We extract hotel listings, dynamic room rates, flight itineraries, car rental pricing, and guest reviews from Travelocity. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Hotels & Stays objects from travelocity.com. All fields typed and schema-versioned.
"property_id": "TRV-849201", "name": "The Plaza Hotel New York", "star_rating": 5.0, "guest_rating": 4.8, "base_price": 850.0, "currency": "USD", "free_cancellation": true
| # | property_id | name | star_rating | guest_rating | review_count | location |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Flights objects from travelocity.com. All fields typed and schema-versioned.
"airline": "Delta Air Lines", "flight_number": "DL492", "departure_airport": "JFK", "arrival_airport": "LHR", "price": 645.0, "currency": "USD", "cabin_class": "Economy"
| # | flight_id | airline | flight_number | departure_airport | arrival_airport | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Packages objects from travelocity.com. All fields typed and schema-versioned.
"package_id": "PKG-99281", "hotel_name": "Waikiki Beach Marriott", "airline": "Hawaiian Airlines", "total_price": 2150.0, "savings_pct": 15, "currency": "USD", "room_type": "Ocean View"
| # | package_id | hotel_name | airline | departure_date | return_date | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Car Rentals objects from travelocity.com. All fields typed and schema-versioned.
"provider": "Enterprise", "car_class": "Midsize SUV", "daily_rate": 65.0, "total_price": 325.0, "currency": "USD", "transmission": "Automatic", "mileage_policy": "Unlimited"
| # | rental_id | provider | car_class | model_example | pickup_location | dropoff_location |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from travelocity.com. All fields typed and schema-versioned.
"property_id": "TRV-849201", "author": "Sarah M.", "stay_date": "2026-08-14", "rating": 5.0, "review_title": "Exceptional service and location", "review_text": "The staff went above and beyond for our anniversary.", "travel_type": "Couples"
| # | review_id | property_id | author | travel_type | stay_date | rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Travelocity scraper handles every layer of the platform including dynamic hotel pricing, complex flight itineraries, bundled packages, and the comprehensive review corpus. We manage all session state and anti-bot circumvention.
Capture base rates, total prices, taxes, and resort fees across multiple room types and occupancy configurations.
Extract multi-city, round-trip, and one-way flight schedules with cabin class availability and baggage policies.
Track dynamic bundle pricing for flight and hotel combinations to calculate implied discounts and savings percentages.
Monitor fleet availability, daily rates, and total rental costs by pickup location and date range.
Extract guest feedback, granular ratings, helpful votes, and management responses across all properties.
Build time-series datasets of price fluctuations for yield management and competitive benchmarking.
Catalogue pet policies, parking fees, cancellation windows, and specific room amenities.
Extract property coordinates, neighbourhood classifications, and proximity to major landmarks or transit hubs.
Access normalised pricing across global points of sale to monitor regional price discrimination.
Track organic rank versus sponsored placements for specific destination queries and travel dates.
Brief in. Clean data out.
Provide destinations, dates, property IDs, or flight routes. We design the extraction schema together.
We configure Scrapy crawlers, residential proxies, and session management tailored to Travelocity.
Schema checks, price normalisation, and anomaly detection occur before production deployment.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on schedule.
Travel aggregators invest heavily in scraping detection. Here is how we stay resilient so your data feed remains uninterrupted.
Travelocity shares backend infrastructure with the broader Expedia Group. We use residential ISP proxies with realistic browser fingerprints and randomised request timing to bypass rate limits and IP bans.
Flight and hotel search results load asynchronously via complex JavaScript payloads. We run full Playwright browser sessions to trigger lazy-loading and capture the complete dataset.
Travel pricing varies wildly based on the user's apparent location. We manage strict cookie sessions tied to specific geo-located proxies to ensure the pricing data reflects your target market accurately.
Travelocity frequently tests new user interfaces. Our selector strategy uses fallback chains combining CSS, XPath, and API interception so layout changes do not break your data pipeline.
For large property catalogues, we maintain a hash index of last-seen values. Subsequent runs only push diffs when room rates or availability change, reducing your downstream processing load.
Online travel agencies monitor competitor rates across identical properties to ensure they maintain the most attractive pricing.
Hotel operators benchmark local market rates and occupancy indicators to adjust their own dynamic pricing models.
Metasearch engines ingest real-time flight and hotel inventory to populate their own comparison platforms.
Enterprise travel managers audit their negotiated corporate rates against public availability to ensure contract compliance.
Hospitality groups mine guest reviews and star ratings to identify operational improvements and track brand perception.
Airlines and analysts evaluate flight route density, carrier competition, and pricing trends to identify profitable new routes.
"Travelocity aggregates millions of dynamic travel pricing signals daily. Without an automated extraction pipeline, you are blind to market fluctuations."
Extracting reliable travel data requires navigating complex search sessions, regional pricing variations, and aggressive bot countermeasures. DataFlirt manages the residential proxy rotation, JavaScript execution, and schema maintenance so your engineering team receives clean pricing feeds.
Everything supported by our travelocity.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 manages JavaScript rendering, cookie sessions, and interaction flows required for travel search forms.
We maintain pools of residential ISP proxies across global regions. Rotation happens per request with sticky sessions to maintain geographic pricing consistency.
Pipelines run on AWS Lambda and Kubernetes. Airflow handles scheduling and dependency management. All state is stored in managed PostgreSQL databases.
Data delivered to where your team already works — no new tooling required.
About travelocity.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and availability data is generally permissible. DataFlirt targets only public, non-authenticated travel data. We do not extract personal user data or circumvent authentication walls. Clients should review Expedia Group terms of service and consult legal counsel for their specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. This approach reliably bypasses the strict rate limits common across OTA platforms.
Yes. Search parameters are fully configurable. You define the check-in dates, length of stay, passenger counts, and cabin classes, and we configure the pipeline to query those exact specifications.
We support hourly, daily, or custom cadences. For high-priority properties or routes, we can configure near real-time streaming pipelines to capture intraday price fluctuations.
Yes. Our schema separates the base rate from taxes, resort fees, and total prices to give you an accurate view of the final cost presented to the consumer.
Our minimum engagements typically start with a defined property list or route set monitored on a weekly basis. For large-scale dynamic monitoring, we price based on search volume and required frequency.
Yes. Travelocity shares backend architecture with Expedia, Hotels.com, and Vrbo. Our extraction schemas often map directly across these platforms, allowing you to monitor the entire network efficiently.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need daily hotel rate monitoring or historical flight pricing trends, we scope, build, and operate the infrastructure.
