Membership renewal pricing scenario tool
Problem
Each year the season membership price is set in a meeting where the head of fan engagement, the CRM manager and a finance lead argue over a percentage increase, working from a spreadsheet built by whoever built it last year. The starting point is usually last year's revenue target divided by the current member count, adjusted by gut feel about what supporters will tolerate. Nobody in the room can say what a two-tier price increase versus a flat rise across all tiers would actually do to renewal count, because the renewal history sits in a CRM export as one long list, not broken down by tier or tenure. The price sheet goes to print, renewals open, and the consequence of the guess is not visible until the window closes months later.
Product idea
A scenario tool for the pricing meeting itself. Upload last season's renewal file (tier, price paid, tenure, renewed or not) and set a small number of levers: a price change by tier, a benefit added or removed, an early-bird discount window. For each lever, enter an assumed renewal sensitivity per segment, whatever the room believes members in that tier will tolerate, and the tool recalculates projected renewal count and revenue against the current baseline. Run two or three scenarios side by side rather than one spreadsheet formula at a time. It does not predict behaviour: the sensitivity assumption comes from the people in the room, not from a model, and the tool exists to make the arithmetic of that assumption visible and comparable, not to replace the judgement behind it.
Who it is for
CRM managers and heads of fan engagement who build the renewal price sheet, typically sponsored by the commercial or finance lead who has to sign off the final number before it goes to print.
Possible first version
A web app that takes an uploaded CSV of last season's membership base (tier, price, tenure, renewed flag), lets the user set a price change and a renewal sensitivity assumption per tier, and shows projected member count and revenue against the current baseline. Up to three scenarios can be saved and compared side by side, with a CSV or PDF export for the pricing meeting. Out of scope for version one: any live connection to the CRM or ticketing system, automatic calculation of renewal sensitivity from historical data, and modelling of any lever beyond price, benefits and early-bird timing.
- Build classification
- Micro-tool
- Rough effort
- 2 week prototype
- Roles involved
- CRM manager, Head of fan engagement, Marketing manager
- Relevant to
- Professional club, League office, Women's league, Venue & stadium operator
- Systems in play
- CRM platforms, Ticketing systems, Spreadsheets
- Product framing
- Test or simulate
Questions we get asked
What data do we actually need to load before this is useful?
A single export from your CRM or ticketing system covering last season's membership base: tier, price paid, tenure and whether each member renewed. If that export does not exist as one file today, that is worth knowing before the build starts, because assembling it is the first real piece of work, not the tool itself. No live connection is needed and none is built in version one.
We already do this in a spreadsheet the week before the pricing meeting. Why change that?
If that spreadsheet already lets everyone in the room change an assumption and see the tier-by-tier consequence live, there is little reason to replace it. In practice the spreadsheet is usually built and understood by one person, gets rebuilt from scratch each year, and breaks under a question nobody anticipated. This puts the same arithmetic in a shared tool that survives the meeting and the person who built it moving on.
Does this pull live numbers from our CRM or ticketing platform?
No. It works from a file exported before the meeting, not a live connection. That is deliberate for version one: a live feed adds integration work that is not needed to test whether the scenario view itself changes how the pricing conversation goes. If the tool proves useful, a scheduled export is a reasonable next step, but it is not in scope now.
Does it predict how members will actually respond to a price change?
No, and it should not be read that way. The renewal sensitivity for each tier is an assumption the room enters, not a forecast the tool produces. What it does is recalculate the member count and revenue consequence of that assumption instantly and consistently across scenarios, so the argument in the room is about the assumption itself rather than about whose spreadsheet formula is right.
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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