Pass completers vs quitters: LTV split for UA bid models
Treating all pass buyers as equal overstates late-season ROAS. Split completers vs quitters with cohort IAE metrics — synthetic lab.
Treating every battle-pass buyer as the same bidder signal overstates late-season ROAS. Completers and quitters diverge on subsequent IAP.
Metric definitions
AppsFlyer Cohort (source read 20 September 2026) exposes in-app event unique users and IAE revenue on cumulative or on-day bases, plus ARPU as revenue / unique users. Map at least two studio events: pass_purchase and pass_complete (or final-track claim). Quitters are pass purchasers who never fire complete by season end.
Illustrative split
Season cohort of pass buyers (teaching only):
| Segment | Users | D30 revenue after pass buy | ARPU |
|---|---|---|---|
| Completers | 600 | 18,000 | 30.00 |
| Quitters | 400 | 4,000 | 10.00 |
| Blended (all pass buyers) | 1,000 | 22,000 | 22.00 |
A bid model that uses blended 22 ARPU for late-season pass buyers will over-pay if the mix shifts toward quitters. Feed completer rate by media source before scaling.
Facts vs limits
| Fact | Limit |
|---|---|
| IAE unique users and revenue are documented | Completer event taxonomy is studio-defined |
| Synthetic ARPU split is labelled | No genre completer rate is claimed |
| Cumulative vs on-day must be stated | SKAN cannot natively carry this split |
