We extract primary ticket inventory, AXS Official Resale pricing, venue schedules, and seating availability. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery 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 Events & Tours objects from axs.com. All fields typed and schema-versioned.
"event_id": "E-48921", "title": "Fred again..", "venue_name": "Red Rocks Amphitheatre", "date_time": "2024-09-15T19:30:00Z", "status": "Active", "public_sale_date": "2024-04-12T10:00:00Z"
| # | event_id | title | artist | venue_name | venue_location | date_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Primary Ticketing objects from axs.com. All fields typed and schema-versioned.
"section": "General Admission", "ticket_type": "Standard", "price": 85.0, "currency": "USD", "fees": 18.5, "total_price": 103.5, "availability": "Low"
| # | event_id | section | row | seat | ticket_type | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for AXS Official Resale objects from axs.com. All fields typed and schema-versioned.
"listing_id": "RES-994821", "section": "Row 4, Sec 2", "quantity": 2, "price_per_ticket": 250.0, "currency": "USD", "seller_type": "Fan"
| # | listing_id | event_id | section | row | seat_start | seat_end |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Venues objects from axs.com. All fields typed and schema-versioned.
"venue_id": "V-102", "name": "Red Rocks Amphitheatre", "city": "Morrison", "state": "CO", "capacity": 9525, "timezone": "America/Denver"
| # | venue_id | name | city | state | country | capacity |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for VIP & Premium objects from axs.com. All fields typed and schema-versioned.
"package_id": "VIP-841", "name": "Soundcheck Experience", "price": 350.0, "currency": "USD", "includes_meet_greet": false, "includes_merch": true
| # | package_id | event_id | name | description | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our AXS scraper navigates virtual waiting rooms and bot protection to extract real-time inventory, dynamic pricing, and secondary market listings directly from the venue maps.
Crawl venue calendars and artist pages to detect newly announced shows before public sale windows open.
Extract standard ticket availability, tier pricing, and section-level capacity for active events.
Monitor secondary market pricing, ticket volumes, and seller competition on the official platform.
Track algorithmic price fluctuations on standard and premium tickets over time.
Map section and row data to specific seating charts for granular inventory analysis.
Extract details on VIP offerings, meet-and-greets, and bundled merchandise pricing.
Track presale windows, access requirements, and early inventory depletion.
Capture base price, service fees, facility charges, and total checkout price.
Scrape events across AXS US, UK, and Europe with localised currency and timezone standardisation.
Run hourly sweeps for high-demand events or daily syncs for long-tail inventory.
Brief in. Clean data out.
Provide venue lists, artist names, or specific event URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for axs.com.
Schema validation, null-rate checks, price-outlier detection, and seating logic tests before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
AXS invests heavily in ticketing bot mitigation. Here is how we stay resilient and maintain data flow.
AXS uses Queue-It virtual waiting rooms for high-demand on-sales. We manage session cookies and token generation to navigate queue systems reliably.
AXS heavily deploys anti-bot scripts. We use residential proxies and Playwright to spoof browser fingerprints and solve JavaScript challenges.
Seat availability is rendered via complex SVG maps and WebSocket feeds. We intercept the raw API responses feeding the seating chart.
AXS restricts access based on IP location. We route traffic through city-specific residential proxies matching the venue region.
For volatile resale markets, we maintain a hash index of active listings and emit only price changes or newly sold tickets.
Ticket brokers track primary availability and official resale prices to inform buying strategies.
Venues and promoters analyse pricing tiers and fee structures across competing events.
Pricing analysts correlate ticket velocity and resale volume with artist popularity for future tours.
Primary sellers monitor algorithmic price shifts on AXS to adjust their own inventory pricing.
Discovery platforms sync local venue schedules, artist dates, and ticket links for consumer apps.
Rights holders audit resale listings to detect speculative ticketing and terms-of-service violations.
"Ticketing data is highly volatile and aggressively protected. Capturing AXS inventory requires defeating waiting rooms and bot mitigation before you even see a price."
Most teams underestimate the investment required: reliable AXS scraping requires residential proxies, full JavaScript rendering for Queue-It waiting rooms, CAPTCHA handling, 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 axs.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 waiting room navigation.
We maintain pools of residential ISP proxies across US, UK, and EU regions. Rotation happens per-request with sticky sessions for queue persistence.
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 axs.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from AXS is generally permissible under applicable law, reinforced by the hiQ v. LinkedIn ruling. DataFlirt targets only public, non-authenticated event and pricing data. We do not extract personal data or circumvent authentication walls.
We manage session cookies, token generation, and residential IPs to navigate queue systems reliably without triggering bot defenses.
Yes, we capture section, row, quantity, and listed price for all resale inventory on the platform.
Pipelines can run hourly for high-demand shows or daily for long-tail inventory. Real-time limits apply based on bot protection and queue systems.
We extract both the base ticket price and the itemised fee structure to calculate the total checkout price.
We support axs.com US, axs.co.uk, and European variants, standardising currency and timezones across all datasets.
No. We only scrape public presale schedules, not the gated inventory requiring specific fan club or credit card codes.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need venue schedules or continuous price monitoring across high-demand tours, we scope, build, and operate the pipeline. Tell us what you need.
