How the CFL unified fan identities across 9 teams, multiple channels, and years of fragmented data, resolving 15% of records that would otherwise go permanently unmatched.
"We've seen those positive results, going from over 24 hours to less than 20 minutes. I think about simplicity, cost, and scalability and Zingg checks all three."
Dave Musambi, Senior Director, Business Intelligence
Canadian Football League
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The Canadian Football League manages fan relationships across 9 teams and multiple digital touchpoints, online, in-store, by phone, and at stadiums. Each interaction generated its own record, in its own format, with no shared identifier. The data team had a Snowflake warehouse and one clear goal: understand every fan as one person, across every channel.
Fan profiles were fragmented by email variations, name spellings, and years of siloed data across teams. Building deterministic rules to unify them would have required enormous manual effort, and would still miss the fuzzy matches that made up the bulk of duplicates. The solution also had to run natively inside Snowflake: no external clusters, no data movement, no maintenance overhead.
The CFL adopted Zingg Enterprise on Snowflake, normalising fan data from all 9 teams into a clean layer before training began. From there, the resolution pipeline ran entirely inside Snowflake, with no data movement and no external clusters.
Dave Musambi, Senior Director, Business Intelligence
Canadian Football League
See how Zingg runs natively on Snowflake — no cluster management, no data movement, no preprocessing overhead.
See how it works →
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