Social Proof Aggregator
Turn customer reviews into buyer personas and messaging insights.
The Challenge
Customer reviews are gold for understanding your target audience — but they're scattered across platforms and take forever to read. This prompt aggregates reviews from multiple sources and synthesizes them into actionable buyer personas.
What This Prompt Does
Aggregate Reviews
Pull from Trustpilot and Google Maps
Find Themes
Identify what customers love and hate
Build Personas
Create buyer profiles based on review evidence
Extract Language
Find phrases to use in your marketing
The Prompt
The Prompt
Task
Use @Trustpilot/Get ReviewsName it "Trustpilot/Get Reviews" and call it with @Trustpilot/Get Reviews to get online reviews and @Google Maps/Search Locations with @Google Maps/Get ReviewsName it "Google Maps/Get Reviews" and call it with @Google Maps/Get Reviews to get location-based reviews. Aggregate the feedback to understand what customers say about a company and build a buyer persona.
Example: Analyze reviews for Sweetgreen to understand their customer base and what they value.
Input
The user will provide a company name.
Example: "What do customers say about Warby Parker?" or "Build a buyer persona for Allbirds based on reviews"
Context
What to Search For
Review content analysis:
- What do customers praise most?
- What pain points led them to this company?
- What alternatives did they consider?
- What language do they use to describe the experience?
Buyer persona indicators:
- Demographics hints (family mentions, professional context)
- Values and priorities (price-sensitive, quality-focused, convenience-driven)
- Use cases and occasions
- Decision factors
Search Strategy
- Pull Trustpilot reviews (multiple pages if available)
- Search Google Maps for company locations
- Get reviews from 2-3 locations for geographic diversity
- Analyze patterns across all review sources
- Synthesize into a buyer persona
What Counts as a Valid Result
- Use actual quotes from reviews
- Note the balance of positive vs negative sentiment
- Include review counts and overall ratings for context
- If a company isn't on Trustpilot, note this and rely on Google Maps
- Don't fabricate persona details — base everything on review evidence
Output
Review Summary: | Source | Rating | Review Count | Sentiment | |--------|--------|--------------|-----------| | Trustpilot | X/5 | Y reviews | Mostly positive/mixed/negative | | Google Maps | X/5 | Y reviews | Mostly positive/mixed/negative |
What Customers Love:
- [Theme 1]
- Example: "[Quote]"
- [Theme 2]
- Example: "[Quote]"
- [Theme 3]
- Example: "[Quote]"
What Customers Complain About:
- [Issue 1] — "[Quote]"
- [Issue 2] — "[Quote]"
Buyer Persona:
Who They Are:
- Demographics: [Age range, life stage, professional context based on review hints]
- Location: [Urban/suburban, regions if apparent]
- Lifestyle: [What their reviews suggest about their lifestyle]
What They Value:
- [Value 1]: Evidence from reviews
- [Value 2]: Evidence from reviews
- [Value 3]: Evidence from reviews
Why They Choose This Brand:
- Primary driver: [Main reason]
- Secondary drivers: [Other factors]
Language They Use: Words and phrases that appear frequently in reviews — use these in your marketing:
- "[Phrase 1]"
- "[Phrase 2]"
- "[Phrase 3]"
Marketing Implications: What this tells you about how to reach and convert this audience.
Example Usage
Try asking:
- →"Build a buyer persona for Sweetgreen based on reviews"
- →"What do Warby Parker customers value most?"
- →"Analyze Allbirds reviews to understand their customer base"