Fan Engagement Analytics
Fan Engagement Analytics is the use of data and advanced analytics to build a unified, granular understanding of sports and esports fans across digital, social, and in-venue touchpoints. It aggregates signals such as ticketing data, app and web behavior, social interactions, content consumption, and in-stadium activity into a single fan profile and segmentation model. On top of this unified view, organizations can predict engagement, propensity to buy tickets or merchandise, churn risk, and content preferences. This application matters because sports and esports properties increasingly depend on direct fan relationships for revenue growth—across tickets, subscriptions, merchandise, and sponsorships. By turning fragmented fan data into actionable intelligence, clubs, leagues, and rights holders can personalize marketing, optimize game-day experiences, and offer more precise audience targeting to sponsors. AI is used to build predictive models, recommend next-best actions, and dynamically segment fans so that every interaction—digital or physical—can be tuned to maximize engagement, loyalty, and commercial return.
The Problem
“Unify fan data into segments and predictive scores for ticket, merch, and retention growth”
Organizations face these key challenges:
Fan data lives in silos (ticketing, app/web, social, email) with no consistent fan identity
Campaign targeting relies on broad segments and gut feel; ROI is hard to prove