We extract tour itineraries, pricing signals, availability calendars, operator intelligence, and reviews from Viator. 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 Tour Listings objects from viator.com. All fields typed and schema-versioned.
"product_code": "11400P1", "title": "Rome in a Day: Colosseum and Vatican Tour", "destination": "Rome, Italy", "duration": "7 hours 30 minutes", "base_price": 125.5, "currency": "EUR", "rating": 4.8, "review_count": 14205, "badge_of_excellence": true
| # | product_code | title | destination | category | duration | base_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Availability objects from viator.com. All fields typed and schema-versioned.
"product_code": "11400P1", "date": "2026-08-15", "time": "08:30:00", "adult_price": 125.5, "child_price": 95.0, "currency": "EUR", "availability_status": "AVAILABLE", "remaining_spots": 12
| # | product_code | date | time | adult_price | child_price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from viator.com. All fields typed and schema-versioned.
"review_id": "REV-9847291", "product_code": "11400P1", "reviewer_name": "Sarah_M", "rating": 5, "travel_date": "2026-07-10", "review_text": "Our guide Marco was exceptional. The skip-the-line access saved us hours.", "helpful_votes": 34, "operator_response": "Thank you Sarah! We are glad Marco made your trip special."
| # | review_id | product_code | reviewer_name | rating | travel_date | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Operator Data objects from viator.com. All fields typed and schema-versioned.
"operator_name": "Walks of Italy", "operator_id": "OP-4421", "total_tours": 45, "average_rating": 4.9, "response_rate": 98, "languages": "['English', 'Spanish', 'French']", "established_year": 2009
| # | operator_name | operator_id | total_tours | average_rating | response_rate | languages |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Itineraries objects from viator.com. All fields typed and schema-versioned.
"product_code": "11400P1", "stop_number": 1, "location_name": "Colosseum", "duration_minutes": 90, "admission_included": true, "description": "Guided tour of the first and second tiers.", "pass_by": false
| # | product_code | stop_number | location_name | duration_minutes | admission_included | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Viator scraper navigates complex calendar widgets, localises currency and language settings, and extracts deeply nested itinerary data without triggering Tripadvisor network bot protections.
Extract tour titles, descriptions, inclusions, exclusions, meeting points, and cancellation policies across any destination or category.
Hydrate availability calendars to capture date-specific pricing, time slots, and remaining ticket counts for deep competitor analysis.
Break down complex tour routes into structured stops, including durations, admission status, and location metadata.
Paginate through thousands of reviews to capture ratings, travel dates, textual feedback, and operator responses.
Profile tour operators by extracting their aggregated ratings, total active listings, and language capabilities.
Spoof headers and cookies to extract pricing in your target currency, avoiding volatile post-extraction exchange rate conversions.
Capture Viator specific metadata like Badge of Excellence, Likely to Sell Out tags, and granular sub-category classifications.
Monitor organic ranking positions for specific destinations and keywords to track visibility against competing operators.
Run continuous pipelines that detect price changes and availability drops, delivering only the modified records to reduce compute load.
Brief in. Clean data out.
Provide destination URLs, category filters, or specific product codes. We design the extraction schema together.
We configure Playwright crawlers, calendar interaction scripts, proxy rotation, and session management for viator.com.
Schema validation, null-rate checks, price outlier detection, and itinerary parsing verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Viator relies heavily on client-side rendering for pricing and availability. Here is how we extract it reliably at scale.
Viator pricing and availability are not present in the static HTML. They load dynamically via complex calendar widgets. We run full Playwright browser sessions to select dates, trigger API calls, and capture the resulting price and ticket variants.
Viator shares bot protection infrastructure with Tripadvisor. We route requests through residential ISP proxies with realistic TLS fingerprints and mimic human interaction patterns when clicking through date selectors.
Pricing changes based on the IP location and browser headers. We strictly control the geolocation of the proxy and inject specific cookie states to ensure you receive pricing in your required currency, eliminating exchange rate noise.
Tour descriptions often contain messy, unstructured itinerary data. Our extraction logic parses these sections into structured arrays, separating meeting points, transit times, and specific attraction stops.
Tour operators frequently adjust prices based on season and demand. We maintain a hash index of pricing per date combination, emitting diffs only when an operator changes their rates or a tour sells out.
Tour operators monitor rival pricing across specific dates and seasons to adjust their own rates and maximise yield.
Travel aggregators ingest Viator inventory to build comprehensive destination guides and price comparison engines.
Travel startups analyse review volumes and categorisation to identify underserved niches in popular tourist destinations.
Hospitality groups mine review text to understand common complaints, popular features, and overall customer satisfaction trends.
Revenue managers correlate availability drops and price hikes to train machine learning models for demand forecasting.
Travel planners extract popular routes and duration metrics to design competitive, highly-rated tour packages.
"Viator holds the most comprehensive catalogue of global experiences and pricing signals, but extracting it requires navigating complex calendar widgets and dynamic localised pricing."
Most teams underestimate the investment required. Reliable Viator scraping requires residential proxies, full JavaScript rendering for availability calendars, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our viator.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, calendar interactions, and cookie sessions. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across target regions. Rotation happens per-request with sticky sessions where calendar hydration requires persistent state.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About viator.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Viator is generally permissible under applicable law. DataFlirt targets only public, non-authenticated tour, pricing, and review data. We do not extract personal data or circumvent authentication walls. Clients should review Viator terms of service and consult legal counsel for specific use cases.
We use Playwright to render the page, interact with the calendar widget, and trigger the internal API calls that return pricing and availability for your specified date ranges.
Yes. We configure the crawler with specific cookies and headers to force Viator to display pricing in your requested currency, avoiding the need for manual exchange rate calculations.
Real-time streaming pipelines can achieve sub-60-minute latency for specific high-priority product codes. Full destination refreshes typically complete within a 12-24 hour window depending on scale.
Yes. We parse the unstructured description text and the structured itinerary sections to extract specific stops, durations, meeting points, and included admissions.
Our smallest packages start at a defined list of destinations or categories with weekly delivery. For continuous daily price tracking across thousands of tours, we price based on compute volume and delivery frequency.
Yes. We can scrape specific destination search pages to track the organic ranking position of targeted product codes over time.
Absolutely. We provide a sample run of up to 100 tours or specific destinations as part of the pre-engagement scoping process to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off destination export or continuous price monitoring across thousands of global tours, we scope, build, and operate the pipeline. Tell us what you need.
