Structured restaurant data from TripAdvisor across global cities - name, rating, review count, cuisines, full address, city and country, phone, and opening hours. Built for location intelligence, hospitality market research, and travel products.
Map restaurant density, cuisines, and ratings by city and country for site selection and expansion.
Benchmark venues on ratings and review volume across markets and cuisines.
Seed discovery and recommendation products with structured venue data and ratings.
Compare your venues against local competitors on rating, review count, and positioning.
Target restaurants by city, cuisine, or rating band for restaurant-tech and supplier outreach.
Use venue attributes and ratings as a structured corpus for geo and recommendation models.
Every record is structured and ready to join against your CRM, data warehouse, or enrichment pipeline.
| Field | Type | Description | Coverage |
|---|---|---|---|
| name | string | Restaurant name | 100% |
| rating | float | Average rating (out of 5) | 100% |
| review_count | integer | Number of reviews | 100% |
| cuisine | string | Cuisine types | 80%+ |
| address | string | Full address | 99%+ |
| city | string | City | 93%+ |
| country | string | Country | 99%+ |
| zip_code | string | Postal code | 77%+ |
| phone | string | Contact phone | 89%+ |
| popularity | string | Local popularity rank | 87%+ |
| meals | string | Meals served | 61%+ |
| opening_hours | multi-string | Opening hours | 53%+ |
| image | string | Photo URL | 82%+ |
| url | string | TripAdvisor page URL | 100% |
Coverage = percentage of records with that field populated. Download sample to inspect full schema →
We work around your infrastructure, not the other way around.
Complete records as a bulk file in your preferred format.
Filtered by any field in the schema.
Weekly or monthly delta updates.
Real-time access against specific identifiers.
Delivered in whatever format your pipeline accepts.
Flat file for Excel, Python, or any data tool.
Nested records for databases or pipelines.
Direct drop into your cloud storage or warehouse.
Download a free sample or talk to us about a custom subset for your use case.