How It Works
Our Tourist Trap Score helps you make informed decisions by analyzing reviews from multiple sources. Here's the process behind every score.
1.We gather reviews from multiple sources
When you search for a place, we fetch review data from Google Maps, TripAdvisor, and web search results. Using multiple sources helps us get a more complete picture than any single platform can provide.
2.AI analyzes the reviews
Our AI (powered by Perplexity Sonar) reads through the reviews and looks for patterns. It considers factors like: Are locals reviewing this place, or only tourists? Do reviews mention high prices for low quality? Are there signs of manufactured hype or menu items designed to maximize profit over quality?
3.A score from 0 to 100 is generated
The AI produces a Tourist Trap Score on a 0–100 scale. Lower scores mean the place is authentic and customer-focused. Higher scores indicate signs of a tourist trap — a place that may prioritize extracting money over delivering a genuine experience.
4.You get red flags and good signs
Along with the score, you see specific red flags (warning signs) and good signs (positive indicators) drawn from the reviews. This gives you the reasoning behind the score so you can make your own judgment.
Understanding the Score
Highly authentic. Locals love it, fair prices, genuine quality.
Good place with minor caveats. Worth visiting.
Mixed signals. Could go either way — do more research.
Multiple warning signs. Likely overpriced or overhyped.
Classic tourist trap. Designed to extract maximum money from visitors.
Limitations
- Scores are AI-generated opinions, not objective facts. They should be one input among many in your decision-making.
- Reviews on any platform can be fake, biased, or outdated. Our analysis is only as good as the data available.
- A place's quality can change over time (new management, seasonal shifts). Our scores reflect a snapshot, not a guarantee.
- Cultural context matters. What feels like a "tourist trap" in one city might be a beloved institution in another.
- We are not affiliated with any of the places analyzed. Scores are not influenced by payments or partnerships.