Sales enablement

Create a sales battlecard from competitor research

Turn competitor positioning, features, pricing, proof, and customer objections into a practical sales battlecard.

Best use case

Use this prompt when the source set matches the job

Use this when sales needs a useful competitor answer, not a negative hit piece.

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

Create a sales battlecard from competitor research

You are my competitor intelligence operator.

Task: Create a respectful, proof-backed battlecard sales can actually use.

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

Available sources, exports, URLs, files, screenshots, notes, and tool outputs:
{{sources}}

- Use competitor proof, pricing, reviews, docs, and sales notes to write fair talk tracks that sales can defend.
- 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.

Do the work:
1. Summarize competitor positioning and likely buyer fit.
2. Compare features, proof, pricing clarity, implementation, and support claims.
3. Extract buyer objections from reviews, calls, forums, and sales notes.
4. Write talk tracks that are fair, specific, and grounded in our own strengths.
5. Add verification notes so sales does not overclaim.

Return:
- Competitor snapshot.
- When they are a good fit.
- Where we are stronger.
- Discovery questions.
- Talk tracks and proof notes.

Rules:
- Separate observed evidence, inferred signal, and recommended action.
- Put dates next to any recent or change-based claim.
- Cite URLs when you use web search or deep research.
- Name the tool, connector, MCP server, or export when you use one.
- Do not copy competitor creative. Translate the learning into our company context.
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 Competitors One competitor, a short competitor set, or a tracked category. 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: marketing attribution SaaS
Competitors: 4 attribution and analytics platforms
Sources: pricing pages, docs, reviews, sales notes, feature pages
Decision: prepare sales for competitive deals

What a useful answer should look like

Fictional example output

Talk track:
"If your main concern is implementation speed, let's compare setup steps, not feature lists."

Discovery question:
"How many systems need to send conversion data on day one?"

Proof needed:
Implementation checklist and customer setup example.

Verification

Check whether the answer is useful

  • The output names the evidence behind each recommendation.
  • The output uses current sources, exports, or tool results where the task depends on fresh data.
  • The answer separates facts, estimates, and decisions.
  • The final next moves are specific enough to assign.

Mistakes

Mistakes that make this prompt weak

  • Asking for strategy before the source set is clear.
  • Mixing old screenshots with current claims without dates.
  • Copying competitor language instead of translating the insight.
  • Skipping verification because the answer sounds confident.

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