No-show pattern report by price tier and channel
Problem
Every matchday, the gap between tickets sold and people who actually turn up costs revenue and nobody currently reports on it beyond a shrug about how a stand looked emptier than expected. The ticketing platform shows total scans against total sales, but no breakdown by price tier, purchase channel or day of week exists anywhere. When someone wants that answer, usually a marketing manager preparing a renewal push, it means pulling the gate scan file from the ticketing platform, pulling a segment list from the CRM, and pivoting the two together in a spreadsheet rebuilt from scratch most weeks. By the time that pivot is finished, the pattern it shows is already two matches old.
Product idea
A scheduled report that joins gate scan data against ticket sales for each fixture, broken down by price tier, purchase channel and day of week, and tracks how the no-show rate for each segment moves across the season rather than showing one match in isolation. It flags segments where the no-show rate is climbing before the pattern is visible at the turnstile, and produces an exportable list of the accounts behind a flagged segment so a renewal or win-back campaign can be built against it directly. It does not attempt to explain why a segment is no-showing: it excludes weather and fixture-importance scoring, and leaves that interpretation to the person who knows the calendar.
Who it is for
Marketing managers building renewal and win-back campaigns, CRM managers who currently rebuild this comparison by hand, and heads of fan engagement who want segment-level attendance trends without commissioning a one-off analysis.
Possible first version
A weekly scheduled report built from two uploaded exports, a gate scan file and a ticket sales file, joined against CRM segment tags supplied as a CSV. It produces a breakdown table by price tier and channel, a trend view of the no-show rate across the season to date, and a flagged-segment list with the underlying account records available as a CSV download. There is no live connection to the ticketing platform or the CRM in version one. Both are manual exports, and the report does not trigger any campaign itself: it only prepares the list for someone else to send.
- Build classification
- Workflow application
- Rough effort
- 4-6 week first release
- Roles involved
- Marketing manager, CRM manager, Head of fan engagement
- Relevant to
- Professional club, League office, Women's league, Venue & stadium operator
- Systems in play
- Ticketing systems, CRM platforms, Spreadsheets
- Product framing
- Analyse data
Questions we get asked
What data do we actually need before this produces anything useful?
A gate scan export and a ticket sales export from the ticketing platform, both usually available as CSV, plus a CRM segment or channel tag for each account. Two matches of data will produce a breakdown table. The trend view and the flagged-segment logic need a full season or close to it, because a single low-turnout match on its own does not tell you whether a segment's no-show rate is rising or whether the weather was bad that day.
Does this replace the reporting built into our ticketing platform?
No. The ticketing platform's own reporting is built for operational questions at the gate: how many have scanned, how many are still outside. This report answers a different question, which segment of supporters is quietly stopping coming, and it needs the CRM's segment and channel data to do that. It sits alongside the ticketing platform's reporting rather than replacing any part of it.
We already reconcile scans against sales in a spreadsheet after every match. Why would we need this?
If that spreadsheet already tracks segment-level no-show rates across a full season and someone keeps it updated every week without fail, you probably do not need this. What a one-off pivot usually cannot hold is the trend: whether a channel's no-show rate has moved over ten matches, not one. This is only worth building if that comparison currently gets thrown away and rebuilt each time rather than kept.
Who is responsible for this once it exists?
Ownership usually sits with the marketing manager or CRM manager who acts on the flagged list, deciding what a renewal or win-back campaign looks like for each segment. The report is only as good as the exports feeding it, so someone in ticketing operations needs to keep producing the gate scan file on a reliable schedule, or the trend line develops gaps that make it unreliable.
Is this your workflow?
Tell us one sports workflow that still runs on paper, spreadsheets, WhatsApp or an outdated system. We will map it and show you what a simpler product looks like.
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