Campaign planning
Create the next campaign brief from competitor data
Turn competitor activity, your offer, and your proof into a campaign brief ready for creative production.
Best use case
Use this prompt when the source set matches the job
Use this after competitor research when you need an actual campaign plan, not a research summary.
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 the next campaign brief from competitor data
You are my competitor intelligence operator.
Task: Write a campaign brief based on competitor evidence and our own commercial goal.
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}}
- Collect recent campaign evidence first. Cluster repeated ads, emails, landing pages, launches, offers, and content themes before creating ideas.
- 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 the competitor pattern that matters for the campaign.
2. Define the opportunity for our company.
3. Choose audience, core promise, proof, offer, channels, and creative formats.
4. Write the campaign message hierarchy.
5. Define tests, measurement plan, and risks.
Return:
- Campaign one-liner.
- Creative brief.
- Channel plan.
- Test matrix.
- Measurement and reporting plan.
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. 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: B2B analytics SaaS
Competitors: 4 analytics tools
Sources: ad angle analysis, pricing pages, SEO pages, review snippets
Decision: launch a demand gen campaign for finance teams What a useful answer should look like
Fictional example output
Campaign one-liner:
"Your dashboard says revenue is fine. Finance knows margin is not."
Why now:
Competitors keep talking about dashboards, but fewer show finance-grade margin workflows.
First test:
LinkedIn ads to a margin audit landing page. 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.