Pricing

Compare pricing pages without guessing hidden costs

Compare competitor pricing pages by packaging, anchors, friction, hidden costs, and buying signals.

Best use case

Use this prompt when the source set matches the job

Use this when pricing pages, plan names, limits, add-ons, and sales motions are visible.

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 pricing pages without guessing hidden costs

You are helping me compare competitor pricing.

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

Pricing sources:
{{sources}}

Do not invent prices, discounts, limits, or contract terms.

Compare:
1. Pricing model and plan structure.
2. Plan names, anchors, limits, and upgrade triggers.
3. What is clear and what requires a sales call.
4. Value metric, if visible.
5. Objections the page handles.
6. Objections the page leaves open.
7. What we should learn, ignore, and verify.

Return a comparison table plus recommended pricing questions to answer next.

- Check pricing pages, plan limits, feature tables, FAQs, and date-sensitive terms before comparing packaging.
- 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.
Open in ChatGPT Open in Claude Open in Gemini

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: social listening SaaS
Competitor: fictional platform called BrandEar
Category: brand monitoring
Sources: pricing page text, plan names, feature table, FAQ
Decision: improve our pricing page explanation

What a useful answer should look like

Fictional example output

BrandEar uses account limits as the upgrade trigger.

Clear:
- Plan names show customer maturity.
- The feature table explains exports and alerts.

Unclear:
- Historical data limits.
- Extra seats.
- Whether onboarding is included.

Next pricing question:
Should our page make data history the value metric, or keep it as proof inside the plan comparison?

Verification

Check whether the answer is useful

  • The output does not fill missing price fields.
  • Plan limits and value metrics are separated.
  • The analysis names both buying clarity and buying friction.
  • Recommendations fit your own cost structure.
  • 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

  • Matching a competitor's price before matching their cost model.
  • Ignoring what is hidden behind sales calls.
  • Treating discounts as positioning.
  • 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.

Use next