Offers
Compare competitor offers by clarity and risk
Compare offers by bundle, guarantee, risk reversal, urgency, bonus, proof, and buying friction.
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.