Data Panda brings your Paylogic Reporting data together with the data from the rest of your festival or event organisation. From one place, we turn it into dashboards, automations, AI workflows and custom apps your ticketing, marketing and finance teams use every day.
Paylogic is the white-label ticketing platform many Dutch and European festival and event organisers run their sales on, part of the CTS Eventim group since 2024. Paylogic Reporting is its reporting layer: the Back Office reports and the reporting dashboard where an organiser downloads sales and financial data and compares how events perform. Ticket sales per event and per type, revenue, refunds and the financial reports the settlement is built on all live here.
Inside the Back Office those numbers sit per event, and every comparison starts with a download. In a warehouse they become one table: editions side by side, sales pace against the same point last year, and the official ticketing figures joined to your ad spend, your ledger and your on-site systems. The numbers you report to partners and bookkeepers stop living in a folder of exports.
Sales and revenue per event, edition and channel in one view, instead of one download per question.
Let the official ticketing numbers drive the routines your team now runs by hand.
Use sales history across editions to forecast demand and time the next announcement.
Small tools on the official sales numbers for people who never open the Back Office.
A list of concrete reports, automations and AI features we have built on Paylogic Reporting data. Pick the one that matches your situation.
Which events are behind on sales pace, this week?
Tickets sold per day per event, plotted against the same point relative to the show last edition, across the whole portfolio at once. The event that is quietly lagging its curve surfaces while there is still budget and calendar left to move, instead of in the post-mortem.
What did each edition actually return, after refunds?
Revenue per event with refunds and ticket mix broken out, lined up edition against edition. The management meeting compares like with like: the same event, the same week relative to the show, the same definitions, rather than three differently filtered downloads.
Which sales channel fills the room?
Sales split between your own shop and partner outlets per event and ticket type, over time. It shows which channel sells the early tickets, which one clears the last rows, and where a partner fee buys volume you would have sold anyway.
Revenue, refunds and VAT per event and period from the official reports, lined up against the ledger and the settlement. The event close runs on numbers that match what the platform reports, without rebuilding them from downloads.
Channel and outlet performance per event, and partner reports that are current instead of quarterly. Renewal talks with outlets and promoters start from what each channel actually sold.
Capacity sold per event in the run-up to the date, with pace alerts when an on-sale stalls. Staffing, site and supplier decisions follow the sales curve instead of the gut feel of the busiest week.
Sales and VAT totals per event and period flow from the Paylogic reports into Exact Online as journal entries, with refunds as their own lines. Finance closes the event period on the same numbers the platform reports, instead of retyping a downloaded financial report.
Daily ad spend per campaign lands next to tickets sold per event and ticket type. Marketing sees which campaign moved the curve and which one ran while sales stood still, and shifts budget mid-flight instead of at the campaign review.
Meta campaign spend and reach per day line up against the sales curve per event, so announcement posts, retargeting flights and line-up drops each get credited with the jump they produced. The next on-sale plan is built on which flight moved tickets, not on which one had the best click price.
Every morning the team channel gets tickets sold yesterday, pace against last edition and capacity left, per event. The whole organisation reads the same number at the same moment, and the question "how are we selling?" stops interrupting the ticketing team.
You keep the reporting tool you already have. We connect it to the warehouse where your Paylogic Reporting 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.
Paylogic Shopping is the storefront and order layer: order-level data with every product, ticket and consumer on it. Paylogic Reporting covers the reporting side of the Back Office: the sales and financial figures an organiser reports on. Organisations that run their own storefront integration typically use both; if you mainly work from the Back Office reports, the Reporting connector is the one you need.
Yes. In the warehouse we add a mapping that groups the editions of the same festival or show, so this year lines up against last year by days-before-show rather than by calendar date. That mapping is yours: one-off events, name changes and venue moves are handled in the model, not lost in a spreadsheet.
We review your Paylogic Reporting setup and the systems around it. Together we pick the first thing worth building.