We extract hotel listings, dynamic pricing, room availability, guest reviews, and flight schedules from Agoda. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
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 agoda.com. All fields typed and schema-versioned.
"property_id": "12345", "name": "Marina Bay Sands", "star_rating": 5, "location": "Singapore", "latitude": 1.2834, "longitude": 103.8607, "total_reviews": 45210, "rating_score": 9.2
| # | property_id | name | star_rating | location | latitude | longitude |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Room Pricing objects from agoda.com. All fields typed and schema-versioned.
"property_id": "12345", "room_type": "Deluxe King", "base_price": 450.0, "discount_price": 395.0, "currency": "SGD", "tax_included": false, "free_cancellation": true, "breakfast_included": true
| # | property_id | room_type | max_occupancy | base_price | discount_price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Guest Reviews objects from agoda.com. All fields typed and schema-versioned.
"review_id": "REV987654", "property_id": "12345", "reviewer_name": "John D.", "country": "United Kingdom", "traveler_type": "Business", "rating": 9.5, "review_title": "Excellent stay", "stay_date": "2026-03-15"
| # | review_id | property_id | reviewer_name | country | traveler_type | rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Flights objects from agoda.com. All fields typed and schema-versioned.
"flight_id": "FL-SQ322", "airline": "Singapore Airlines", "flight_number": "SQ322", "departure_airport": "SIN", "arrival_airport": "LHR", "departure_time": "2026-04-10T23:30:00Z", "price": 1250.0, "currency": "SGD"
| # | flight_id | airline | flight_number | departure_airport | arrival_airport | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Search Results objects from agoda.com. All fields typed and schema-versioned.
"keyword": "Phuket resorts", "check_in": "2026-12-01", "check_out": "2026-12-07", "position": 1, "property_id": "87654", "price": 120.5, "secret_deal": false, "coupon_eligible": true
| # | keyword | check_in | check_out | position | property_id | name |
|---|---|---|---|---|---|---|
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Our Agoda scraper handles every layer of the platform: hotel listings, dynamic pricing, room availability, flight schedules, and the review corpus. JavaScript rendering, session management, and bot circumvention are built in.
Name, address, geo-coordinates, star ratings, and exhaustive amenity lists across global properties.
Capture real-time room rates, tax inclusions, and stock scarcity warnings per check-in and check-out window.
Track gated promotional rates, AgodaCash accruals, and tier-specific discounts using injected session cookies.
Extract full review text, traveler demographics, sub-scores for cleanliness, and management responses.
Monitor airline routes, transit durations, layovers, and dynamic ticket pricing across Agoda Flights.
Simulate bookings from specific origin countries to capture region-locked pricing and local currency rates.
Extract granular booking conditions, refund windows, and pay-at-hotel eligibility for every room type.
Compare Agoda mobile app rates versus desktop rates to identify platform-specific discounting strategies.
Run daily market snapshots or configure high-frequency continuous pipelines for rapid price changes.
Brief in. Clean data out.
Provide destination IDs, hotel lists, or flight routes. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for agoda.com.
Schema validation, null-rate checks, price-outlier detection, and sample payloads before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Agoda invests heavily in scraping detection. Here is how we stay resilient, and why teams choose managed infrastructure over DIY.
Agoda uses Akamai and Datadome. We bypass this using ISP-grade residential proxies, TLS fingerprinting, and realistic interaction delays trained on human behaviour.
Agoda search results and pricing grids rely heavily on client-side rendering. We hydrate the DOM fully before extraction to capture data headless clients miss.
Agoda displays different prices based on the user IP. We route requests through region-specific nodes to capture exact local rates and geo-locked promotions.
Travel OTAs constantly A/B test UI elements. Our pipelines use multi-layered selectors and API interception to ensure zero data loss when layouts change.
Scraping forward-looking availability requires massive request volume. We distribute this load across Kubernetes clusters to capture 365-day calendars.
Hotels and channel managers audit Agoda against direct booking sites to ensure contractual rate compliance.
OTAs and travel agencies track Agoda dynamic pricing and promotional discounting to adjust their own margins.
Airlines and hospitality groups ingest forward-looking availability data to optimise their yield management algorithms.
Real estate and tourism boards analyse property density, average nightly rates, and review sentiment across regions.
Hedge funds track listing growth, discount velocity, and review volume as proxy metrics for travel demand.
LLM developers ingest structured property details and historical pricing to train conversational travel agents.
"Agoda processes millions of dynamic pricing updates daily. Capturing this data at scale requires infrastructure that can outpace their rate limits and geo-fencing."
Extracting travel data is notoriously difficult due to origin-based pricing, aggressive anti-bot measures like Datadome, and massive combinatorial complexity across dates and room types. DataFlirt manages the proxy rotation, JavaScript hydration, and API interception so your data science team receives clean, normalised records ready for analysis.
Everything supported by our agoda.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows.
We maintain pools of residential ISP proxies globally. Rotation happens per-request with sticky sessions where required to bypass Datadome.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in Postgres.
Data delivered to where your team already works — no new tooling required.
About agoda.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available property and pricing data is generally permissible. We do not extract PII or breach authenticated user accounts. Clients should consult legal counsel for specific use cases.
We use high-reputation residential proxies, realistic TLS fingerprints, and human-like interaction delays to maintain high success rates.
Yes. We configure pipelines to query specific check-in and check-out date ranges, adult and child counts, and specific room configurations.
Yes. We can extract obscured property details and match them against known databases to reveal the hidden hotel name.
We support high-frequency streaming for real-time price tracking, achieving sub-15-minute latency for targeted property lists.
Yes. Agoda alters pricing based on the searcher IP. We route traffic through geo-specific proxies to capture exact local market rates.
Our smallest packages start at a defined list of 5,000 properties with daily delivery. We scale up to full global catalogue extraction.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off property catalogue dump or a continuous price-monitoring feed across 1M hotels, we scope, build, and operate the pipeline. Tell us what you need.
