We extract hotel listings, flight schedules, dynamic pricing, room availability, and guest reviews from Expedia. 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 Hotel Listings objects from expedia.com. All fields typed and schema-versioned.
"property_id": "h124892", "name": "The Ritz-Carlton, Tokyo", "star_rating": 5.0, "guest_rating": 4.8, "review_count": 1402, "vip_access": true, "latitude": 35.6655, "longitude": 139.7308
| # | property_id | name | star_rating | address | latitude | longitude |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Room Rates objects from expedia.com. All fields typed and schema-versioned.
"property_id": "h124892", "room_type": "Deluxe Room, City View", "board_basis": "Room Only", "price_per_night": 850.0, "taxes_and_fees": 120.5, "total_price": 970.5, "currency": "USD", "refundable": false, "available_rooms": 3
| # | property_id | room_type | board_basis | price_per_night | taxes_and_fees | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Flight Itineraries objects from expedia.com. All fields typed and schema-versioned.
"flight_id": "f892341", "airline": "Singapore Airlines", "flight_number": "SQ11", "departure_airport": "LAX", "arrival_airport": "NRT", "duration_mins": 710, "stops": 0, "price": 1250.0, "cabin_class": "Economy"
| # | flight_id | airline | flight_number | departure_airport | arrival_airport | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Guest Reviews objects from expedia.com. All fields typed and schema-versioned.
"review_id": "r981244", "property_id": "h124892", "rating": 5, "travel_type": "Couples", "date_stayed": "2026-03-15", "title": "Exceptional service and views", "helpful_votes": 12, "language": "en"
| # | review_id | property_id | author | rating | travel_type | date_stayed |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Car Rentals objects from expedia.com. All fields typed and schema-versioned.
"rental_id": "c45912", "provider": "Hertz", "car_type": "Compact SUV", "transmission": "Automatic", "seats": 5, "price_per_day": 45.0, "total_price": 135.0, "currency": "USD", "mileage_policy": "Unlimited"
| # | rental_id | provider | car_type | transmission | seats | doors |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Expedia scraper processes dynamic pricing, complex flight itineraries, and hotel inventory across global point-of-sale regions. We handle IP localisation, session management, and bot mitigation natively.
Extract property names, star ratings, geo-coordinates, amenity lists, and high-resolution image URLs for any destination globally.
Capture dynamic nightly rates, tax breakdowns, board basis, and cancellation policies across thousands of check-in date permutations.
Extract multi-city itineraries, layover durations, operating carriers, and fare class pricing directly from Expedia search results.
Route requests through point-of-sale specific residential IPs to capture localised pricing and regional inventory differences.
Mine the full review corpus including star ratings, travel types, stay dates, text bodies, and management responses.
Track rental availability, daily rates, transmission types, and mileage policies across major airport and city pickup locations.
Identify properties carrying the VIP Access badge and extract associated perk data for loyalty program analysis.
Extract cabin baggage allowances, checked bag fees, and seat selection costs associated with specific flight fare classes.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences with change-detection diffing.
Brief in. Clean data out.
Provide destination lists, airport codes, date ranges, or specific property IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, point-of-sale proxy rotation, and GraphQL query interception for expedia.com.
Schema validation, null-rate checks, price-outlier detection, and timezone normalisation before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Travel aggregators use advanced anti-bot systems and dynamic GraphQL endpoints. Here is how we maintain extraction stability.
Expedia alters pricing and inventory based on the user's geographic location. Our crawlers use residential ISP proxies matched to your required Point-of-Sale, ensuring you extract the exact pricing a local user would see.
Expedia relies heavily on complex GraphQL requests for dynamic data. Instead of brittle DOM parsing, our Playwright instances intercept and extract the raw JSON responses, yielding highly structured and reliable data.
Travel sites deploy aggressive bot protection. We manage TLS fingerprinting, automated token solving, and realistic interaction patterns to maintain high success rates without triggering CAPTCHA walls.
Checking prices across a 90-day window for multiple lengths of stay creates thousands of permutations. Our Airflow orchestrator distributes these search spaces across parallel workers to ensure timely data delivery.
For continuous price monitoring, we maintain a hash index of last-seen values per property and date pair. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Hotel chains and revenue managers monitor OTA listings to ensure pricing compliance and identify unauthorised discounting.
Airlines and hospitality groups track competitor pricing and inventory depth to optimise their own dynamic pricing algorithms.
Analysts track destination popularity, average daily rates, and review sentiment to identify macro travel trends.
Niche travel aggregators feed Expedia pricing and inventory data into their own comparison engines.
Enterprise travel teams audit booked rates against public OTA prices to ensure their corporate booking tools deliver value.
Machine learning teams train itinerary planning models and recommendation engines on real-world flight and hotel data.
"Expedia aggregates the world's travel inventory, but extracting accurate, geo-specific pricing at scale requires sophisticated infrastructure."
Travel pricing is highly volatile and tightly guarded by advanced bot protection. Building this internally means dedicating engineers to proxy management, GraphQL token reverse-engineering, and continuous schema updates. DataFlirt absorbs this operational overhead so your team can focus on revenue optimisation.
Everything supported by our expedia.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 deduplication. Playwright handles JavaScript rendering, GraphQL interception, and bot mitigation flows.
We maintain pools of residential ISP proxies across major global markets, ensuring accurate Point-of-Sale pricing and bypassing IP-based rate limits.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About expedia.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and inventory data is generally permissible. DataFlirt targets only public, non-authenticated hotel, flight, and car rental data. We do not extract personal data or circumvent authentication walls. Clients should review Expedia's ToS and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic TLS fingerprints, and automated token solving. Our infrastructure is designed to maintain high success rates without triggering CAPTCHA blocks.
Yes. We route requests through residential proxies located in your target country, ensuring the pricing and inventory reflect what a local user would see.
Real-time streaming pipelines achieve sub-60-minute latency for specific flight routes or hotel properties. Bulk extractions across large date ranges typically complete within a 4-8 hour window.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series table per property or flight route from the date your pipeline starts.
Our smallest packages start at a defined list of properties or flight routes with daily delivery. For larger global extractions, we price based on volume and delivery frequency.
Yes. We provide a sample run of up to 100 properties or flight routes as part of the pre-engagement scoping process to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a targeted hotel pricing monitor or a global flight itinerary feed - we scope, build, and operate the pipeline. Tell us what you need.
