We extract tour catalogues, daily itineraries, live pricing, departure availability, and traveller reviews from G Adventures. 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 g-adventures.com. All fields typed and schema-versioned.
"tour_id": "DPQA", "name": "Inca Trail", "travel_style": "Active", "physical_rating": "4 - Demanding", "duration_days": 7, "start_location": "Cusco", "base_price": 1249.0
| # | tour_id | name | url | travel_style | physical_rating | trip_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Itinerary Details objects from g-adventures.com. All fields typed and schema-versioned.
"day_number": 3, "day_title": "Inca Trail to Machu Picchu", "meals_included": "['Breakfast', 'Lunch', 'Dinner']", "accommodation_type": "Camping", "activities": "['Hiking', 'Guided Tour']", "travel_time": "6 hours"
| # | tour_id | day_number | day_title | day_description | meals_included | accommodation_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Departures & Pricing objects from g-adventures.com. All fields typed and schema-versioned.
"departure_date": "2024-08-12", "return_date": "2024-08-18", "price": 1249.0, "availability_status": "Available", "spaces_left": 4, "guarantee_status": "Guaranteed Departure"
| # | tour_id | departure_date | return_date | price | discount_price | availability_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inclusions & Specs objects from g-adventures.com. All fields typed and schema-versioned.
"chief_experience_officer": true, "group_size_max": 16, "transport_types": "['Train', 'Private Vehicle', 'Walking']", "age_requirement": "12+", "packing_list": "['Hiking boots', 'Daypack', 'Water bottle']", "visa_requirements": "Check local consulate"
| # | tour_id | chief_experience_officer | group_size_min | group_size_max | transport_types | age_requirement |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Traveller Reviews objects from g-adventures.com. All fields typed and schema-versioned.
"review_id": "REV-99214", "rating": 5.0, "review_date": "2023-11-04", "travel_month": "October 2023", "traveller_type": "Solo Traveller", "review_text": "Incredible experience on the trail. The CEO was highly knowledgeable."
| # | review_id | tour_id | reviewer_name | rating | review_date | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our G Adventures scraper handles the complete travel catalogue: dynamic availability calendars, complex multi-day itineraries, and localised pricing, with JavaScript rendering and anti-bot circumvention built in.
Title, style, physical grading, duration, start points, and end points extracted for every tour.
Capture live dates, spaces remaining, and guaranteed departure flags across all scheduled trips.
Extract base price, localised currency variations, and seasonal discounts tied to specific departure dates.
Full text descriptions, included meals, transport types, and daily activities parsed into structured arrays.
Extract Chief Experience Officer (CEO) presence, group size limits, age requirements, and packing lists.
Aggregate ratings, review text, travel dates, and traveller demographics from the review sections.
Extract pricing in USD, GBP, EUR, AUD, and CAD by routing requests through regional proxies.
Identify hotel types, camping details, homestays, and transit methods specified in the trip dossier.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or weekly cadences.
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 g-adventures.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 booking engines invest heavily in scraping detection to protect pricing data. Here is how we stay resilient.
G Adventures loads departure dates and pricing via asynchronous requests when users interact with the calendar. We intercept these API calls and replicate the payload structures to extract availability data without rendering the entire DOM.
Pricing changes based on the user's location. We route traffic through specific regional proxies (e.g., UK residential IPs for GBP pricing) to ensure you receive accurate, localised rates rather than default USD values.
Travel sites monitor request velocity heavily. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to avoid IP bans and CAPTCHA walls.
Booking interfaces update frequently. Our selector strategy uses multiple fallback chains per field, including JSON-LD structured data extraction, so a layout change does not break your data pipeline overnight.
For large travel catalogues, we maintain a hash index of last-seen values per departure date. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Online travel agencies synchronise tour inventory, pricing, and availability to display accurate options to their users.
Tour operators track pricing, seasonal discounts, and guaranteed departures to optimise their own pricing strategies.
Analysts track popular travel routes, duration trends, and physical grading distributions to identify whitespace in the adventure travel market.
Machine learning teams use structured day-by-day itineraries to train LLMs and recommendation engines for trip planning.
Product teams mine traveller reviews to evaluate CEO performance, accommodation quality, and overall trip satisfaction.
Revenue managers correlate spaces left on specific departures with booking dates to model demand curves and optimise yield.
"G Adventures holds a massive repository of structured experiential travel data, but extracting day-by-day itineraries and live pricing at scale requires dedicated infrastructure."
Most teams underestimate the investment required: reliable travel 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 g-adventures.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 calendar widgets.
We maintain pools of residential ISP proxies across global regions to extract localised pricing and avoid rate limits.
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 g-adventures.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from G Adventures is generally permissible under applicable law. DataFlirt targets only public, non-authenticated tour, pricing, and itinerary data. We do not extract personal data or circumvent authentication walls.
We intercept the background API requests triggered by the calendar UI or use full Playwright sessions to render the calendar and extract the availability states and pricing arrays directly from the DOM.
Yes. We route requests through region-specific residential proxies (e.g., UK for GBP, Australia for AUD) to capture the exact localised pricing displayed to users in those markets.
Pipelines can be configured to run daily or hourly depending on your requirements. Change-detection ensures you only process updates when availability or pricing shifts.
Yes. We extract the complete trip details including day-by-day itineraries, physical grading, packing recommendations, and visa requirements.
Our smallest packages start at a defined set of tour URLs or specific travel styles with weekly delivery. Contact us with your use case for a scoped quote.
Absolutely. We provide a sample run of up to 50 tours as part of the pre-engagement scoping process so you can validate schema fit and field completeness.
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 thousands of departures, we scope, build, and operate the pipeline. Tell us what you need.
