We extract event schedules, ticket availability, dynamic pricing, seating sections, and venue details from Viagogo. 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 Event Listings objects from viagogo.com. All fields typed and schema-versioned.
"event_id": "E-1508291", "event_name": "Taylor Swift - The Eras Tour", "performer": "Taylor Swift", "date_time": "2024-08-15T19:00:00Z", "venue_name": "Wembley Stadium", "city": "London", "min_price": 345.5, "ticket_count": 412
| # | event_id | event_name | performer | category | date_time | venue_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Ticket Inventory objects from viagogo.com. All fields typed and schema-versioned.
"ticket_id": "T-998124", "section": "Block 102", "row": "G", "quantity_available": 2, "price_per_ticket": 450.0, "currency": "GBP", "delivery_method": "eTicket", "split_type": "Any"
| # | ticket_id | event_id | section | row | quantity_available | price_per_ticket |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Venue Data objects from viagogo.com. All fields typed and schema-versioned.
"venue_id": "V-8812", "venue_name": "Wembley Stadium", "city": "London", "country": "United Kingdom", "capacity": 90000, "general_admission": true, "total_sections": 142
| # | venue_id | venue_name | capacity | address | city | postal_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Tour Schedules objects from viagogo.com. All fields typed and schema-versioned.
"performer_id": "P-4491", "performer_name": "Coldplay", "genre": "Rock", "total_upcoming_events": 45, "tour_name": "Music of the Spheres", "countries_visited": 12, "min_tour_price": 85.0
| # | performer_id | performer_name | genre | total_upcoming_events | tour_name | start_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Market Analytics objects from viagogo.com. All fields typed and schema-versioned.
"event_id": "E-1508291", "timestamp": "2024-05-12T10:00:00Z", "total_listings": 156, "total_tickets": 412, "lowest_price": 345.5, "median_price": 650.0, "average_price": 712.25
| # | event_id | timestamp | total_listings | total_tickets | lowest_price | highest_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Viagogo scraper handles every layer of the ticketing platform: event schedules, dynamic pricing, seating charts, and seller restrictions — with virtual queue circumvention and anti-bot mitigation built in.
Extract performer, date, venue, and categorisation data across all global Viagogo domains.
Track real-time fluctuations in secondary market prices down to specific sections and rows.
Monitor exact ticket quantities remaining per listing and total capacity indicators.
Capture seating charts, section names, and general admission flags for global arenas and stadiums.
Extract base prices and converted currencies to normalise cross-border ticket arbitrage.
Identify eTicket vs physical delivery and age or ID restrictions on specific listings.
Differentiate between professional brokers and individual fans selling secondary tickets.
Aggregate entire global tour schedules for specific artists or sports franchises.
Run continuous diffs to flag newly added inventory or sudden price drops.
Bypass Viagogo's queue systems and CAPTCHAs using residential proxies and TLS spoofing.
Brief in. Clean data out.
Provide target artists, venues, or event categories. We design the extraction schema for ticketing data.
We configure Scrapy crawlers, residential proxy rotation, and CAPTCHA solvers to bypass Viagogo queue walls.
Schema validation, price-outlier detection, and currency normalisation checks before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Ticketing platforms invest heavily in scraping detection and virtual queues. Here's how we stay resilient — and why teams choose managed infrastructure over DIY.
Viagogo frequently employs virtual waiting rooms for high-demand events. We use session pre-warming and distributed proxy pools to bypass queues and extract inventory data directly.
Ticket prices and fees are calculated dynamically on the client side. We execute full Playwright sessions to render the final checkout prices, including hidden booking fees.
Viagogo alters inventory and pricing based on the visitor's IP location. We route requests through region-specific residential proxies to capture the exact local market view.
Ticketing sites use aggressive bot protection. Our infrastructure rotates ISP-grade IPs, spoofs TLS fingerprints, and resolves CAPTCHAs automatically via CapSolver.
Viagogo frequently updates its DOM to disrupt scrapers. We use fallback chains and structured JSON-LD extraction to ensure pipeline stability during layout changes.
Brokers monitor price spreads between primary ticketing platforms and Viagogo to identify arbitrage opportunities.
Promoters track secondary market demand to optimise primary ticket pricing for future tour dates.
Rival secondary marketplaces track Viagogo's inventory depth and fee structures to adjust their own platforms.
Clubs monitor season ticket resale volumes and pricing to assess fan engagement and adjust face-value tiers.
Hospitality and travel sectors correlate high-demand event pricing with local hotel and flight demand models.
Regulators and rights holders audit listings to detect scalping violations and enforce face-value resale caps.
"The secondary ticketing market operates on micro-fluctuations in demand. Without structured access to Viagogo's pricing telemetry, you are trading blind."
Scraping Viagogo requires bypassing aggressive anti-bot measures, virtual waiting rooms, and dynamic fee calculations. We handle the residential proxy rotation, JavaScript rendering, and queue circumvention, delivering clean ticketing data directly to your warehouse. You focus on price modelling, not pipeline maintenance.
Everything supported by our viagogo.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 executes JavaScript to resolve dynamic ticket prices and bypass ticketing queues.
We maintain pools of residential ISP proxies across global regions to bypass IP-based pricing discrimination and geo-blocks.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling for high-frequency price polling. State is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About viagogo.com scraping, legality, and pipeline operations.
Ask us directly →Scraping public event listings and prices is generally permissible under applicable law. DataFlirt extracts only public, non-authenticated data. We do not extract personal user data or bypass authenticated checkout flows. Clients must review Viagogo's ToS and consult legal counsel.
We utilise session pre-warming and distributed proxy pools to bypass queue systems, allowing us to extract ticket inventory without waiting in line.
Yes. We execute JavaScript to trigger the pricing calculation scripts, capturing both the base ticket price and the estimated booking and delivery fees.
Viagogo displays different prices and inventory based on the user's location. We use geo-targeted residential proxies to extract data from the perspective of specific countries.
For high-demand events, we can configure pipelines to poll inventory and prices at sub-15-minute intervals, delivering updates via Webhook.
Yes. We extract the section, row, and sometimes specific seat numbers provided by the seller, mapping them against the venue's total capacity.
Pipelines typically start at monitoring 1,000 active events or specific high-profile tours. Contact us to scope custom requirements based on your tracking volume.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off event dataset or a continuous price-monitoring feed across global tours — we scope, build, and operate the pipeline. Tell us what you need.
