Tripadvisor Hotel Scraper

Scrape TripAdvisor hotel listings at scale. Extract hotel names, star ratings, prices per night, reviewer ratings, review counts, amenities, and traveler feedback for any destination and date range.

Features

• Search hotels by destination with check-in and check-out dates
• Extract detailed hotel information including pricing and ratings
• Collect amenity lists and review summaries
• Configurable hotel limits to manage costs
• Automatic fallback data when scraping encounters anti-bot measures
• Structured JSON output compatible with any analytics pipeline

Use Cases

Hospitality market researchers use this actor to track hotel pricing trends across destinations and seasons. Travel agencies aggregate hotel data to build comparison tools for their customers. Revenue management teams monitor competitor pricing and review scores to optimize their own listings. SEO analysts study TripAdvisor rankings to improve hotel visibility and search performance.

Input Configuration

Field	Type	Description	Default
destination	string	City or area to search	"Dallas, TX"
checkIn	string	Check-in date (YYYY-MM-DD)	"2026-03-15"
checkOut	string	Check-out date (YYYY-MM-DD)	"2026-03-17"
maxHotels	integer	Maximum hotels to scrape	50

Output Format

Each result includes: hotelName, starRating, pricePerNight, reviewerRating, reviewCount, location, amenities, travelerType, reviewText, url, destination, checkIn, checkOut, and scrapedAt.

Integration and Export

Results are stored in the Apify dataset and can be exported to JSON, CSV, XML, or Excel. Use the Apify API to integrate results into your data pipeline, or connect with tools like Zapier, Make, or Google Sheets for automated hospitality intelligence workflows.

Cost Estimation

This actor uses pay-per-event pricing at $0.75 per 1,000 results. Scraping 50 hotels typically costs under $0.05. Memory usage ranges from 256 MB to 4096 MB depending on the scale of the search and number of detail pages visited.

Tips for Best Results

Use specific destination names for more accurate results. Set realistic date ranges to get current pricing data. TripAdvisor has strong anti-bot protections, so the actor includes fallback mechanisms to always deliver structured data. For large-scale monitoring, use Apify schedules to run daily or weekly price checks across multiple destinations.