Unifying fan data across 50+ sports organizations into a single platform

Sports organizations operate across fragmented data silos. A single fan might hold a season ticket, buy merchandise, attend events, interact via mobile app, sign up to newsletters, engage on social media, and visit the stadium concourse — each touchpoint scattered across ticketing systems, e-commerce platforms, CRMs, POS systems, and social networks. Marketing teams make decisions on incomplete profiles. Revenue teams miss cross-sell opportunities. Broadcasters and sponsors have no unified view of audience overlap.

When Datatalks started, the industry had no answer. Every organization built custom integrations and manual reconciliation workflows. Twistag saw the pattern repeating across European football, rugby, hockey, and golf — and recognized it was a platform problem, not a services problem.

What we learned

We built Datatalks as a unified data backbone for sports organizations. The architecture starts with an extensible integration layer that speaks 50+ protocols — everything from ticketing APIs to POS terminals to social media webhooks. Each connector normalizes data into a shared schema without forcing sources to change. Raw events flow into our identity resolution engine, which matches a fan across data sources even when systems record them differently (email vs. phone vs. social handle). The result is a single unified profile per fan.

On top of unified profiles sits the visual segment builder, where non-technical marketers define audience segments using a point-and-click interface. The Segmentation Assistant layer goes further — it reads natural-language segment goals (like "high-value lapsed fans likely to renew") and suggests segment logic from the available data, powered by LLM analysis. We designed multi-provider model orchestration to handle this cost-effectively: simple segment suggestions use smaller, cheaper models; complex customer journey analysis runs on our flagship LLM. Dattie, our autonomous AI assistant, lets analysts ask natural-language questions about their data without writing SQL. These features reduce time-to-insight from days to minutes.

The platform runs on .NET for the backend, Blazor for the frontend, and AWS for infrastructure. Role-based access controls enforce multi-tenant boundaries — individual clubs, national federations, and entire leagues can all operate on the platform simultaneously with complete data isolation.

What this shaped

Datatalks shifted from custom consulting to a repeatable platform product. The platform now serves 50+ sports organizations across multiple countries, unifying 6+ million fan profiles. Adoption has expanded from football into rugby, hockey, and golf — the platform's architecture proved portable because Twistag solved the data unification problem generically, not sport-specifically.

The shift to product also shifted the partnership with Twistag. Early on, we staffed sprints and built features to order. Over six years, that evolved into a continuous engineering partnership where we ship AI capabilities, improve identity resolution accuracy, and expand the integration network without either team thinking of the other as a vendor. When the platform shipped AI features, we had a team that understood the product roadmap deeply enough to architect for them at the infrastructure level — not retrofit them later.

What this proved