keyword-research
kostja94/marketing-skills
Discover high-intent, low-competition keywords and build topical maps for SEO content strategy.
What is keyword-research?
Guides keyword research for SEO by finding target keywords, assessing search intent and difficulty, and building topical maps. Use this when researching keywords for content planning, analyzing search behavior, or identifying ranking opportunities—especially for low-volume, high-intent terms that often rank faster and convert better.
- Discover keywords via Google autocomplete, People Also Ask, and Related Searches using the alphabet method and position variants
- Identify search intent (informational, navigational, commercial, transactional) from modifier words and SERP analysis
- Evaluate keywords by search volume, difficulty, CPC, and SERP features to prioritize achievable targets
- Cluster keywords by SERP overlap, semantic similarity, or intent for pillar-cluster content structure
- Extract seed keywords from competitor content and existing articles to find ranking gaps
- Test product positioning clarity using function words and input-to-output patterns
How to install keyword-research
npx skills add https://github.com/kostja94/marketing-skills --skill keyword-researchHow to use keyword-research
- 1.Identify your product, audience, goals, and available tools (Google Keyword Planner, Google Trends, or SEO tools)
- 2.Use discovery methods: customer language, Google autocomplete (alphabet method), People Also Ask, Related Searches, and competitor reverse analysis
- 3.Categorize keywords by search intent using modifier words (how, best, vs, buy, price) and SERP checks
- 4.Evaluate and screen keywords by search volume (100+/month typical), keyword difficulty, CPC, and SERP features
- 5.Cluster keywords by SERP overlap or semantic similarity, then map to pillar pages and cluster content
- 6.Prioritize achievable keywords: remove irrelevant terms, filter very low volume, assess ranking difficulty, and focus on commercial/transactional intent
Use cases
- Find long-tail keywords for a new blog or product launch with lower competition and faster ranking potential
- Analyze competitor titles and URLs to identify content gaps and untapped keyword opportunities
- Build a topical map by clustering related keywords for pillar pages and supporting cluster content
- Discover high-intent transactional keywords (buy, price, coupon) to prioritize for conversion-focused pages
- Validate SEO fit for a new product or feature by testing if users actually search for it
- Content strategists and SEO specialists planning keyword-driven content calendars
- Product marketers validating search demand before launching new features or positioning
- Startup founders researching organic growth opportunities with limited PPC budget
- Agencies auditing competitor keyword strategies and identifying ranking opportunities
- Teams aligning SEO and Google Ads keyword lists to avoid cannibalization
keyword-research FAQ
~70% of search traffic is long-tail (low-volume) keywords; they have lower competition, higher conversion intent, and rank faster. High-volume keywords are harder to rank for and often have mixed intent, making them less efficient for new sites.
Type a seed keyword + space + each letter (a–z) and numbers (0–9) into Google search. Record relevant autocomplete suggestions. Example: 'SEO a' yields 'SEO audit,' 'SEO agency.' This uncovers real user searches that keyword tools often miss because they filter low-volume terms.
Search the keyword and check the SERP: knowledge cards/Wikipedia = informational; product lists/reviews = commercial; brand sites = navigational. Compare the top-ranking pages to your product. If your content would fit naturally in the top 10, the intent aligns.
Clustering groups related keywords by SERP overlap (same top-ranking pages), semantic similarity, or intent. This reveals which keywords can be served by a single page and which need separate content, enabling efficient pillar-cluster content structure and internal linking.
Screen in order: 1) Remove irrelevant terms, 2) Filter very low volume (below ~100/month for most niches), 3) Assess achievability (keyword difficulty, SERP features, competitor strength), 4) Prioritize commercial/transactional intent and high CPC, which signal stronger business value.
Full instructions (SKILL.md)
Source of truth, from kostja94/marketing-skills.
name: keyword-research description: When the user wants to research keywords, find target keywords, or analyze search intent. Also use when the user mentions "keyword research," "keyword tool," "target keywords," "search volume," "search intent," "keyword difficulty," "topical map," "keyword clustering," "People Also Ask," "Google autocomplete," "autocomplete keywords," or "alphabet method." For clusters, use content-strategy. metadata: version: 1.3.1
SEO Content: Keyword Research
Guides keyword research for SEO: finding target keywords, assessing difficulty, understanding search intent, and building topical maps. ~95% of keywords get fewer than 10 searches/month; low-volume, high-intent terms often yield faster rankings and conversion.
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Initial Assessment
Project context: Read root contextus.md when present and load only the modules relevant to this task. Without Contextus, use available project material or user-provided facts and ask for missing information; do not create a parallel context system.
Identify:
- Product/service: What you offer
- Audience: Who searches for it
- Goals: Traffic, conversions, brand
- Tool access: Google Keyword Planner, Google Trends, or SEO tools
Discovery Methods
Base Discovery
| Method | Purpose |
|---|---|
| User perspective | What pain points? What would they search? Customer language from product context |
| Tool expansion | Related keywords, questions, suggestions; Google autocomplete, PAA, Related Searches |
| Competitor reverse | Analyze competitor titles, H1, URL; identify topics they rank for; find gaps (#4–10 = opportunity) — see competitor-research |
| Google PAA | People Also Ask and Related Searches; high-value signals from real user behavior |
| Extract from article | When auditing existing content: extract seed keywords from title, H1, H2s, meta keywords, first 100 words; then search "[primary keyword]" or "[primary keyword] related keywords" for opportunities; use "[primary keyword]" site:competitor.com if competitors known |
Google Autocomplete (Long-Tail Discovery)
Google autocomplete reflects real user searches; suggestions only appear if queries have actual traffic. Free; often uncovers low-volume long-tail that keyword tools miss. ~70% of search traffic is long-tail; lower competition, higher conversion.
Alphabet method (seed + space + letter):
- Type seed keyword + space + each letter:
keyword a,keyword b, ...keyword z - Record relevant suggestions; repeat with numbers 0-9
- Example:
SEO a-> "SEO audit," "SEO agency";SEO b-> "SEO basics," "SEO best practices"
Position variants (seed in different positions):
- Prefix:
a keyword,b keyword(discover what users add before) - Suffix:
keyword a,keyword b(most common; alphabet method) - Middle:
how to keyword a,best keyword for(question + modifier combos)
Question modifiers:
how to keyword,what is keyword,why keyword,when to keyword,keyword vskeyword for beginners,keyword for small business,keyword without
Why it works: Keyword tools filter low-volume terms; autocomplete only shows queries with real traffic. Use with PAA and Related Searches for full coverage. Categorize results by intent (informational, commercial, transactional).
Incremental Discovery
- User feedback: Support, community, reviews, NPS—high-frequency questions = unmet search demand
- Multi-platform search: Reddit, Quora, X (Twitter), Hacker News—real questions and discussions
Search Intent
| Intent | Content type | Example |
|---|---|---|
| Informational | Blog, guide, FAQ | "how to optimize sitemap" |
| Navigational | Brand page | "alignify login" |
| Commercial | Comparison, review | "SEO tools comparison" |
| Transactional | Product, pricing | "best SEO tool pricing" |
Intent Identification
Modifier words (often signal intent):
| Intent | Modifiers |
|---|---|
| Informational | "how," "what," "why," "guide," "tutorial" |
| Commercial | "best," "compare," "vs," "review," "top" |
| Transactional | "buy," "price," "cheap," "coupon," "free shipping" |
| Local | Location names |
SERP check: Search the term—knowledge cards/Wiki → informational; product lists/reviews → commercial; brand sites → navigational. Broader terms often show mixed SERP. See serp-features for feature types.
Long-Tail Expansion
- Google Autocomplete: Alphabet method, position variants, question modifiers; see above. Primary source for long-tail.
- Intent modifiers: Core + "how," "best," "vs," "compare," "price"
- Question words: "how to," "what is," "why," "when"
- Functional modifiers: Core + "-er/-or" (e.g., "image optimizer" for tool-type queries); often higher conversion
- Clustering: Group by SERP overlap (same top pages), semantic similarity, or intent.
Keyword Clustering & Topical Map
| Method | Use |
|---|---|
| SERP overlap | Keywords with overlapping top-ranking pages → same cluster |
| Semantic | Group by meaning, LSI, related concepts |
| Intent-based | Group by intent; separate pages if intent differs within cluster |
Pillar–cluster (map keywords to structure):
- Pillar (Hub): Broad topic page; links to clusters
- Cluster (Spoke): Focused subtopic; links back to pillar
- Target long-tail first; then pillar. Interlink clusters within topic.
- See content-strategy for full pillar-cluster planning and implementation.
Evaluate & Screen
| Factor | Consider |
|---|---|
| Search volume | Monthly searches; ~100+/month typical floor; niche can relax |
| Keyword difficulty (KD) | New sites target lower KD |
| CPC | Higher CPC often = stronger commercial intent |
| SERP features | Featured Snippet, PAA, zero-click; SERP features can satisfy intent without click—affects real traffic; see serp-features (Zero-Click section), featured-snippet |
| Screening order | 1) Remove irrelevant 2) Filter very low volume 3) Assess achievability 4) Prioritize commercial/transactional |
Product Positioning Test (SEO Fit)
Test if positioning is clear enough for search:
- XXX + Function words: Generator, Creator, Maker, Builder, Changer, Shortener, Scraper, Converter, Downloader, Translator, Extender, Summarizer, Resizer, Remover, Extractor, Recorder, Rewriter, Solver, Calculator; or Platform, Tool, Software, App, Provider, Assistant, Copilot
- Input + to + Output: e.g., "image to video," "text to speech"—clear input/output signals intent
Agent/Copilot products: Pure native Agent hard to grow via SEO; users rarely search "agent." Release related features first (e.g., CRM, sales bot for sales agent) to build traffic, then funnel to Agent product.
Principles
- Core rule: Someone must search it—validate with tools; avoid inventing terms
- Functional keywords: Tool-type (-er/-or) often convert better; users are closer to action
- Multi-language: Re-research in target language; don't translate existing lists. See translation for translation workflow.
SEO–PPC Keyword Synergy
Keyword research serves both SEO and Google Ads. Align both channels to avoid duplication, cannibalization, and wasted spend.
| Data flow | Use |
|---|---|
| keyword-research → google-ads | Keyword list, clusters, intent; support terms (login, forum, pricing) → negative keywords for PPC |
| google-ads → keyword-research | PPC conversion rate, Search Terms report → SEO priority; high-converting PPC terms = worth ranking organically |
| keyword-research → landing-page | Clusters → dedicated LP per intent; PAA questions → FAQ sections |
| GSC organic rank 4+ | If you rank well organically, consider reducing/pausing PPC on those terms to avoid cannibalization |
PPC data for SEO priority: SEO ROI ≈ (Organic clicks × PPC conversion rate × Customer value) − SEO cost. Use PPC conversion data to validate which keywords to pursue in organic.
Reference: Backlinko – SEO and PPC: 8 Smart Ways to Align
Data Sources
| Source | Use |
|---|---|
| Ahrefs | Keywords Explorer, Site Explorer |
| SEMrush | Keyword Overview, Organic Research |
| GSC | Search queries, impressions, clicks |
| GA | Traffic by landing page |
| PostHog | Feature/search usage |
Report Workflow
- Parse — Read Excel/CSV, infer keyword, volume, KD, intent, etc. from headers
- Enrich — Web search, visit competitor/product pages; read root
contextus.mdif present - Build — Structure data for report
- Generate — Output report in chosen format
Output Format
- Keyword list with volume, KD, intent
- Keyword mapping to pages/content
- Content gaps (competitors rank, you don't)
- Priority ranking for implementation
- Topical map (cluster → pillar → page mapping)
Report Structure Reference
| Section | Content |
|---|---|
| Executive Summary | Priorities (top 3) |
| Keyword Overview | Total keywords, primary intent, avg KD, content gaps count |
| Keyword List | Keyword, volume, KD, intent, priority, target page |
| Keyword Mapping | Page/URL, target keywords, status |
| Content Gaps | Keywords competitors rank for that you don't |
| Action Plan | Priority, action, impact, effort |
| Appendix | Search intent reference (Informational, Commercial, Transactional, Navigational) |
Related Skills
- seo-strategy: SEO workflow, Product-Led SEO, audit approach; keyword research is Content phase
- google-ads: Keywords inform Search targeting; PPC data feeds back into SEO priority
- paid-ads-strategy: When to use paid vs organic; channel selection
- content-strategy: Keywords inform content plan; topic clusters
- content-optimization: Keyword placement, density vs stuffing, H2 keywords
- title-tag, meta-description: Keywords in title, description
- heading-structure: Keywords in H1, H2
- link-building: Keywords inform link targets
- serp-features: SERP features in keyword screening; PAA, Featured Snippet
- featured-snippet: Snippet-worthy query targeting
- competitor-research: Competitor keyword/topic analysis; reverse engineering
- faq-page-generator: PAA questions to FAQ sections; question-based keyword to FAQ content
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