Agent prompt
Service Page Search Review Prompt
A copy/paste prompt for reviewing a commercial service page against the live search result, competitor pages, buyer objections, and AI recommendation criteria.
Use it to turn a weak service page into a sharper commercial asset with clearer positioning, better proof, stronger FAQs, and the same buyer-trust standard Searchmaxxed applies before recommending a rebuild.
How to use it
- Paste it into your AI assistant or editor of choice.
- Fill in your page, keyword, business context, and proof assets.
- Do not let the assistant invent facts. Anything unproven should be flagged as missing proof.
Copy/paste prompt
You are helping improve a commercial service page for a real business. Your job is to diagnose one commercial service page and produce a buyer-facing rebuild plan so it has a better shot at ranking in Google, converting buyers, and being recommended by AI search tools. Target page: [INSERT PAGE URL OR FILE PATH] Target keyword: [INSERT COMMERCIAL KEYWORD] Business context: - Company: [INSERT COMPANY] - What we sell: [INSERT OFFER] - Who we serve: [INSERT ICP] - Locations/industries: [INSERT IF RELEVANT] - Proof assets available: [CASE STUDIES / TESTIMONIALS / REVIEWS / CLIENT LOGOS / RESULTS] - Claims we are allowed to make: [INSERT] - Claims we must NOT make: [INSERT] Rules: - Do not invent facts, numbers, clients, guarantees, certifications, awards, locations, or case studies. - Flag anything that needs evidence as [MISSING PROOF]. - Prefer specific buyer language over polished generic marketing copy. - Keep the page useful for humans first, but structure it so Google and AI tools can understand and cite it. Do this in order: 1. Inspect the current page Identify: - current H1 - title/meta description if available - section structure - offer clarity - proof currently used - vague claims - missing buyer questions - missing objections - unclear CTAs - missing comparison information - missing internal links 2. Research the live search result Search the target keyword and inspect the top 5 organic competitors. For each competitor, extract: - URL - title - H1 - H2/H3 structure - offer framing - proof used - FAQs - comparison sections - pricing/risk language - CTAs - schema if detectable - unique angles - sections they cover that our page does not 3. Research buyer language Check Google autocomplete, People Also Ask, Reddit, Quora, YouTube comments, reviews, forums, and competitor testimonials where relevant. Extract: - exact buyer questions - common objections - pain phrases - comparison language - pricing/risk concerns - “best for / not best for” signals 4. Test AI recommendation gaps Ask AI-search-style questions such as: - “Who are the best providers for [category]?” - “Would you recommend [company] for [problem]?” - “What information is missing from this page?” - “What would make this company more trustworthy?” - “Which competitors appear more credible and why?” Summarise what evidence the page needs before an AI tool could confidently recommend it. 5. Produce a gap report Create a table with these columns: - Gap - Why it matters - Competitor evidence - Buyer evidence - Priority: high/medium/low - Recommended fix - Page section to add or improve 6. Rebuild the page Rewrite or restructure the page with: - sharper positioning - clear buyer pain - specific service breakdown - use cases - deliverables - proof sections - comparison section - objection handling - FAQs from real buyer questions - AI-answer-friendly summaries - internal link suggestions - stronger CTA 7. If you can edit the page - find the relevant page/component/file - edit the page directly - preserve existing style/components where possible - run lint/build/tests if available - fix failures caused by the edit - show the final diff 8. Final output Return: - before/after summary - sections added - search-result gaps fixed - AI recommendation gaps fixed - buyer objections answered - proof still needed - internal links to add - next 3 commercial pages to rebuild
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