We extract venue listings, ticket pricing, availability calendars, operating hours, and user reviews from Tiqets. 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 Attraction Listings objects from tiqets.com. All fields typed and schema-versioned.
"attraction_id": "tq_8921", "title": "Louvre Museum", "destination": "Paris", "category": "Museums", "rating": 4.8, "review_count": 12405, "latitude": 48.8606, "longitude": 2.3376
| # | attraction_id | title | destination | category | rating | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ticket Pricing objects from tiqets.com. All fields typed and schema-versioned.
"ticket_id": "tk_102", "name": "Standard Admission", "price": 22.0, "original_price": 22.0, "currency": "EUR", "cancellation_policy": "Free cancellation before 23:59 day before", "mobile_ticket": true, "instant_delivery": true
| # | attraction_id | ticket_id | name | price | original_price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Availability Calendar objects from tiqets.com. All fields typed and schema-versioned.
"attraction_id": "tq_8921", "date": "2024-08-15", "time_slot": "10:00", "available": true, "capacity": 14, "price_modifier": 0.0, "currency": "EUR", "scraped_at": "2024-06-12T08:00:00Z"
| # | attraction_id | date | time_slot | available | capacity | price_modifier |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Venue Information objects from tiqets.com. All fields typed and schema-versioned.
"attraction_id": "tq_8921", "address": "Rue de Rivoli", "city": "Paris", "country": "France", "opening_hours": "09:00", "closing_hours": "18:00", "accessibility": "Wheelchair accessible", "audio_guide_languages": "['English', 'French', 'Spanish']"
| # | attraction_id | address | city | country | opening_hours | closing_hours |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for User Reviews objects from tiqets.com. All fields typed and schema-versioned.
"review_id": "rv_99281", "attraction_id": "tq_8921", "author_country": "UK", "rating": 5, "date": "2024-05-20", "text": "Incredible experience, skip the line was essential.", "language": "en", "helpful_votes": 12
| # | review_id | attraction_id | author_name | author_country | rating | date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Tiqets scraper handles the complexities of travel platforms: dynamic pricing logic, complex calendar structures, multilingual content, and anti-bot circumvention.
Titles, descriptions, exact geo-coordinates, categories, and practical information like opening hours and accessibility features.
Capture base prices, discounted rates, fast-track options, and combo deals across multiple currencies.
Extract deep availability data including date-specific pricing, time-slot capacity, and sold-out states.
Full review text, ratings, visitor nationality, visit dates, and helpful vote counts across all paginated views.
Capture pricing in EUR, USD, GBP, and 20+ other currencies as natively displayed on the platform.
Extract latitude and longitude coordinates for precise mapping and spatial analysis of attraction density.
Identify and map bundled tickets linking multiple attractions into a single purchase.
Extract complex opening hour schedules including seasonal variations and holiday closures.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences.
Brief in. Clean data out.
Provide destination cities, attraction URLs, or category filters. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for tiqets.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 platforms invest in scraping detection and dynamic content delivery. Here is how we maintain data fidelity.
Travel OTAs use strict bot detection. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to blend in with legitimate tourist traffic.
Tiqets uses dynamic React components for calendars and ticket selection. We run full Playwright browser sessions to trigger date pickers, hydrate pricing widgets, and capture data invisible to headless HTTP clients.
Availability calendars require sequential interaction. Our pipeline programmaticly traverses months and days, expanding time-slots to extract granular capacity and dynamic pricing rules without triggering rate limits.
For large venue catalogues, we maintain a hash index of last-seen values per field. 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, missing calendars, and coverage drops. SLA uptime is contractual.
Online travel agencies monitor Tiqets pricing and combo deals to maintain parity and optimise their own markups.
Revenue managers analyse sold-out dates and time-slot capacity to predict peak tourist volumes across major cities.
Tourism boards and investors track attraction density, review sentiment, and pricing trends to evaluate destination performance.
LLM developers use structured venue data, operating hours, and geo-coordinates to ground itinerary generation models.
Attraction operators track competitor pricing across seasons to inform their own dynamic pricing strategies.
Hospitality brands ingest review text across multiple languages to identify operational issues and visitor satisfaction trends.
"Tiqets holds highly structured availability and pricing data for global attractions — crucial for travel intelligence, yet locked behind complex JavaScript calendars."
Extracting data from modern OTAs requires navigating dynamic DOMs, interactive date pickers, and strict rate limits. DataFlirt manages the residential proxies, browser automation, and schema maintenance required to turn Tiqets into a reliable data feed. Your engineering team gets clean data, not maintenance debt.
Everything supported by our tiqets.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. 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 (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 tiqets.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Tiqets is generally permissible under applicable law. DataFlirt targets only public, non-authenticated venue, pricing, and review data. We do not extract personal data or circumvent authentication walls. Clients should review Tiqets ToS and consult legal counsel for specific use cases.
We use headless browsers via Playwright to programmatically interact with the date picker widgets. The pipeline traverses the specified date range, capturing capacity, time-slots, and dynamic pricing for each day.
Yes. Tiqets supports multiple locales. We can configure the pipeline to extract descriptions, reviews, and metadata in your preferred language or across multiple languages simultaneously.
Pipeline cadences are configurable. We can run daily sweeps across a large catalogue, or high-frequency hourly checks on a targeted list of high-priority attractions to monitor dynamic pricing changes.
Our smallest packages start at a defined list of destinations or attractions with weekly delivery. For global coverage or high-frequency calendar scraping, we price based on compute volume and delivery frequency.
Absolutely. We provide a sample run of up to 100 attractions, including pricing and calendar data, as part of the pre-engagement scoping process. This validates schema fit and data quality before contract signing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off venue catalogue export or a continuous availability-monitoring feed across 10,000 attractions — we scope, build, and operate the pipeline. Tell us what you need.
