Answers that do not mention Moz

If you’re a small niche blog on a tight budget, I wouldn’t start with an expensive all-in-one SEO suite. Your goal is less “find the biggest keywords” and more find keywords where weak sites are already ranking.

My shortlist

Ahrefs' free generator can surface keyword ideas, questions, search volume and some difficulty information, while its SERP Checker lets you inspect the actual top 10 results. Ahrefs Ahrefs

LowFruits is particularly interesting for your situation: its core purpose is identifying long-tail keywords where the SERP contains comparatively weak sites. That's often more useful for a small blog than simply looking at a generic “KD 20” score. Techcognate theStacc

What I'd actually use

$0/month:

1. Use Google Keyword Planner to generate a big list.
2. Use Ahrefs Free Keyword Generator to expand each seed into questions, related phrases and long tails.
3. Put promising keywords into a spreadsheet.
4. Manually check the Google SERP.
5. Prioritize keywords where several results are from small/niche sites, forums, weakly optimized pages, or pages that don't directly satisfy the query.

Google Keyword Planner is free, although its SEO usefulness is somewhat limited because search-volume data can be presented as ranges rather than precise numbers. Ahrefs Ahrefs

Around $20–30/month: I'd seriously consider LowFruits if your primary objective is “give me keywords my small site has a realistic shot at ranking for.” Current 2026 comparisons put it around the low-$20s/month, with pay-as-you-go options also available. theStacc Consumercat

Around $30/month: KWFinder/Mangools is probably the better choice if you want a more conventional, easy-to-use keyword research suite rather than a specialist low-competition finder. Techcognate AppSEO

Don't blindly trust Keyword Difficulty

This is probably the most important point.

A keyword with KD 15 isn't automatically easier than one with KD 25. Difficulty scores are estimates based on particular signals. For example, Ahrefs' KD is primarily based on the backlink strength of the top-ranking pages and explicitly recommends doing actual SERP analysis rather than relying on KD alone. Ahrefs

For a small site, I'd score each candidate something like:

Ranking opportunity =

• Low/medium competition
• Search intent you can satisfy exceptionally well
• At least 1–3 weak pages currently ranking
• Reasonable search demand
• Topic closely related to your site's authority
• Realistic ability to create something substantially better

That can beat chasing a keyword with 10,000 searches/month where the first page is dominated by giant sites.

My recommended budget stack

$0:
Google Keyword Planner + Ahrefs Free Keyword Generator + Google Search Console

~$20–30/month:
LowFruits + free Google/Ahrefs tools

~$30/month:
KWFinder/Mangools

I would not pay $100+ per month for Semrush or Ahrefs initially unless you're doing enough SEO work that their competitor research, backlink data, rank tracking, etc. will actually save you substantial time. Current comparisons put the major full suites substantially above the budget-oriented options. Techcognate theStacc

If you tell me your niche + roughly how many pages/articles your site has + whether your site is new or already getting Google traffic, I can give you a very specific keyword-research workflow and a scoring formula for deciding which long-tails to publish first.

For a SaaS client, I’d use a stack rather than relying on a single keyword tool. The key is to distinguish search volume from commercial relevance.

Recommended SaaS keyword-research stack

Ahrefs explicitly supports filtering keywords by informational, navigational, commercial and transactional intent. Ahrefs Help Center Semrush similarly combines intent, volume, competition and SERP/competitor data. Semrush

1. Start with Ahrefs/Semrush, but don't trust the intent label blindly

For SaaS, I'd build seed groups around:

• [category] software
• [category] platform
• [category] tool
• best [category] software
• [category] software comparison
• [competitor] alternatives
• [competitor] vs [competitor]
• [category] pricing
• [category] cost
• [product category] for [industry/use case]
• [product category] for [job role]
• [product] demo
• [product] free trial

Then filter toward commercial + transactional intent.

The important distinction is that "commercial" doesn't necessarily mean "ready to buy." Someone searching best project management software is valuable, but someone searching [brand] pricing or [brand] alternatives is usually much further down the funnel.

2. Use GSC as your "reality check"

This is one of the most valuable tools once you have access to the client's account.

search.google.com

Export queries and look for:

• High impressions + low CTR
• Positions ~4–20
• Queries containing product/category terms
• Queries generating conversions or landing on money pages
• Long-tail queries that your keyword tool doesn't surface
• Existing pages ranking for commercially relevant terms

GSC lets you filter queries, pages, countries, devices and other dimensions, including regex filters. Google Help Google Help

This is especially useful because you're analyzing actual searches that have already triggered the client's site, rather than estimated keyword-tool demand.

3. Use SERP analysis to kill "informational fluff"

This is the step I'd make mandatory.

For every prospective keyword, ask:

"If our SaaS ranked #1 here, would a meaningful percentage of these searchers plausibly become pipeline?"

Then inspect the SERP.

For example:

what is CRM

Probably informational fluff for a mature CRM SaaS.

CRM software for small business

Much more commercially relevant.

best CRM for SaaS startups

Strong commercial investigation.

HubSpot alternatives

Very strong competitive/commercial intent.

HubSpot pricing

Extremely strong product intent.

The SERP itself is your best intent classifier. If the results are dominated by Wikipedia, educational guides, definitions and beginner articles, don't automatically create a page just because volume looks attractive.

If the SERP contains SaaS product pages, comparison pages, pricing pages, review sites and vendors, that's a much stronger signal.

4. Use CPC as a signal, not a ranking factor

Google Keyword Planner can help here because it exposes metrics such as average monthly searches and top-of-page bid ranges. Google Help

A useful heuristic is:

High CPC + relevant SaaS query + commercial SERP = investigate

But don't automatically discard a $0-CPC keyword or prioritize a high-CPC keyword. CPC reflects advertising economics, not necessarily organic conversion propensity.

5. Build an agency-specific intent score

I'd actually put every keyword into a spreadsheet/database with something like:

Buyer Intent Score =

• +3 transactional
• +2 commercial investigation
• +2 contains product/category
• +2 comparison/alternative intent
• +2 pricing/cost intent
• +1 "for [industry/use case]"
• +1 competitor term
• +1 strong commercial SERP
• −3 definition/question intent
• −2 educational/how-to SERP
• −2 unrelated audience/use case

Then classify:

• 8+ → BOFU / money-page candidate
• 5–7 → commercial content
• 2–4 → supporting content
• ≤1 → probably informational / deprioritize

You can adjust the weights based on the SaaS's actual conversion data.

The bigger trick: don't filter out all informational keywords

For SaaS SEO, I'd separate the keyword universe into:

Tier 1 — Revenue

• pricing
• alternatives
• comparisons
• best tools
• software/platform/tool terms
• product/category + use case
• competitor searches
• demo/trial/signup terms

Tier 2 — Problem-aware

• [problem] software
• how to solve [business problem]
• [workflow] automation
• [process] tools
• [use case] platform

Tier 3 — Educational

• definitions
• how-to guides
• broad educational questions
• templates
• terminology

Tier 3 isn't useless—it can build topical authority and introduce prospects earlier in the funnel. But don't let Tier 3 dominate the editorial calendar simply because it has 10× the search volume.

My preferred workflow

Ahrefs/Semrush → competitor gap → intent filtering → GSC → SERP validation → conversion data → keyword prioritization

That gives you three independent signals:

1. Does anyone search for it?
2. Does the SERP indicate commercial intent?
3. Does this audience actually matter to the SaaS business?

That third question is where many SEO agencies go wrong.

I'd also tie the final keyword list to ICP + use case + funnel stage + target URL + estimated business value, rather than delivering the client a giant 10,000-keyword export.

1. Does anyone search for it?
2. Does the SERP indicate commercial intent?
3. Does this audience actually matter to the SaaS business?

That third question is where many SEO agencies go wrong.

I'd also tie the final keyword list to ICP + use case + funnel stage + target URL + estimated business value, rather than delivering the client a giant 10,000-keyword export.

If the SERP contains SaaS product pages, comparison pages, pricing pages, review sites and vendors, that's a much stronger signal.

4. Use CPC as a signal, not a ranking factor

Google Keyword Planner can help here because it exposes metrics such as average monthly searches and top-of-page bid ranges.

A useful heuristic is:

High CPC + relevant SaaS query + commercial SERP = investigate

For a SaaS client, I’d avoid treating keyword research as “find high-volume keywords.” The goal is find queries where the searcher is plausibly evaluating, adopting, switching to, or buying software—then use SERP evidence to eliminate informational traffic.

The stack I’d use

• ahrefs.com — primary research tool.

Use Keywords Explorer for seed expansion, competitor keywords, CPC, SERP features, traffic potential, intent, and clustering. Ahrefs specifically supports intent filtering and SERP analysis, which is useful for separating commercial queries from educational ones. Ahrefs Ahrefs

• semrush.com — excellent alternative/complement.

Keyword Magic + Keyword Gap are particularly useful for SaaS because you can find keywords competitors rank for and filter by intent, CPC, difficulty, etc. Semrush's current tooling explicitly exposes search intent and CPC alongside volume and difficulty. Semrush Semrush

• Google Search Console — mandatory for an existing SaaS site.

This gives you the actual queries already producing impressions/clicks, which is extremely valuable for finding commercial terms Google already associates with the client's pages. It doesn't provide the competitive metrics that Ahrefs/Semrush do, so use it alongside them. Ahrefs

• Google Keyword Planner — validation layer.

Particularly useful for CPC/commercial-value signals and Google-derived demand data. I wouldn't use it as your primary discovery database.

• Google SERPs themselves — the final arbiter.

This is the part agencies often skip. If you're unsure whether crm software or crm reporting is actually buyer intent, inspect the top 10. If most results are product pages, comparison pages, review sites, demos, pricing pages, etc., that's much stronger evidence of commercial intent than an algorithmic “commercial” label.

How I'd filter the keyword export

I'd build a scoring model rather than simply filtering Intent = Commercial.

1. Start with buyer-intent modifiers

For SaaS, heavily prioritize terms containing things like:

• software
• platform
• tool
• solution
• app
• pricing
• cost
• demo
• trial
• buy
• alternative
• alternatives
• vs
• comparison
• review
• best
• for [industry]
• for [use case]
• enterprise
• integration
• implementation

For example:

Very strong:

• project management software
• best project management software for agencies
• asana alternatives
• project management software pricing
• enterprise project management platform

Potentially useful but needs SERP validation:

• project management workflow
• project management automation
• project management dashboard

Usually informational:

• what is project management
• how to manage a project
• project management tips
• project management examples

Ahrefs similarly recommends modifiers such as buy, order, sale, best price, best, top, review, and alternatives, while emphasizing that SERP inspection is the stronger validation step. Ahrefs

2. Use CPC as a signal, not a filter

For SaaS, CPC can be surprisingly useful.

If someone is paying meaningful money to advertise against:

employee scheduling software

that's evidence that the query has commercial value.

But don't say “CPC > $X = buyer intent.” Some informational keywords have expensive CPCs, and some highly valuable SaaS queries have relatively little paid competition.

I'd give CPC a weighted score instead.

3. Use SERP composition as your strongest intent filter

This is the filter I'd put into your agency process.

Score each keyword based on what's ranking:

So if you have:

“employee onboarding software”

and the SERP is primarily SaaS vendors and comparison sites → high priority.

But:

“employee onboarding process”

with guides, templates, HR blogs and PDFs dominating → probably informational.

That's much more reliable than blindly trusting keyword-tool intent labels.

4. Steal the competitors' money keywords

For a SaaS onboarding, I'd make this one of the first deliverables.

Take 5–10 competitors into Ahrefs/Semrush and export:

Competitor → Organic keywords → position 1–20 → commercial modifiers/intents → relevant landing pages

Then look for patterns such as:

• [category] software
• [category] platform
• best [category] software
• [competitor] alternatives
• [competitor] vs [competitor]
• [category] pricing
• [category] for [vertical]
• [category] for [job role]
• [category] integration
• [category] automation

This often produces a much better SaaS keyword universe than starting with generic topic brainstorming.

5. Don't automatically throw away informational keywords

I'd separate them into three buckets, rather than “good/bad”:

Tier 1 — BOFU

pricing, demo, software, platform, alternatives, comparison, vendor/product terms

These should generally map to money pages.

Tier 2 — MOFU

best, reviews, comparisons, use cases, “[category] for [industry]”

These can generate excellent commercial traffic and comparison content.

Tier 3 — TOFU

what is, how to, guide, examples, definition, tips

Keep only the TOFU terms that have a credible path toward the SaaS product. Otherwise, they're often the “informational fluff” you're trying to avoid.

My recommended agency workflow

I'd actually build the onboarding spreadsheet like this:

Ahrefs/Semrush discovery → competitor gap → GSC enrichment → automated filtering → manual SERP validation → keyword clustering → page mapping

For every keyword, retain:

Keyword | Volume | KD | CPC | Intent | SERP type | Competitor ranking | Current client URL | Funnel stage | Business relevance | Priority

Then give each keyword a Buyer Intent Score / 100.

A simple version:

Business relevance 30% + SERP intent 30% + CPC 15% + commercial modifiers 15% + competitor evidence 10%

That prevents the classic agency mistake of delivering 5,000 “relevant” keywords where 4,200 are people looking for definitions and how-to articles.

If I were setting up the stack from scratch for a SaaS agency, I'd use Ahrefs + GSC as the core, Semrush if you want stronger competitor/PPC research, and a spreadsheet/script for the actual buyer-intent scoring. The tools discover the keywords; your scoring framework decides whether they're worth pursuing. Semrush Ahrefs

• [category] software
• [category] platform
• best [category] software
• [competitor] alternatives
• [competitor] vs [competitor]
• [category] pricing
• [category] for [vertical]
• [category] for [job role]
• [category] integration
• [category] automation

This often produces a much better SaaS keyword universe than starting with generic topic brainstorming.

5. Don't automatically throw away informational keywords

I'd separate them into three buckets, rather than “good/bad”:

Tier 1 — BOFU

pricing, demo, software, platform, alternatives, comparison, vendor/product terms

These should generally map to money pages.

Tier 2 — MOFU

best, reviews, comparisons, use cases, “[category] for [industry]”

These can generate excellent commercial traffic and comparison content.

Tier 3 — TOFU

what is, how to, guide, examples, definition, tips

Keep only the TOFU terms that have a credible path toward the SaaS product. Otherwise, they're often the “informational fluff” you're trying to avoid.

My recommended agency workflow

I'd actually build the onboarding spreadsheet like this:

Ahrefs/Semrush discovery → competitor gap → GSC enrichment → automated filtering → manual SERP validation → keyword clustering → page mapping

For every keyword, retain:

Keyword | Volume | KD | CPC | Intent | SERP type | Competitor ranking | Current client URL | Funnel stage | Business relevance | Priority

Then give each keyword a Buyer Intent Score / 100.

A simple version:

Business relevance 30% + SERP intent 30% + CPC 15% + commercial modifiers 15% + competitor evidence 10%

That prevents the classic agency mistake of delivering 5,000 “relevant” keywords where 4,200 are people looking for definitions and how-to articles.

If I were setting up the stack from scratch for a SaaS agency, I'd use Ahrefs + GSC as the core, Semrush if you want stronger competitor/PPC research, and a spreadsheet/script for the actual buyer-intent scoring. The tools discover the keywords; your scoring framework decides whether they're worth pursuing. Semrush Ahrefs

For a brand-new site, I’d avoid paying $100+/month for an SEO suite initially. The most useful setup is a combination of one tool for generating long-tail ideas, one for assessing difficulty, and manual SERP inspection.

Here are the tools I’d prioritize:

If I were launching a site today, I'd start with Ahrefs' free tools. Its Keyword Generator produces related phrases and questions, while its separate Keyword Difficulty Checker estimates ranking difficulty. Ahrefs explicitly recommends combining difficulty with actual SERP analysis rather than treating KD as definitive. Ahrefs Ahrefs

A particularly effective $0 workflow

Suppose your niche is backyard vegetable gardening.

Start with broad seeds such as:

raised garden bed
tomato plants
vegetable garden

Put those into ahrefs.com and look especially at its Questions and search-suggestion ideas. Ahrefs supports filters including word count and Keyword Difficulty in its fuller keyword workflow, which are particularly useful for exposing long-tail phrases. Ahrefs Ahrefs

Instead of targeting:

raised garden beds

look for things like:

best soil for raised garden beds in florida
how deep should raised beds be for tomatoes
can you put raised garden beds over grass
vegetables that grow in shallow raised beds

Then manually Google promising phrases.

For a new domain, the SERP is often more informative than the tool's difficulty number. I'd get interested when page one contains things such as Reddit/Quora/forum discussions, small niche blogs, pages that only partially answer the query, outdated articles, or pages with relatively weak backlink profiles. Conversely, if every result is from huge authoritative sites with highly targeted pages, a "KD 5" keyword may still not be attractive.

LowFruits is the first paid tool I'd consider

lowfruits.io is particularly interesting for this specific strategy because its whole premise is finding low-competition SERPs and weaker ranking competitors, rather than merely producing giant keyword lists.

That distinction matters.

For a new site, I care less about finding:

10,000 keywords with volume

and more about finding:

100 keywords where Google is already willing to rank sites comparable to mine.

Don't overlook Google itself

Autocomplete is one of the best free long-tail generators available. Try modifier patterns such as:

how to [topic]
[topic] for beginners
[topic] without ___
[topic] for ___
best ___ for ___
why does ___
can you ___
___ vs ___
___ alternatives
___ problems

Then mine People Also Ask and related searches.

Google Keyword Planner can help establish whether there's meaningful search demand, but don't confuse its Competition metric with organic SEO difficulty. That metric concerns advertising competition; Ahrefs' KD, for example, attempts to estimate organic ranking difficulty. Ahrefs

One important change I'd make for a brand-new site

Don't require every keyword to have 500+ searches/month.

A keyword showing only 20–100 searches can be excellent if the intent is strong and the SERP is weak. Individual long-tail queries have low volume by definition, and one well-structured article can rank for many related queries rather than only its primary keyword. Ahrefs

I'd therefore prioritize roughly:

weak SERP → clear intent → topical relevance → business value → estimated volume

rather than:

search volume → KD → everything else.

If you tell me the niche/topic of the new site, I can also show you a practical process for finding the first 50–100 low-competition keywords without buying Ahrefs or Semrush.

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

Best methods

1. Start with native-language seed terms

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

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

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

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

2. Use keyword tools with country/language targeting

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

ahrefs.com

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

semrush.com

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

3. Mine Google itself

This is one of my favorite approaches for smaller languages.

Search your native-language seed and collect:

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

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

4. Use Google Trends for language-specific demand

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

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

There's also an important distinction:

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

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

5. Mine your own Search Console data

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

Export queries from Google Search Console and look for:

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

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

6. Look outside traditional SEO tools

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

Depending on the language, mine:

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

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

A particularly effective workflow

I'd use this pipeline:

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

Then score each candidate on something like:

One important warning

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

A native speaker might use completely different:

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

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

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

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

One important warning

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

A native speaker might use completely different:

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

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

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

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

Yes. If your main goal is “find lots of long-tail keywords → filter by intent → filter by ranking difficulty”, I’d shortlist these:

My pick: Semrush

Semrush Keyword Magic Tool is probably the closest match to exactly what you're describing. It lets you generate large keyword sets and filter simultaneously by keyword difficulty, search intent, volume, word count, SERP features, and included/excluded words. It also automatically groups related keywords into topical subgroups. Semrush Semrush

A useful workflow would be:

1. Enter your seed keyword.
2. Set Intent = informational / commercial / transactional, depending on what you want.
3. Set KD ≤ 30 (or lower if your site is new).
4. Set a minimum search volume appropriate to your niche.
5. Filter by word count ≥ 4–5 to bias toward long-tail terms.
6. Look at the SERPs for the remaining keywords before creating content.

Semrush specifically recommends looking for long-tail variants and filtering by low KD to uncover easier opportunities. Semrush

Ahrefs is arguably better for serious SEO research

Ahrefs Keywords Explorer has an enormous keyword database and lets you filter by search intent, keyword difficulty, traffic potential, volume, etc. Its intent classification includes informational, navigational, commercial, and transactional intent. Ahrefs Help Center Ahrefs

The big advantage is its SERP analysis and Traffic Potential. Ahrefs' KD is primarily based on the backlink strength of the top-ranking pages, so you can use it to identify queries where the competition's link profiles are relatively weak. Ahrefs Help Center

LowFruits is worth considering if you're specifically hunting "easy wins"

If your objective isn't just low KD, but keywords where weak websites are already ranking, I'd add LowFruits to the stack. That's a different and often more useful concept than relying on a generic 0–100 difficulty score.

For example, rather than simply saying:

“Keyword has KD 18, therefore it's easy.”

you want to ask:

“Are there several low-authority sites ranking on page one?”

That's often a much stronger indication of an opportunity.

What I'd use depending on your situation

• New/small website: Semrush + LowFruits
• Established SEO site: Ahrefs
• Agency/content team: Semrush
• Simple/cheap keyword research: KWFinder
• Maximum opportunity hunting: Ahrefs + LowFruits

One important caveat: don't treat keyword difficulty as an absolute measure of ranking difficulty. Different tools calculate it differently. Ahrefs' KD, for example, is heavily backlink-based, while actual ranking difficulty also depends on content quality, topical authority, search intent, SERP features, brand strength, and the quality of the current results. Ahrefs Help Center

If you tell me your niche/site and roughly how authoritative the site is, I can also give you a specific filter recipe (e.g. KD < 20 + 4+ words + commercial intent + 100+ searches/month) for finding long-tail opportunities.

If your objective isn't just low KD, but keywords where weak websites are already ranking, I'd add LowFruits to the stack. That's a different and often more useful concept than relying on a generic 0–100 difficulty score.

For example, rather than simply saying:

“Keyword has KD 18, therefore it's easy.”

you want to ask:

“Are there several low-authority sites ranking on page one?”

That's often a much stronger indication of an opportunity.

What I'd use depending on your situation

• New/small website: Semrush + LowFruits
• Established SEO site: Ahrefs
• Agency/content team: Semrush
• Simple/cheap keyword research: KWFinder
• Maximum opportunity hunting: Ahrefs + LowFruits

One important caveat: don't treat keyword difficulty as an absolute measure of ranking difficulty. Different tools calculate it differently. Ahrefs' KD, for example, is heavily backlink-based, while actual ranking difficulty also depends on content quality, topical authority, search intent, SERP features, brand strength, and the quality of the current results.

If your goal is specifically question-based keywords + traffic potential + competitiveness, I’d shortlist these:

1. ahrefs.com — best overall

• Has a Questions filter for queries containing words like how, why, what, etc. Ahrefs Help Center
• Shows search volume, Keyword Difficulty (KD), SERP data, and Traffic Potential. Ahrefs
• Its Traffic Potential is particularly useful because it estimates the organic traffic the current #1 page gets from all the keywords it ranks for, rather than looking only at volume for one query. Ahrefs Help Center
• My pick if you're building an SEO content strategy.
• semrush.com — best for filtering and prioritization

• Has a dedicated Questions-only filter. Semrush
• Lets you filter/sort by volume, keyword difficulty, intent, CPC, SERP features, etc. Semrush
• Semrush also has Potential Traffic and Personal Keyword Difficulty, which can make prioritization more tailored to your particular domain. Semrush
• My pick if you want lots of filtering and a broader marketing/SEO platform.

My recommendation

If you want a simple workflow like:

Find questions → estimate traffic → assess competition → decide what to write

I'd choose Ahrefs.

A useful prioritization formula would be:

Priority = Traffic Potential × Relevance ÷ Difficulty

For example, I'd rather target a question with 5,000 potential visits and KD 15 than one with 20,000 volume but KD 80, assuming both are equally relevant to your business.

If you tell me your niche/website topic, I can also recommend the best tool for your specific use case and give you a concrete keyword-research workflow.

If your main goal is keyword difficulty + related-keyword clustering + turning the research into a content plan, I’d shortlist these:

1. Semrush — best overall for content planning

semrush.com

My top pick for your use case. Its Keyword Strategy Builder automatically groups keywords into topics, pillar pages, and subpages, while incorporating search volume, keyword difficulty, intent, and SERP data. Semrush Semrush

It also has Keyword Magic Tool, which automatically groups related terms into topic-specific subgroups and provides difficulty/volume data. Semrush

Best if: you want to go from “here are my seed keywords” → “here's my content roadmap.”

2. Ahrefs — best for deep SEO research

ahrefs.com

Ahrefs Keywords Explorer provides Keyword Difficulty, search volume, Traffic Potential, Parent Topic, and instant clustering by both parent topic and terms. Ahrefs

Its KD score is particularly straightforward: it's a 0–100 estimate based primarily on the backlink strength of top-ranking pages. Ahrefs

Best if: you care heavily about competitive analysis, SERPs, backlinks, and finding keywords that have realistic ranking potential.

3. Ubersuggest plugin — easiest lightweight option inside ChatGPT

I also found an available Ubersuggest plugin that can provide keyword ideas, related search terms, estimated search volume, keyword difficulty, and CPC directly in ChatGPT.

Best if: you want quick keyword research without adopting a full enterprise SEO platform.

My recommendation

For content planning specifically, I'd choose Semrush. Its clustering functionality is closest to your exact requirement because it doesn't just tell you that keywords are related—it organizes them into pillar/subpage structures you can turn directly into an editorial plan. Semrush

If you're primarily an SEO specialist doing deep competitive research, I'd choose Ahrefs instead.

If you want, I can also compare Semrush vs Ahrefs vs Ubersuggest specifically for keyword clustering, pricing, API/plugin availability, and content-calendar workflows.

If your main job is “find obscure question-style queries → prioritize them → hand writers a clean export,” I’d shortlist these:

1. Semrush — best overall for your workflow.

Keyword Magic Tool has a dedicated Questions filter, topical grouping, difficulty/volume filters, keyword lists, and exports to CSV/XLSX. That makes it particularly good for turning research into writer-ready batches. Semrush Semrush
semrush.com

2. Ahrefs — best if prioritization quality matters more than sheer workflow convenience.

Keywords Explorer can filter specifically for questions, surface related terms, analyze search intent, identify weak-ranking opportunities, and organize keywords into lists. You can export reports to CSV or Google Sheets. Ahrefs Help Center Ahrefs Help Center Ahrefs
ahrefs.com

3. LowFruits — worth considering if “niche” means low-competition long-tail.

Its focus is less “give me every question” and more “show me questions/long-tail queries where relatively weak sites are already ranking.” That's potentially excellent for finding assignments your writers can actually win. Consumercat

4. AlsoAsked / AnswerThePublic — best as question-discovery supplements.

They're useful for uncovering the language and question chains people use, especially around a seed topic, but I wouldn't make either the primary prioritization/export system if you need robust SEO metrics. Consumercat

What I'd choose

For a content team, I'd probably use:

Semrush → filter Questions → filter by difficulty/volume/intent → cluster/group → export → writers

That is the cleanest all-in-one workflow. Semrush explicitly supports exporting selected keywords and preserving keyword groups in Excel, which is handy for handing writers organized topic batches rather than a giant undifferentiated CSV. Semrush

If your definition of “prioritized” is more sophisticated—e.g. low difficulty + meaningful traffic potential + weak competitors + strong informational intent—I'd lean Ahrefs. Its current Keywords Explorer specifically supports intent analysis, keyword clustering, and identifying opportunities based on the SERPs. Ahrefs

My pick: Semrush for a writer-oriented production workflow; Ahrefs for deeper SEO opportunity analysis.

If you tell me your niche + approximate monthly keyword-research volume + number of writers, I can recommend the specific tool/workflow (including what columns and scoring formula I'd put in the exported writer list).

If your priority is keyword discovery + search-intent classification + fast filtering for genuinely low-competition opportunities, I’d recommend LowFruits.

lowfruits.io

Why it fits especially well:

• Keyword discovery: generates long-tail ideas from seed keywords, Google Autocomplete, related queries, PAA, and wildcard searches. LowFruits LowFruits
• Intent filtering: lets you filter for intent, including pre-purchase/commercial intent and informational queries. LowFruits LowFruits
• Low-competition identification: rather than relying only on a generic KD number, it analyzes the actual SERPs and highlights weak/low-authority sites ranking in the top results. LowFruits
• Easy filtering: you can narrow results by topic, intent, SERP difficulty, weak domains, volume, and other attributes. LowFruits LowFruits
• Keyword clustering: groups related keywords by SERPs/semantics, making it easier to turn opportunities into content clusters. LowFruits

My pick

LowFruits is probably the best match if your goal is “show me keywords I could realistically rank for” rather than simply “give me a giant keyword database.”

If you want a more all-in-one SEO suite, Semrush is the stronger alternative: it combines keyword suggestions, intent, difficulty, competitor keyword gaps, and extensive filtering. semrush.com semrush.com

For pure low-competition opportunity hunting, though, I'd start with LowFruits.

A strong fit is Semrush or Ahrefs for full SEO workflows, but for specifically long-tail + question keywords + filtering + CSV export, consider:

• ahrefs.com — robust keyword explorer, difficulty/volume metrics, SERP analysis, filters, and exports.
• semrush.com — strong intent filters, keyword clustering, competitor research, and CSV exports. TechRadar
• keywordtool.io — excellent for autocomplete-based long-tail and question discovery. TechRadar
• hypersuggest.com — built around question discovery, advanced filtering, and CSV/XLSX exports. HyperSuggest
• ranklogs.com — surfaces long-tail ideas, related questions, intent, prioritization, and CSV export. Ranklogs

If you want a lighter/free option focused on question mining:

• rankseedhq.com — finds question-style and long-tail queries with filtering and CSV export. rankseed

For an SEO team workflow, I’d pick Semrush/Ahrefs; for content ideation and FAQ mining, HyperSuggest or rankseed are more targeted.

Yes. Marketers usually use a stack, because different tools are good at different parts of long-tail research.

Best tools by use case

If your goal is specifically niche + long-tail + questions

I'd use this workflow:

1. Start with Semrush or Ahrefs

Put in a broad seed such as:

backyard chickens

Then pull:

• long-tail variations
• questions
• related terms
• competitor keywords
• low-difficulty queries

Both Semrush and Ahrefs have explicit ways of filtering for question queries. Semrush Ahrefs Help Center

2. Run the same seed through AlsoAsked

This is where things get interesting. Instead of simply giving you keyword variations, it helps reveal the question relationships around the topic.

For example, you might go from:

backyard chickens

to:

• Can you keep chickens in a small backyard?
• How many chickens should a beginner get?
• What do chickens need in a backyard?
• Do backyard chickens attract rats?
• How much does it cost to keep chickens?
• What chickens are best for cold climates?

That's often more useful for content planning than a giant spreadsheet of keyword variations.

3. Run the topic through LowFruits

Now ask a different question:

Which of these searches could a relatively small site realistically rank for?

That's where tools like LowFruits become particularly useful. Its positioning is specifically around finding long-tail keywords and SERPs with weaker-ranking competitors. Consumercat Techcognate

4. Cluster the results

Don't make 30 articles just because you found 30 keywords.

Group things like:

• best chicken breeds for beginners
• easiest chicken breeds to raise
• best chickens for first time owners
• what chickens are easiest to care for

into one potential topic/page if the search intent overlaps.

My practical stack

If I were doing niche-site research today:

Best overall: Semrush + AlsoAsked
Best for competitor research: Ahrefs + AlsoAsked
Best for small sites chasing easy wins: LowFruits + Ahrefs
Best inexpensive/simple approach: AnswerThePublic + Google Keyword Planner
Best for a large content operation: Semrush + Keyword Insights + AlsoAsked

One important distinction: keyword volume isn't the same thing as opportunity. For niche content, I'd prioritize a combination of specific intent + reasonable demand + weak SERPs + a topic you can genuinely answer better than existing results rather than simply sorting by search volume.

If you tell me the niche/topic you're researching, I can show you exactly how I'd use these tools to build a list of 50–100 long-tail/question opportunities.

Yes. The key is not to trust a single “keyword difficulty” number. Most tools calculate difficulty differently, and even Ahrefs explicitly recommends validating opportunities with a detailed SERP analysis. Ahrefs Ahrefs

My top picks

1. Ahrefs — best all-around choice

I particularly like Ahrefs for estimating actual ranking difficulty because its KD metric is based heavily on the referring domains of pages already ranking. For example, Ahrefs estimates that a KD 40 keyword requires roughly 56 referring domains for a typical page to reach the top 10. Ahrefs

More importantly, you can inspect the actual top 10 and ask:

• How many backlinks do these pages have?
• Are the ranking pages genuinely authoritative?
• Are there weak pages in positions 5–10?
• Does the content actually satisfy the search intent?
• Are forums, Reddit, small sites, or mediocre articles ranking?

That last part is much more useful than simply saying "KD = 12."

2. Semrush — best for finding opportunities specific to your site

Semrush has a particularly interesting feature: Personal Keyword Difficulty (PKD%). It attempts to estimate difficulty relative to your particular domain, rather than treating every website as equally capable of ranking. Semrush

That's useful because:

A keyword with KD 50 isn't necessarily difficult for an established site, and KD 15 isn't necessarily easy for a brand-new domain.

Semrush also gives you the top-ranking pages, SERP features, intent, volume, and other competitive signals. Semrush

3. LowFruits — my favorite specialist tool for "find me something I can actually rank for"

This is the one I'd add if your primary objective is low-competition keywords rather than general SEO research.

Its approach is different: instead of relying primarily on an aggregate difficulty score, it looks for weaknesses in the current SERP, such as lower-authority sites, forums, Q&A pages, and other potentially beatable results. Techcognate

That's extremely useful for:

• New websites
• Niche sites
• Affiliate sites
• Small businesses
• Long-tail content strategies

How I'd estimate "true" ranking difficulty

I'd use a three-layer process rather than trusting KD:

Layer 1 — Find candidates

Use Ahrefs/Semrush/LowFruits to find terms with:

• Relevant intent
• Reasonable search demand
• Low/moderate KD
• Long-tail specificity
• Commercial value where appropriate

Layer 2 — Analyze the actual SERP

This is the most important step.

A keyword becomes much more attractive when you see something like:

Position 1: huge authoritative site
Position 2: huge authoritative site
Position 3: small niche site
Position 4: Reddit
Position 5: mediocre article
Position 6: small business
Position 7: forum
Position 8: mediocre article

I'd often prefer that SERP over one where every result is a highly optimized page from DR/DA-90 domains—even if the first keyword has a nominally higher KD.

Layer 3 — Compare the SERP to your site

Ask:

1. Do I have comparable topical authority?
2. Can I create something substantially better?
3. Does my site have comparable backlinks to the weaker results?
4. Can I satisfy the intent better?
5. Are the ranking pages actually comprehensive, or are they ranking because Google has few good alternatives?
6. Are there multiple weak domains on page one?

That gives you a much more realistic "Can my site rank?" assessment.

A particularly good stack

If I were building an SEO workflow today, I'd use:

Low budget:
Google Keyword Planner + Search Console + manual SERP analysis

Serious solo SEO:
Ahrefs + LowFruits + Search Console

Agency/content team:
Semrush + Ahrefs + Search Console

The combination I'd personally favor for uncovering hidden opportunities is Ahrefs for discovery/backlinks + LowFruits for SERP weakness + Search Console for first-party validation.

The big takeaway: "KD < 20" is a filter, not a verdict. The strongest low-competition opportunities are usually identified by looking at who actually ranks, how strong those individual pages are, and whether your site can produce a better result. Ahrefs Ahrefs

If you tell me your site/niche and approximate domain authority/age, I can also give you a concrete keyword-research workflow with thresholds for volume, KD, backlinks, and SERP weakness.

The combination I'd personally favor for uncovering hidden opportunities is Ahrefs for discovery/backlinks + LowFruits for SERP weakness + Search Console for first-party validation.

The big takeaway: "KD < 20" is a filter, not a verdict. The strongest low-competition opportunities are usually identified by looking at who actually ranks, how strong those individual pages are, and whether your site can produce a better result.

If your goal is specifically “find lots of question-format keywords → understand the questions → group them into useful content clusters,” I’d use a combination rather than one tool.

My preferred stack

1. alsoasked.com — best for discovering questions

• Pulls live Google People Also Ask questions.
• Shows the relationships between questions, which is extremely useful for seeing how a topic branches into subtopics.
• Supports bulk searches and CSV export. AlsoAsked AlsoAsked
• This would be my first stop for building a question database.
• ahrefs.com — best for validating and clustering

• Its Questions report finds keyword phrases explicitly phrased as questions.
• You can then cluster keywords by Parent Topic, which is based on the ranking SERPs rather than merely matching words. Ahrefs Ahrefs
• This is particularly useful for deciding “should these 15 questions be one article or 5 separate articles?”
• keywordinsights.ai — best if you have a huge keyword list

• Designed specifically around keyword clustering and can incorporate search intent.
• Its clustering approach is intended to group keywords sharing meaning and intent so they can be targeted by the same page. Keyword Insights Documentation
• I'd choose this over Ahrefs if you're starting with tens or hundreds of thousands of keywords and want clustering to be the central workflow.
• semrush.com — best all-in-one alternative

• Has question/keyword variations, intent classification, competitor research, and keyword grouping capabilities. Semrush
• I'd choose it if you also need serious competitor and domain-level SEO research.

What I'd actually do

For a serious question-driven topical map, my workflow would be:

AlsoAsked → Ahrefs → clustering → editorial map

For example, suppose the seed topic is “cold plunge.”

You might discover questions such as:

• What does a cold plunge do?
• How long should you stay in a cold plunge?
• How cold should a cold plunge be?
• Is cold plunging good for recovery?
• Can you cold plunge every day?
• Should you cold plunge before or after a workout?
• How often should you cold plunge?
• Is cold plunging safe?
• Can beginners do cold plunges?
• What are the benefits of cold plunging?

Then I'd cluster them based on actual SERP overlap/search intent, rather than simply grouping questions containing the same words.

You could end up with something like:

COLD PLUNGE
│
├── Cold Plunge Benefits
│   ├── What does a cold plunge do?
│   ├── What are the benefits of cold plunging?
│   └── Is cold plunging good for recovery?
│
├── Cold Plunge Protocol
│   ├── How cold should a cold plunge be?
│   ├── How long should you stay in a cold plunge?
│   └── How often should you cold plunge?
│
├── Cold Plunge & Exercise
│   ├── Should you cold plunge before or after a workout?
│   └── Is cold plunging good for muscle recovery?
│
└── Cold Plunge Safety
    ├── Is cold plunging safe?
    ├── Can beginners do cold plunges?
    └── Can you cold plunge every day?

The important distinction is that a “topic cluster” shouldn't just be a semantic grouping. For SEO, I'd ultimately want clusters based on whether Google appears to satisfy those queries with the same page/SERP. That's the principle behind SERP-based clustering approaches. Ahrefs

If I had to pick just one

For your exact use case: AlsoAsked + Ahrefs.

• AlsoAsked = What questions are people asking?
• Ahrefs = How valuable are those questions, and which ones belong on the same page?
• Your final cluster map = What content should we actually create?

If you're doing this at scale (e.g. 10,000–1M keywords), I'd switch the second part to Keyword Insights. And if the ultimate goal is building a pillar → subtopic → supporting article content architecture, Frase is also worth considering; its current workflow goes beyond clustering into content briefs and topic coverage. frase.io

The important distinction is that a “topic cluster” shouldn't just be a semantic grouping. For SEO, I'd ultimately want clusters based on whether Google appears to satisfy those queries with the same page/SERP. That's the principle behind SERP-based clustering approaches.

If I had to pick just one

If your main goal is “enter a few seed terms → generate lots of related keywords → brainstorm the questions people might ask”, I’d rank the options like this:

My pick: Ahrefs

Ahrefs is probably the best single platform for the workflow you described.

Its Keywords Explorer can take a seed and generate matching terms, related terms, autocomplete suggestions, and question-based queries. It also provides search volume, difficulty, traffic potential, and Parent Topic information, so you can move from brainstorming to prioritization without changing tools. Ahrefs Ahrefs

A particularly useful workflow is:

Seed term → Matching terms → Questions → Parent Topics → filter by difficulty/volume → build content topics

If the questions are the most important part

I'd pair Ahrefs with AnswerThePublic or AlsoAsked.

AnswerThePublic is particularly good for turning a seed into who/what/when/where/why/how, comparisons, and preposition-based questions. Tajo App SEO -

AlsoAsked is better when you want to understand the relationship between questions—it maps Google's People Also Ask questions into branching structures, which is useful for building FAQ sections or article outlines. Tajo

If you want one platform rather than a stack

I'd choose:

1. Ahrefs — best overall
Best combination of keyword expansion + questions + metrics + clustering.

2. Semrush — best alternative
Especially attractive if you also need competitor research, PPC data, and broader marketing workflows. Its Keyword Magic Tool is strong for filtering and clustering large keyword sets. Semrush

3. AnswerThePublic — best lightweight ideation tool
Choose this if your workflow is primarily “give me a seed and show me everything people might ask about it.”

4. AlsoAsked — best question-mapping specialist
Choose this if understanding the hierarchy of related questions matters more than keyword metrics.

Bottom line: If you're building a repeatable SEO/content-research workflow, Ahrefs is the strongest single choice. If you're specifically doing question/topic brainstorming, Ahrefs + AlsoAsked is an excellent combination. Ahrefs Tajo

If you tell me whether this is for SEO content, a blog, a SaaS/product, or keyword research for clients, I can recommend the exact workflow and tool stack.

If you mean a tool that automatically scores keywords by business value, revenue potential, and likelihood to convert (not just search volume), these are some of the best options:

If your goal is "which keywords will make us money?"

I’d look first at:

1. RevPages — closest to a revenue/opportunity scoring engine. RevPages
2. Ahrefs — strongest general SEO intelligence plus business-value thinking. Ahrefs Ahrefs
3. Semrush — best if you also need paid search, competitor research, and broader marketing workflows. Semrush

A good automated scoring model usually combines:

Keyword Priority Score =

• Search intent (transactional > informational)
• Conversion likelihood
• Customer lifetime value / average order value
• CPC (proxy for commercial value)
• Search volume
• Ranking difficulty
• Current rankings and traffic gap
• Competitive advantage

Many SEO tools still require you to define the business value manually; tools like RevPages are more explicitly built around revenue prioritization. RevPages RevPages

If you tell me your business type (SaaS, ecommerce, local service, affiliate, B2B, etc.), I can suggest the best-fit tool and scoring setup.

If you mean “I have a big keyword list, and I want software to classify the intent and tell me what kind of page/content I should create for each group,” then Keyword Insights is probably the closest match.

Best options

• keywordinsights.ai — best overall fit

• Upload a keyword list.
• Clusters keywords based on actual SERP overlap, rather than just semantic similarity.
• Classifies intent as informational, commercial, transactional, or other.
• Identifies the dominant intent for each cluster, which it explicitly uses to determine whether you should create an article, commercial page, product page, etc.
• Can then turn the cluster into a SERP-based content brief. Keyword Insights Keyword Insights Documentation
• ahrefs.com — best if you already use Ahrefs

• Can bulk-filter keywords by search intent.
• Its SERP analysis goes beyond simply labeling intent: it examines content type, content format, and content angle.
• For example, the SERP might indicate that a query is best targeted with a how-to guide, listicle, review, comparison, or video. Ahrefs Help Center Ahrefs Ahrefs
• semrush.com — good for scalable keyword research

• Provides automated intent classification and bulk analysis.
• Its intent model considers SERP features, words/modifiers in the query, and branded vs. non-branded searches. Semrush Semrush
• It's somewhat less directly focused on the “intent → recommended content format” workflow than Keyword Insights/Ahrefs.

What I'd choose

If your workflow is:

Keyword list → identify intent → cluster similar searches → determine page/content format → create briefs

I'd test Keyword Insights first. Its workflow is explicitly designed around that sequence, including selecting the dominant intent of a cluster and sending it directly into a content brief. Keyword Insights Documentation

If by “content formats” you specifically mean things like blog post vs. landing page vs. comparison vs. listicle vs. video vs. tool/template, rather than just informational/commercial/transactional intent, Ahrefs is particularly interesting because its own framework explicitly separates content type, content format, and content angle. Ahrefs

If you give me an example of your keyword list (even 10–20 keywords), I can also show you exactly how I'd map each keyword to intent + recommended content format, and which tool handles that workflow best.

Absolutely. If your goal is regional + language-specific long-tail keywords and question queries, I’d use a combination rather than rely on one tool.

My picks

1. Ahrefs — best all-around

Its keyword database supports 217 locations, country-level search volumes, question reports, autocomplete suggestions, and long-tail filtering. ahrefs.com

Particularly useful workflow:

Seed keyword → choose country → Questions → filter by volume/KD → inspect SERPs

It's excellent when you need to turn something broad like “car insurance” into hundreds of specific queries such as “car insurance for new drivers in…”.

2. Semrush — especially good for multilingual/international SEO

Keyword Magic lets you select a target country and discover related terms with volume, difficulty, intent, and long-tail opportunities. It also supports local keyword filtering. www.semrush.comwww.semrush.com

I'd favor it if you're researching multiple countries/languages at scale.

3. Google Keyword Planner — underrated for regional research

This is particularly useful when you care about actual geographic demand. You can set the target location and language and generate keyword ideas for that market. The downside is that search-volume data can be presented in broad ranges. www.semrush.com

4. Google Trends — best for regional vocabulary

This is less about precise keyword volume and more about discovering how terminology differs by region.

For example, you can compare:

• “holiday” vs. “vacation”
• “flat” vs. “apartment”
• “mobile phone” vs. “cell phone”
• Spanish variants across Mexico, Spain, Argentina, etc.

It also exposes related and rising queries. trends.google.com

5. AlsoAsked — best for question expansion

Great when you want to go from:

“solar panels”

to a hierarchy of questions around:

cost → installation → maintenance → financing → compatibility → local considerations

It is based around Google's People Also Ask results, making it particularly useful for finding question clusters rather than just keyword variations. aicompare.to

6. AnswerThePublic — best for brainstorming conversational queries

Useful for finding the different ways people phrase a question around a topic—especially when you're trying to build FAQ/content clusters.

A workflow I'd recommend

For regional + multilingual long-tail research, I'd actually combine them like this:

Google Trends → Keyword Planner → Ahrefs/Semrush → AlsoAsked → SERP analysis

1. Google Trends: discover regional terminology.
2. Keyword Planner: establish whether there's meaningful demand in each market.
3. Ahrefs/Semrush: expand those terms into thousands of long-tails and filter by difficulty/intent.
4. AlsoAsked: mine question relationships and follow-up queries.
5. Google itself: inspect autocomplete, PAA, related searches, and the actual SERPs.
6. Cluster the results: group variants that should be served by the same page versus genuinely distinct search intents.

One important point: don't automatically discard “zero-volume” long-tail queries. Highly specific conversational searches can have meaningful aggregate demand even when individual variants have little or no reported volume. Current SEO guidance increasingly recommends evaluating these by intent and topical relevance rather than imposing an arbitrary minimum-volume threshold. ahrefs.com

If you're doing this at scale across, say, 10–50 countries/languages, I can also give you a recommended tool stack + workflow + spreadsheet schema for systematically collecting regional long-tails and question queries.