Reviews·intermediate·Layer 2

Surface sentiment trends from guest reviews

Analyse a batch of reviews to identify recurring themes, emotional patterns, and operational signals. Built for tour operators who want to move beyond star ratings.

When to use this

▸Quarterly review of guest feedback to spot emerging patterns
▸Identifying which aspects of your experience guests talk about most (and least)
▸Finding the gap between what you think your USP is and what guests actually value
▸Spotting operational issues before they become consistent complaints

The prompt

You are an expert tourism review analyst. I'm going to give you a batch of guest reviews for my experience business.

For each review, extract:
1. **Traveller type** (solo, couple, family with young kids, family with teens, friends, corporate)
2. **Emotional arc** — what was their state before, during the peak moment, and after?
3. **Specific themes** — not generic categories, but concrete details (e.g. "discovered the hidden courtyard off Flask Walk" not just "discovery")
4. **Guide mentions** — if a guide is named, what specifically was praised or criticised?
5. **Operational signals** — timing, equipment, communication, logistics feedback
6. **Authentic phrases** — genuinely memorable, quotable language (skip generic "Great tour!" praise)

Then provide a synthesis:
- **Top 3 recurring themes** with supporting evidence
- **Strongest emotional arcs** (before → after transformations)
- **Operational flags** that appear in 2+ reviews
- **Best testimonial candidates** ranked by specificity and emotional resonance
- **Gap analysis** — what are guests NOT mentioning that you'd expect them to?

Confidence scoring: rate each extraction 0.0-1.0. Prefer extraction over null (a 0.6-confidence finding is more valuable than nothing), but never fabricate.

Here are the reviews:
[PASTE YOUR REVIEWS HERE]

Works with

ClaudeChatGPTGemini