We extract property details, dynamic room rates, availability calendars, and guest reviews from Hotels.com. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Property Listings objects from hotels.com. All fields typed and schema-versioned.
"property_id": "ho123456", "name": "The Ritz-Carlton", "star_rating": 5.0, "guest_rating": 9.4, "city": "London", "total_reviews": 1402
| # | property_id | name | type | star_rating | address | city |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Room Rates & Availability objects from hotels.com. All fields typed and schema-versioned.
"room_name": "Deluxe King Room", "price_per_night": 450.0, "currency": "GBP", "refundable": false, "breakfast_included": true, "left_in_stock": 3
| # | property_id | room_id | room_name | check_in_date | check_out_date | adults |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Guest Reviews objects from hotels.com. All fields typed and schema-versioned.
"review_id": "rev9876", "rating": 10.0, "stay_date": "2023-10-12", "trip_type": "Couples", "review_title": "Exceptional service", "helpful_votes": 12
| # | review_id | property_id | author | rating | stay_date | review_title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Amenities & Facilities objects from hotels.com. All fields typed and schema-versioned.
"category": "Pool", "amenity_name": "Indoor Pool", "is_free": true, "is_on_site": true, "restricted_hours": "06:00-22:00", "surcharge_amount": 0
| # | property_id | category | amenity_name | is_free | is_on_site | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from hotels.com. All fields typed and schema-versioned.
"search_query": "Paris", "position": 1, "name": "Hotel Lutetia", "display_price": 650.0, "sponsored": false, "badge_text": "VIP Access"
| # | search_query | check_in | check_out | position | property_id | name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline handles dynamic date payloads, geographic price discrimination, and aggressive anti-bot layers to deliver structured accommodation data at scale.
Extract property name, exact location, descriptions, star ratings, and high-resolution image URLs across millions of listings.
Capture exact room rates based on specific check-in and check-out dates, guest counts, and room configurations.
Monitor inventory levels and capture low-stock indicators to gauge booking velocity for specific properties.
Paginate through all guest reviews, capturing text, ratings, trip types, and helpful vote counts.
Extract structured lists of pools, parking, wifi, accessibility features, and on-site dining options.
Capture cancellation windows, pet policies, deposit requirements, and hidden fee structures.
Extract exact latitude and longitude data for spatial analysis and map-based application development.
Extract rates in local currency or force normalisation to USD, EUR, or GBP via session headers.
Capture property status markers like VIP Access, 'Fabulous', or 'Exceptional' promotional tags.
Run daily or hourly pipelines to monitor price volatility and rate adjustments over time.
Brief in. Clean data out.
Provide destination cities, property IDs, or specific dates. We design the extraction schema together.
We configure Scrapy crawlers, residential proxy rotation, and GraphQL payload interception for Hotels.com.
Schema validation, null-rate checks, and price anomaly detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Expedia Group invests heavily in bot mitigation. Here is how we maintain data flow.
Hotels.com uses aggressive bot protection. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full TLS spoofing to bypass WAF challenges.
Room rates are not in the static HTML. We intercept and reverse-engineer the underlying GraphQL API calls, injecting your specific date and guest parameters to extract clean JSON responses.
Prices on Hotels.com often change based on the user's IP location. We route requests through specific geographic proxy pools to capture the exact rates shown to users in your target markets.
The Hotels.com frontend undergoes constant A/B testing. By targeting the underlying API endpoints rather than fragile DOM elements, we ensure your data pipeline remains stable during UI updates.
Missing price data ruins analysis. We monitor extraction payloads in real time, alerting on null-rate spikes and automatically retrying failed requests before delivery.
OTAs and hotel chains monitor listings to ensure properties do not offer cheaper rates on competing platforms.
Hotel operators track competitor pricing across specific date ranges to adjust their own daily rates.
Real estate investors track total room inventory and availability metrics in target cities.
Hospitality groups aggregate review text to identify operational flaws and track guest satisfaction trends.
Meta-search engines build comprehensive inventory databases to power their own flight and hotel comparison tools.
Algorithmic pricing engines ingest local market rates to adjust property prices based on local compression.
"Hotels.com holds the definitive graph of global accommodation inventory and dynamic pricing, but accessing it requires navigating aggressive anti-bot systems."
Extracting travel data at scale is a constant battle against rate limits, dynamic payloads, and geographic price discrimination. DataFlirt manages the residential proxy rotation, GraphQL payload reverse-engineering, and session handling so your data team receives clean, normalised parquet files instead of HTTP 403 errors.
Everything supported by our hotels.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright handles token generation and session initialization before handing off to lightweight HTTP clients.
We maintain pools of residential ISP proxies across global regions, ensuring requests originate from the correct geographic location to capture accurate local pricing.
Pipelines run on Kubernetes clusters. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About hotels.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Hotels.com is generally permissible. DataFlirt targets only public, non-authenticated property, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, realistic browser fingerprints, and automated solvers. For pricing data, we intercept the underlying GraphQL APIs rather than scraping the DOM, which reduces block rates significantly.
Yes. You provide the parameters (check-in, check-out, adults, children), and we inject those into the request payloads to extract the exact rates.
Yes. Hotels.com frequently uses geographic price discrimination. We route requests through proxy nodes in your specified target country to capture accurate local pricing.
We can configure pipelines to run daily, hourly, or on custom intervals. For specific property sets, we can achieve sub-15-minute latency.
No. Extracting loyalty pricing requires authenticated sessions, which violates our policy of only extracting publicly available data.
Yes. We paginate through the entire review history, capturing ratings, text, and metadata for every available guest review.
Our minimum engagement typically starts at a defined list of 1,000 properties or specific destination cities with daily delivery. Contact us for a precise quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily price feed for 5,000 properties or a complete review extraction across Europe, we scope, build, and operate the pipeline. Tell us your requirements.
