Data Panda brings your Ticketmatic data together with the data from the rest of your venue. From one place, we turn it into dashboards, automations, AI workflows and custom apps your team uses every day.
Ticketmatic was founded in Leuven in 2007 by Erik Lesire and Bart De Man and has since grown into one of Europe's specialised ticketing platforms for the cultural sector. The product covers ticketing and e-commerce, audience CRM, event and seat-plan management, access control through a mobile scanner app, and marketing automation, all in one stack. Ticketmatic reports more than 300 cultural organisations on the platform, 16.5 million tickets sold and 8.7 million unique buyers in a year, with venues like Concertgebouw Brugge, VIERNULVIER, De Roma, De Grote Post and den Atelier among the named customers.
The point of pulling Ticketmatic into a warehouse is not that it lacks reporting. It is that the questions that move the needle for a venue tend to cross years and channels. Subscriber retention from one season to the next, the share of revenue that came in at full price versus discount, donation conversion per programme line, no-show rates by ticket type. Those answers live inside Ticketmatic in pieces; in a warehouse they sit beside your accounting, your email tool and your sponsor reporting, and they survive the next season switch.
One picture of every show, every channel and every season instead of season-bound exports.
Keep Ticketmatic in sync with the marketing, accounting and ops tools around it.
Turn ticketing history into forecasts and scoring that steer the next show, price or campaign.
Small internal tools on top of Ticketmatic data for people who should not be learning Ticketmatic.
A list of concrete reports, automations and AI features we have built on Ticketmatic data. Pick the one that matches your situation.
How many of last season's subscribers came back?
Subscribers from the previous season matched against this season's sales, by programme line and by venue. Shows the share that renewed, the share that bought single tickets only, and the share that disappeared, ranked by lost revenue.
What share of our revenue is at full price?
Sold tickets split by price type, per show and per venue, with discounts, vouchers and complimentary tickets called out separately. Lets the programmer see whether a show that looked sold-out paid for itself.
How many tickets are sold but not scanned?
Tickets with a sale but no scan event by the time the doors closed, per event, ticket type and channel. The number that backs the conversation about whether overbooking subscriber seats is safe.
Sold tickets per price type set against the receipts in your accounting tool, per show and per venue. The month-end reconciliation between Ticketmatic and the bookkeeper stops being a Friday-afternoon CSV exercise.
Subscriber lapse risk, first-timer conversion to a second show and donation propensity per segment. Email and ad audiences move into Mailchimp or Klaviyo on triggers, not on a manual export the day before send.
No-show rate per ticket type, scan throughput per gate, and sold-out alerts that reach the front-of-house team in Slack before the queue forms.
Subscribers, single-ticket buyers, lapsed donors and first-timers move from Ticketmatic into Mailchimp as live audiences. Open, click and unsubscribe events flow back, so the same person is not asked twice and the segment that is in season-launch mode is the one that receives the campaign.
Bought a ticket, attended, lapsed for a season or upgraded to a subscription each become Klaviyo events. Pre-show reminder, post-show survey, win-back and cross-sell flows fire on the actual ticketing reality, not on guessed list memberships.
Daily sales close in Ticketmatic lands as journal entries in Exact Online with the right VAT split per ticket type, per venue and per sales channel. Refunds, vouchers redeemed and complimentary tickets are coded so the bookkeeper does not have to disentangle them by hand.
Buyers, subscribers, members and donors land as HubSpot contacts and companies with their full ticketing history, last attendance and lifetime spend. The development team works sponsor and major-gift outreach from one timeline instead of asking the box office for a list.
Sold-out, low-stock, refund spikes, payment failures and big-group bookings post into the channel that the front-of-house, marketing or finance team already lives in. Cuts the lag between the event in Ticketmatic and the person who needs to act on it.
Each programmed event becomes a monday.com item with sales-to-date, capacity, venue and key dates. Programmers, communications and production work the same season board without anyone having to log into Ticketmatic to check the curve.
These are the 14 tables we currently pull from Ticketmatic 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 Ticketmatic 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.
We review your Ticketmatic setup and the systems around it. Together we pick the first thing worth building.