We extract guided tour catalogues, day-by-day itineraries, seasonal pricing, and departure availability from Insight Vacations. 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 Overview objects from insightvacations.com. All fields typed and schema-versioned.
"tour_id": "IV-EUR-2026-928", "title": "European Discovery", "countries_visited": 7, "duration_days": 14, "travel_style": "Discovery", "base_price": 4295.0, "currency": "USD", "rating": 4.8
| # | tour_id | title | destination_region | countries_visited | duration_days | travel_style |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Itinerary Details objects from insightvacations.com. All fields typed and schema-versioned.
"tour_id": "IV-EUR-2026-928", "day_number": 3, "day_title": "Paris to Lucerne", "location_start": "Paris", "location_end": "Lucerne", "meals_included": "['Breakfast', 'Dinner']", "accommodation": "Hotel Astoria Lucerne", "activity_level": "Moderate"
| # | tour_id | day_number | day_title | location_start | location_end | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Departures & Pricing objects from insightvacations.com. All fields typed and schema-versioned.
"tour_id": "IV-EUR-2026-928", "departure_date": "2026-06-14", "end_date": "2026-06-28", "availability_status": "Available", "price": 4295.0, "discount_price": 3995.0, "guaranteed_departure": true, "seats_remaining": 6
| # | tour_id | departure_date | end_date | availability_status | price | discount_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inclusions & Accommodation objects from insightvacations.com. All fields typed and schema-versioned.
"tour_id": "IV-EUR-2026-928", "hotel_name": "Hotel Astoria Lucerne", "hotel_rating": "4 Star", "hotel_location": "Lucerne, Switzerland", "nights_stay": 2, "transport_type": "Luxury Coach", "guide_included": "Travel Director"
| # | tour_id | hotel_name | hotel_rating | hotel_location | nights_stay | meal_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from insightvacations.com. All fields typed and schema-versioned.
"tour_id": "IV-EUR-2026-928", "review_id": "REV-992817", "rating": 5, "review_date": "2025-08-12", "review_title": "Incredible European Journey", "travel_date": "July 2025", "verified_traveler": true
| # | tour_id | review_id | author | rating | review_date | review_title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles every layer of the platform: tour catalogues, day-by-day itineraries, dynamic departure pricing, and seat availability, with JavaScript rendering and session management built in.
Day-by-day routing, location data, activity descriptions, and included meals parsed into structured arrays.
Extract all future departure dates, end dates, and guaranteed departure flags for every published tour.
Capture base prices, promotional discounts, single supplements, and multi-currency variations based on geographic region.
Extract hotel names, star ratings, and locations linked to specific itinerary days across the catalogue.
Monitor seat availability statuses and sell-out warnings to model booking velocity and demand.
Paginate through guest reviews to extract ratings, text, verified traveller flags, and travel dates.
Rotate through regional proxies to capture accurate pricing for US, UK, EU, and Australian markets.
Capture add-on excursions, their descriptions, and supplementary costs associated with specific tour days.
Run daily pipelines to detect price drops, newly added departure dates, or sold-out tours.
Brief in. Clean data out.
Provide target regions, travel styles, or specific tour URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for insightvacations.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Travel sites rely on complex pricing engines and regional variations. Here is how we maintain data integrity.
Insight Vacations displays different prices and currencies based on user location. We route requests through residential proxies in your target markets to ensure you capture accurate local pricing.
Departure dates and availability statuses are loaded dynamically via API calls and JavaScript. We use Playwright to render the full booking calendar and extract the hydrated state.
Tour descriptions and day-by-day itineraries often contain unstructured text. Our parsers use regular expressions and DOM traversal to normalise this into clean, queryable arrays.
We maintain a hash index of last-seen values for departure dates. Subsequent runs only push diffs, allowing you to easily track price drops or availability changes over time.
Every run emits structured logs to our observability stack. We alert on null-rate spikes or missing pricing data and respond before you notice.
Tour operators track Insight Vacations pricing and promotions to adjust their own seasonal rates and maintain competitiveness.
Travel analysts monitor catalogue expansions, new destinations, and retired routes to identify industry trends.
Revenue managers correlate sell-out rates and guaranteed departure flags to model consumer travel demand.
Travel agents and aggregators ingest structured itinerary data to build comparison tools and custom booking portals.
Machine learning teams use structured day-by-day itineraries to train travel recommendation engines and generative models.
Hospitality teams mine guest reviews to understand customer satisfaction regarding specific hotels, tour guides, and destinations.
"Insight Vacations holds a premium dataset of guided global itineraries, but extracting day-by-day routing and seasonal pricing requires dedicated pipeline infrastructure."
Most teams underestimate the investment required: reliable travel scraping requires residential proxies to bypass geo-pricing, full JavaScript rendering for availability calendars, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our insightvacations.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 for dynamic pricing calendars and interaction flows.
We maintain pools of residential ISP proxies across target regions. Rotation happens per-request to capture accurate local pricing and bypass geo-restrictions.
Pipelines run on AWS Lambda and ECS. 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 insightvacations.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated tour catalogues, itineraries, and pricing data. We do not extract personal data or circumvent authentication walls.
Insight Vacations alters pricing based on visitor IP. We configure your pipeline to route requests through residential proxies located in your target markets (e.g. US, UK, Australia) to ensure accurate currency and price capture.
Pipelines can be scheduled daily, weekly, or monthly. For dynamic pricing and availability tracking, daily runs are standard. Full catalogue refreshes typically complete within a 2-4 hour window.
Yes. We parse the unstructured HTML descriptions into clean arrays containing day numbers, titles, start/end locations, included meals, and accommodation details.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series record for departure dates, allowing you to track price fluctuations over time.
Our selectors use multiple fallback chains per field. We monitor for null-rate spikes in real time and update parsers promptly if Insight Vacations modifies their DOM structure.
Our packages start at a defined tour volume with weekly delivery. For continuous daily pricing updates across multiple regions, we price based on compute volume and delivery frequency.
Yes. We provide a sample run of up to 20 tours as part of the pre-engagement scoping process, allowing you 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 catalogue extract or a continuous price-monitoring feed across multiple regions, we scope, build, and operate the pipeline. Tell us what you need.
