{"slug":"find-topics-to-write","title":"Find Topics to Write: Research, PAA Mining, Clustering, and Gap Analysis","tags":["topic-research","keyword-research","paa","content-planning","topic-clusters"],"agent_summary":"4-step topic discovery system: search trend research, PAA mining, topic clustering, and gap analysis. Outputs a prioritized topic list with article title suggestions, content type, and keyword target. Used to fill a content calendar from scratch.","trigger_phrases":["what should I write about","find topics to write","content topic ideas","topic research","blog topic ideas","what topics to cover","content ideas for"],"runnable":true,"markdown":"\n# Find Topics to Write: Research, PAA Mining, Clustering, and Gap Analysis\n\nThe correct sequence for topic discovery is: understand what people search, mine what they ask, cluster related questions, map against what already exists. This produces a prioritized list with zero guesswork.\n\n---\n\n## Step 1: Seed Keyword Research\n\nStart with 3-5 seed keywords that represent the core of the business or niche:\n\n**Sources for seed keywords:**\n- Primary services or products offered\n- Geographic + service combinations (\"roof repair [city]\")\n- Problem-based searches (\"how to fix [problem]\")\n- Comparative searches (\"[service] vs [alternative]\")\n\n**For each seed keyword, expand to:**\n- The primary keyword (high volume, competitive)\n- 3-5 long-tail variants (more specific, lower competition)\n- 2-3 question variants (PAA candidates)\n\n---\n\n## Step 2: PAA Mining\n\nRun PAA Researcher in Deep Mode for the top 2-3 seed keywords. (See paa-researcher-modes.mdx for full protocol)\n\nFrom PAA mining, extract:\n- All questions at awareness stage\n- All questions at consideration stage (these have highest content ROI)\n- All questions at decision stage\n- Questions that competitors are NOT currently answering well\n\n**Quick identification of unanswered PAA:**\n- Search the PAA question in Google\n- If position 1-3 results only partially answer the question, or the content is 3+ years old → gap confirmed\n- If position 1-3 results are from low-authority sites → opportunity confirmed\n\n---\n\n## Step 3: Topic Clustering\n\nGroup related topics and questions into content clusters. Each cluster gets one primary article (the pillar) and 2-4 supporting pieces.\n\n**Cluster structure:**\n\n```\nCLUSTER: [Topic name]\nPrimary keyword: [main keyword — pillar content]\nPillar article: [title + target word count]\n\nSupporting pieces:\n1. [Supporting keyword] → [content type: FAQ / comparison / how-to]\n2. [Supporting keyword] → [content type]\n3. [Supporting keyword] → [content type]\n\nInternal link plan:\n- Pillar links to all supporting pieces\n- Supporting pieces all link back to pillar\n- Supporting pieces link to each other where contextually relevant\n```\n\n---\n\n## Step 4: Gap Analysis Against Existing Content\n\nBefore adding any topic to the production queue, check:\n\n1. Does any existing page already target this keyword?\n2. Is the existing page ranking (positions 1-20)?\n3. Does the existing page fully cover the topic?\n\n**Decision matrix:**\n\n| Existing Content? | Ranking? | Action |\n|------------------|---------|--------|\n| No | N/A | Create new |\n| Yes | No | Update existing (refiner workflow) or rewrite |\n| Yes | Positions 4-20 | Update and expand existing page |\n| Yes | Positions 1-3 | Leave it — don't disturb a winner |\n\n---\n\n## Step 5: Priority Output\n\nScore each topic and output a production list:\n\n```\nTOPIC PRODUCTION LIST:\n\nTier 1 — Produce immediately:\n1. [Title] | [Keyword] | [Word count] | [Content type] | Priority: [score]\n2. ...\n\nTier 2 — Produce this quarter:\n...\n\nTier 3 — Monitor / Low priority:\n...\n```\n\n**Tier criteria:**\n- Tier 1: High commercial intent + easy to medium difficulty + no existing content\n- Tier 2: Informational with traffic potential + medium difficulty + cluster value\n- Tier 3: Long-tail informational + low volume + nice-to-have coverage\n\n---\n\n## Topic Discovery Sources\n\nBeyond search data, mine these for high-signal topic ideas:\n\n| Source | What to Look For |\n|--------|----------------|\n| Reddit (subreddits in niche) | Recurring questions, complaints, \"what I wish I knew\" |\n| YouTube comments on competitor videos | Unanswered questions, complaints about existing content |\n| Google autocomplete | Long-tail variants of seed keywords |\n| Answer the Public | Visual map of question + preposition variants |\n| Client sales calls / CRM | Actual questions customers ask before buying |\n| Review mining (GMB, Yelp, G2) | Problems solved, language customers use |\n\nCustomer language beats algorithmic data — when both sources agree on a topic, it's highest priority.\n\n#content-sop #topic-research #keyword-research #content-planning\n","html":"

Find Topics to Write: Research, PAA Mining, Clustering, and Gap Analysis

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The correct sequence for topic discovery is: understand what people search, mine what they ask, cluster related questions, map against what already exists. This produces a prioritized list with zero guesswork.

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Step 1: Seed Keyword Research

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Start with 3-5 seed keywords that represent the core of the business or niche:

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Sources for seed keywords:

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For each seed keyword, expand to:

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Step 2: PAA Mining

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Run PAA Researcher in Deep Mode for the top 2-3 seed keywords. (See paa-researcher-modes.mdx for full protocol)

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From PAA mining, extract:

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Quick identification of unanswered PAA:

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Step 3: Topic Clustering

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Group related topics and questions into content clusters. Each cluster gets one primary article (the pillar) and 2-4 supporting pieces.

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Cluster structure:

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CLUSTER: [Topic name]\nPrimary keyword: [main keyword — pillar content]\nPillar article: [title + target word count]\n\nSupporting pieces:\n1. [Supporting keyword] → [content type: FAQ / comparison / how-to]\n2. [Supporting keyword] → [content type]\n3. [Supporting keyword] → [content type]\n\nInternal link plan:\n- Pillar links to all supporting pieces\n- Supporting pieces all link back to pillar\n- Supporting pieces link to each other where contextually relevant\n
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Step 4: Gap Analysis Against Existing Content

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Before adding any topic to the production queue, check:

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    \n
  1. Does any existing page already target this keyword?
    2. \n
  2. Is the existing page ranking (positions 1-20)?
    3. \n
  3. Does the existing page fully cover the topic?
    4. \n
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Decision matrix:

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| Existing Content? | Ranking? | Action |\n|------------------|---------|--------|\n| No | N/A | Create new |\n| Yes | No | Update existing (refiner workflow) or rewrite |\n| Yes | Positions 4-20 | Update and expand existing page |\n| Yes | Positions 1-3 | Leave it — don't disturb a winner |

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Step 5: Priority Output

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Score each topic and output a production list:

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TOPIC PRODUCTION LIST:\n\nTier 1 — Produce immediately:\n1. [Title] | [Keyword] | [Word count] | [Content type] | Priority: [score]\n2. ...\n\nTier 2 — Produce this quarter:\n...\n\nTier 3 — Monitor / Low priority:\n...\n
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Tier criteria:

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Topic Discovery Sources

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Beyond search data, mine these for high-signal topic ideas:

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| Source | What to Look For |\n|--------|----------------|\n| Reddit (subreddits in niche) | Recurring questions, complaints, \"what I wish I knew\" |\n| YouTube comments on competitor videos | Unanswered questions, complaints about existing content |\n| Google autocomplete | Long-tail variants of seed keywords |\n| Answer the Public | Visual map of question + preposition variants |\n| Client sales calls / CRM | Actual questions customers ask before buying |\n| Review mining (GMB, Yelp, G2) | Problems solved, language customers use |

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Customer language beats algorithmic data — when both sources agree on a topic, it's highest priority.

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#content-sop #topic-research #keyword-research #content-planning

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