Monitoring
Create a weekly competitor change digest
Summarize recent competitor changes by source, impact, confidence, and recommended response.
Best use case
Use this prompt when the source set matches the job
Use this every week after collecting website changes, new ads, SEO pages, email campaigns, product launches, or pricing updates.
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 weekly competitor change digest
You are my competitor intelligence operator.
Task: Turn recent competitor changes into a concise weekly digest a founder, marketer, or product lead can act on.
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 website changes, campaign logs, SEO exports, pricing checks, and tracked notes to separate new changes from old noise.
- 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. Group changes by competitor and signal type.
2. Mark each change as confirmed, likely, or needs checking.
3. Estimate strategic importance without pretending you know performance.
4. Identify what deserves action this week and what should only be logged.
5. Write a short executive version and a working version with evidence links.
Return:
- One-page digest.
- Change log table.
- Top 3 actions to consider.
- Verification queue for next week.
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. 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: B2B webinar platform
Competitors: 5 webinar and event tools
Sources: tracked homepage screenshots, 14 new ads, 6 new blog URLs, pricing page diff notes
Decision: decide what changed enough to discuss in Monday planning What a useful answer should look like
Fictional example output
Top change:
Two competitors moved from "run webinars" to "repurpose webinar content." This is confirmed in homepage copy and new blog titles.
Action:
Review our own post-event content angle before changing the homepage.
Log only:
One pricing FAQ edit. Low signal until we see plan or packaging changes. 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.