We extract activity listings, dynamic pricing calendars, combo package details, and verified reviews from Klook. 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 Activities & Tours objects from klook.com. All fields typed and schema-versioned.
"activity_id": "7942-universal-studios-japan-ticket", "title": "Universal Studios Japan Studio Pass", "location_city": "Osaka", "rating": 4.8, "review_count": 84215, "booking_count": "1M+", "base_price": 5400.0, "currency": "JPY", "instant_confirmation": true
| # | activity_id | title | category | location_city | location_country | supplier_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing Calendars objects from klook.com. All fields typed and schema-versioned.
"activity_id": "7942-universal-studios-japan-ticket", "package_name": "1 Day Studio Pass", "date": "2026-10-15", "availability_status": "AVAILABLE", "adult_price": 8600.0, "child_price": 5600.0, "currency": "JPY", "discount_pct": 0
| # | activity_id | package_id | package_name | date | availability_status | adult_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Transport & Rail objects from klook.com. All fields typed and schema-versioned.
"transport_type": "TRAIN", "operator": "JR West", "departure_station": "Shin-Osaka", "arrival_station": "Kyoto", "departure_time": "09:15:00", "duration_minutes": 14, "ticket_class": "Reserved Seat", "price": 1420.0
| # | route_id | transport_type | operator | departure_station | arrival_station | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from klook.com. All fields typed and schema-versioned.
"review_id": "rev_9841245", "activity_id": "7942-universal-studios-japan-ticket", "rating": 5, "author_country": "Singapore", "travel_date": "2026-09-12", "package_booked": "1 Day Studio Pass - Adult", "review_text": "Easy to scan QR code at the entrance. No need to queue for tickets.", "helpful_votes": 42
| # | review_id | activity_id | author_name | author_country | rating | review_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Combo Packages objects from klook.com. All fields typed and schema-versioned.
"combo_id": "combo_osaka_pass", "combo_name": "Klook Pass Osaka", "included_activities": "['Universal Studios Japan', 'Osaka Aquarium Kaiyukan', 'Umeda Sky Building']", "combo_price": 12500.0, "currency": "JPY", "savings_pct": 22, "validity_days": 30, "refund_eligibility": false
| # | combo_id | activity_id | combo_name | included_activities | total_value | combo_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Klook scraper handles complex travel platform layers: dynamic availability calendars, localised currency pricing, combo package structures, and paginated review corpora.
Extract titles, descriptions, meeting points, inclusions, and exclusion policies for thousands of tours and activities globally.
Scrape date-specific pricing and availability statuses. We hydrate the JavaScript calendars to capture rates for any future date range.
Capture pricing in USD, EUR, JPY, SGD, or any supported currency using locale-specific headers and residential proxies.
Extract schedules, operators, ticket classes, and availability for point-to-point transport and regional rail passes.
Paginate through thousands of user reviews per activity. Capture ratings, travel dates, package variants booked, and helpful votes.
Map included attractions, total value, and savings percentages for bundled Klook Passes and multi-attraction combos.
Extract structured rules for refunds, cut-off times, and instant confirmation statuses to model inventory risk.
Extract exact coordinates, meeting points, and route itineraries for complex multi-day tours.
Run daily diffs on pricing calendars to detect flash sales, availability drops, and seasonal rate changes.
Brief in. Clean data out.
Provide destination URLs, activity IDs, or category lists. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for klook.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Travel aggregators rely on aggressive bot mitigation and heavy client-side rendering. Here is how we maintain stable extraction.
Klook employs strict bot detection based on IP reputation and TLS fingerprints. Our crawlers route through residential ISP proxies in target regions, applying realistic browser fingerprints and randomised delays to avoid blocks.
Klook's date-based pricing and availability calendars are heavily JavaScript-rendered. We run full Playwright browser sessions to interact with date pickers, triggering the underlying XHR requests to capture accurate future pricing.
Travel platforms dynamically alter pricing and availability based on the visitor's IP and locale headers. We enforce strict session parameters to ensure data is consistently scraped in your required currency and language.
Activity pages on Klook vary wildly depending on the supplier and category. Our extraction logic uses fallback chains and JSON-LD parsing to ensure reliable field mapping despite DOM inconsistencies.
For massive pricing calendars, we maintain a hash index of last-seen values. Subsequent runs only push diffs — reducing compute cost, storage bloat, and downstream processing load.
Online travel agencies monitor Klook's pricing, combo discounts, and availability to adjust their own marketplace rates.
Tour operators track daily price fluctuations across competitor listings to optimise their own revenue management systems.
Research firms analyse booking volumes, review velocity, and destination popularity to identify emerging travel trends.
Airlines and hoteliers correlate attraction availability and pricing with flight data to predict regional tourism spikes.
Metasearch engines ingest Klook inventory to display real-time attraction and transport options alongside flights and hotels.
LLM developers train travel recommendation models using Klook's vast corpus of activity descriptions, reviews, and itineraries.
"Klook holds the definitive inventory for APAC travel and experiences, but extracting dynamic calendar availability requires significant infrastructure."
Most teams underestimate the investment required: reliable Klook scraping requires residential proxies, full JavaScript rendering for date-pickers, CAPTCHA handling, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our klook.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 for complex date pickers.
We maintain pools of residential ISP proxies across global regions. Rotation happens per-request with sticky sessions where required for stable currency extraction.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 klook.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We configure the crawler to interact with Klook's availability calendars, extracting pricing and inventory status for any defined date range (e.g., next 90 days).
We use region-specific residential proxies combined with strict locale and currency headers to ensure all pricing data is extracted in your required target currency.
For targeted activity lists, pipelines can run at hourly cadences. Full catalogue refreshes typically run daily or weekly depending on the volume of pages.
Yes. We extract the parent package details alongside the list of included activities, mapping the total value and advertised savings percentages.
We employ ISP-grade residential proxies, realistic browser fingerprinting via Playwright, and automated CAPTCHA solvers to maintain high success rates without triggering blocks.
We build a time-series database from the day your pipeline begins. We do not have retroactive historical data prior to the pipeline start date.
Yes. We provide a sample run of up to 100 activities as part of the scoping process, allowing you to validate schema fit and data quality before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or a continuous price-monitoring feed across 100K activities — we scope, build, and operate the pipeline. Tell us what you need.
