We extract property listings, dynamic pricing grids, availability calendars, and guest reviews from cottages.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 cottages.com. All fields typed and schema-versioned.
"property_id": "UKC4582", "name": "Seaview Retreat", "location": "Whitby", "region": "North Yorkshire", "max_guests": 6, "bedrooms": 3, "pets_allowed": true, "star_rating": 4.8
| # | property_id | name | location | region | max_guests | bedrooms |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Availability & Pricing objects from cottages.com. All fields typed and schema-versioned.
"property_id": "UKC4582", "check_in_date": "2026-07-11", "check_out_date": "2026-07-18", "nights": 7, "base_price": 1250.0, "total_price": 1250.0, "available": true, "minimum_stay": 3
| # | property_id | check_in_date | check_out_date | nights | base_price | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Amenities & Features objects from cottages.com. All fields typed and schema-versioned.
"property_id": "UKC4582", "wifi": true, "parking": true, "hot_tub": false, "enclosed_garden": true, "open_fire": true, "beach_nearby": true
| # | property_id | wifi | parking | hot_tub | enclosed_garden | open_fire |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Guest Reviews objects from cottages.com. All fields typed and schema-versioned.
"review_id": "REV-992817", "property_id": "UKC4582", "guest_name": "Sarah T.", "rating": 5.0, "review_date": "2025-08-14", "party_type": "Family", "review_text": "Excellent location near the harbour."
| # | review_id | property_id | guest_name | rating | review_date | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from cottages.com. All fields typed and schema-versioned.
"keyword": "cottages with hot tubs", "region": "Cornwall", "search_date": "2026-05-01", "position": 3, "property_id": "CORN882", "weekly_price": 895.0, "promoted_badge": "Customer Choice"
| # | keyword | region | search_date | position | property_id | name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our cottages.com scraper handles complex calendar hydration, dynamic pricing grids, and regional pagination to deliver structured property intelligence without manual intervention.
Title, description, guest capacity, bedroom configuration, and high-resolution image arrays mapped to distinct property IDs.
Extract 12-month forward availability blocks to map occupancy rates and booking velocity across regions.
Capture weekly rates, short-break pricing, and seasonal adjustments across specific date ranges and party sizes.
Structured extraction of hot tubs, enclosed gardens, pet allowances, and accessibility features.
Extract guest feedback, aggregate star ratings, party types, and management responses for sentiment analysis.
Map properties to specific counties, national parks, and proximity metrics like distance to coast or pub.
Track 'Customer Choice', 'New to cottages.com', and discount flags to monitor platform merchandising.
Render single-page application components to capture lazy-loaded calendar grids and pricing matrices.
Run daily pipelines that only output pricing changes and new bookings to minimise storage bloat.
Brief in. Clean data out.
Provide region URLs, property IDs, or search parameters. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and calendar iteration logic for cottages.com.
Schema validation, null-rate checks, price-outlier detection, and sample data review before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Holiday rental platforms obscure pricing behind interactive calendars. Here is how we extract structured data reliably.
cottages.com loads availability via background XHR requests. We intercept these JSON payloads directly rather than parsing HTML tables, ensuring 100% accuracy on date blocks and status flags.
Prices change based on party size, duration, and lead time. We iterate through defined parameter matrices to build complete pricing curves for every property, rather than relying on default search prices.
We route requests through UK-based residential proxies to prevent geographic blocking and rate-limiting from standard data centre IPs, ensuring continuous access to regional inventory.
We maintain a hash index of calendar states. Subsequent runs only push booking changes and price adjustments, reducing downstream processing load and providing a clean log of booking velocity.
Every run emits structured logs to our observability stack. We alert on schema drift or missing price nodes and respond before data quality degrades.
Holiday let agencies track competitor pricing, seasonal rate curves, and minimum stay rules to optimise their own yields.
Property investors map regional occupancy rates and yield potential to identify high-performing postcodes for acquisition.
OTAs and regional booking platforms monitor inventory overlap and exclusivity across UK holiday regions.
Algorithmic pricing engines ingest forward-looking availability to train supply-demand models for specific micro-markets.
Analysts isolate the premium commanded by specific features like hot tubs or enclosed gardens in different regions.
Meta-search platforms integrate clean property data, pricing, and availability into unified travel portals.
"Cottages.com holds the definitive supply and pricing matrix for UK domestic tourism, but extracting it requires navigating complex calendar hydration and dynamic rate grids."
Most teams underestimate the complexity of holiday rental extraction. Reliable pipelines require UK residential proxies, JavaScript execution for calendar state, and XHR interception for pricing payloads. DataFlirt absorbs this infrastructure overhead so your analysts can focus on yield modelling and market share.
Everything supported by our cottages.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 JavaScript rendering and XHR interception for calendar data, ensuring we capture dynamic pricing grids.
UK-specific ISP proxies ensure we see localised pricing and avoid geographic rate limits. Rotation happens per-request to maintain high throughput.
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 cottages.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available property details, pricing, and availability is generally permissible under applicable law. DataFlirt targets only public, non-authenticated data. We do not extract personal user data or circumvent authentication walls. Clients should review platform terms of service and consult legal counsel for specific use cases.
We intercept the background XHR requests that populate the calendar UI. This allows us to extract the raw JSON payloads containing exact date blocks, minimum stay rules, and availability status without parsing complex HTML structures.
Yes. We configure the crawler to request specific parameter matrices, such as 3-night, 4-night, and 7-night pricing curves for each property across the calendar year.
We can poll high-value properties daily or even hourly to track booking velocity. Full catalogue refreshes typically run on a 24-hour cycle to capture overnight pricing adjustments.
We extract the highest resolution location data exposed by the platform, which typically includes map pins, regional identifiers, and postcode sectors.
Our smallest packages start at a defined region list with weekly delivery. For national coverage or high-frequency polling, we price based on compute volume and delivery cadence.
Absolutely. We provide a sample run of up to 100 properties as part of the pre-engagement scoping process, allowing you to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off regional property export or a continuous availability feed across the UK - we scope, build, and operate the pipeline. Tell us what you need.
