Data Panda brings your Ticketmaster events, orders and inventory together with the rest of your event business. From one place, we turn it into dashboards, automations, AI workflows and custom apps your promoters, marketing and finance teams use every day.
Ticketmaster started in Phoenix, Arizona in 1976 and merged with Live Nation in 2010 to form Live Nation Entertainment. It is the dominant ticketing platform worldwide for arenas, theatres, sports leagues and festivals, running both the primary sale and a large slice of the resale market through TicketWeb and TicketExchange.
For promoters and venues, the working surface is TM1: TM1 Events to build the show, TM1 Sales for the box office, TM1 Entry for the door, TM1 Reports for the after-action. The Partner API exposes what TM1 sees: events the partner has listed, the live availability per allocation, enriched event metadata and the orders that haven't been redeemed yet. Pulling that into a warehouse is how sell-through against capacity, channel mix per event, and the gap between tickets sold and tickets scanned at the door stop being three different exports stitched together the morning after.
Sell-through, pacing and channel mix per event in one place, across every show in your roster.
Turn event and order events into the bookings, emails and CRM updates your team would otherwise do by hand.
Use your event, availability and order history to forecast demand and shape pricing windows.
Small promoter and venue tools that sit on Ticketmaster data instead of yet another export.
A list of concrete reports, automations and AI features we have built on Ticketmaster data. Pick the one that matches your situation.
How is the next show pacing against the same week last tour?
Daily pickup per event, plotted against the pacing curve of the same show on the previous tour and the budget for this run, broken down by allocation and price tier. Promoters spot a slow city in time to move a price tier or open up a hold, instead of finding out on settlement night.
What is the gap between tickets sold and tickets that walked in?
Sold figures from the partner orders feed, joined to the unredeemed-orders table close to door time and the scan data after the show. The no-show percentage per event, genre and venue stops being a hunch and becomes a number that drives the next on-sale and the next ad budget.
Which buyers should we email about the next show in this venue?
Attended-buyer rosters per event, joined to genre, venue and repeat history across the season. Marketing builds a list of people who turned up to a comparable show, with the right consent, instead of blasting every order from the last twelve months.
Ticket revenue per show, settlement-ready, with the partner order detail to back it. Fees, refunds and unredeemed orders are visible per event so the cash position before settlement night is no longer a TM1 Reports export plus a spreadsheet.
Promoter, agent and sponsor performance across the season in one view: which acts, which venues and which markets delivered the sell-through. The next on-sale conversation runs on numbers from the warehouse, not on what last week's recap said.
Pacing, channel mix and unredeemed orders per show, side by side with the door scan. Production teams see where attendance is drifting from the manifest in time to staff the right gates and call the right shuttles.
Attended-buyer rosters from Ticketmaster land in Klaviyo segmented by event, genre and venue, with consent flags preserved. The thank-you mail for last night's show goes out by lunchtime, the next-on-sale teaser goes only to people who turned up, and the no-show segment gets a different message instead of being lumped in with the rest.
Partner-order detail and attendance flags from Ticketmaster flow into HubSpot as contacts and timeline activity, with genre, venue, repeat-attendance and lead-time per event attached. Sales and partnerships work the buyer base on real stay patterns instead of a CSV pulled the day before a sponsor pitch.
Ticket revenue, fees and refunds per event from the partner-orders feed land in Exact Online as the right journal entries, split per show and per venue. Settlement night stops being a manual reclass, and the monthly P&L per tour or per venue is in the ledger by the time finance opens it.
GA4 sessions and campaign parameters from the on-sale page are joined to the confirmed Ticketmaster orders they produced, including refunds and no-shows. Marketing sees which campaigns brought in real paying attendees rather than checkout starts, and ad spend per show gets a real ROI number next to it.
These are the 4 tables we currently pull from Ticketmaster into your warehouse. Query them directly in SQL, join them to the rest of your stack, or build reports on top.
Missing a table you need? We can extend the sync. Tell us what is missing and we will build it for you.
You keep the reporting tool you already have. We connect it to the warehouse where your Ticketmaster data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
The connector reads through Ticketmaster's Partner API, which means you get the events you have been listed on as a partner, the live availability per allocation, the enriched event metadata and the partner orders that haven't been redeemed yet. The public Discovery API view of every event in the catalog is not the same dataset, and Partner API access is gated on a relationship with Ticketmaster. If you don't have partner credentials, the connector won't fill.
Partner orders cover the sale you are entitled to as the partner. Resale through TicketWeb or TicketExchange follows a separate access model and is not part of the partner orders feed by default. If your partnership covers resale visibility, the same warehouse pattern can read it; if it doesn't, the resale gap is honest and visible in the model rather than hidden.
The Partner Orders Unredeemed table gives you the orders that are still open, which is the inverse of what was scanned. Joined to the orders feed and the door scan extract, you get a per-event sold-versus-attended ratio. It's the closest a warehouse can get to a real attendance number without a separate scan integration on top.
We review your Ticketmaster setup and the systems around it. Together we pick the first thing worth building.