Attributing real-world outcomes to sponsorships
summary
Claims a platform that ties sponsorships to real outcomes by matching rights-holder PII, location and TV exposure, and transaction data via partners like Reveal Mobile, Kinetic, Fiserv, Experian and LiveRamp. Builds audiences from Twitter and Twitch, runs one-to-one and cohort controls, and reports 14% sales lift examples, portfolio-level 3.2% assisted revenue ($59.1M) and 4.8M transactions from 40M matched fans (8.2M customers). Uses t-tests and confidence scores (85–95%), a three-party matching model for privacy, and a GCP/BigQuery ETL stack.
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chapters (9)
- 0:00Start
- 3:32Attribution: What is it?
- 5:46Goal 1: Brand Affinity Lift
- 8:25How are fans actually spending at a Brand?
- 13:093-Party Matching Model
- 23:021:1 Control Group Methodology
- 26:51Confidence scoring is key...
- 29:02What is acceptable confidence?
- 35:47In Summary...
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