Convert messy competitor research notes into prioritized actions your team can actually decide on.
This is a working analyst brief. Sources go in. Patterns, risks, and decisions come out.
You are an operator turning competitor notes into decisions.
My company:
{{my_company}}
Market:
{{market}}
Goal:
{{goal}}
Raw competitor notes:
{{sources}}
Turn the notes into:
1. Findings that matter.
2. Findings to ignore.
3. Action items grouped by marketing, product, sales, and research.
4. Priority score for each action: impact, effort, confidence.
5. Owner suggestion.
6. What to verify before doing the action.
7. A 7-day action plan.
Rules:
- Do not create actions from weak evidence.
- Keep actions specific enough for a task manager.
- Say when the best next step is "verify first."
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.
- Long-context triage: First extract the decisive evidence and discard irrelevant material. Then analyze only the evidence that can change the recommendation.
- Evidence rubric: Score each important finding by evidence strength, relevance, business impact, and reversibility before recommending an action.
- Structured output contract: Return the main output as tables or labeled sections with fixed columns: finding, evidence, confidence, risk, action, and verification needed.
- Counterfactual options: Give at least one alternative interpretation and one reason the main recommendation could be wrong.
- Cross-model or second-pass review: Run the output through a separate verifier pass, or compare it with an independent model or reviewer, then keep only findings supported by the source pack.Copy the prompt. Fill the variables. Then check the output for real.
These are selected for this specific competitor research job. Use the prompt-ready instruction when it helps, and skip it when the condition does not fit.
Use when: Use when the answer depends on competitor pages, screenshots, ads, pricing, SEO exports, or reviews.
Prompt move: Build a source table first with source, date checked, claim, confidence, and business meaning. Use only that table for the final recommendations.
Skip when: Skip only for brainstorming with no factual claims.
Use when: Use when you have a stable pack of competitor pages, PDFs, call notes, screenshots, exports, or long research notes.
Prompt move: 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.
Skip when: Skip when you only have one or two short sources.
Use when: Use when pasting many pages, long exports, transcripts, or screenshots.
Prompt move: First extract the decisive evidence and discard irrelevant material. Then analyze only the evidence that can change the recommendation.
Skip when: Skip for short, clean source packs.
Use when: Use when recommendations could change strategy, positioning, pricing, ads, or product priorities.
Prompt move: Score each important finding by evidence strength, relevance, business impact, and reversibility before recommending an action.
Skip when: Skip for prompts that only organize notes without recommending action.
Use when: Use when the output must be compared, reviewed, or turned into tasks.
Prompt move: Return the main output as tables or labeled sections with fixed columns: finding, evidence, confidence, risk, action, and verification needed.
Skip when: Skip when the desired output is narrative copy.
Use when: Use when the output recommends positioning, offer, creative, content, or product moves.
Prompt move: Give at least one alternative interpretation and one reason the main recommendation could be wrong.
Skip when: Skip for factual extraction or source verification.
Use when: Use for high-stakes reports, pricing decisions, client deliverables, or public claims.
Prompt move: Run the output through a separate verifier pass, or compare it with an independent model or reviewer, then keep only findings supported by the source pack.
Skip when: Skip for fast internal drafts.
| Variable | Meaning | Type | Example |
|---|---|---|---|
{{my_company}} | Your company, product, or brand | string | Northstar CRM |
{{competitor}} | The competitor you want to analyze | string | Acme CRM |
{{market}} | The category or market context | string | B2B CRM for agencies |
{{sources}} | URLs, screenshots, notes, exports, or pasted copy | list | Homepage URL, pricing URL, ad screenshots |
{{goal}} | The business goal behind the research | string | Improve demo conversion |
The output below is fictional. It shows the shape you are looking for, not a real competitor result.
my_company = DemoKit
market = demo automation software
goal = improve demo conversion
sources = notes from competitor websites, ads, pricing pages, and sales page teardownsFictional example output:
Findings that matter:
- Two competitors explain setup time above the fold.
- One competitor uses a low-friction "watch sample demo" CTA.
Ignore:
- A generic blog category with no connection to demo conversion.
7-day plan:
Day 1: Verify setup claims.
Day 2: Draft a setup-time proof block.
Day 3: Add a sample demo CTA experiment brief.
Day 4-5: Build page variant.
Day 6-7: QA and launch test.It turns research into tasks with owners and confidence.
It keeps weak evidence out of the action list.
It gives a short 7-day plan so the notes do not sit forever.
Paste the page copy, ad screenshots, pricing table, SEO notes, or transcript first.
Use it as a source-backed brief: keep strong evidence, downgrade weak evidence, and decide what deserves action.
Ask for observations, risks, and next actions tied to the evidence.
Every factual claim has a source or is marked as unverified.
Pricing, dates, and product claims were checked on the original source.
The output separates observation from interpretation.
The output gives actions you can reject, edit, or test.
Nothing is treated as final just because an AI tool wrote it.
Paste raw notes, not polished conclusions.
Delete actions with low confidence.
Move the top three verified actions into your project tool.