We extract resort profiles, rental listings, resale inventory, points valuations, and historical availability from RedWeek. 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 Resort Profiles objects from redweek.com. All fields typed and schema-versioned.
"resort_id": "R4219", "name": "Marriott's Maui Ocean Club", "brand": "Marriott Vacation Club", "city": "Lahaina", "state": "Hawaii", "rating": 4.8, "review_count": 342, "total_rentals": 145, "total_resales": 32
| # | resort_id | name | brand | address | city | state |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Rental Listings objects from redweek.com. All fields typed and schema-versioned.
"listing_id": "L982145", "resort_id": "R4219", "check_in_date": "2026-07-11", "check_out_date": "2026-07-18", "nights": 7, "price": 2800.0, "unit_size": "2 Bedroom", "sleeps": 8, "verified_status": true
| # | listing_id | resort_id | check_in_date | check_out_date | nights | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Resale Listings objects from redweek.com. All fields typed and schema-versioned.
"listing_id": "S44192", "resort_id": "R4219", "price": 12500.0, "usage_type": "Annual", "maintenance_fees": 1850.0, "deeded": true, "points_allocation": "None", "week_number": "Float", "verified_status": true
| # | listing_id | resort_id | price | points_allocation | week_number | usage_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from redweek.com. All fields typed and schema-versioned.
"review_id": "V99102", "resort_id": "R4219", "rating": 5, "date_posted": "2025-11-04", "travel_date": "2025-10-01", "title": "Perfect family getaway", "helpful_votes": 12, "owner_status": "Guest"
| # | review_id | resort_id | author | rating | date_posted | travel_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Points Systems objects from redweek.com. All fields typed and schema-versioned.
"system_name": "Disney Vacation Club", "resort_id": "R1102", "season": "Magic", "unit_type": "1 Bedroom Villa", "points_required": 240, "exchange_company": "Interval International", "maintenance_fee_per_point": 8.67
| # | system_name | resort_id | season | tier | unit_type | points_required |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our RedWeek scraper handles every layer of the timeshare market: resort directories, rental availability, resale valuations, and owner reviews — with JavaScript rendering and anti-bot circumvention built in.
Extract resort metadata, location coordinates, brand affiliations, and aggregated review scores across the entire RedWeek catalogue.
Capture check-in dates, unit sizes, sleep capacity, and per-night pricing for all active rental listings.
Track asking prices, maintenance fees, deed statuses, and float vs fixed week parameters for secondary market listings.
Distinguish between RedWeek Verified listings, full-service managed rentals, and unverified owner postings.
Full review text, star ratings, travel dates, and helpful vote counts paginated across all resort profiles.
Standardise extraction across complex ownership types, from legacy fixed weeks to modern points-based systems (MVC, DVC, HGVC).
Extract annual maintenance fees for resale listings to calculate true cost of ownership and cap rates.
Query listings via geographic bounding boxes to capture inventory in highly specific sub-markets.
Run one-off bulk exports or configure continuous pipelines at daily cadences with change-detection diffing.
Brief in. Clean data out.
Provide resort IDs, geographic regions, or specific brands. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for redweek.com.
Schema validation, null-rate checks, price-outlier detection, and sample rentals before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting structured data from fragmented timeshare listings requires resilient infrastructure. Here's how we ensure reliable delivery.
RedWeek employs standard anti-scraping measures. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to maintain uninterrupted access.
Location-based searches and dynamic availability calendars require JavaScript execution. We run full Playwright browser sessions to trigger lazy-loaded inventory and map-bound queries.
Timeshare listings vary wildly between points, weeks, and fractional ownership. Our extraction logic normalises these disparate formats into a unified, predictable schema.
For active rental tracking, we maintain a hash index of last-seen values per listing. 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, inventory drops, and schema drift, ensuring your timeshare data remains accurate.
Brokers and appraisers use resale asking prices and maintenance fee data to generate accurate comparables for the secondary market.
Hospitality analysts compare timeshare rental rates against traditional hotel ADRs to identify pricing inefficiencies in high-demand markets.
HOAs and management companies track secondary market activity for their resorts to monitor brand health and owner liquidity.
Vacation club developers monitor resale values and rental yields of competing brands to adjust their own direct-sale pricing strategies.
Proptech ML teams use historical RedWeek pricing and availability data to train predictive models for vacation rental demand.
Analysts track listing velocity and days-on-market proxies to understand timeshare liquidity trends across different seasons and regions.
"RedWeek holds the definitive secondary market for timeshare liquidity, but extracting unified pricing across fragmented point systems requires dedicated infrastructure."
Most teams underestimate the investment required: reliable RedWeek scraping requires residential proxies, full JavaScript rendering for map interfaces, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our redweek.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 and map interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
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 redweek.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from RedWeek is generally permissible under applicable law. DataFlirt targets only public, non-authenticated resort, pricing, and review data. We do not extract personal owner contact details or circumvent authentication walls.
Our schema is designed to normalise timeshare complexity. We capture the raw listing type (e.g., 250 DVC points, or Week 42 Annual) and map it to standardized fields so you can query across different vacation clubs uniformly.
We configure pipelines based on your requirements. Daily refreshes of active rental inventory are standard, completing within a 4-6 hour window for targeted resort lists.
Yes. We can scope the extraction to specific entities like Marriott Vacation Club, Wyndham, Hilton Grand Vacations, or Disney Vacation Club, rather than the entire global directory.
Yes. Where maintenance fees are published on the resale listing, we extract the numerical value and currency to aid in cap rate and valuation modelling.
Our smallest packages start at a defined resort list (typically top 500-1,000 high-volume resorts) with weekly delivery. For the full global catalogue, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off resort directory dump or a continuous rental pricing feed across 9,000 properties — we scope, build, and operate the pipeline. Tell us what you need.
