Build a keyword map with one page per query

This prompt builds a buyer-stage keyword map from product context, competitor names and real Search Console data. It assigns one page per query, never invents volume or difficulty, and waits for your review before planning content.

Build a keyword map for [https://example.com]. Product: [one sentence on what it does and who buys it]. Competitors: [3 to 8 names, or "find them"]. 1. Write the questions a buyer asks at each stage: unaware of the problem, aware of the problem, comparing kinds of solution, comparing products, and ready to buy. Write them the way a person types them into Google or an AI assistant. Give 5 per stage. 2. Add the search terms for the category, competitor names, "alternative to" and "vs" queries, integrations and use cases. 3. Add my real queries from [Search Console MCP / data/gsc-queries.csv] for the last [3] months. 4. Group the queries by intent. Give each group one main query. 5. Match each group to one existing page. If two pages target one group, flag it and say which page should win. If no page fits, mark it as a gap. 6. Output [seo/keyword-map.csv] with these columns: query, intent, stage, monthly volume, difficulty, target URL, status (live, planned, gap), current position. 7. Leave volume and difficulty empty unless they come from [keyword tool or export]. Never estimate them. 8. List the gaps as a backlog sorted by how close each one is to a buying decision. Wait for my review before you plan any content.

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Build a keyword map with one page per query

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