Content and On-Page SEO skill 02 of 13
Keyword Research SKILL.md
The Keyword Research skill makes Claude, Codex or another AI agent find what your customers actually search for and turn it into a short list of targets mapped to pages. It starts from your products, customer language and Search Console data, expands with suggestions and tools, labels every volume and difficulty figure as an estimate, groups keywords by shared results, and ranks clusters by value and effort rather than volume alone.
keyword-research/SKILL.md, version 1.0.0, 1,206 words.
By Afeez Adebayo, Marketing, SEO & Growth Expert with 10+ years of experience.
Created 10 October 2026. Updated 10 October 2026. Free to use under CC BY 4.0.
Keyword research is finding out what people type when they need what you offer, how often, what they expect to see, and which of those searches are worth the effort to win. Done well, it gives a short list of targets mapped to pages, not a spreadsheet of thousands of phrases nobody acts on.
This skill builds that list from first-party data first, uses third-party tools for scale, and labels every estimate as an estimate.
Operating principles
- Start with the customer and the business, not the tool. Products, problems, objections and the words customers use come first.
- First-party data beats estimates. Search Console queries show real demand for your site; tool volumes are modelled guesses.
- Group by intent, not by wording. Keywords that return the same results belong to one page.
- Value over volume. A 90-search phrase that converts can beat a 9,000-search phrase that never will.
- Every target maps to a page, existing or planned. A keyword with no page is a note, not a plan.
When to use, and when not to
Use it for new sites, new sections or products, content planning, finding gaps against competitors, and checking whether existing pages target the right phrases.
Don't use it to decide page structure for a whole topic (topical-map), to analyse a single result page in depth (search-intent-serp-analysis) or to write the page (content-brief, seo-content-writing).
Inputs to ask for, in one message
- What the business sells, to whom, in which countries and languages.
- The products, services or topics that matter most commercially.
- Search Console query data for 12 to 16 months, if the site exists.
- Two to five competitors that rank for what you want.
- Access to or exports from a keyword tool (Semrush, Ahrefs, Google Keyword Planner or similar), if available.
- Customer language: sales call notes, support tickets, reviews, community questions.
Raw SKILL.md file
This is the exact file agents read, including the credit header and licence notice. Save it as keyword-research/SKILL.md.
--- name: keyword-research description: "Find, size, group and prioritise the searches a business should target: seed lists from customers and products, expansion with Search Console, Google suggestions and third-party tools, labelled volume and difficulty estimates, intent and funnel stage, business value scoring, clustering by shared results, and a target list mapped to existing or new pages. Use whenever someone asks for keyword research, keyword ideas, a keyword list, search volume, keyword difficulty, long-tail keywords, what customers search for, or which topics to write about next." license: CC-BY-4.0 metadata: author: Afeez Adebayo author_url: https://afeezadebayo.com author_linkedin: https://www.linkedin.com/in/afeez-adebayo/ author_x: https://x.com/za_icon source: https://afeezadebayo.com/skills-md/marketing/content-seo/keyword-research/ category: marketing subcategory: content-seo version: "1.0.0" created: "2026-10-10" updated: "2026-10-10" --- # Keyword Research Keyword research is finding out what people type when they need what you offer, how often, what they expect to see, and which of those searches are worth the effort to win. Done well, it gives a short list of targets mapped to pages, not a spreadsheet of thousands of phrases nobody acts on. This skill builds that list from first-party data first, uses third-party tools for scale, and labels every estimate as an estimate. ## Operating principles 1. **Start with the customer and the business,** not the tool. Products, problems, objections and the words customers use come first. 2. **First-party data beats estimates.** Search Console queries show real demand for your site; tool volumes are modelled guesses. 3. **Group by intent, not by wording.** Keywords that return the same results belong to one page. 4. **Value over volume.** A 90-search phrase that converts can beat a 9,000-search phrase that never will. 5. **Every target maps to a page,** existing or planned. A keyword with no page is a note, not a plan. ## When to use, and when not to Use it for new sites, new sections or products, content planning, finding gaps against competitors, and checking whether existing pages target the right phrases. Don't use it to decide page structure for a whole topic (`topical-map`), to analyse a single result page in depth (`search-intent-serp-analysis`) or to write the page (`content-brief`, `seo-content-writing`). ## Inputs to ask for, in one message 1. What the business sells, to whom, in which countries and languages. 2. The products, services or topics that matter most commercially. 3. Search Console query data for 12 to 16 months, if the site exists. 4. Two to five competitors that rank for what you want. 5. Access to or exports from a keyword tool (Semrush, Ahrefs, Google Keyword Planner or similar), if available. 6. Customer language: sales call notes, support tickets, reviews, community questions. ## Workflow ### Step 1. Build seeds List products, problems solved, use cases, audiences, alternatives and comparisons. Add customer phrases from tickets, reviews and calls. Aim for 20 to 50 seed terms. ### Step 2. Expand - Search Console: queries with impressions but few clicks, and queries where you rank 8 to 30. - Google: autocomplete, People also ask and related searches for each seed. - Tools: matching terms, questions and competitor ranking keywords. - Communities: Reddit, Quora, industry forums and review sites for real questions. ### Step 3. Clean Remove duplicates, misspellings you don't want to target, irrelevant meanings and brand terms of competitors you won't target. Normalise singular and plural. ### Step 4. Label each keyword | Field | Values | |---|---| | Volume | Estimated monthly searches, labelled "estimate" with tool and country | | Difficulty | Tool score, labelled "estimate"; check against the actual results | | Intent | Informational, commercial investigation, transactional, navigational | | Funnel stage | Problem aware, solution aware, product aware, ready to buy | | Business value | 0 none, 1 indirect, 2 relevant, 3 core product or service | | Current rank | From Search Console or a rank tool | ### Step 5. Cluster Group keywords that share most of their top 10 results; those share one page. Name each cluster by its main query. Clusters with different result types (guides versus product pages) stay separate even if the words look similar. ### Step 6. Prioritise Score each cluster: potential (demand times realistic click share), value, and effort (difficulty against your site's authority and existing content). Favour clusters where you already rank on page two or three, or where an existing page needs only improvement. ### Step 7. Map to pages Assign each priority cluster to an existing URL or a new page, with one main keyword and supporting keywords. Flag clusters already split across two pages for `keyword-cannibalisation`. ## Reading the numbers with care - Tool volumes are modelled from clickstream and ad data; they can be wrong by a wide margin, especially for small markets and new terms. - Keyword Planner shows ranges for most accounts and groups close variants. - Search Console impressions depend on where you rank; low impressions may mean you are not visible yet, not that demand is low. - Zero-volume terms can still bring visits; customer phrases often appear as zero in tools. ## Worked example A payroll SaaS for small businesses started with 30 seeds from product pages and support tickets. Expansion produced 2,400 terms; cleaning left 1,100. Clustering by shared results gave 140 clusters. Prioritising by value and current rank highlighted 25 clusters: 9 already ranked on page two through weak pages, 11 needed new comparison and how-to pages, and 5 were product terms mapped to feature pages. The final plan was 25 targets mapped to 25 URLs, with volumes labelled as Semrush estimates for the UK and US. ## Output format ``` # Keyword research: <business>, <market>, <date> ## Summary (clusters found, priority clusters, quick wins) ## Priority clusters | Cluster | Main keyword | Supporting keywords | Est. volume (tool, country) | Intent | Value | Current rank | Target URL | Action | ## Full keyword list (spreadsheet) ## Notes on data sources and limits ``` ## Building seed lists that work | Source | What it gives you | Example | |---|---|---| | Product and feature pages | The core vocabulary | "payroll", "pension auto-enrolment" | | Sales calls | Buying triggers and objections | "switching from our accountant" | | Support tickets | Problems and how-to questions | "how to correct a payslip" | | Reviews (yours and competitors') | Words customers use to praise or complain | "easy for a two-person team" | | Community threads | Long, real questions | "cheapest way to pay first employee" | | Competitor navigation | Topics the market expects | Guides, templates, calculators | ## Edge cases and judgement calls | Situation | What to do | |---|---| | Brand-new market with no data | Rely on customer interviews, community questions and competitor rankings; label volumes as low-confidence estimates | | Niche B2B with tiny volumes | Prioritise by value and intent; a handful of searches can be worth more than thousands of consumer clicks | | Keywords with mixed intent | Check the results; target the intent the business can serve, and note the other | | Competitor brand terms | Usually avoid targeting directly; comparison pages may suit "X alternatives" searches if they are fair | | Several languages or countries | Research each market separately; translations rarely match how locals search | | Seasonal terms | Use Google Trends and 12 to 24 months of data before judging demand | ## Handoffs to related skills - Turning clusters into a site structure: `topical-map` - Checking intent for a cluster: `search-intent-serp-analysis` - Briefing a page: `content-brief` - Clusters already split across pages: `keyword-cannibalisation` - Conversational questions for AI search: the AEO & GEO `query-fan-out-mapping` skill ## Quality bar: what excellent research includes - Clusters grouped by shared results, each with one target URL. - Every estimate labelled with tool, country and date. - Priorities explained by value, realistic click share and effort. - Quick wins identified from existing rankings. - A short list the team can act on this quarter, not only a long spreadsheet. ## Common mistakes - Chasing the biggest volumes with no link to the product. - Presenting tool volumes as facts. - One page per keyword variant, which creates cannibalisation. - Ignoring Search Console queries the site already shows for. - Delivering a long list with no page mapping or priority. ## Questions to ask before you recommend targets - Which products or services should get traffic first? - Which countries and languages count? - What content already exists, and what can the team produce each month? - How strong is the site compared with the sites ranking now? ## Self-check before you answer - Is every estimate labelled with its tool and country? - Are clusters based on shared results, not just shared words? - Is every priority cluster mapped to one page? - Did I rank by value and effort, not volume alone? ## Official documentation - Google Search Console Performance report: https://support.google.com/webmasters/answer/7576553 - Google Keyword Planner: https://support.google.com/google-ads/answer/7337243 - How Google Search works: https://developers.google.com/search/docs/fundamentals/how-search-works - Google Trends: https://trends.google.com/ --- Created by Afeez Adebayo, Marketing, SEO & Growth Expert Website: https://afeezadebayo.com LinkedIn: https://www.linkedin.com/in/afeez-adebayo/ X: https://x.com/za_icon Source: https://afeezadebayo.com/skills-md/marketing/content-seo/keyword-research/ Licence: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). You may copy, share and adapt this skill, including for commercial use, as long as you credit Afeez Adebayo and link to the source URL above. Keep this notice in any copy or adapted version.
Workflow
Step 1. Build seeds
List products, problems solved, use cases, audiences, alternatives and comparisons. Add customer phrases from tickets, reviews and calls. Aim for 20 to 50 seed terms.
Step 2. Expand
- Search Console: queries with impressions but few clicks, and queries where you rank 8 to 30.
- Google: autocomplete, People also ask and related searches for each seed.
- Tools: matching terms, questions and competitor ranking keywords.
- Communities: Reddit, Quora, industry forums and review sites for real questions.
Step 3. Clean
Remove duplicates, misspellings you don't want to target, irrelevant meanings and brand terms of competitors you won't target. Normalise singular and plural.
Step 4. Label each keyword
| Field | Values |
|---|---|
| Volume | Estimated monthly searches, labelled "estimate" with tool and country |
| Difficulty | Tool score, labelled "estimate"; check against the actual results |
| Intent | Informational, commercial investigation, transactional, navigational |
| Funnel stage | Problem aware, solution aware, product aware, ready to buy |
| Business value | 0 none, 1 indirect, 2 relevant, 3 core product or service |
| Current rank | From Search Console or a rank tool |
Step 5. Cluster
Group keywords that share most of their top 10 results; those share one page. Name each cluster by its main query. Clusters with different result types (guides versus product pages) stay separate even if the words look similar.
Step 6. Prioritise
Score each cluster: potential (demand times realistic click share), value, and effort (difficulty against your site's authority and existing content). Favour clusters where you already rank on page two or three, or where an existing page needs only improvement.
Step 7. Map to pages
Assign each priority cluster to an existing URL or a new page, with one main keyword and supporting keywords. Flag clusters already split across two pages for keyword-cannibalisation.
Reading the numbers with care
- Tool volumes are modelled from clickstream and ad data; they can be wrong by a wide margin, especially for small markets and new terms.
- Keyword Planner shows ranges for most accounts and groups close variants.
- Search Console impressions depend on where you rank; low impressions may mean you are not visible yet, not that demand is low.
- Zero-volume terms can still bring visits; customer phrases often appear as zero in tools.
Worked example
A payroll SaaS for small businesses started with 30 seeds from product pages and support tickets. Expansion produced 2,400 terms; cleaning left 1,100. Clustering by shared results gave 140 clusters. Prioritising by value and current rank highlighted 25 clusters: 9 already ranked on page two through weak pages, 11 needed new comparison and how-to pages, and 5 were product terms mapped to feature pages. The final plan was 25 targets mapped to 25 URLs, with volumes labelled as Semrush estimates for the UK and US.
Output format
# Keyword research: <business>, <market>, <date>
## Summary (clusters found, priority clusters, quick wins)
## Priority clusters
| Cluster | Main keyword | Supporting keywords | Est. volume (tool, country) | Intent | Value | Current rank | Target URL | Action |
## Full keyword list (spreadsheet)
## Notes on data sources and limitsBuilding seed lists that work
| Source | What it gives you | Example |
|---|---|---|
| Product and feature pages | The core vocabulary | "payroll", "pension auto-enrolment" |
| Sales calls | Buying triggers and objections | "switching from our accountant" |
| Support tickets | Problems and how-to questions | "how to correct a payslip" |
| Reviews (yours and competitors') | Words customers use to praise or complain | "easy for a two-person team" |
| Community threads | Long, real questions | "cheapest way to pay first employee" |
| Competitor navigation | Topics the market expects | Guides, templates, calculators |
Edge cases and judgement calls
| Situation | What to do |
|---|---|
| Brand-new market with no data | Rely on customer interviews, community questions and competitor rankings; label volumes as low-confidence estimates |
| Niche B2B with tiny volumes | Prioritise by value and intent; a handful of searches can be worth more than thousands of consumer clicks |
| Keywords with mixed intent | Check the results; target the intent the business can serve, and note the other |
| Competitor brand terms | Usually avoid targeting directly; comparison pages may suit "X alternatives" searches if they are fair |
| Several languages or countries | Research each market separately; translations rarely match how locals search |
| Seasonal terms | Use Google Trends and 12 to 24 months of data before judging demand |
Handoffs to related skills
- Turning clusters into a site structure:
topical-map - Checking intent for a cluster:
search-intent-serp-analysis - Briefing a page:
content-brief - Clusters already split across pages:
keyword-cannibalisation - Conversational questions for AI search: the AEO & GEO
query-fan-out-mappingskill
Quality bar: what excellent research includes
- Clusters grouped by shared results, each with one target URL.
- Every estimate labelled with tool, country and date.
- Priorities explained by value, realistic click share and effort.
- Quick wins identified from existing rankings.
- A short list the team can act on this quarter, not only a long spreadsheet.
Common mistakes
- Chasing the biggest volumes with no link to the product.
- Presenting tool volumes as facts.
- One page per keyword variant, which creates cannibalisation.
- Ignoring Search Console queries the site already shows for.
- Delivering a long list with no page mapping or priority.
Questions to ask before you recommend targets
- Which products or services should get traffic first?
- Which countries and languages count?
- What content already exists, and what can the team produce each month?
- How strong is the site compared with the sites ranking now?
Self-check before you answer
- Is every estimate labelled with its tool and country?
- Are clusters based on shared results, not just shared words?
- Is every priority cluster mapped to one page?
- Did I rank by value and effort, not volume alone?
Official documentation
- Google Search Console Performance report: https://support.google.com/webmasters/answer/7576553
- Google Keyword Planner: https://support.google.com/google-ads/answer/7337243
- How Google Search works: https://developers.google.com/search/docs/fundamentals/how-search-works
- Google Trends: https://trends.google.com/
On this page
- When to use this skill, and when not to
- Example prompts
- Example output
- What the agent needs from you
- How this skill hands off to related skills
- How to run the Keyword Research skill step by step
- Situations this skill handles
- What makes this skill different
- Practical tips from real projects
- Frequently asked questions
- Changelog
When to use this skill, and when not to
Use it for a new site, section or product, for quarterly content planning, to find gaps against competitors, or to check whether existing pages target the right phrases. It is also useful when a team has a long keyword list and no idea which terms matter.
Don’t use it to structure a whole topic (use Topical Maps and Content Clusters), to analyse one results page in depth (use Search Intent and SERP Analysis) or to write the page (use SEO Content Briefs).
Example prompts
- “Find the keywords a UK payroll software company for small businesses should target first.”
- “Here is our Search Console export. Which queries are we close to page one for?”
- “Compare our keyword coverage with these three competitors and list the gaps.”
- “Group these 2,000 keywords into clusters that each need one page.”
- “Find long-tail questions our customers ask about invoice financing.”
Example output
The skill returns a fixed structure. A shortened example for an imaginary site:
# Keyword research: payroll software, UK, 10 October 2026 ## Summary 1,100 keywords after cleaning, 140 clusters, 25 priority clusters (9 quick wins on page two). ## Priority clusters | Cluster | Main keyword | Est. volume (Semrush, UK) | Intent | Value | Rank | Target URL | | Payroll for small business | small business payroll | 1,900 (estimate) | Commercial | 3 | 14 | /payroll/small-business/ | | Employer NI | how to calculate employer ni | 880 (estimate) | Informational | 2 | none | new guide |
Volumes are always labelled with their tool and country, and every priority cluster is mapped to one existing or new URL.
What the agent needs from you
The skill asks what you sell, to whom and in which countries and languages, the products or topics that matter most commercially, Search Console query data if the site exists, two to five competitors, exports from any keyword tool you use, and real customer language from sales calls, support tickets and reviews.
How this skill hands off to related skills
Research feeds the rest of the set. Clusters become a structure through Topical Maps, each target is checked with Search Intent and SERP Analysis and briefed with SEO Content Briefs. Clusters already split across two pages go to Keyword Cannibalisation, and existing pages on page two go to On-Page SEO Optimisation.
How to run the Keyword Research skill step by step
- Install the skill as
keyword-research/SKILL.md. - Describe the business: what you sell, to whom, in which countries and languages, and which products matter most.
- Share first-party data: 12 to 16 months of Search Console queries, if the site exists.
- Add customer language from sales calls, support tickets, reviews and community threads.
- Name two to five competitors and share keyword tool exports if you use one.
- Review the priority clusters, each mapped to one page, and send the top ones to the brief skill.
The skill labels every volume and difficulty figure with its tool and country, because third-party numbers are estimates.
Situations this skill handles
Keyword research changes with the business and the market. The skill handles these cases:
| Situation | What the skill does |
|---|---|
| New market with no data | Uses customer interviews, community questions and competitor rankings, and labels volumes as low confidence |
| Niche B2B with tiny volumes | Prioritises by value and intent rather than volume |
| Long list nobody acts on | Clusters by shared results and maps each cluster to one page |
| Several countries | Researches each market separately instead of translating keywords |
| Keywords with mixed intent | Checks the results and targets the intent the business can serve |
| Existing site with page-two rankings | Finds quick wins in Search Console before planning new pages |
What makes this skill different
Most keyword research hands over a spreadsheet sorted by volume. This skill starts from customers and the business, uses Search Console as the most reliable demand data, groups keywords that share results into clusters, and ranks clusters by value, realistic click share and effort.
The result is a short list of targets mapped to pages, with quick wins from existing rankings first. Every estimate is labelled, and zero-volume customer phrases are kept when they match real buying questions.
Practical tips from real projects
- Search Console first. Queries you already show for are the most reliable demand data you have.
- Cluster by results, not words. If two keywords share most of their top ten, they belong to one page.
- Value beats volume. A small phrase that converts can be worth more than a large one that never will.
- Map every target to a page before writing anything.
- Re-run quarterly, because demand and results change.
For AI search, keyword research is only half the picture. Buyers also ask long, contextual questions in assistants, and those rarely show up in keyword tools. Pair this skill with the AEO and GEO query fan-out skill to map those conversational prompts to the same pages, so one content plan serves both classic search and AI answers.
A practical example: a payroll software company started with 30 seed terms from its product pages and support tickets, expanded them to 2,400 phrases, cleaned them to 1,100 and grouped them into 140 clusters. Prioritising by value and current rankings left 25 targets, nine of them already on page two through weak pages. Improving those nine came before writing anything new, because the fastest gains usually sit in pages Google already half-trusts.
Keep the research alive after the first pass. Each quarter, re-check the priority clusters in Search Console, retire targets that turned out to have no real demand, and add new questions from sales and support. Research that is refreshed regularly stays tied to what customers actually ask.
Frequently asked questions
How accurate are keyword volumes?
Third-party volumes are modelled estimates and can be well off, especially in small markets. The skill labels them as estimates and gives more weight to your own Search Console data.
Should I target high-volume keywords first?
Not by default. The skill ranks clusters by business value, realistic click share and effort, so a smaller phrase that converts often comes before a large one that doesn’t.
What is keyword clustering?
Grouping keywords that return mostly the same results, because one page can rank for all of them. It stops sites from creating a separate page for every variant.
Can it do research without paid tools?
Yes, using Search Console, Google suggestions, People also ask, Keyword Planner and community questions. Paid tools add scale and competitor data.
What about zero-volume keywords?
Many real customer phrases show zero in tools but still bring visitors who convert. The skill keeps them when they match the product and intent.
Changelog
- 1.0.0, 10 October 2026: first release.
Use, adapt and share this skill under CC BY 4.0: credit Afeez Adebayo and link to this page.
All Content and On-Page SEO skills
- Content SEO Audit
- Search Intent and SERP Analysis
- Topical Maps and Content Clusters
- SEO Content Briefs
- SEO Content Writing
- Title Tags and Meta Descriptions
- On-Page SEO Optimisation
- Image SEO
- E-E-A-T and Content Quality
- Content Refresh and Decay Recovery
- Keyword Cannibalisation
- Content Pruning and Consolidation
