We extract property listings, dynamic pricing, room availability, amenities, and guest reviews from Holiday Inn. 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 Details objects from holidayinn.com. All fields typed and schema-versioned.
"hotel_id": "LONHI", "name": "Holiday Inn London - Kensington High St.", "city": "London", "country": "UK", "star_rating": 4.0, "total_rooms": 706, "check_in_time": "15:00", "check_out_time": "12:00"
| # | hotel_id | name | address | city | country | coordinates |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Availability objects from holidayinn.com. All fields typed and schema-versioned.
"hotel_id": "LONHI", "room_type_id": "KING_STANDARD", "date": "2026-08-14", "base_rate": 185.0, "taxes": 37.0, "total_price": 222.0, "currency": "GBP", "ihg_points_rate": 35000, "available_rooms": 4
| # | hotel_id | room_type_id | date | base_rate | taxes | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Room Types & Features objects from holidayinn.com. All fields typed and schema-versioned.
"room_type_id": "KING_STANDARD", "name": "Standard Room with 1 King Bed", "max_occupancy": 2, "bed_type": "King", "square_footage": 250, "smoking_allowed": false, "accessible": true
| # | room_type_id | name | description | max_occupancy | bed_type | square_footage |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Amenities objects from holidayinn.com. All fields typed and schema-versioned.
"hotel_id": "LONHI", "has_pool": true, "has_gym": true, "pet_friendly": false, "wifi_included": true, "breakfast_available": true, "restaurant_on_site": true
| # | hotel_id | has_pool | has_gym | parking_fee | pet_friendly | wifi_included |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Guest Reviews objects from holidayinn.com. All fields typed and schema-versioned.
"review_id": "REV-982347", "hotel_id": "LONHI", "rating": 4.5, "title": "Great location and clean rooms", "date_posted": "2026-02-10", "traveler_type": "Business", "response_from_hotel": true
| # | review_id | hotel_id | author | rating | title | text |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our pipeline navigates the IHG booking engine, handling dynamic calendar loads, regional pricing variations, and complex room availability matrices.
Extract hotel name, address, geocoordinates, star ratings, and contact details across the entire Holiday Inn global portfolio.
Catalogue every room configuration, bed type, square footage, accessibility features, and occupancy limit per property.
Capture base rates, taxes, and total prices across multiple dates, lengths of stay, and guest counts.
Monitor inventory levels and sold-out dates for specific room types to model demand curves.
Extract points-based pricing and reward night availability alongside standard fiat currency rates.
Structure unstructured amenity lists into boolean fields for pools, gyms, parking, and pet policies.
Scrape guest reviews, ratings, stay dates, and management responses to track property sentiment.
Force specific currencies and language locales via HTTP headers and session cookies to ensure normalised pricing.
Run daily or hourly availability checks, delivering only changed records to reduce downstream processing.
Brief in. Clean data out.
Provide target cities, hotel IDs, or coordinate radii. We map the IHG booking engine for your required date ranges.
We configure Scrapy / Playwright crawlers, manage regional proxies, and handle IHG session persistence.
Schema validation, currency normalisation checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting accurate travel data requires managing state, session cookies, and dynamic XHR requests. We handle the infrastructure.
Holiday Inn's booking engine relies heavily on session cookies established during the initial search. Our crawlers maintain persistent browser contexts, ensuring subsequent API calls for pricing and availability return accurate, non-cached data.
Pricing data is not present in the initial HTML DOM. We use Playwright to execute JavaScript, trigger calendar interactions, and intercept the underlying JSON payloads from IHG's internal pricing APIs.
Hotel pricing often varies based on the searcher's IP location. We route requests through region-specific residential proxies to capture accurate local pricing and bypass geo-blocking.
Aggressive scraping triggers WAF blocks. We distribute requests across thousands of IPs, implement randomised delays, and monitor 429 response rates to maintain high throughput without burning proxy pools.
Cancellation policies and tax structures vary by region. We parse raw text into structured, queryable fields, separating base rates from local taxes and standardising cancellation deadlines.
Online travel agencies monitor direct-booking rates on holidayinn.com to ensure contract compliance and parity.
Rival hotel chains track Holiday Inn pricing strategies, promotional offers, and seasonal rate adjustments.
Pricing analysts model demand curves by tracking room availability and rate changes over time.
Metasearch engines enrich their catalogues with direct property data, amenities, and high-resolution images.
Investors analyse property density, star ratings, and review sentiment to identify underserved markets.
Enterprise travel managers audit negotiated rates against public pricing to optimise corporate travel spend.
"The hospitality industry runs on dynamic pricing. Accessing real-time availability and rate data across thousands of properties is the foundation of competitive revenue management."
Extracting data from the IHG booking engine requires more than simple HTTP requests. It demands full browser rendering to execute complex search flows, session persistence to maintain state, and distributed proxy networks to capture accurate, localized pricing without triggering WAF defenses. DataFlirt manages this pipeline end-to-end.
Everything supported by our holidayinn.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 executes JavaScript and manages session cookies required for the IHG booking engine.
Pools of residential ISP proxies ensure accurate localized pricing and prevent WAF blocking during high-volume availability checks.
Pipelines run on AWS Lambda and ECS. Airflow schedules daily or hourly price checks. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About holidayinn.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and property information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated data. We do not extract personal data, bypass authentication walls, or violate GDPR. Clients should review IHG's ToS and consult legal counsel.
We use Playwright to maintain persistent browser contexts, ensuring the necessary session cookies and tokens are passed to subsequent XHR requests for pricing and availability.
Yes. We configure pipelines to query specific date ranges (e.g., 30, 60, 90 days out), lengths of stay, and guest counts based on your requirements.
Pipelines can be scheduled at daily, hourly, or custom intervals. High-frequency checks focus on specific properties and dates to minimize latency.
Yes. We extract both standard fiat currency rates and the corresponding IHG Rewards points required for a free night, when available.
Our smallest packages start at a defined list of properties (typically 500-5,000) with daily delivery. Contact us with your specific use case for a scoped quote.
Yes. The underlying booking engine is shared across the IHG portfolio. We can extract data for Crowne Plaza, InterContinental, Staybridge Suites, and other IHG brands using the same infrastructure.
Absolutely. We provide a sample run of up to 50 properties across specified dates as part of the pre-engagement scoping process.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete property catalogue or continuous price monitoring across thousands of locations — we scope, build, and operate the pipeline. Tell us what you need.
