Best use case

Use this prompt when the source set matches the job

Use this when you need to improve your offer, not just your copy.

Before you paste

Give the prompt sources, tools, dates, and a decision

  • Paste raw notes with labels like homepage, pricing page, ad copy, SERP notes, offer page, export, screenshot, or review set.
  • Add the date you checked anything that can change, especially ads, prices, search results, AI answers, and website pages.
  • Tell AI which tools it can use: web search, deep research, files, code, browser, MCP, Semrush, Ahrefs, Similarweb, Panoramata, Sheets, or your own workspace.
  • Tell AI what decision the answer should support, so it gives you a useful recommendation instead of a generic summary.

Modern AI workflow

Use the prompt with current AI tools, not only a blank chat box

  • Use deep research or web search for current public evidence, then cite the URLs and date checked.
  • Use file or data analysis for exports, screenshots, CSVs, and historical logs. Do not summarize rows by instinct.
  • Use MCP/connectors when available so the AI can query Semrush, Ahrefs, Similarweb, Panoramata, Sheets, CRM, or your own files directly.
  • Use agent mode for multi-step research: collect, extract, compare, verify, then write.
  • Use artifacts, Canvas, tables, or charts when the output is a map, report, dashboard, or campaign plan.

Prompt

Compare competitor offers by clarity and risk

You are helping me compare competitor offers.

My company: {{my_company}}
Competitor: {{competitor}}
Category: {{category}}
Decision I need to support: {{decision}}

Offer sources:
{{sources}}

Compare:
1. Core product or service.
2. Main promise.
3. Bundle, bonus, trial, guarantee, consultation, discount, or package.
4. Risk reversal.
5. Proof.
6. Friction before purchase.
7. What makes the offer easier or harder to say yes to.

Then suggest offer improvements for my company that do not rely on fake urgency, fake scarcity, or copying.

- Pull out the actual offer mechanics first: bundle, trial, guarantee, consultation, discount, bonus, proof, and buying friction.
- Use any provided URLs, files, screenshots, exports, or connected tool outputs before analyzing.
- Cite the source, export, tool, or URL behind any claim that affects the decision.

Edit the prompt first if needed. ChatGPT and Claude open prefilled; Gemini opens with the prompt copied.

Variables

Replace these fields before you run the prompt

Variable What it means Example
{{my_company}} Required My company The company, product, store, or service you are comparing against the competitor. A DTC skincare brand selling refillable face wash
{{competitor}} Required Competitor The competitor you want to analyze. Use one competitor at a time when the source set is deep. Brand X
{{category}} Required Market or category The buying context. This helps the AI avoid comparing the wrong kind of business. Premium skincare, France and UK
{{sources}} Required Sources and retrieval targets Paste collected sources, exports, screenshots, notes, URLs to check, or the MCP/tool datasets the AI should use. Homepage copy, pricing page, top 5 ads, title tags, Semrush export, Ahrefs export, Similarweb notes, Panoramata campaign examples
{{decision}} Required Decision to support The action you need to take after the analysis. Rewrite our landing page hero and offer comparison table

Example

Use this example to match the right level of detail

Source notes you paste into AI

My company: SEO agency for Shopify brands
Competitor: fictional agency called RankForge
Category: ecommerce SEO services
Sources: service page, audit offer, pricing notes
Decision: improve our lead magnet and discovery offer

What a useful answer should look like

Fictional example output

RankForge's offer is easy to understand because it sells an audit before the retainer.

What works:
- Clear first step.
- Concrete deliverable.
- Less commitment than a retainer.

What to test:
Offer a "category SEO gap map" with 3 competitor examples and a 30-day page plan.

Verification

Check whether the answer is useful

  • Offer mechanics are separated from page copy.
  • The recommendation improves buyer clarity.
  • Risk reversal is real, not fake reassurance.
  • Any missing price or guarantee detail is marked unknown.
  • Current claims include URLs, dates checked, and source confidence.
  • Tool outputs, exports, and AI-generated inferences are clearly separated.
  • The answer uses tables, charts, artifacts, or a report structure when that makes the decision easier.

Mistakes

Mistakes that make this prompt weak

  • Calling a discount an offer strategy.
  • Adding bonuses that make delivery messy.
  • Using fake urgency because a competitor does.
  • Using the prompt like a chat-only summary when modern AI could search, analyze files, run tools, or schedule follow-ups.
  • Letting the AI create a polished answer without showing the evidence trail.

Source notes

Use AI to collect data, then make it show the evidence

A good AI workflow can search, inspect pages, analyze exports, call MCP tools, compare screenshots, and build tables. Make it show URLs, dates, exports, screenshots, or connector results behind the answer before you trust the recommendation.

What you should do next

Run it once, then verify the useful parts

Replace the fields, paste a labeled source set, run the prompt, and check the answer before using it in a strategy report.