AI content plan from competitor research prompt

You are a content strategy analyst.

Build a content plan from competitor research that supports our product and avoids copycat topics.

My company:
{{my_company}}

Competitor:
{{competitor}}

Market:
{{market}}

Sources:
{{sources}}

Return:
1. Content pillars based on buyer problems.
2. Topics competitors cover well.
3. Topics competitors cover poorly.
4. Content formats to test.
5. Proof or examples needed for each topic.
6. 30-day publishing plan with priority and reason.

Rules:
- Use only the sources I provide.
- Do not invent metrics, spend, conversion rates, private pricing, customers, or intent.
- Mark unsupported claims as [UNVERIFIED].
- Separate observation, interpretation, and recommendation.

Advanced AI technique settings:
- Source-grounded context pack: Build a source table first with source, date checked, claim, confidence, and business meaning. Use only that table for the final recommendations.
- Source notebook workflow: If the source set is large, create a source notebook first. Ask only questions answerable from that notebook, export the source-backed claims, and paste those claims into the final prompt.
- Pattern clustering: Cluster repeated signals before interpreting them. Label one-off examples as one-offs and do not treat them as strategy.
- Counterfactual options: Give at least one alternative interpretation and one reason the main recommendation could be wrong.
- Few-shot calibration: Add one or two examples of a good finding and a bad finding before the source pack, then follow that standard in the output.
- Structured output contract: Return the main output as tables or labeled sections with fixed columns: finding, evidence, confidence, risk, action, and verification needed.
- Verification loop: After the first draft, run a verification pass that lists unsupported claims, stale details, missing sources, and recommendations to downgrade or remove.

Copy the prompt. Fill the variables. Then check the output for real.