Scrape TripAdvisor with AI

# Scrape TripAdvisor — SoloStack Skill File
> Drop this file into your SoloStack repo and Claude Code will use it as
> context to run this workflow automatically.
---
## Overview
Extract TripAdvisor reviews, hotel listings, restaurant data, and ratings using Apify and Claude Code.
**Apify Actor:** `maxcopell/tripadvisor`
**Pricing:** ~$4 per 1,000 listings
## Capabilities
1. **Hotel & resort scraping** — Extract full listing details for hotels including name, star rating, price range, amenities, location, and aggregate review scores.
2. **Restaurant data** — Scrape restaurant listings with cuisine type, price level, rating, review count, and ranking within their destination.
3. **Review extraction** — Pull individual reviews with star ratings, review text, travel type (business, couple, family), date, and helpfulness votes.
4. **Destination search** — Scrape all listings for a destination — hotels, restaurants, and attractions — to build a comprehensive market overview.
5. **Competitive benchmarking** — Compare multiple properties side-by-side with standardized metrics: rating, review volume, response rate, and price positioning.
6. **Photo and media extraction** — Capture listing photos, traveler photos, and management responses to understand how competitors present themselves visually.
## Pipeline
1. **Define scope** — Provide destination URLs, hotel names, restaurant categories, or search queries to scrape
2. **Run the scraper** — Apify's TripAdvisor Scraper extracts listings, reviews, ratings, pricing, and amenity data
3. **Normalize results** — Data is cleaned with consistent rating scales, price formats, and deduplicated review entries
4. **Generate insights** — Build competitive dashboards, review trend reports, or feed data into your hospitality analytics pipeline
## Use Cases
- **Hospitality market research:** Analyze hotel and restaurant markets in any destination to identify pricing gaps, underserved segments, and competitive positioning opportunities.
- **Review monitoring:** Track your property's review trends over time and compare against competitors. Catch service issues early by detecting recurring complaints.
- **Competitor benchmarking:** Compare your hotel or restaurant against local competitors on ratings, review volume, amenities, pricing, and management response rates.
- **Local SEO research:** Understand how TripAdvisor ranks properties in your area to optimize your listing's title, description, photos, and response strategy for better visibility.
## Warnings
- TripAdvisor uses anti-scraping measures. The Apify actor handles this with proxy rotation, but runs over 2,000 listings may need to be split into batches.
- Review text is copyrighted by reviewers and TripAdvisor. Use scraped reviews for internal analysis only — do not republish review content on your own platforms.
- Pricing data on TripAdvisor is often sourced from booking partners and may not reflect the property's direct rates. Verify prices with the property directly.
- TripAdvisor occasionally restructures their pages, which can temporarily affect scraper accuracy. Apify maintains regular updates to handle these changes.
## Sample Output
```json
{
  "name": "The Mulia Resort & Villas Bali",
  "type": "hotel",
  "rating": 4.8,
  "reviewsCount": 3241,
  "priceRange": "$350 - $1,200",
  "ranking": "#3 of 542 hotels in Nusa Dua",
  "location": {
    "address": "Jl. Raya Nusa Dua Selatan, Nusa Dua 80363",
    "latitude": -8.8178,
    "longitude": 115.2326
  },
  "amenities": [
    "Free WiFi",
    "Pool",
    "Spa",
    "Beach Access",
    "Restaurant",
    "Fitness Center"
  ],
  "recentReview": {
    "rating": 5,
    "title": "Absolutely stunning property",
    "text": "From the moment we arrived...",
    "travelType": "Couples",
    "date": "2026-02-15"
  },
  "managementResponses": 89,
  "responseRate": "94%"
}
```
Download the complete skill file with full implementation details,
agent prompts, and ready-to-run scripts.