We extract hotel listings, dynamic pricing, room availability, and amenity data from Travelodge. 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 Profiles objects from travelodge.com. All fields typed and schema-versioned.
"hotel_id": "TL0142", "name": "London Central City Road", "city": "London", "postcode": "EC1V 2PT", "coordinates": "51.5264, -0.0883", "star_rating": 3, "total_rooms": 392
| # | hotel_id | name | address | city | postcode | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Room Pricing objects from travelodge.com. All fields typed and schema-versioned.
"hotel_id": "TL0142", "check_in_date": "2026-08-14", "room_type": "SuperRoom Double", "rate_type": "Saver", "price": 149.99, "currency": "GBP", "is_available": true
| # | hotel_id | check_in_date | check_out_date | room_type | rate_type | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Amenities & Add-ons objects from travelodge.com. All fields typed and schema-versioned.
"hotel_id": "TL0142", "has_wifi": true, "wifi_fee": 3.0, "has_restaurant": true, "breakfast_price": 9.5, "pet_fee": 20.0, "early_check_in_fee": 10.0
| # | hotel_id | has_wifi | wifi_fee | has_parking | parking_fee | has_restaurant |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Availability Calendar objects from travelodge.com. All fields typed and schema-versioned.
"hotel_id": "TL0142", "month": 8, "year": 2026, "room_type": "Standard Double", "available_days": 24, "min_price": 89.99, "max_price": 219.99
| # | hotel_id | month | year | room_type | available_days | min_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Location & Transit objects from travelodge.com. All fields typed and schema-versioned.
"hotel_id": "TL0142", "nearest_station": "Old Street Underground", "distance_station_miles": 0.2, "nearest_airport": "London City Airport", "distance_airport_miles": 7.5, "local_attractions": "['Silicon Roundabout', 'Shoreditch High Street']"
| # | hotel_id | nearest_station | distance_station_miles | nearest_airport | distance_airport_miles | local_attractions |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Travelodge scraper handles every layer of the booking platform: location listings, dynamic pricing matrices, availability calendars, and add-on fees, with session state management and anti-bot circumvention built in.
Extract all ~600 UK, Ireland, and Spain locations including full addresses, coordinates, and descriptive metadata.
Capture Saver, Flexible, and SuperRooms rates across multiple dates, timestamped per crawl.
Track sold-out dates and remaining inventory signals across the entire booking calendar.
Extract costs for unlimited breakfast, wifi access, pet policies, and early check-in fees per location.
Capture distances to train stations, airports, and local landmarks directly from the property page.
Iterate through booking calendars up to 355 days in advance, maintaining search session state.
Standard, SuperRoom, and Accessible rooms mapped accurately with capacity constraints.
Target specific postcodes, cities, or regions without scraping the entire national catalogue.
Run daily sweeps or high-frequency checks for volatile pricing periods and event dates.
Brief in. Clean data out.
Provide hotel IDs, target regions, or date ranges. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for travelodge.com.
Schema validation, null-rate checks, price-outlier detection, and sample rates before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Booking engines invest heavily in session validation and bot defence. Here is how we stay resilient.
Travelodge uses perimeter defence systems that block datacentre IPs. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management, trained on real user behaviour.
Booking engines require strict session state maintenance. We automate the calendar interaction flows precisely, ensuring accurate rate retrieval across hundreds of future dates without triggering session resets.
Travelodge updates its front-end structure regularly. Our selector strategy uses multiple fallback chains per field, so a minor layout change does not break your data pipeline overnight.
For large date ranges, we maintain a hash index of last-seen values per date. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, and coverage drops, responding before you notice.
OTAs and budget hotel chains track Travelodge rates to benchmark their own pricing models.
Revenue managers adjust their inventory pricing based on Travelodge availability and rate hikes during local events.
Analysts track sell-out velocities across regions to gauge domestic travel demand and economic health.
Metasearch engines enrich their mapping with direct prices to validate parity agreements.
Procurement teams automate budget tracking for corporate stays across the UK network.
Hedge funds track RevPAR indicators and forward-looking pricing to model hospitality sector performance.
"Travelodge pricing dictates the baseline for the UK budget hospitality market, but capturing their dynamic rate calendar requires dedicated infrastructure."
Most teams underestimate the investment required: reliable hospitality scraping demands residential proxies, strict session state management for date traversal, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers focus on the analysis, not the infrastructure.
Everything supported by our travelodge.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, cookie sessions, and interaction flows for the booking calendar.
We maintain pools of residential ISP proxies across UK and ES regions. Rotation happens per request with sticky sessions required for date traversal.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About travelodge.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and availability information is generally permissible. DataFlirt targets only public, non-authenticated rate data. We do not extract personal data or circumvent authentication walls.
We use UK residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and strict session state management to traverse the booking calendar without triggering blocks.
Yes. We can configure the pipeline to traverse dates 30, 90, or 355 days into the future, targeting specific postcodes or the entire national network.
Real-time pipelines achieve sub-60-minute latency for specific event dates. Full national sweeps across a 90-day window complete within 4 to 8 hours.
Yes. We extract property-level metadata including breakfast costs, parking availability and fees, pet charges, and early check-in rates.
Our packages start at a defined list of locations or regions with daily delivery. For full national coverage and deep date traversal, we price based on volume and frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off location dump or a continuous price-monitoring feed across 600 hotels, we scope, build, and operate the pipeline. Tell us what you need.
