Keynote: Scale Your IAPs With Purchase Behavior Targeting Data Insights
summary
A payments-processing company offers first-party purchase behavior targeting that sidesteps IDFA and cookies by matching on phone numbers, claiming high match rates to social platforms. Benchmarks show 95% of players never pay while ~5% drive >80% of revenue. Case results include 3.9x ROAS and 3.6x LTV for NEXON, 95% higher ROAS with Upland plus 37% lower CPA, and a social casino seeing 50% higher day‑7 ROAS and 2x lifetime value.
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chapters (12)
- 0:00Introduction
- 0:47Talk overview
- 3:18IDFA and cookie deprecation impact
- 6:43Compliant targeting data need
- 8:08Bango purchase data processing
- 9:12Targeting users who pay in similar apps
- 10:59Finding new players via payer overlap
- 12:48High LTV payment behaviors
- 13:49Layering targeting strategies
- 15:33Social platform performance insights
- 17:21Purchase behavior targeting benefits
- 18:23Q&A
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