How we turned global basketball data into a subscriber growth engine across 61 countries.
NBA League Pass had a global audience problem. Not a lack of fans — the NBA had those. The problem was converting them: knowing which markets were underpriced, which content was driving subscriptions versus churn, and where paid media dollars were generating returns versus getting wasted on already-converted fans.
The data existed. It was scattered across consumption platforms, broadcast rights databases, social media affinity signals, and pricing records across dozens of markets. Nobody had connected it.
League Pass needed to go from gut-feel market decisions to a systematic, data-driven growth model — one that worked across 61 focus countries, in different languages, different price sensitivities, and radically different competitive conditions.
Ingested first-party consumption data, third-party audience signals, broadcast deal structures, social affinity data, and historical pricing across every target market into a single decisioning model. For the first time, all the signal lived in one place.
The model scored each of the 61 focus countries across growth potential, pricing elasticity, content affinity, and paid media efficiency — producing a ranked action plan updated every season. Not a spreadsheet. A live system.
Recommendations from the model fed directly into media buying, product pricing, and content prioritization. No insight sat in a deck — it drove action. The distance between analysis and execution was measured in hours, not quarters.
Now in its fourth year of use, the model incorporates performance feedback loops so each season's results improve the next season's predictions. Every outcome sharpens the next decision.
"The model doesn't just tell you what happened. It tells you what to do next — in which market, at which price, with which content."
— From The Future · NBA League Pass Engagement
We build the models, connect the data, and drive the decisions. If you want strategy that compounds — let's talk.
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