ChatGPT answers, unedited

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.

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.

If your site targets a non-English audience, the biggest

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.

If your site is in a language other than English, the process is fundamentally the same, but you need tools that use search data from your target language and country rather than relying on translated English keywords.

Here's a practical workflow.

1. Start with native-language seed keywords

Avoid translating English keywords directly. Instead:

• List the words your audience actually uses.
• Ask native speakers how they'd search.
• Check competitors' page titles and headings.
• Look at customer emails, support tickets, and reviews.

For example, literal translations often miss common phrasing, slang, or regional variations.

2. Use Google's own search features

These work in nearly every language.

Search your seed keyword on Google using the target country's Google domain and language settings, then collect:

• Autocomplete suggestions
• "People Also Ask" questions
• Related searches
• Bolded synonyms in results

These often reveal excellent long-tail keywords.

3. Keyword research tools with international databases

The best general-purpose tools include:

The key is selecting the correct language and country database before searching.

4. Use Google Search Console

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

Look for:

• impressions with low clicks
• queries ranking in positions 8–20
• long phrases
• question-based searches

These represent real searches from your audience.

5. Mine forums and communities

Every language has its own discussion sites.

Examples include:

• Reddit (where relevant)
• country-specific forums
• Facebook groups
• local Q&A websites
• industry communities

Look for repeated questions people ask in natural language.

6. Use AI—but validate with search data

AI is excellent for expanding topics.

For example, ask:

Give me 100 questions a homeowner in Spain might ask about solar panels in Spanish.

or

List informational, transactional, and comparison searches in Polish for accounting software.

Then verify those ideas using keyword tools or Search Console.

7. Analyze competitors

Tools like Ahrefs and Semrush let you see:

• pages bringing traffic
• keywords they rank for
• question keywords
• content gaps

This works regardless of language as long as the tool has data for that region.

8. Look for question keywords

Many languages have equivalents of:

• how
• why
• what
• when
• where
• best
• cheapest
• near me
• vs
• review

Most keyword tools can filter keywords that begin with question words in the target language.

9. Evaluate keyword difficulty manually

In smaller language markets, keyword difficulty scores can be less reliable. Check the search results yourself:

• Are the top results from large, authoritative websites?
• Are there forum threads or smaller niche sites ranking?
• Are the pages comprehensive or relatively thin?
• Is the search intent clear and consistent?

If weaker pages rank, you may have an opportunity even if the tool's difficulty score seems high.

10. Build topic clusters

Instead of targeting isolated keywords, group related long-tail searches into comprehensive content.

For example:

Main topic

• Installing solar panels

Supporting articles:

• Cost of installation
• Government incentives
• Maintenance
• Winter performance
• Roof requirements
• Battery storage
• Common mistakes

This approach tends to perform better than creating many thin pages.

If your language is low-resource

For languages with limited keyword databases (for example, Latvian, Lithuanian, Georgian, Armenian, or some African languages), combine multiple sources:

• Google Search Console
• Google Autocomplete
• Competitor research
• AI-generated keyword ideas
• Local forums
• Internal site search logs

These often provide richer insights than keyword tools alone.

If you tell me which language and country you're targeting (for example, Finnish in Finland, Arabic in Egypt, Thai in Thailand, etc.), I can recommend the tools that have the strongest keyword coverage for that specific market and suggest techniques that work well there.

If your site targets a non-English audience, the biggest challenge is that many keyword tools are much stronger in English than in other languages. The best results usually come from combining several data sources rather than relying on a single tool.

Here are the methods that tend to work well.

1. Use Google Search itself (often the highest-quality source)

Search in the target language and look for:

• Autocomplete suggestions
• "People Also Ask" questions (where available)
• Related searches at the bottom
• Google Images autocomplete
• Google Shopping autocomplete (for commercial topics)

For example, instead of translating an English keyword, search as a native speaker would.

Example:

• English: "best running shoes"
• Spanish users might search:
  • "mejores zapatillas para correr"
  • "qué zapatillas sirven para..."
  • "cómo elegir zapatillas..."

Those reveal natural phrasing that translation often misses.

2. Use SEO tools with international databases

The better ones include:

• Ahrefs
  • Strong keyword explorer
  • Good question reports
  • Supports many countries/languages

• Semrush
  • Keyword Magic Tool
  • Question filtering
  • Local country databases

• Mangools
  • Easier interface
  • Works surprisingly well for medium-sized languages

• SE Ranking
  • Good international coverage
  • Often cheaper

These tools are strongest when you select the correct country database rather than using "global."

3. Use Google Search Console

This is one of the most valuable sources because it shows what real users are already searching.

Look for:

• queries with many impressions
• positions 8–25
• long phrases
• question words
• unexpected variations

Often you'll discover hundreds of long-tail phrases that no keyword tool reports.

4. Mine forums and communities in the target language

Every language has its own communities.

Look for:

• Reddit (where applicable)
• local discussion forums
• Facebook groups
• Quora equivalents
• country-specific Q&A sites

Extract:

• exact wording
• recurring questions
• terminology
• slang
• beginner questions

These are excellent sources of article ideas.

5. Use autocomplete scraping tools

These expand Google's suggestions automatically.

Popular options:

• Keyword Tool
• AnswerThePublic
• AlsoAsked
• Keyword Sheeter

They often support dozens of languages.

6. Use AI—but start from native keywords

A mistake is asking AI:

"Translate my English keyword."

A better prompt is:

"Generate 100 ways native speakers in Poland would search for information about X. Include beginner questions, buying intent, troubleshooting, comparisons, and conversational searches."

Then verify those suggestions using Search Console or keyword tools.

7. Analyze competitors in the same language

Don't analyze English competitors.

Instead:

• export their ranking keywords
• identify their informational pages
• inspect FAQ sections
• review category pages
• examine title tags and H2 headings

Often you'll uncover many long-tail opportunities that general keyword databases miss.

8. Use question words specific to the language

Every language has its own common interrogatives.

For example:

• who
• what
• when
• where
• why
• how
• which
• can
• should
• does

Combine them with seed keywords to generate article ideas.

9. Look at search suggestions on local marketplaces

If your topic involves products, marketplaces can reveal buying-intent phrases.

Examples include:

• Amazon (where relevant)
• local e-commerce sites
• classifieds
• pharmacy websites
• travel booking sites

Autocomplete there often surfaces commercial long-tail keywords that Google tools don't.

10. Build topical clusters instead of isolated keywords

Instead of targeting only:

"coffee grinder"

Create clusters around:

• buying guides
• comparisons
• troubleshooting
• maintenance
• beginner questions
• price
• reviews
• alternatives
• accessories

This naturally captures hundreds of long-tail searches.

If search volume is low

Many languages have limited keyword data. In that case, rely more heavily on:

• Google Search Console
• Google autocomplete
• competitor rankings
• internal site search
• customer support questions
• social media comments
• community discussions

These often reveal valuable queries that commercial tools never report.

A practical workflow

1. Start with 20–50 seed keywords in the target language (not translated literally).
2. Expand them using Google Autocomplete and question tools.
3. Validate search demand with Ahrefs or Semrush where data exists.
4. Check Google Search Console for real impressions and low-hanging opportunities.
5. Group related long-tail keywords into topic clusters instead of creating one page per keyword.
6. Review native-language forums and competitor content to find gaps and natural phrasing.

If you tell me the language (for example, Polish, Thai, Arabic, Finnish, Vietnamese, etc.) and the topic or niche of your site, I can recommend the tools and techniques that tend to work best for that specific language and market.