Track competitor rates, monitor OTA rankings, aggregate guest reviews, and watch availability shift across Booking.com, Expedia, Airbnb, Hotels.com, and direct hotel websites — updated as often as every hour.
Hospitality data scraping is the automated extraction of structured information from online travel agencies (OTAs), hotel booking platforms, and review sites. This includes room rates, availability calendars, star ratings, amenity listings, cancellation policies, and guest review scores — all collected at scale and delivered in a format your revenue management or analytics systems can immediately use.
For hotels, resorts, serviced apartments, and travel tech companies, this data is the foundation of competitive pricing strategy. Manual rate shopping across dozens of OTAs is slow and error-prone. DataFlirt automates this entirely — tracking hundreds of competitor properties across every relevant channel, around the clock.
Whether you're a revenue manager at a boutique hotel, a chain managing thousands of properties, or a travel tech company building the next-generation RMS, structured hospitality data gives you the real-time market visibility to make faster, smarter pricing decisions.
Comprehensive extraction built for reliability, accuracy, and scale.
Track room rates across room types, date ranges, occupancy configurations, and advance booking windows across all major OTAs.
Monitor live inventory and availability across platforms in real time — catch sell-outs and flash sales as they happen.
Collect guest reviews, ratings, response times, and sentiment scores from TripAdvisor, Booking.com, Google, and Expedia.
Extract property amenities, check-in/out policies, cancellation terms, and pet/breakfast policies at scale.
Continuously compare your own rates across all OTAs and direct site to detect parity violations the moment they occur.
Gather competitor property data by destination, micro-market, and proximity to key landmarks or demand generators.
Every field you need, structured and ready to use downstream.
A proven process that turns any source into clean structured data — reliably.
{ "property": "The Oberoi Mumbai", "ota": "booking.com", "scraped_at": "2025-06-10T08:45:00Z", "room_type": "Deluxe King", "check_in": "2025-06-15", "rate": { "currency": "INR", "nightly": 18500, "taxes_included": true, "breakfast": "included" }, "availability": "available", "cancellation": "free_until_48h", "review_score": 9.1, "rank_position": 3 }
Built on proven open-source tools and cloud infrastructure — no vendor lock-in.
OTAs heavily fingerprint scrapers. We use geo-matched residential IPs to ensure accurate localised pricing.
Booking.com, Expedia, and Airbnb are SPA-heavy. Our Playwright fleet renders them exactly as a real browser.
We systematically query across your full date window matrix — every check-in date × length of stay combination.
Diff engine detects price changes between crawls and fires webhook alerts when thresholds are crossed.
Data lands directly in your S3 bucket, Snowflake, BigQuery, or PostgreSQL instance on your schedule.
Full rate history stored from day one, enabling seasonality analysis and year-on-year comparisons.
From solo analysts to enterprise data teams — here's how organizations use this data.
Hotels that price confidently aren't guessing — they're looking at real-time data. DataFlirt gives revenue managers and travel tech teams the structured, hourly-updated competitive intelligence to set rates that win market share without leaving money on the table. Whether you're managing one property or ten thousand, our hospitality data infrastructure scales with you.
Start free and scale as your data needs grow.
For small teams and projects getting started with data.
For growing teams with serious data requirements.
For large organizations with custom requirements.
Everything you need to know before getting started.
Join data teams worldwide using DataFlirt to power products, research, and operations with reliable, structured web data.
