Case study · League-scale fan data
How a league unified fan identity, consent and data standards across 32 independently owned clubs without taking their activation away from them. The hard part was never the technology.
32
Club stacks, one model
A harmonised data model connecting the league's stack with those of all 32 clubs, giving one view of the fan across web, app, stadium and partner channels.
60%
Fan overlap across clubs
The share of fans who appear in more than one club's records, as stated publicly by the league. Identity resolution was never optional.
30%
Less over-communication
The reduction in duplicate and conflicting messages across teams once one profile governed the send.
544
Game-day sends, minimum
272 regular-season games, two clubs each, before any other outreach. The volume that makes a shared cadence rule necessary.
Thirty-two clubs, each a separate business with its own owner, its own stack and its own view of who its fans are. Six in ten of those fans sit in more than one club's records. Every club, and the league, wanted to talk to them on the same days. A platform cannot settle that. An agreement can.
The first artefact was a charter, not a contract: what a fan record is, which entity owns it, which purposes it may be used for, and who may act on it. Privacy, consent, data standards and cross-club integration were written down and signed before any pipe was built. Thirty-two independent commercial entities agreed the nouns first.
My part
Authored the enterprise governance framework and the club-facing standards that sat under it.
The league resolves identity and sets the standards. Each club keeps its own activation: its journeys, its tone, its commercial decisions. Nothing central sends on a club's behalf, and nothing at a club breaks the shared model. That split is what makes competing entities willing to share.
My part
Modernised the Connected Identity and data platforms, with club toolkits and executive readouts that moved adoption from the pilot clubs to the whole league.
Rather than one platform for everyone, a common model that each club's existing stack maps into. The hard integration work is done once, at the model, and the clubs keep the tools their teams already run. A cadence rule across all senders then becomes enforceable, which is where the over-communication number comes from.
My part
Ran the business relationship and product layer between the league's data and marketing-technology teams and the 32 clubs through the rollout.
The league's own summary of the operating rule is worth keeping: the system reads the signal, and humans decide the play. The model tells a club what it knows about a fan today. The club decides what, if anything, to do about it.
The same three decisions, in the same order. Charter, then federated identity, then a clean room in place of file exchange.
The league archetypeA federation in miniature. One data model, per-club tenancy, consent by jurisdiction, and group analytics on aggregates rather than shared fan records.
The ownership-group archetypeKnow what the league already holds about your fans and what you may use. Build the club-owned anchor so you are a tenant by choice, not by default.
The established club archetypeA working version of the tenant split, where a club, a brand and a league each see a different cut of the same session, runs in the Studio on synthetic data.
The figures above are the league's own published numbers. The account of the three decisions and the architecture is mine, from the inside of the programme, and it names no club-level data, no contract terms and no vendor configuration.
I ran the business relationship and marketing-technology product function for the programme. I did not build it alone, and the clubs did the activation work that produced the results. Where I describe my part, it is the part I would defend in a room with the people who were there.
If this is your problem
A first call is fifteen minutes and needs no preparation. Bring the number of entities that have to agree, and I will tell you where it usually breaks.