We extract hotel listings, flight schedules, dynamic pricing, room availability, and reviews from Wotif. 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 Listings objects from wotif.com. All fields typed and schema-versioned.
"property_id": "W-192847", "name": "Meriton Suites Kent Street", "star_rating": 5.0, "location": "Sydney Central Business District", "review_score": 9.2, "review_count": 4182, "price_per_night": 245.0, "currency": "AUD"
| # | property_id | name | star_rating | location | latitude | longitude |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Flight Itineraries objects from wotif.com. All fields typed and schema-versioned.
"flight_id": "QF-409-SYD-MEL", "airline": "Qantas Airways", "flight_number": "QF409", "departure_airport": "SYD", "arrival_airport": "MEL", "duration_minutes": 95, "price": 189.0, "cabin_class": "Economy"
| # | flight_id | airline | flight_number | departure_airport | arrival_airport | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Room Types objects from wotif.com. All fields typed and schema-versioned.
"room_id": "RM-9921", "room_name": "Luxury Studio Suite", "max_occupancy": 2, "price": 245.0, "cancellation_policy": "Fully refundable before 14:00 on check-in day", "breakfast_included": false, "mates_rates_applied": true, "stock_left": 3
| # | room_id | property_id | room_name | max_occupancy | bed_type | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Package Deals objects from wotif.com. All fields typed and schema-versioned.
"package_id": "PKG-SYD-BNE-5N", "destination": "Brisbane", "hotel_name": "Brisbane Marriott Hotel", "flight_included": true, "nights": 5, "total_price": 1250.0, "discount_pct": 15, "travel_dates": "2026-10-12 to 2026-10-17"
| # | package_id | destination | hotel_name | flight_included | nights | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Guest Reviews objects from wotif.com. All fields typed and schema-versioned.
"review_id": "REV-884712", "property_id": "W-192847", "rating": 10.0, "review_date": "2026-08-14", "stay_date": "August 2026", "review_text": "Exceptional views of the harbour and perfect location for transit.", "traveller_type": "Couples"
| # | review_id | property_id | guest_name | rating | review_date | stay_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Wotif scraper navigates dynamic search parameters, location-based pricing, and complex inventory displays. We handle the session state and JavaScript execution required to extract accurate travel data.
Extract properties across AU/NZ and global destinations including star ratings, amenities, and exact geospatial coordinates.
Capture dynamic flight pricing across all carriers, including baggage inclusions, layover durations, and cabin classes.
Map complex room hierarchies, bed configurations, cancellation terms, and remaining inventory levels.
Identify member-only discounts and promotional pricing structures specific to the Wotif platform.
Extract bundled flight and hotel package data, calculating implied discounts and total trip costs.
Paginate through guest reviews, capturing sub-ratings for cleanliness, service, and location.
Scrape ancillary travel services, local experiences, and rental car availability tied to specific travel dates.
Extract exact latitude and longitude coordinates along with neighbourhood proximity indicators.
Run daily sweeps across major routes or track specific properties continuously for yield management.
Brief in. Clean data out.
Provide destination lists, route pairs, date ranges, or specific property IDs. We design the extraction schema.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for wotif.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Travel aggregators deploy aggressive scraping countermeasures and dynamic frontend architectures. Here is how we maintain pipeline stability.
Expedia Group platforms use advanced perimeter protection. Our crawlers use AU/NZ residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass blocks.
Wotif alters prices based on IP location, search history, and time of day. We normalise session parameters and use clean browser contexts for every search to ensure baseline pricing accuracy.
Wotif relies on heavy frontend hydration for inventory displays. We run full Playwright browser sessions to trigger lazy-loaded room rates and flight options that standard HTTP clients miss.
Travel platforms update layouts constantly for A/B testing. We target structured JSON-LD data blocks first, backed by multiple XPath and CSS fallback chains to prevent schema breakage.
We monitor pipeline health continuously. Automated alerts trigger on null-rate spikes, missing inventory blocks, or sudden price anomalies, allowing us to patch selectors before your downstream processes fail.
Monitor Wotif pricing against direct channels and competing OTAs to ensure rate parity and identify margin opportunities.
Hoteliers track market occupancy signals and dynamic rate fluctuations in their local area to optimise their own pricing.
Feed metasearch engines and niche travel apps with Wotif inventory, package deals, and flight routes.
Analyse destination popularity, seasonal pricing trends, and review sentiment across the AU/NZ travel market.
Train pricing models, demand forecasting algorithms, and recommendation engines on historical travel datasets.
Evaluate travel sector recovery, property performance metrics, and regional demand shifts for private equity analysis.
"Wotif holds critical pricing intelligence for the AU and NZ travel markets. Accessing this data at scale requires bypassing sophisticated bot protection and rendering complex single page applications."
Travel aggregators rely on heavy JavaScript execution and strict rate limits. DataFlirt manages the residential proxy rotation, session hydration, and schema maintenance required to extract Wotif inventory continuously. Your engineers get clean Parquet files, not CAPTCHA blocks.
Everything supported by our wotif.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 and interaction flows required for Wotif search results.
We maintain pools of residential ISP proxies across AU/NZ regions. Rotation happens per session to prevent IP bans and ensure accurate localized pricing.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About wotif.com scraping, legality, and pipeline operations.
Ask us directly →Expedia Group platforms use advanced bot mitigation. We use AU/NZ residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and strict session management to bypass these systems reliably.
Yes. We can configure extraction pipelines to capture standard public rates alongside promotional Mates Rates and mobile-only discounts.
Real-time streaming pipelines achieve sub-60-minute latency for defined route pairs and property lists. Full market sweeps typically complete within a 12-hour window.
Yes. Our Wotif pipelines cover the entire platform catalogue, including hotel listings, flight itineraries, package deals, car hire, and activities.
Yes. Every pipeline run produces timestamped snapshots. You can build time-series databases for room rates and flight prices from the date your pipeline starts.
Our smallest packages start at a defined list of 500 properties or 100 route pairs with daily delivery. Contact us with your specific parameters for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily sweep of Sydney hotels or continuous flight price monitoring across the APAC region, we build and operate the pipeline. Tell us what you need.
