Are outdated pages ranking?
• Are results poorly localized?

A low-volume keyword with weak competition can outperform a high-volume generic term.

Language variations

Check:

• formal vs informal wording
• regional differences
• spelling variations
• singular/plural forms
• local terminology

6. Useful additional sources for international SEO

• search.google.com — Once your site has traffic, it reveals the exact queries users use in that language.
• bing.com — Helpful for some markets where Bing has stronger usage.
• keywordtool.io — Uses autocomplete sources across languages.
• alsoasked.com — Finds question relationships from “People also ask” data.

A practical workflow

1. Pick 20–50 seed topics in the target language.
2. Expand them using: - Google autocomplete
3. People Also Ask
4. local forums
5. competitor keywords
6. Remove unnatural translations.
7. Group keywords by search intent.
8. Check volume and competition.
9. Create content around topic clusters, not individual keywords.

For very small-language markets, SERP analysis + native phrasing research usually matters more than keyword volume estimates, because the databases may underestimate demand.

For a non-English website, long-tail keyword research works best when you combine native-language search data, question discovery, and SERP analysis in the target market. Many English-focused SEO tools have weaker coverage outside English, so a mix of tools is usually better.

1. Use country-specific keyword databases

ads.google.com

• Set the target country and language rather than relying on your account defaults.
• Export related keywords, search volume, competition, and variations.
• Useful for languages with strong Google usage.

semrush.com

• Supports many languages and locations.
• Good for: - long-tail variations
• keyword clusters
• intent filtering
• competitor keyword discovery

ahrefs.com

• Strong for international SEO because it provides: - keyword difficulty
• clicks estimates
• SERP analysis
• related terms in many languages

2. Mine real questions people ask

Long-tail keywords are often questions, especially in non-English markets.

answerthepublic.com

Useful for finding:

• "how to..."
• "why..."
• "best..."
• "vs..."
• "near me..."
• problem-based searches

Enter the keyword in the target language. Results quality varies by language, so validate them afterward.

alsoasked.com

Good for discovering Google's "People Also Ask" questions by country and language.

Google itself:

Search your topic in the target language and collect:

• autocomplete suggestions
• "People also ask"
• related searches
• forum/community results

Autocomplete is especially valuable because it reflects actual search behavior.

3. Analyze local competitors

For non-English SEO, competitors often reveal keywords faster than tools.

Process:

1. Find the top-ranking sites in the target language.
2. Export their ranking keywords.
3. Identify pages ranking for: - low-volume terms
4. question queries
5. comparison searches
6. specific product/service variations

Tools:

• semrush.com
• ahrefs.com

4. Use local-language SEO tools

Depending on the language, regional tools can outperform global platforms.

Examples:

• Japanese: keywordmap.jp
• Korean: searchadvisor.naver.com (important because Naver has significant market share)
• Chinese: e.baidu.com
• Russian: wordstat.yandex.com
• German/French/Spanish/Italian: Semrush, Ahrefs, Sistrix, and Google tools generally have stronger coverage

5. Use native-language SERP evaluation

Finding a keyword is only half the job. Evaluate:

Search intent

Ask:

• Are results informational, commercial, or transactional?
• Are searchers looking for guides, products, services, comparisons, or local businesses?

Competition quality

Look at:

• domain authority of ranking sites
• content depth
• whether results actually answer the query
• gaps in existing pages

Content gaps

Long-tail opportunities often appear when:

• current results are outdated
• pages are poorly translated
• answers are too generic
• no one addresses a specific user situation

6. Use forums and communities in the target language

These are excellent sources of natural phrasing.

Examples:

• Reddit communities in the target language
• local forums
• YouTube comments
• Facebook groups
• Quora equivalents
• marketplace reviews

Look for repeated phrases:

• "How do I..."
• "Is it worth..."
• "What is the difference between..."
• "Which one should I choose..."

Those phrases often become high-converting long-tail keywords.

7. Use AI carefully for keyword expansion

AI can help generate variations, but validate everything with search data.

Good prompts:

• "Generate 100 search queries a native speaker would use when trying to solve [problem] in [language]."
• "Group these keywords by search intent."
• "Rewrite these keywords using natural phrasing used in [country]."

Avoid relying on direct translation. A phrase that sounds logical in English may not be how people search in another language.

8. Build a practical workflow

A reliable international keyword workflow:

1. Pick a topic.
2. Collect: - Google autocomplete terms
3. People Also Ask questions
4. competitor keywords
5. forum language
6. Expand with Ahrefs/Semrush/Keyword Planner.
7. Remove: - unnatural translations
8. irrelevant variants
9. keywords with mismatched intent
10. Group into content clusters: - main topic page
11. supporting articles
12. FAQ pages
13. comparison pages
14. Verify the final terms with native speakers or local SERPs.

The biggest mistake in multilingual SEO is translating English keywords. The best long-tail opportunities usually come from discovering how native speakers describe their problems, not from translating existing English searches.

Avoid relying on direct translation. A phrase that sounds logical in English may not be how people search in another language.

8. Build a practical workflow

A reliable international keyword workflow:

Yes. For a non-English site, I’d avoid treating keyword research as “translate my English keywords.” The goal is to discover what people actually type in that language and market, including colloquial wording, local terminology, misspellings, and question formats.

Best methods

1. Start with native-language seed keywords

Create a small set of genuinely native seeds for each major topic. Ideally, have a native speaker/local SEO review them rather than simply translating English terms.

Then expand each seed using:

• Singular/plural and grammatical variations
• Formal vs. conversational wording
• Regional vocabulary
• Local product/service names
• Common abbreviations
• Spelling mistakes and transliterations
• “how,” “why,” “can I,” “where,” “which,” “is it worth it,” etc. in the target language

This matters because literal translations can have very different search demand from the phrase a native speaker would actually use.

2. Use Google autocomplete and related searches

This is one of the best sources for long-tail language-specific phrasing because you're observing actual search behavior rather than relying entirely on translated keyword databases.

Try seeds in the target language and collect:

• Autocomplete suggestions
• “People also ask” questions
• Related searches
• Search-result snippets
• Questions appearing in forums and community sites

I'd especially look for repeated question patterns. For example, if several searches follow the structure “[product] + is it safe to…”, that can reveal an entire content cluster rather than just one keyword.

3. Google Trends is particularly useful for multilingual research

trends.google.com lets you compare search behavior by country and language. Importantly, Google distinguishes between an exact search term and a broader topic. Topics can aggregate related searches across languages, while search terms are literal strings. Google Help Google Help

For example, you can compare:

• Local-language wording A vs. wording B
• Formal vs. colloquial terminology
• Two competing translations
• Different regional terms

This is excellent for deciding which native phrasing deserves to become the primary keyword.

4. Use a serious keyword database for volume + competition

For larger-scale research, I'd consider:

• ahrefs.com — particularly good for finding questions, autocomplete suggestions, related terms, and keywords that competing pages rank for. Its Keyword Generator supports question keywords and location-specific search-volume estimates. Ahrefs Ahrefs also publishes a locale list showing the languages/countries supported by Keywords Explorer. Ahrefs Help Center
• semrush.com — useful for multilingual keyword databases, keyword grouping, intent, difficulty, SERP features, and a dedicated questions filter. Semrush Semrush
• ads.google.com — useful as a second source for localized search-volume estimates, particularly when you're targeting a specific country.

Don't rely on one database's volume number. In smaller-language markets, estimates can be much less reliable than in English.

5. Mine your own Google Search Console data

This is arguably the highest-value source once the site has traffic.

search.google.com shows the actual queries that generated impressions and clicks for your site. You can analyze queries alongside pages, countries, CTR, impressions, and average position. Google Help Google Help

Look specifically for:

• Queries with impressions but few/no clicks
• Queries where you're ranking around positions 5–20
• Very specific queries that already generate impressions
• Questions for which your existing page appears
• Unexpected synonyms/wording
• Queries that don't have a dedicated page yet

Those are often much better long-tail opportunities than keywords discovered from a generic keyword tool.

6. Mine competitors' rankings in the target language

Put 5–20 strong local competitors into Ahrefs/Semrush and extract:

• Keywords they rank for
• Long-tail keywords driving traffic
• Questions
• Keywords where multiple competitors rank
• Keywords where they rank in positions 4–20
• Pages receiving traffic from clusters of related queries

The intersection of several competitors' keyword sets is particularly valuable: it indicates a topic that the local market already considers relevant.

7. Research questions outside traditional SEO tools

For question discovery, don't restrict yourself to keyword databases.

Look at the target-language equivalents of:

• Reddit
• Quora
• YouTube comments
• Local forums
• Facebook groups
• Product reviews
• App-store reviews
• E-commerce reviews
• Customer-support questions
• Community sites

You're looking for the language people use when they have a problem, rather than the polished terminology marketers use.

For example, a keyword tool might give you:

“best X for Y”

But a forum might reveal:

“X doesn't work when I do Y — what am I doing wrong?”

The second can be a much more useful long-tail content opportunity.

How I'd evaluate the keywords

I'd score each candidate on something like this:

I'd give language quality unusually high weight for non-English SEO.

A keyword with 500 searches/month that sounds unnatural to native speakers can be substantially less valuable than a naturally phrased keyword with 100 searches/month.

A particularly effective workflow

For each topic, I'd do this:

Native seeds → Google autocomplete/PAA → Ahrefs/Semrush expansion → competitor keywords → forums/reviews → Google Trends → Search Console → SERP analysis → keyword clustering.

Then cluster keywords by search intent, not merely by similar words.

For example, these might all belong to one content cluster:

• “how to clean X”
• “best way to clean X”
• “can I clean X with Y”
• “X cleaning instructions”
• “what can I use to clean X”
• “[local-language colloquial version of the same question]”

You don't necessarily want six pages. You may want one excellent page that answers the whole question cluster.

One important multilingual SEO rule

Don't automatically create one translated page per keyword.

Instead, determine whether the local audience has:

1. the same concept + different wording → one page can target the cluster;
2. a genuinely different intent → separate page;
3. a culturally/local-specific question → create native content rather than translated content.

Google Trends' distinction between literal search terms and broader topics is useful here because it helps separate wording differences from genuinely different search interests. Google Help

If you tell me the language/country your site targets and your niche, I can suggest a concrete multilingual keyword-research stack and workflow—including which tools I'd use, what I'd search for, and how I'd build a long-tail/question database for that particular market.

The second can be a much more useful long-tail content opportunity.

How I'd evaluate the keywords

I'd score each candidate on something like this:

I'd give language quality unusually high weight for non-English SEO.

A keyword with 500 searches/month that sounds unnatural to native speakers can be substantially less valuable than a naturally phrased keyword with 100 searches/month.

A particularly effective workflow

For each topic, I'd do this:

Native seeds → Google autocomplete/PAA → Ahrefs/Semrush expansion → competitor keywords → forums/reviews → Google Trends → Search Console → SERP analysis → keyword clustering.

Then cluster keywords by search intent, not merely by similar words.

For example, these might all belong to one content cluster:

• “how to clean X”
• “best way to clean X”
• “can I clean X with Y”
• “X cleaning instructions”
• “what can I use to clean X”
• “[local-language colloquial version of the same question]”

You don't necessarily want six pages. You may want one excellent page that answers the whole question cluster.

One important multilingual SEO rule

Don't automatically create one translated page per keyword.

Instead, determine whether the local audience has:

1. the same concept + different wording → one page can target the cluster;
2. a genuinely different intent → separate page;
3. a culturally/local-specific question → create native content rather than translated content.

Google Trends' distinction between literal search terms and broader topics is useful here because it helps separate wording differences from genuinely different search interests.

Yes. For multilingual SEO, the biggest mistake is translating English keyword lists and assuming people search the same way. You want to discover the native search language—including colloquialisms, local terminology, spelling variants, and question patterns.

Best methods/tools

A particularly good multilingual workflow

Suppose your site is about home coffee equipment and you're targeting German speakers.

Don't start with:

English keyword → translate → German keyword

Instead:

1. Build topic concepts in English.

For example:

• best espresso machine
• espresso machine for beginners
• how to clean espresso machine
• espresso machine making weird noise

2. Have a native speaker/LLM generate search-intent variants, not literal translations.

For each concept, generate:

• formal wording
• colloquial wording
• abbreviated wording
• regional variants
• singular/plural variants
• beginner questions
• troubleshooting questions
• comparison questions
• "is X worth it?" questions
• "how much does X cost?" questions

3. Put those native-language seeds into Keyword Planner/Ahrefs/Semrush.

This is where you'll uncover the second layer of long tails that wouldn't appear from translation alone.

4. Use Google itself as a question generator.

Take a native phrase and progressively search:

[topic]
[topic] wie
[topic] warum
[topic] welche
[topic] kann man
[topic] lohnt sich
[topic] erfahrungen
[topic] problem

For languages where those interrogative words differ, use the equivalent local patterns.

Then mine:

• autocomplete
• People Also Ask
• related searches
• titles/headings of ranking pages

5. Check Google Trends in the target country.

This is especially valuable for multilingual SEO because you can compare different ways of expressing the same concept. Google Trends lets you compare terms across languages and locations, while its "topic" data can aggregate related searches across languages. support.google.comsupport.google.com

For example, you might discover that the technically correct translation has substantially less interest than the colloquial term people actually use.

Don't overlook regional language differences

This matters enormously for languages such as:

• Spanish — Spain vs Mexico vs Argentina
• Portuguese — Brazil vs Portugal
• French — France vs Canada vs Belgium
• German — Germany vs Austria vs Switzerland
• Arabic — Modern Standard Arabic vs country-specific usage
• Chinese — Simplified vs Traditional + regional vocabulary

Google Trends can show geographic differences in relative search interest, which makes it useful for deciding whether a keyword is genuinely appropriate for your target market. support.google.com

How I'd evaluate a long-tail keyword

Don't rank keywords solely by volume. I'd score each candidate on:

Opportunity = relevance × intent × demand × SERP weakness

Look at:

1. Intent — Is the searcher looking for information, comparison, a product, or a solution?
2. Business value — Could this query eventually lead to a customer?
3. Demand — Keyword Planner/Ahrefs/Semrush estimates + Trends.
4. SERP competition — Who actually ranks?
5. Content quality — Are the current results genuinely good?
6. Localization — Are results from the correct country and language?
7. Specificity — Does the long tail reveal a particular problem/use case?
8. Question depth — Can you answer the question substantially better than existing results?

The last two are particularly useful for multilingual sites because low-volume questions can collectively form a substantial topic cluster.

One important caveat

Don't assume that a keyword database's "zero volume" means nobody searches it. Long-tail queries in smaller languages can fall below reporting thresholds. Google Trends itself notes that queries with insufficient search volume may not generate a graph. support.google.com

So I'd treat third-party volume as directional, not absolute.

My preferred stack

For a serious multilingual SEO project, I'd use:

Google Keyword Planner → Ahrefs/Semrush → Google autocomplete/PAA → Google Trends → Search Console → native-speaker SERP review

The native SERP review is the quality-control step. Search the query exactly as a local user would and ask: "Would an actual person in this market phrase the problem this way?"

If you tell me the language(s), target country, and what your site sells/does, I can also give you a concrete multilingual keyword-research process—including how I'd generate hundreds of long-tail questions without simply translating English keywords.

Yes. For non-English SEO, the biggest mistake is treating translation as keyword research. You generally want to discover how native speakers actually search, including regional vocabulary, spelling variants, colloquialisms, and question phrasing.

Best methods and tools

For languages other than English, I'd use this workflow

1. Start with native-language seed concepts, not translated English keywords.

For example, don't simply translate:

“best running shoes for flat feet”

into another language and assume that's what people search.

Instead, find the local ways people describe the problem, product, and intent. A native speaker might use a completely different construction.

2. Use Google itself as a language-specific research tool.

Search the seed term in the target country's Google and collect:

• autocomplete suggestions
• “People also ask”
• related searches
• suggested category/product terms
• titles and wording used by ranking pages

Do this while using the target country's Google results, because vocabulary can differ dramatically between countries that share a language.

For example, Spanish SEO should usually be researched separately for Spain, Mexico, Argentina, Colombia, etc., rather than treating “Spanish” as one market.

3. Mine questions systematically.

Take a core topic and generate question modifiers such as:

• what / which
• how
• why
• when
• where
• can
• should
• is it worth it
• alternatives
• comparison
• price/cost
• problems
• benefits
• reviews
• for beginners
• near me
• before/after

Then validate those questions against actual search results.

4. Look for long-tail intent, not just low-volume keywords.

A keyword with 20 searches/month can be more valuable than one with 2,000 if the searcher is much closer to conversion.

I'd classify your candidates into buckets such as:

• Informational: “how does X work?”
• Problem: “why does X happen?”
• Comparison: “X vs Y”
• Commercial: “best X for Y”
• Transactional: “buy X”
• Local: “X near me”
• Post-purchase: “how to use/fix X”
• Question: “can I X if Y?”

Particularly useful for multilingual SEO

Google Trends is underrated. It can reveal that two apparently equivalent words have very different popularity in different countries.

Ahrefs/Semrush are useful when you need scale, but check their database coverage for your particular language/country. English tends to have much deeper keyword datasets than smaller languages.

Google Search Console becomes extremely powerful after launch. Export queries containing question words, modifiers, product terms, etc. You'll often discover long-tail queries that third-party databases don't report.

Forums and social communities are especially useful for languages with weaker SEO databases. Search native-language discussions for phrases people actually use. Those phrases can become excellent long-tail keyword candidates.

One important trick: don't automatically "correct" the language

For multilingual keyword research, misspellings, slang, abbreviations, local terminology, and mixed-language searches can matter.

For example, people may search using:

• an English product name inside an otherwise non-English query
• an untranslated technical term
• local slang
• a regional spelling
• an acronym
• a singular/plural form that sounds grammatically unusual

If real users search that way and the intent is legitimate, it's data—not necessarily something to eliminate.

A practical stack

If I were building a non-English keyword research process today, I'd use:

Discovery: Google autocomplete + PAA + Trends + native forums
↓
Expansion: Ahrefs/Semrush + AlsoAsked/AnswerThePublic + LLM
↓
Validation: Google SERPs + Keyword Planner + Trends
↓
Prioritization: search intent + business value + ranking difficulty + topical relevance
↓
Reality check: Search Console after publishing

The key is to use AI for expansion, but search engines and real search data for validation. AI can produce wonderfully plausible keywords that essentially nobody searches.

If you tell me the language, target country, and type of site/niche, I can also suggest a concrete multilingual long-tail research process and the best tools for that particular market.

Yes. For a non-English site, I’d avoid simply translating an English keyword list. The best results come from researching how people actually search in the target language and market, including colloquialisms, regional vocabulary, misspellings, and question phrasing.

Best tools

• ahrefs.com — One of the strongest options for multilingual research. It supports a large number of country/language combinations, including Spanish, French, German, Portuguese, Arabic, Japanese, Korean, Vietnamese, Thai, Turkish, Polish, etc. Its keyword database has separate indexes for search patterns and keywords websites rank for. Ahrefs Help Center
• semrush.com — Particularly useful for long-tail discovery because it groups related terms, has a Questions filter, intent/KD filters, and language filtering. Semrush currently reports 28B+ keywords across 142 regional databases. Semrush Semrush
• ads.google.com — Good free/low-cost validation source. You can specify both location and language, enter seed terms or a website, and get search-volume estimates and related ideas. Google Help Google Help
• Google Search Console — Extremely valuable once your site has traffic. Your actual impressions reveal long-tail queries that third-party tools may never show, especially very low-volume queries.
• Google itself — Search your target-language seeds and mine autocomplete, People Also Ask, related searches, and the actual wording of top-ranking pages. This is particularly important for languages where keyword databases are thinner.

How I'd find long-tail questions

Suppose your site is about running shoes and is in Spanish.

Don't just translate:

best running shoes for beginners

into:

mejores zapatillas para correr para principiantes

Instead, start with several native-language seed concepts, then expand them.

For example:

• zapatillas para empezar a correr
• qué zapatillas usar para correr
• cómo elegir zapatillas para correr
• zapatillas correr principiantes
• qué zapatillas son mejores para correr
• zapatillas para correr si tengo...
• cuánto duran las zapatillas de running

Then use Ahrefs/Semrush/Google to expand those into hundreds of variations.

The important distinction is that long-tail keywords aren't necessarily just long phrases. They're often highly specific intent:

"qué zapatillas usar para correr si peso 100 kg"

may be much more valuable than a generic high-volume keyword such as "zapatillas running."

A particularly good method for questions

Build question modifiers in the target language, rather than translating an English question list.

For example, identify the local equivalents of:

• what / which
• how
• why
• when
• where
• how much
• how long
• can I
• is it worth
• does X work
• X vs Y
• X or Y
• alternatives to X
• problems with X
• X for [specific audience]
• X without [constraint]

Then combine them with your topical seeds.

For Spanish, for example:

cómo, qué, cuál, cuándo, dónde, por qué, cuánto, puedo, merece la pena, es mejor, se puede, etc.

For German you'd use an entirely different set of natural constructions. That's why native-language query expansion beats machine-translating an English keyword list.

Semrush's Questions filter is useful here; it specifically surfaces question-form queries and can be combined with its other filters. Semrush

Don't overlook regional language

This is one of the biggest opportunities in international SEO.

The same language can have substantially different search vocabulary by country.

For example, Spanish searches in:

• Spain
• Mexico
• Argentina
• Colombia
• Chile

can use different words for the same product or concept.

So I'd research country + language, not merely "Spanish."

Ahrefs explicitly provides country/language locales such as Spain, Mexico, Argentina, Colombia, Chile, etc. Ahrefs Help Center Google Keyword Planner likewise lets you narrow keyword ideas by geographic location and language. Google Help

How to evaluate the keywords

I'd score each candidate on five dimensions:

For long-tail keywords, I would put intent and SERP competitiveness above raw volume.

A keyword with 20 searches/month where you can rank #1 and the searcher is highly qualified can be considerably better than a 10,000/month term dominated by huge sites.

The underrated technique: competitor mining

For multilingual SEO, this is one of my favorite approaches.

Find 3–10 successful sites actually operating in the target language/country and put their domains into Ahrefs or Semrush.

Look for:

1. Keywords they rank for that you don't.
2. Keywords where they're ranking positions 4–20.
3. Question queries driving impressions.
4. Pages receiving traffic from hundreds of related long-tail queries.
5. Topics competitors have covered poorly.

Semrush's Keyword Gap, for example, is specifically designed to compare competitors' keyword portfolios and identify gaps. Semrush

Then inspect the actual SERPs for the best opportunities. Don't blindly trust a difficulty score.

My preferred workflow

I'd use this pipeline:

1. Native seed research → 2. Keyword database expansion → 3. Google SERP mining → 4. Competitor keyword mining → 5. Search Console data → 6. Cluster questions by intent → 7. Manually evaluate SERPs

For each keyword, keep:

keyword | country | language | volume | KD | intent | SERP type | ranking competitors | business value | content cluster

Then cluster semantically related queries into one page/topic rather than creating a separate page for every tiny variation.

That last point matters a lot: 30 different long-tail queries may actually represent one underlying search intent and should often be answered by one exceptionally comprehensive page.

If you tell me the language + target country + what your site sells/covers, I can give you a concrete multilingual keyword-research process, including the best tools for that particular language and a set of question/long-tail patterns to start with.

My preferred workflow

I'd use this pipeline:

For non-English SEO, the biggest mistake is treating keyword research as a direct translation exercise. Search behavior, vocabulary, spelling variants, and the way people phrase questions can differ substantially by country and language.

A good workflow combines native-language search data + SERP analysis + question mining + competitor research.

Tools worth using

For long-tail questions specifically

I'd use this process:

1. Start with native-language seed terms.

Don't translate your English keyword literally. Instead, get 10–30 concepts in English and have a native speaker—or an LLM with strong knowledge of the target market—generate the ways someone in that country would actually express each concept.

For example, instead of translating:

"best way to clean a leather sofa"

also investigate variations equivalent to:

• how to clean...
• what can I use to clean...
• can I clean X with Y?
• X has a stain, what do I do?
• how do I remove X from...
• is X safe for...
• X vs Y for cleaning...
• how often should I...

Those question patterns are often where the long tail lives.

2. Put the native-language seeds into Google itself.

Autocomplete and PAA are particularly useful because they expose Google's understanding of the local search ecosystem.

Search the term, then investigate:

• Autocomplete suggestions
• People Also Ask
• Related searches
• Top-ranking pages
• Featured snippets
• Forums appearing in the SERPs

Repeat this for several different formulations rather than just one translated keyword.

3. Mine competitors in the target country.

This is one of the highest-value methods.

In Ahrefs/Semrush/Sistrix, find websites ranking for your major topics in the target country, then export the keywords for which those sites rank.

Filter for things like:

• low difficulty
• informational intent
• 3+ word queries
• question words
• relatively low-volume terms
• keywords where competitors rank with relatively weak pages

You can uncover hundreds or thousands of long-tail opportunities this way.

4. Build a multilingual question corpus.

For each topic, collect questions from:

• Google PAA
• Google autocomplete
• Reddit
• Quora
• local forums
• YouTube comments/search
• competitor FAQs
• customer-support questions
• your Search Console data

Then cluster them by search intent, not simply by linguistic similarity.

For example:

"how to fix X"
"X isn't working"
"why does X happen"
"X stopped working"

may belong to one underlying problem even though the wording differs.

One particularly important issue: localization

Suppose your site targets Spanish speakers.

Don't think:

English keyword → Spanish translation → Spanish keyword

Think:

Topic → Spain terminology / Mexican terminology / Argentine terminology / etc. → actual SERPs → search intent

"Car," "computer," "apartment," "cell phone," etc. can have materially different search terms across countries. Even spelling, formality, and preferred question structures can differ.

So language and country should be separate dimensions in your research.

How I'd evaluate a long-tail keyword

Don't obsess over volume alone. I'd score each opportunity on something like:

Opportunity = relevance × intent × ranking feasibility × commercial value

Look at:

1. Is the query genuinely relevant?
2. Does the SERP match the content you could produce?
3. Are the current results weak, outdated, or poorly localized?
4. Is there evidence of commercial intent?
5. Does the keyword represent a larger topic cluster?
6. Can one page answer several closely related questions?
7. Is the wording actually used by people in your target market?

A keyword with 20 searches/month and extremely strong intent can be much more valuable than one with 2,000 searches/month where the intent is ambiguous.

An advanced tactic: reverse-engineer questions from SERPs

This works especially well for smaller languages.

Take a high-value topic and examine the top 10–20 pages ranking in the target country. Extract:

• H2/H3 headings
• FAQ questions
• title phrasing
• terms repeatedly used in the pages
• questions in PAA
• related entities/topics

Then use those to generate a second round of searches.

This creates a loop:

seed → local SERP → questions → competitor pages → related terms → new searches → SERP validation

That's generally much more reliable than simply asking an SEO tool for "long-tail keywords in German/French/Japanese/etc."

If you tell me the language + target country + your site's topic, I can suggest a concrete multilingual keyword-research workflow and the best tools/data sources for that particular market.

Yes. For non-English SEO, the biggest mistake is treating keyword research as a direct translation exercise. Search behavior, phrasing, slang, spelling variants, and the way people ask questions can differ substantially by language and country.

Best methods

1. Use Google Keyword Planner in the target language/country
   • Set the location and language explicitly.
   • Look at related terms, search volumes, and keyword variations.
   • Don't just translate your English seed keywords—enter native-language seed phrases.

2. Mine Google autocomplete

Search your core topic in the target language and vary the query:

• what is X equivalents
• how to X
• X vs Y
• X for beginners
• X price
• X near me
• can X...
• is X...

Autocomplete is particularly useful for discovering natural, conversational long-tail queries.

3. Use Google's "People also ask"

Search several variations of your topic in the target language. Record recurring questions and group them by intent. This is often better for question discovery than relying solely on keyword-volume databases.

4. Use SEO platforms with international databases

Good options include:

• Semrush — international keyword databases, keyword variations, questions, SERP analysis.
• Ahrefs — keyword explorer, matching terms, related terms, questions and country-specific SERPs.
• Mangools — simpler interface and useful country/language targeting.
• KeywordTool.io — useful for autocomplete-based long-tail discovery across multiple search engines.

5. Use native-language SERP analysis

This is one of the most valuable methods. Search the target query as a local user would and examine:

• titles of ranking pages
• headings
• related searches
• PAA questions
• forums and Q&A sites
• terminology competitors use

You can discover long tails that conventional keyword tools don't have enough data for.

For questions specifically

I'd combine Google PAA + autocomplete + Reddit/forums + competitor pages.

For example, rather than translating:

"best running shoes for flat feet"

into another language, start with the native-language concept and see how actual users phrase it. You might find several distinct intents equivalent to:

• best shoes for people with flat feet
• running shoes for flat feet
• shoes that help with flat feet
• can I run with flat feet?
• are stability shoes good for flat feet?
• flat feet causing knee pain when running
• how to choose running shoes for flat feet

Those aren't merely linguistic variations—they represent different search intents and potentially different pages.

Tools for discovering questions at scale

• AlsoAsked — maps Google's People Also Ask relationships and is particularly useful for building question/topic clusters. AlsoAsked
• AnswerThePublic — generates question and phrase variations around a seed topic. AnswerThePublic
• Google Trends — useful for comparing native terminology, regional variations, and emerging queries. Google Trends
• Google Search Console — once you have traffic, this becomes one of your best sources because it reveals the actual language users employ to reach your site.

An important trick for multilingual SEO

If your site targets, say, Brazilian Portuguese, don't research just "Portuguese."

Research:

language + country + audience

For example, Brazilian Portuguese can differ meaningfully from European Portuguese in vocabulary and search behavior. The same applies to Spanish across Mexico, Spain, Argentina, Colombia, etc.

I'd therefore build keyword datasets around:

Topic → country → native seed terms → autocomplete → PAA → SERPs → competitor keywords → Search Console → clustering

Then evaluate each keyword on search intent, relevance, SERP competition, business value, and topical coverage, rather than relying on search volume alone.

If you tell me the language/country and your site's niche, I can also suggest a concrete research workflow and the best tools for that particular market.

Yes. For non-English SEO, the key is not to simply translate your English keyword list. Search behavior, phrasing, word order, dialect, and even what people consider a “natural” question can differ substantially by market.

Best methods and tools

1. Start with native-language seed terms

Suppose your site is about running shoes in Spanish.

Don't start with:

English keyword → machine translation → Spanish keyword

Instead, have a native speaker—or an LLM plus native-speaker validation—generate multiple ways a person in that market might actually search:

• comprar zapatillas para correr
• mejores zapatillas para correr
• zapatillas para correr principiantes
• qué zapatillas usar para correr
• zapatillas para correr si tengo el pie ancho
• cómo elegir zapatillas para correr
• cuánto duran unas zapatillas de running

The last few are particularly valuable because they're closer to problem/question searches rather than generic head terms.

2. Use Ahrefs or Semrush with the country + language set correctly

Both are particularly useful for international keyword research.

Ahrefs supports a large number of country/language combinations—for example Spanish in Spain, Mexico, Colombia, etc.—rather than treating “Spanish” as one homogeneous search market. help.ahrefs.comahrefs.com

Its keyword reports can also surface Questions, Google autocomplete suggestions, related terms, and terms that top-ranking pages rank for. help.ahrefs.com

Semrush's Keyword Magic Tool similarly provides related keywords, topic subgroups, question-only filtering, volume, difficulty and SERP information, with regional keyword databases. www.semrush.com

Important: select the actual target market.
For example, don't research generic “Spanish” if you're targeting Mexico. Search behavior for Mexico, Spain, Argentina, Colombia, etc. can be quite different.

3. Mine questions separately

For question-focused long tails, I'd build a question corpus using several sources:

Keyword tools

• Filter for question keywords in Ahrefs/Semrush.
• Use broad seeds rather than very specific ones. Ahrefs specifically recommends broad seeds when using its Questions filter. help.ahrefs.com

Google autocomplete
Search the local-language seed and try modifiers equivalent to:

• how
• why
• what
• which
• when
• can
• is
• does
• where
• how much
• how long

But don't assume literal translations. The natural question words and constructions of the target language matter.

SERP “People also ask”
Search your seed terms in the target language and country. Record recurring questions and look at the pages Google considers authoritative enough to answer them.

4. Use Google Keyword Planner as a reality check

Google Keyword Planner lets you specify both location and language, and provides search-volume/trend estimates. business.google.com

This is useful because a third-party tool might tell you that a particular long-tail has, say, 150 searches/month, but Keyword Planner can give you another data point from Google's ecosystem.

I'd use it less as an absolute truth and more as validation of relative demand.

5. Mine your competitors' local-language traffic

This is one of my favorite methods.

Take 5–20 competitors that genuinely rank in the target country and put their domains into Ahrefs/Semrush.

Look specifically for:

• keywords ranking positions 4–30
• question keywords
• very long queries
• keywords with relatively low difficulty
• queries where multiple competitors rank
• queries where competitors have weak/thin pages

You're essentially asking:

“What does Google already believe people in this language/market want, and which competitors are successfully answering it?”

That's usually more useful than generating thousands of AI-translated keywords.

6. Don't overlook local vocabulary

This is especially important in multilingual SEO.

For example, users might use different words for the same object depending on country, region, or demographic.

You can discover these differences through:

• Google autocomplete
• local competitor sites
• Google Trends
• Reddit/local forums
• YouTube search suggestions
• customer support queries
• product reviews
• native-speaking writers/editors

Google Trends is particularly useful for comparing alternative terms across geographic markets.

7. Use your own Search Console data as a gold mine

Once your site has traffic, Search Console becomes one of the best sources because you're no longer guessing what your audience searches.

Export queries and look for:

High impressions + low CTR
→ potential title/meta/content improvements.

Position 5–20
→ existing pages with realistic opportunities.

Very specific queries
→ potential FAQ sections or dedicated pages.

Unexpected questions
→ excellent content opportunities.

Several related queries landing on one page
→ potential topic cluster.

And don't throw away low-volume queries. Individually they may look insignificant, but hundreds of related long tails can represent substantial aggregate demand.

A particularly effective workflow

I'd use this process for each language/market:

1. Build 50–100 native seed concepts
Not translations—actual concepts and problems customers have.

2. Expand them in Ahrefs/Semrush
Collect related terms, questions, autocomplete-derived ideas and competitor terms. www.semrush.comhelp.ahrefs.com

3. Expand again using Google
Autocomplete + PAA + related searches.

4. Validate with Keyword Planner
Check local search demand and trends. business.google.com

5. Analyze the local SERP
Look at the actual results—not just keyword metrics.

6. Cluster by search intent
For example:

“best running shoes”
“best running shoes for beginners”
“best running shoes for wide feet”
“what running shoes should beginners use”

Some deserve separate pages; others belong on the same comprehensive page.

7. Score opportunities

I'd prioritize something like:

Opportunity = relevance × demand × ranking feasibility × business value

rather than simply sorting by search volume.

One major caveat with non-English keyword data

Third-party databases aren't equally strong in every language. Ahrefs itself notes that data depth varies considerably by market: larger markets tend to have stronger long-tail datasets, while smaller markets can have thinner and less reliable volume estimates. help.ahrefs.comahrefs.com

So for a smaller language, I would put more weight on actual SERPs, autocomplete, Search Console, competitor analysis and native-speaker research, rather than blindly trusting a volume number.

If you tell me the language + target country + what your site sells/covers, I can give you a concrete multilingual keyword-research workflow, including the best tools for that particular language and how I'd find the question/long-tail opportunities.

Yes. For a non-English site, I’d avoid simply translating an English keyword list. Search behavior, phrasing, spelling, and question formats differ by language and country, so the best approach is to research natively in the target language.

Best tools

A workflow I'd recommend

1. Start with native seed terms.

Don't translate:

"best accounting software for freelancers"

into another language and stop there.

Instead, have a native speaker—or an LLM plus native-speaker validation—generate variations around:

• product/service terminology
• colloquial terminology
• regional terminology
• synonyms
• abbreviations
• spelling variants
• problem-based searches
• comparison searches
• "how do I..." questions
• "is X worth it?" questions
• "X vs Y" searches
• audience-specific modifiers

For example, people may search for a product using its English name, a localized name, an abbreviation, or an entirely different colloquial expression.

2. Put those seeds into Google Keyword Planner with the correct country + language.

This is particularly important. Google lets you specify both location and language when generating keyword ideas. support.google.comsupport.google.com

I'd export everything rather than concentrating only on high-volume terms. Long-tail queries are frequently low-volume individually but valuable collectively.

3. Run the same seeds through Ahrefs/Semrush.

For questions specifically, Ahrefs is particularly useful because its keyword ideas include a Questions filter and search-suggestion-derived keywords. help.ahrefs.com

Semrush can similarly filter by questions, intent, word count, difficulty, and language. www.semrush.com

Look for patterns rather than individual keywords:

"how to X"
"X without Y"
"X for [specific audience]"
"X price"
"X vs Y"
"is X worth it"
"why does X..."
"can X..."

Then translate those patterns into the target language, rather than translating the English queries literally.

4. Mine Google itself

This is one of the most underrated techniques for international SEO.

Search the target-language seed in Google while using the appropriate country/location and collect:

• Autocomplete suggestions
• People Also Ask questions
• Related searches
• Question-like queries appearing in the SERP
• Titles/headings used by ranking pages

The important thing is that you're observing how actual users phrase the problem in that language.

For example, grammatical differences can make an English question pattern a poor proxy for the target language.

5. Use Google Trends to validate language-specific demand

Google Trends is particularly useful when you're deciding between several seemingly equivalent expressions.

It can compare terms across languages and countries, and its Topics feature can group concepts across different language expressions. support.google.com

I'd use it to answer:

• Which synonym is actually used?
• Is this terminology growing?
• Does vocabulary differ between countries?
• Is the query seasonal?
• Is the "translated" term actually used by searchers?

This is especially important for languages spanning multiple markets—for example, Spanish, Portuguese, Arabic, French, and German.

6. Look at competitors in the target market

This can uncover long tails that keyword databases miss.

In Ahrefs/Semrush:

1. Find 3–10 strong competitors in the target language/country.
2. Export their organic keywords.
3. Filter for informational/question queries.
4. Filter by lower difficulty.
5. Look for keywords where competitors rank but have relatively weak content.
6. Cluster them by search intent.

Ahrefs' "Also rank for" data is useful here because it identifies keywords ranking pages commonly rank for beyond your initial seed. help.ahrefs.com

7. Don't judge long-tail keywords by volume alone

For international SEO, I'd score opportunities roughly like this:

Opportunity = relevance × intent × traffic potential × ranking feasibility × business value

A keyword with 30 searches/month can be substantially better than one with 3,000 if:

• the searcher has strong commercial intent,
• your product solves exactly the problem,
• the SERP is weak,
• and the query isn't adequately answered by existing pages.

Also look at Traffic Potential, not just keyword volume. Ahrefs, for example, provides traffic-potential estimates and SERP analysis in addition to volume. ahrefs.com

One particularly useful technique: build a "question modifier" dictionary

For each language, create a list of native question/problem modifiers.

For example, conceptually:

• how
• why
• when
• where
• which
• can
• should
• is it
• what is
• how much
• how long
• difference between
• alternatives to
• versus

Then combine these with your topical entities and let Keyword Planner/Ahrefs/Semrush expand them.

But don't blindly translate the modifier list. Have a native speaker validate the natural forms. Languages often have multiple ways of expressing the same intent, and some literal translations will produce queries nobody actually searches.

If I were building the process from scratch

I'd use:

Google Keyword Planner → Semrush/Ahrefs → Google autocomplete/PAA → Google Trends → competitor analysis → Search Console → native-speaker review

And I'd maintain a spreadsheet/database with:

keyword | language | country | translation/meaning | volume | KD | intent | SERP features | competitor URLs | business value | content cluster

The most important distinction is language ≠ market. For example, Spanish searches in Spain, Mexico, Argentina, and the US can use different vocabulary and have different SERPs. Research each important country separately rather than treating "Spanish" as one search market. Google itself allows geographic targeting down to countries, regions, and cities in Keyword Planner. support.google.comsupport.google.com

If you tell me which language(s) and country you're targeting, I can also give you a concrete long-tail/question research workflow for that market, including which tools are strongest for that particular language.

Yes. For non-English SEO, the biggest mistake is treating keyword research as English keyword research translated into another language. Search behavior, wording, spelling variants, local terminology, and question patterns can differ substantially.

Here’s a practical stack:

1. Google Search Console — start with your own data

If the site already gets organic traffic, this is often the best source.

Look at:

• Queries generating impressions but few clicks
• Queries with low average position (e.g. 8–30)
• Queries containing question words
• Queries that differ from the wording you expected
• Country/language-specific query patterns

Export the queries and cluster them by meaning, not just exact words.

2. Google Keyword Planner

Useful for volume and commercial intent, particularly when you select the target country and language rather than relying on global settings.

Be careful with very low-volume terms: Google often groups related queries, so reported volume can substantially understate the number of individual long-tail variations.

3. Google itself: autocomplete + People Also Ask

This is particularly valuable for questions in other languages.

Search your main topic using native-language terms and examine:

• Autocomplete suggestions
• People Also Ask
• Related searches
• Search-result titles/headings
• Featured snippets

Try modifying the query with native equivalents of:

• how
• why
• what
• when
• where
• which
• can
• is it
• how much
• how long
• alternatives
• comparison
• near me / locally relevant modifiers

Don't simply translate English question templates—look at how native speakers actually formulate the questions.

4. Semrush / Ahrefs

Both can be useful for multilingual keyword discovery.

Good workflows include:

• Entering a seed term in the target language
• Looking at matching/related terms
• Filtering for questions
• Examining SERPs for the target country
• Looking at competitors ranking for the topic
• Finding terms where competitors rank but your site doesn't

The important setting is the country/database, not merely the language.

5. AlsoAsked

Great for discovering the relationship between questions.

It can help you turn one topic into a hierarchy such as:

Main topic → subtopic → specific question → follow-up question

That's especially useful for building FAQ sections, topical clusters, and informational content.

6. AnswerThePublic

Useful for generating question variations around a seed topic. For less-common languages, coverage can be uneven, so I'd treat it as a discovery tool, not a definitive volume source.

7. Native-language SERP research

This is one of the most underrated methods.

Search the topic exactly as a local user would and inspect the actual results. Look for:

• Repeated terminology
• Synonyms
• Regional vocabulary
• Informal vs. formal phrasing
• Questions appearing in titles
• Forums/Reddit-like discussions
• Autocomplete suggestions
• “Related searches”
• Competitor FAQ sections

If possible, have a native speaker validate your keyword list. A grammatically correct translation can still be something that almost nobody searches.

8. Reddit, forums, YouTube, TikTok, Quora equivalents

For long-tail questions, communities can be more valuable than traditional keyword tools.

Search the target language for patterns like:

“how do I…”
“has anyone…”
“is it worth…”
“what's the difference between…”
“why does…”
“which one…”
“where can I…”

These often reveal problem language that conventional keyword tools don't capture well.

9. Google Trends

Excellent for comparing terminology.

For example, you might discover that two terms have essentially the same English meaning but one is overwhelmingly preferred in a particular country.

Compare:

• Synonyms
• Formal vs. colloquial terms
• Regional variants
• Singular/plural forms
• Different spellings
• Transliterations

Use the target country when possible.

10. AI as a clustering/expansion layer

LLMs are particularly useful after you've collected real search data.

Give the model your raw queries and ask it to classify them into:

• Same search intent
• Different intent
• Informational
• Commercial investigation
• Transactional
• Navigational
• Question
• Comparison
• Troubleshooting
• Local intent

You can then create topic clusters rather than producing one page for every slight keyword variation.

But don't use AI-generated keywords as evidence that people actually search them. Validate promising suggestions against Search Console, Keyword Planner, third-party keyword databases, Google SERPs, Trends, or community discussions.

A strong multilingual workflow

I'd use something like:

Real queries → native-language expansion → SERP validation → volume/trend validation → intent clustering → content mapping

For example:

1. Export your site's existing queries from Search Console.
2. Add competitor keywords from Ahrefs/Semrush.
3. Use Google autocomplete/PAA to find questions.
4. Mine forums, Reddit, YouTube, etc. for natural phrasing.
5. Use an LLM to cluster and normalize the queries.
6. Check search demand in Keyword Planner/Ahrefs/Semrush.
7. Manually inspect the SERP for the highest-value clusters.
8. Have a native speaker sanity-check terminology.
9. Map each distinct intent to an existing or new page.

The last step is important: 10 long-tail keywords don't necessarily deserve 10 pages. If Google consistently returns the same results for all 10, they're probably variations of one search intent.

For languages with limited keyword-tool coverage

This is where I'd lean more heavily on Google SERPs + Search Console + native communities + Google Trends rather than trusting a keyword database's volume estimates.

And if your site targets multiple countries that share a language—e.g. Spanish across Spain, Mexico, Argentina, and Colombia—research them separately. The vocabulary and search intent can differ enough to justify different keyword sets and sometimes different content.

If you tell me the language + target country + your site's niche, I can give you a specific multilingual keyword-research workflow and the best tools for that combination.

Yes. For a non-English site, I’d avoid simply translating your English keyword list. The goal is to discover how people actually search in that language, including local terminology, colloquialisms, spelling variations, and question formats.

Best tools and methods

1. Google Keyword Planner — good baseline

• Set the target country + language, rather than translating an English keyword list.
• Start with native-language seed terms.
• Export keyword ideas and look for longer, specific queries.
• Particularly useful when you ultimately care about Google Ads data as well as SEO.

2. Ahrefs Keywords Explorer — excellent for multilingual SEO
Ahrefs Keywords Explorer supports a very large number of country/language combinations. Its keyword-ideas reports include Matching terms, Related terms, Search suggestions, and question filtering. help.ahrefs.comhelp.ahrefs.com

A particularly useful workflow is:

broad native-language seed → matching terms → questions → related terms → SERP analysis

Don't start with an extremely specific seed. Ahrefs specifically recommends broader seeds when you're trying to uncover a larger set of question queries. help.ahrefs.comhelp.ahrefs.com

3. Semrush Keyword Magic Tool — particularly good for questions
Semrush Keyword Magic Tool has a Questions filter, topic grouping, intent, difficulty, SERP features, and language filtering. This makes it useful for finding long-tail questions at scale. www.semrush.com

For example, instead of only researching the equivalent of:

"coffee machine"

you'd want to uncover native-language variations corresponding to things such as:

• which coffee machine is best for...
• how to clean...
• why does my coffee machine...
• can I use X in...
• how much does X cost...
• X vs Y
• is X worth it...
• where can I buy X...

The actual wording should come from the target language, not machine translation.

4. Google autocomplete + People Also Ask

This is one of my favorite ways to find genuinely long-tail questions.

Search your native-language seed in Google and record:

• autocomplete suggestions
• People Also Ask questions
• related searches at the bottom
• variations appearing in the SERPs
• terminology used by ranking pages

Google's autocomplete can also feed keyword databases such as Ahrefs' Search suggestions report. help.ahrefs.comhelp.ahrefs.com

For questions, don't restrict yourself to the English equivalents of who/what/why/how. Every language has its own natural question constructions.

5. Google Trends — especially valuable for localization

Google Trends is excellent for figuring out which local wording people actually use.

You can compare different terms across countries and languages, and Google distinguishes between literal search terms and broader Topics, which can aggregate related searches across languages. support.google.comsupport.google.com

For example, if you're unsure whether people in Spain use terminology A or B, compare:

A vs B → Spain → 12 months / 5 years

Then look at:

• Related searches
• Rising searches
• regional differences
• seasonality

This is often more useful than translating your English keyword.

6. Mine local communities

For really good long-tail questions, go where native speakers actually ask questions:

• Reddit communities in the target language
• local forums
• Quora equivalents
• Facebook groups
• YouTube comments
• TikTok/Instagram comments
• product reviews
• local Q&A sites
• customer-support conversations

Look for recurring formulations such as:

"Has anyone had this problem with...?"
"Is it normal that...?"
"Can I...?"
"What happens if...?"
"Which one should I choose...?"

These can reveal zero-/low-volume-looking keywords that have strong real-world intent.

7. Your own Google Search Console data

If the site already gets traffic, this is arguably the most valuable source.

Export queries from GSC and look for:

• 4–10+ word queries
• questions
• queries with impressions but low CTR
• queries ranking positions 5–20
• unexpected terminology
• queries you didn't deliberately target

Then cluster them by search intent, not just by matching words.

A multilingual workflow I'd recommend

For each important topic, I'd use roughly this process:

1. Native speaker → create 5–20 seed concepts

Not translations. Actual terms a person in that market would use.

2. Ahrefs/Semrush → expand

Generate thousands of variants, questions, related terms and competitor keywords.

3. Google autocomplete/PAA → collect questions

Especially useful for very specific queries.

4. Google Trends → validate language + geography

Determine which synonym/phrase is actually used in the target market. Trends can compare terms by geography and language. support.google.com

5. Forums/social → discover "human" questions

This is where you'll often find the really long-tail queries that keyword databases underrepresent.

6. SERP analysis → evaluate the opportunity

For each promising query, inspect the first page:

• Are the results actually answering the query?
• Are they local-language pages?
• Are they authoritative?
• Are forums/reddit appearing?
• Are the results old or weak?
• Is Google showing PAA/video/local/product features?
• Does one page rank for dozens of related queries?

7. Cluster

Group queries that can be answered by the same page. Don't create 30 pages simply because you found 30 slightly different long-tail phrases.

One important multilingual SEO trap

Don't assume search volume is directly comparable across languages.

A keyword with 1,000 searches/month in Germany isn't necessarily "smaller" than one with 10,000 in the US in the way the raw numbers suggest. Search behavior, population, Google usage, language distribution, and keyword-tool coverage all differ.

Also, Google Trends numbers are normalized relative-interest data, not absolute search volume. support.google.com

So I'd score opportunities using several signals:

The biggest advantage you can get is native-language SERP analysis. If your competitors are mostly translating generic English SEO content, finding the questions and terminology that native speakers actually use can uncover excellent long-tail opportunities that conventional keyword translation misses.

If you tell me the language + country and what your site sells/does, I can also show you a concrete multilingual keyword-research process and which tools I'd use for that particular market.

Yes. For a non-English site, I’d avoid simply translating an English keyword list. Search behavior, wording, synonyms, spelling variants, and even the way people formulate questions can differ by language and country.

Best tools and methods

1. Start with your own Search Console data

This is particularly powerful for multilingual SEO because you can discover queries you wouldn't have thought to translate.

Search Console's Performance data can be broken down by query, page, country, device, etc. developers.google.com

Look for:

• queries with high impressions but low CTR
• queries ranking positions 5–20
• very specific queries with only a handful of impressions
• unexpected synonyms/wording
• questions you aren't explicitly targeting
• queries in different languages from your site's primary language

Google also introduced Query groups, which can group similar queries—including different phrasings and languages—around the same underlying intent. developers.google.com

Important: don't discard a keyword merely because its individual volume is tiny. Ten closely related searches at 20 searches/month each can represent a meaningful topic cluster.

2. Use Ahrefs or Semrush for discovery

Ahrefs Keywords Explorer is particularly useful because its keyword database supports a large number of language/locale combinations. Its Matching terms → Questions functionality is designed specifically to surface question-style long tails. help.ahrefs.com

Semrush Keyword Magic Tool similarly lets you filter for Questions, group related terms, analyze intent/difficulty, and research different languages within country databases. www.semrush.com

For example, don't just research:

"running shoes"

For a Spanish site, you might research the equivalent seed and then expand it independently, looking for questions around:

• choosing shoes for different surfaces
• sizing
• pronation
• durability
• injuries
• weather
• specific running distances
• regional terminology

The key is that you're looking for the language's native search vocabulary, rather than mechanically translating your English vocabulary.

3. Mine Google Trends for language-specific demand

Google Trends is particularly useful when you have several possible translations or synonyms.

Google specifically recommends looking at related queries/topics, geographic popularity, and related terms in other languages. developers.google.com

Suppose you have three possible terms in German. Instead of guessing which is "correct," compare them in the target country and inspect:

Top related queries + Rising queries + regional interest.

This can reveal that a technically correct translation isn't actually the phrase consumers use.

4. Mine questions outside traditional keyword tools

This is one of the best ways to find genuinely long-tail queries.

Search the native-language versions of:

• Reddit
• Quora
• niche forums
• YouTube comments
• Facebook groups
• local Q&A sites
• product reviews
• community discussions
• autocomplete suggestions

Ahrefs itself recommends forums and communities because users tend to express their questions in their own words rather than in polished "SEO language." ahrefs.com

For example, a keyword tool might give you:

"best X for Y"

A forum might reveal the much better content opportunity:

"I have X problem and Y situation—would product Z actually work?"

That second formulation can become both a long-tail keyword and a much better piece of content.

5. Use an LLM—but as an expansion tool, not the volume source

This is where AI is very useful.

Give it a seed topic and ask it to generate categories such as:

• native-language synonyms
• colloquial expressions
• regional variations
• common misspellings
• beginner questions
• comparison questions
• troubleshooting questions
• "how do I..." questions
• "is X worth it?" questions
• "X vs Y" questions
• questions a customer would ask before buying

Then put those suggestions back into Google Trends, Ahrefs/Semrush, autocomplete, and Search Console.

In other words:

LLM → generate possibilities
Search data → verify demand
SERP → verify intent and competition

That's much safer than treating an AI-generated keyword's supposed search volume as fact.

How I'd evaluate a multilingual long-tail

I'd score each candidate on roughly five dimensions:

1. Search demand
Volume, impressions, Trends trajectory—but don't demand huge volume for a long-tail.

2. Intent
Does the searcher want information, comparison, a product, a solution, or a transaction?

3. SERP fit
Search the query in the actual target language and country. Look at what Google is rewarding.

4. Competition
Don't just look at KD. Examine whether the current results actually answer the query well.

5. Business value
A 30-search/month query from someone ready to buy can be considerably more valuable than a 5,000-search/month informational query.

I'd particularly look for low-volume + high-intent + weak SERP combinations.

A very effective workflow

For each target language/country:

Seed topics → native-language expansion → Ahrefs/Semrush → Google autocomplete/PAA → Trends → forums/communities → Search Console → SERP analysis → cluster by intent

Then cluster the resulting keywords by search intent, rather than creating one page per keyword.

For example, 25 different long-tail questions might all represent one underlying topic. Google's own Search Console Query Groups are increasingly useful for recognizing this kind of relationship. developers.google.com

One final point: language ≠ market. Spanish in Spain, Mexico, Argentina, and Colombia can have substantially different vocabulary and search behavior. Research at the language + country/market level whenever possible. Semrush, for example, provides regional keyword databases, while Ahrefs has locale-specific keyword data. help.ahrefs.com

If you tell me what language(s) your site targets and what your niche is, I can give you a concrete multilingual long-tail research process—including which tools I'd use, what filters I'd apply, and how I'd build the keyword/question clusters.

Finding long-tail keywords in non-English languages is often harder because many English-first SEO tools have weaker coverage. The good news is that there are several reliable approaches that work well when combined.

1. Use Google Search itself (often the best source)

Google's own suggestions are based on real searches in that language.

Look at:

• Google Autocomplete
• "People Also Ask"
• Related Searches at the bottom of results
• Google Images autocomplete (surprisingly useful for product keywords)
• YouTube autocomplete (for informational topics)

Example workflow:

1. Search a broad keyword in the target language.
2. Record autocomplete suggestions.
3. Open the top results.
4. Collect the "People Also Ask" questions.
5. Search those questions and repeat.

This often uncovers dozens of genuine long-tail queries.

2. Keyword research tools with international databases

These generally have the best non-English support:

For smaller languages, compare multiple tools because search volume estimates can vary significantly.

3. Use Google Search Console

If your site already has traffic, this is one of the highest-value data sources.

Look for queries that:

• have impressions but few clicks
• rank around positions 8–25
• contain 3–8 words
• include question words

These are often the easiest long-tail opportunities to improve.

4. Mine forums and community sites in that language

People naturally ask questions using the words they actually search for.

Look at:

• Reddit (if active in your language)
• Local discussion forums
• Facebook groups
• Quora (where available)
• Local equivalents (these vary by country)

Collect recurring questions and phrasing.

5. Analyze competitors

Instead of starting from keywords, start from pages.

Find:

• competitors ranking well
• their FAQ pages
• category pages
• blog posts
• support articles

SEO tools can often show all the keywords each page ranks for.

6. Use AI for keyword expansion (carefully)

Large language models are good at generating variations after you have seed keywords.

For example, start with:

"Best hiking backpack"

Ask AI to generate:

• beginner questions
• comparison searches
• purchase intent keywords
• problem-based searches
• regional wording
• informal wording
• synonym variations

Then validate those ideas using Google or SEO tools rather than assuming they're all searched.

7. Look at search suggestions from multiple platforms

Different platforms reveal different intent.

Useful sources include:

• Google
• YouTube
• Amazon (for products)
• TikTok
• Pinterest
• local ecommerce marketplaces

Each has its own autocomplete.

8. Use Google Trends

Even if exact volume isn't available, it helps identify:

• rising topics
• regional differences
• seasonal searches
• alternative wording

This is especially useful in markets with limited keyword volume data.

9. Build topic clusters instead of isolated keywords

Instead of targeting:

"running shoes"

Create pages covering:

• best running shoes for beginners
• running shoes for flat feet
• trail running shoes
• running shoes under a certain price
• how to choose running shoes
• common mistakes when buying running shoes

Each page naturally captures many long-tail searches.

10. Analyze Google's "People Also Ask"

Question keywords are often easier to rank for.

Collect questions like:

• How do I...?
• Why does...?
• What is...?
• Which is better...?
• When should...?

Then answer them thoroughly with dedicated sections or standalone articles.

11. Check search operators

Use searches like:

"<keyword>" site:forum

or

"<keyword>" inurl:forum

to discover real user discussions and common phrasing in your target language.

12. Use Wikipedia in the target language

The table of contents, internal links, and article titles often reveal terminology and related concepts that people search for.

Evaluating long-tail keywords

Don't rely only on search volume. Consider:

• Search intent: Does it match what your page offers?
• Competition: Can your site realistically rank?
• Topical relevance: Is it central to your niche?
• Business value: Will ranking help you achieve your goals?
• SERP quality: Are the top results weak, outdated, or missing information?
• Content gap: Can you create something clearly better?

Many valuable long-tail keywords have very low reported search volume because keyword databases have limited coverage, especially in smaller languages. They can still drive meaningful traffic when grouped into comprehensive content.

A practical workflow

1. Gather 20–50 seed keywords.
2. Expand them with Google Autocomplete and related searches.
3. Collect "People Also Ask" questions.
4. Expand variations with an SEO tool.
5. Mine competitors' ranking pages.
6. Group keywords by search intent.
7. Create comprehensive pages that naturally target dozens of related long-tail phrases instead of one exact keyword.
8. Monitor Google Search Console and refine content based on the actual queries your pages begin to rank for.

For sites in languages with smaller search ecosystems (e.g., Finnish, Czech, Thai, Hebrew, etc.), this combination of Google Search + Search Console + competitor analysis + local forums often uncovers far more actionable long-tail opportunities than relying on keyword volume tools alone.

Yes. For a non-English site, I’d avoid simply translating your English keyword list. Long-tail research works much better when you discover the phrases people actually use in that language and country.

Best tool stack

A workflow I'd recommend

Suppose your site is in Spanish and you sell accounting software.

Don't start with:

accounting software → translate → software de contabilidad

Instead, build a seed universe:

• product/category terms
• problems
• use cases
• audiences
• comparisons
• features
• questions
• pricing
• alternatives
• regulatory/local terms

Then put Spanish seeds into Ahrefs/Semrush and generate variations such as:

• cómo llevar la contabilidad de...
• cómo hacer...
• qué programa usar para...
• software de contabilidad para...
• ... gratis
• ... para pequeñas empresas
• diferencia entre X y Y
• cuánto cuesta...
• es obligatorio...
• cómo solucionar...

The important part is that the modifiers should be discovered from the target language, rather than translated from an English modifier list.

Finding questions specifically

Semrush is useful here because its Keyword Magic Tool has a Questions filter. www.semrush.comwww.semrush.com

But I'd combine that with actual Google SERPs.

For each important seed:

1. Search it in the target country.
2. Record autocomplete suggestions.
3. Look at People Also Ask.
4. Look at related searches.
5. Open the top-ranking pages.
6. Extract recurring questions/subtopics from those pages.
7. Put those questions back into your keyword tool.
8. Cluster the resulting queries by search intent, not merely by wording.

This last step matters enormously in languages where several grammatical variations can represent the same search intent.

Use Google Trends for language differences

Google Trends is especially useful when you don't speak the language well.

For example, you might discover that three apparently equivalent translations exist, but one is overwhelmingly more popular in the target market.

Compare:

[term A] vs [term B] vs [term C]

Then set the country/region and language appropriately.

You can also use Trends to catch emerging long-tails that have little historical volume. That's important because a keyword showing "0" or very low volume in an SEO database isn't necessarily worthless.

Your existing Search Console data is gold

If the site already gets organic traffic, I'd actually start here.

Search Console gives you the queries that are already generating impressions/clicks, and you can analyze them by country. support.google.com

Look especially for:

High impressions + low CTR
→ Your page may be ranking for a valuable query but needs a better title/snippet or stronger alignment.

Impressions + average position 8–30
→ Excellent candidates for content improvement.

Queries you didn't intentionally target
→ Often the best source of unexpected long-tail opportunities.

Multiple question variations pointing to the same page
→ Potentially a broader topic cluster rather than 10 separate articles.

One big warning: don't trust keyword volume too much

This is particularly important for long-tail keywords and smaller languages.

A keyword tool saying 10 searches/month doesn't mean the query has no value. Third-party databases have incomplete coverage, and long-tail demand gets fragmented across many variants.

I'd score candidates on something like:

Opportunity = relevance × intent × SERP weakness × business value × evidence of demand

rather than:

Opportunity = search volume

For example, a query with 20 estimated searches/month where the searcher is clearly ready to buy can be much more valuable than a 2,000-volume informational query.

Competitor mining is especially powerful

For each target country/language, identify 5–10 sites that actually rank locally, then put them into Ahrefs/Semrush.

Look for:

• keywords where competitors rank 1–20
• pages receiving traffic from dozens/hundreds of related long-tails
• questions competitors rank for that you don't
• low-authority sites ranking unusually well
• keywords where the SERP doesn't satisfy the query particularly well

Ahrefs and Semrush both have competitor keyword functionality that makes this much faster. help.ahrefs.comwww.semrush.com

And don't overlook native speakers

For serious international SEO, I'd have a native speaker/local SEO review the final keyword clusters, not necessarily do all the initial research.

They can catch things tools won't:

• unnatural translations
• regional vocabulary
• formal vs conversational phrasing
• singular/plural preferences
• local abbreviations
• words with different meanings in different countries
• queries that technically translate correctly but nobody actually searches

My preferred process is therefore:

SEO tools → Google autocomplete/PAA → local SERP → Trends → competitor analysis → native-speaker validation → clustering → content mapping

If you tell me the language + target country + what your site sells/does, I can show you a concrete long-tail/question research process for that market, including which tools I'd use and exactly what filters I'd apply.

For non-English websites, long-tail keyword research works best when you combine native-language data sources, search-engine data, and language-specific SERP analysis. Translation alone usually misses how people actually search.

1. Use native keyword research tools

Semrush

Good for:

• Keyword volume by country/language
• Related keywords
• Question keywords
• Competitor keyword gaps
• SERP analysis

Tip: Set the database to the target country (e.g., Spain, France, Japan), not just the language.

Ahrefs

Useful for:

• Long-tail keyword discovery
• “Questions” reports
• Parent topic analysis
• Finding low-competition terms competitors rank for

Google Keyword Planner

Still valuable for:

• Local-language search volume
• Country-specific trends
• Commercial intent keywords

Use the correct:

• Location
• Language
• Search network settings

2. Mine Google’s own suggestions

Google autocomplete is one of the best sources for long-tail queries because it reflects real searches.

Methods:

• Type a keyword in the target language and collect suggestions
• Add modifiers:
  • “how”
  • “why”
  • “best”
  • “near me”
  • “price”
  • “comparison”
  • “problem”
  • “alternative”
  • “vs”

Example (Spanish):

• zapatos running
• zapatos running para
• zapatos running para pies
• zapatos running para pies planos

Tools that automate this:

• Keyword Tool
• AnswerThePublic

3. Find questions in the target language

Question keywords are often the easiest long-tail opportunities.

Sources:

Google “People Also Ask”

Search your topic in the target language and record:

• Questions
• Related searches
• Featured snippets

AlsoAsked

Useful for mapping question clusters from Google’s “People Also Ask.”

Forums and communities

Native speakers often use natural wording that keyword tools miss:

• Reddit (for languages with active communities)
• Local forums
• Q&A sites
• Facebook groups
• Regional equivalents

Look for:

• “How do I…”
• “Is it normal that…”
• “What is the best…”
• “Does anyone recommend…”

4. Use local search engines when relevant

Google dominates many markets, but not all.

Examples:

• China → Baidu
• South Korea → Naver
• Japan → Google + Yahoo Japan
• Russia → Yandex

Their autocomplete and keyword tools can reveal local phrasing differences.

5. Analyze competitors in the same language

Avoid translating English competitors.

Instead:

1. Search your main topic in the target language.
2. Find websites ranking in that language.
3. Export their keywords using Ahrefs/Semrush.
4. Filter for:
   • Low difficulty
   • 3+ word phrases
   • Question terms
   • Keywords where competitors rank poorly

Look especially at:

• Blog posts
• FAQs
• Category pages
• Comparison pages

6. Use native-language SERP analysis

For each keyword, evaluate:

Search intent

Is the user looking for:

• Information?
• A product?
• A service?
• A comparison?
• A local provider?

Competition quality

Check:

• Are ranking pages authoritative?
• Are results outdated?
• Are answers thin?
• Are forums ranking because no good content exists?

Long-tail opportunities often appear when the SERP is weak.

7. Use AI carefully for expansion

AI is useful for generating keyword variations, but validate everything with real search data.

Good workflow:

1. Give AI:
   • Target language
   • Country
   • Audience
   • Product/service
2. Generate:
   • Synonyms
   • Questions
   • Pain points
   • Regional wording
3. Verify with:
   • Google autocomplete
   • Keyword Planner
   • Ahrefs/Semrush
   • SERPs

Avoid directly translating English keywords because:

• Search volume may not exist
• Native phrasing may differ
• Cultural intent may change

8. Build a multilingual keyword workflow

A practical process:

Extra tip: use native speakers for “search language”

The highest-value long-tail terms are often not literal translations.

Example:

English:

“best laptop for graphic design students”

A machine translation might produce a grammatically correct phrase, but native users may search something closer to:

“laptop para diseño gráfico universitarios”

or

“qué portátil comprar para estudiar diseño gráfico”

The difference can determine whether a page gets traffic.

For multilingual SEO, the strongest approach is usually:
local keyword discovery → SERP validation → content creation, rather than English keyword list → translation.

Finding long-tail keywords in non-English languages is often harder because many English-first SEO tools have weaker coverage. The good news is that there are several reliable approaches that work well when combined.

1. Use Google Search itself (often the best source)

Google's own suggestions are based on real searches in that language.

Look at:

• Google Autocomplete
• "People Also Ask"
• Related Searches at the bottom of results
• Google Images autocomplete (surprisingly useful for product keywords)
• YouTube autocomplete (for informational topics)

Example workflow:

1. Search a broad keyword in the target language.
2. Record autocomplete suggestions.
3. Open the top results.
4. Collect the "People Also Ask" questions.
5. Search those questions and repeat.

This often uncovers dozens of genuine long-tail queries.

2. Keyword research tools with international databases

These generally have the best non-English support:

For smaller languages, compare multiple tools because search volume estimates can vary significantly.

3. Use Google Search Console

If your site already has traffic, this is one of the highest-value data sources.

Look for queries that:

• have impressions but few clicks
• rank around positions 8–25
• contain 3–8 words
• include question words

These are often the easiest long-tail opportunities to improve.

4. Mine forums and community sites in that language

People naturally ask questions using the words they actually search for.

Look at:

• Reddit (if active in your language)
• Local discussion forums
• Facebook groups
• Quora (where available)
• Local equivalents (these vary by country)

Collect recurring questions and phrasing.

5. Analyze competitors

Instead of starting from keywords, start from pages.

Find:

• competitors ranking well
• their FAQ pages
• category pages
• blog posts
• support articles

SEO tools can often show all the keywords each page ranks for.

6. Use AI for keyword expansion (carefully)

Large language models are good at generating variations after you have seed keywords.

For example, start with:

"Best hiking backpack"

Ask AI to generate:

• beginner questions
• comparison searches
• purchase intent keywords
• problem-based searches
• regional wording
• informal wording
• synonym variations

Then validate those ideas using Google or SEO tools rather than assuming they're all searched.

7. Look at search suggestions from multiple platforms

Different platforms reveal different intent.

Useful sources include:

• Google
• YouTube
• Amazon (for products)
• TikTok
• Pinterest
• local ecommerce marketplaces

Each has its own autocomplete.

8. Use Google Trends

Even if exact volume isn't available, it helps identify:

• rising topics
• regional differences
• seasonal searches
• alternative wording

This is especially useful in markets with limited keyword volume data.

9. Build topic clusters instead of isolated keywords

Instead of targeting:

"running shoes"

Create pages covering:

• best running shoes for beginners
• running shoes for flat feet
• trail running shoes
• running shoes under a certain price
• how to choose running shoes
• common mistakes when buying running shoes

Each page naturally captures many long-tail searches.

10. Analyze Google's "People Also Ask"

Question keywords are often easier to rank for.

Collect questions like:

• How do I...?
• Why does...?
• What is...?
• Which is better...?
• When should...?

Then answer them thoroughly with dedicated sections or standalone articles.

11. Check search operators

Use searches like:

"<keyword>" site:forum

or

"<keyword>" inurl:forum

to discover real user discussions and common phrasing in your target language.

12. Use Wikipedia in the target language

The table of contents, internal links, and article titles often reveal terminology and related concepts that people search for.

Evaluating long-tail keywords

Don't rely only on search volume. Consider:

• Search intent: Does it match what your page offers?
• Competition: Can your site realistically rank?
• Topical relevance: Is it central to your niche?
• Business value: Will ranking help you achieve your goals?
• SERP quality: Are the top results weak, outdated, or missing information?
• Content gap: Can you create something clearly better?

Many valuable long-tail keywords have very low reported search volume because keyword databases have limited coverage, especially in smaller languages. They can still drive meaningful traffic when grouped into comprehensive content.

A practical workflow

1. Gather 20–50 seed keywords.
2. Expand them with Google Autocomplete and related searches.
3. Collect "People Also Ask" questions.
4. Expand variations with an SEO tool.
5. Mine competitors' ranking pages.
6. Group keywords by search intent.
7. Create comprehensive pages that naturally target dozens of related long-tail phrases instead of one exact keyword.
8. Monitor Google Search Console and refine content based on the actual queries your pages begin to rank for.

For sites in languages with smaller search ecosystems (e.g., Finnish, Czech, Thai, Hebrew, etc.), this combination of Google Search + Search Console + competitor analysis + local forums often uncovers far more actionable long-tail opportunities than relying on keyword volume tools alone.

Finding long-tail keywords in non-English languages is often harder because many English-first SEO tools have weaker coverage. The good news is that there are several reliable approaches that work well when combined.

1. Use Google Search itself (often the best source)

Google's own suggestions are based on real searches in that language.

Look at:

• Google Autocomplete
• "People Also Ask"
• Related Searches at the bottom of results
• Google Images autocomplete (surprisingly useful for product keywords)
• YouTube autocomplete (for informational topics)

Example workflow:

1. Search a broad keyword in the target language.
2. Record autocomplete suggestions.
3. Open the top results.
4. Collect the "People Also Ask" questions.
5. Search those questions and repeat.

This often uncovers dozens of genuine long-tail queries.

2. Keyword research tools with international databases

These generally have the best non-English support:

For smaller languages, compare multiple tools because search volume estimates can vary significantly.

3. Use Google Search Console

If your site already has traffic, this is one of the highest-value data sources.

Look for queries that:

• have impressions but few clicks
• rank around positions 8–25
• contain 3–8 words
• include question words

These are often the easiest long-tail opportunities to improve.

4. Mine forums and community sites in that language

People naturally ask questions using the words they actually search for.

Look at:

• Reddit (if active in your language)
• Local discussion forums
• Facebook groups
• Quora (where available)
• Local equivalents (these vary by country)

Collect recurring questions and phrasing.

5. Analyze competitors

Instead of starting from keywords, start from pages.

Find:

• competitors ranking well
• their FAQ pages
• category pages
• blog posts
• support articles

SEO tools can often show all the keywords each page ranks for.

6. Use AI for keyword expansion (carefully)

Large language models are good at generating variations after you have seed keywords.

For example, start with:

"Best hiking backpack"

Ask AI to generate:

• beginner questions
• comparison searches
• purchase intent keywords
• problem-based searches
• regional wording
• informal wording
• synonym variations

Then validate those ideas using Google or SEO tools rather than assuming they're all searched.

7. Look at search suggestions from multiple platforms

Different platforms reveal different intent.

Useful sources include:

• Google
• YouTube
• Amazon (for products)
• TikTok
• Pinterest
• local ecommerce marketplaces

Each has its own autocomplete.

8. Use Google Trends

Even if exact volume isn't available, it helps identify:

• rising topics
• regional differences
• seasonal searches
• alternative wording

This is especially useful in markets with limited keyword volume data.

9. Build topic clusters instead of isolated keywords

Instead of targeting:

"running shoes"

Create pages covering:

• best running shoes for beginners
• running shoes for flat feet
• trail running shoes
• running shoes under a certain price
• how to choose running shoes
• common mistakes when buying running shoes

Each page naturally captures many long-tail searches.

10. Analyze Google's "People Also Ask"

Question keywords are often easier to rank for.

Collect questions like:

• How do I...?
• Why does...?
• What is...?
• Which is better...?
• When should...?

Then answer them thoroughly with dedicated sections or standalone articles.

11. Check search operators

Use searches like:

"<keyword>" site:forum

or

"<keyword>" inurl:forum

to discover real user discussions and common phrasing in your target language.

12. Use Wikipedia in the target language

The table of contents, internal links, and article titles often reveal terminology and related concepts that people search for.

Evaluating long-tail keywords

Don't rely only on search volume. Consider:

• Search intent: Does it match what your page offers?
• Competition: Can your site realistically rank?
• Topical relevance: Is it central to your niche?
• Business value: Will ranking help you achieve your goals?
• SERP quality: Are the top results weak, outdated, or missing information?
• Content gap: Can you create something clearly better?

Many valuable long-tail keywords have very low reported search volume because keyword databases have limited coverage, especially in smaller languages. They can still drive meaningful traffic when grouped into comprehensive content.

A practical workflow

1. Gather 20–50 seed keywords.
2. Expand them with Google Autocomplete and related searches.
3. Collect "People Also Ask" questions.
4. Expand variations with an SEO tool.
5. Mine competitors' ranking pages.
6. Group keywords by search intent.
7. Create comprehensive pages that naturally target dozens of related long-tail phrases instead of one exact keyword.
8. Monitor Google Search Console and refine content based on the actual queries your pages begin to rank for.

For sites in languages with smaller search ecosystems (e.g., Finnish, Czech, Thai, Hebrew, etc.), this combination of Google Search + Search Console + competitor analysis + local forums often uncovers far more actionable long-tail opportunities than relying on keyword volume tools alone.

Finding long-tail keywords in non-English languages is often harder because many English-first SEO tools have weaker coverage. The good news is that there are several reliable approaches that work well when combined.

1. Use Google Search itself (often the best source)

Google's own suggestions are based on real searches in that language.

Look at:

• Google Autocomplete
• "People Also Ask"
• Related Searches at the bottom of results
• Google Images autocomplete (surprisingly useful for product keywords)
• YouTube autocomplete (for informational topics)

Example workflow:

1. Search a broad keyword in the target language.
2. Record autocomplete suggestions.
3. Open the top results.
4. Collect the "People Also Ask" questions.
5. Search those questions and repeat.

This often uncovers dozens of genuine long-tail queries.

2. Keyword research tools with international databases

These generally have the best non-English support:

For smaller languages, compare multiple tools because search volume estimates can vary significantly.

3. Use Google Search Console

If your site already has traffic, this is one of the highest-value data sources.

Look for queries that:

• have impressions but few clicks
• rank around positions 8–25
• contain 3–8 words
• include question words

These are often the easiest long-tail opportunities to improve.

4. Mine forums and community sites in that language

People naturally ask questions using the words they actually search for.

Look at:

• Reddit (if active in your language)
• Local discussion forums
• Facebook groups
• Quora (where available)
• Local equivalents (these vary by country)

Collect recurring questions and phrasing.

5. Analyze competitors

Instead of starting from keywords, start from pages.

Find:

• competitors ranking well
• their FAQ pages
• category pages
• blog posts
• support articles

SEO tools can often show all the keywords each page ranks for.

6. Use AI for keyword expansion (carefully)

Large language models are good at generating variations after you have seed keywords.

For example, start with:

"Best hiking backpack"

Ask AI to generate:

• beginner questions
• comparison searches
• purchase intent keywords
• problem-based searches
• regional wording
• informal wording
• synonym variations

Then validate those ideas using Google or SEO tools rather than assuming they're all searched.

7. Look at search suggestions from multiple platforms

Different platforms reveal different intent.

Useful sources include:

• Google
• YouTube
• Amazon (for products)
• TikTok
• Pinterest
• local ecommerce marketplaces

Each has its own autocomplete.

8. Use Google Trends

Even if exact volume isn't available, it helps identify:

• rising topics
• regional differences
• seasonal searches
• alternative wording

This is especially useful in markets with limited keyword volume data.

9. Build topic clusters instead of isolated keywords

Instead of targeting:

"running shoes"

Create pages covering:

• best running shoes for beginners
• running shoes for flat feet
• trail running shoes
• running shoes under a certain price
• how to choose running shoes
• common mistakes when buying running shoes

Each page naturally captures many long-tail searches.

10. Analyze Google's "People Also Ask"

Question keywords are often easier to rank for.

Collect questions like:

• How do I...?
• Why does...?
• What is...?
• Which is better...?
• When should...?

Then answer them thoroughly with dedicated sections or standalone articles.

11. Check search operators

Use searches like:

"<keyword>" site:forum

or

"<keyword>" inurl:forum

to discover real user discussions and common phrasing in your target language.

12. Use Wikipedia in the target language

The table of contents, internal links, and article titles often reveal terminology and related concepts that people search for.

Evaluating long-tail keywords

Don't rely only on search volume. Consider:

• Search intent: Does it match what your page offers?
• Competition: Can your site realistically rank?
• Topical relevance: Is it central to your niche?
• Business value: Will ranking help you achieve your goals?
• SERP quality: Are the top results weak, outdated, or missing information?
• Content gap: Can you create something clearly better?

Many valuable long-tail keywords have very low reported search volume because keyword databases have limited coverage, especially in smaller languages. They can still drive meaningful traffic when grouped into comprehensive content.

A practical workflow

1. Gather 20–50 seed keywords.
2. Expand them with Google Autocomplete and related searches.
3. Collect "People Also Ask" questions.
4. Expand variations with an SEO tool.
5. Mine competitors' ranking pages.
6. Group keywords by search intent.
7. Create comprehensive pages that naturally target dozens of related long-tail phrases instead of one exact keyword.
8. Monitor Google Search Console and refine content based on the actual queries your pages begin to rank for.

For sites in languages with smaller search ecosystems (e.g., Finnish, Czech, Thai, Hebrew, etc.), this combination of Google Search + Search Console + competitor analysis + local forums often uncovers far more actionable long-tail opportunities than relying on keyword volume tools alone.

Finding long-tail keywords in non-English languages is often harder because many English-first SEO tools have weaker coverage. The good news is that there are several reliable approaches that work well when combined.

1. Use Google Search itself (often the best source)

Google's own suggestions are based on real searches in that language.

Look at:

• Google Autocomplete
• "People Also Ask"
• Related Searches at the bottom of results
• Google Images autocomplete (surprisingly useful for product keywords)
• YouTube autocomplete (for informational topics)

Example workflow:

1. Search a broad keyword in the target language.
2. Record autocomplete suggestions.
3. Open the top results.
4. Collect the "People Also Ask" questions.
5. Search those questions and repeat.

This often uncovers dozens of genuine long-tail queries.

2. Keyword research tools with international databases

These generally have the best non-English support:

For smaller languages, compare multiple tools because search volume estimates can vary significantly.

3. Use Google Search Console

If your site already has traffic, this is one of the highest-value data sources.

Look for queries that:

• have impressions but few clicks
• rank around positions 8–25
• contain 3–8 words
• include question words

These are often the easiest long-tail opportunities to improve.

4. Mine forums and community sites in that language

People naturally ask questions using the words they actually search for.

Look at:

• Reddit (if active in your language)
• Local discussion forums
• Facebook groups
• Quora (where available)
• Local equivalents (these vary by country)

Collect recurring questions and phrasing.

5. Analyze competitors

Instead of starting from keywords, start from pages.

Find:

• competitors ranking well
• their FAQ pages
• category pages
• blog posts
• support articles

SEO tools can often show all the keywords each page ranks for.

6. Use AI for keyword expansion (carefully)

Large language models are good at generating variations after you have seed keywords.

For example, start with:

"Best hiking backpack"

Ask AI to generate:

• beginner questions
• comparison searches
• purchase intent keywords
• problem-based searches
• regional wording
• informal wording
• synonym variations

Then validate those ideas using Google or SEO tools rather than assuming they're all searched.

7. Look at search suggestions from multiple platforms

Different platforms reveal different intent.

Useful sources include:

• Google
• YouTube
• Amazon (for products)
• TikTok
• Pinterest
• local ecommerce marketplaces

Each has its own autocomplete.

8. Use Google Trends

Even if exact volume isn't available, it helps identify:

• rising topics
• regional differences
• seasonal searches
• alternative wording

This is especially useful in markets with limited keyword volume data.

9. Build topic clusters instead of isolated keywords

Instead of targeting:

"running shoes"

Create pages covering:

• best running shoes for beginners
• running shoes for flat feet
• trail running shoes
• running shoes under a certain price
• how to choose running shoes
• common mistakes when buying running shoes

Each page naturally captures many long-tail searches.

10. Analyze Google's "People Also Ask"

Question keywords are often easier to rank for.

Collect questions like:

• How do I...?
• Why does...?
• What is...?
• Which is better...?
• When should...?

Then answer them thoroughly with dedicated sections or standalone articles.

11. Check search operators

Use searches like:

"<keyword>" site:forum

or

"<keyword>" inurl:forum

to discover real user discussions and common phrasing in your target language.

12. Use Wikipedia in the target language

The table of contents, internal links, and article titles often reveal terminology and related concepts that people search for.

Evaluating long-tail keywords

Don't rely only on search volume. Consider:

• Search intent: Does it match what your page offers?
• Competition: Can your site realistically rank?
• Topical relevance: Is it central to your niche?
• Business value: Will ranking help you achieve your goals?
• SERP quality: Are the top results weak, outdated, or missing information?
• Content gap: Can you create something clearly better?

Many valuable long-tail keywords have very low reported search volume because keyword databases have limited coverage, especially in smaller languages. They can still drive meaningful traffic when grouped into comprehensive content.

A practical workflow

1. Gather 20–50 seed keywords.
2. Expand them with Google Autocomplete and related searches.
3. Collect "People Also Ask" questions.
4. Expand variations with an SEO tool.
5. Mine competitors' ranking pages.
6. Group keywords by search intent.
7. Create comprehensive pages that naturally target dozens of related long-tail phrases instead of one exact keyword.
8. Monitor Google Search Console and refine content based on the actual queries your pages begin to rank for.

For sites in languages with smaller search ecosystems (e.g., Finnish, Czech, Thai, Hebrew, etc.), this combination of Google Search + Search Console + competitor analysis + local forums often uncovers far more actionable long-tail opportunities than relying on keyword volume tools alone.