IsCool: do not let purchase revenue stand in for a hybrid game's value

IsCool's historical ad-revenue case illustrates a measurement decision that remains worth examining: which revenue streams are present when a team ranks acquisition sources?

What the public case establishes

Adjust's IsCool Entertainment case describes combining impression-level advertising revenue with in-app purchase data to evaluate acquisition. The historical implementation referenced MoPub. The account says more granular revenue helped the publisher distinguish valuable users and adjust spending; it does not provide independent campaign-level causal evidence. Adjust case study.

This debrief analyses a public customer case published by a commercial supplier. It is not an original UA Ledger interview. The chronology below follows the supplier’s account; we did not inspect the advertiser’s dashboards or interview its staff.

The decision worth examining

If a game earns money through both ads and purchases, an IAP-only ranking can favour the wrong source even when the arithmetic is flawless. The omission is a business-model choice disguised as a reporting convenience. Adding ad revenue is not enough unless the team also defines when it becomes available, whether values are estimates, and how later adjustments enter historical cohorts.

The worksheet separates purchase revenue, advertising revenue and unresolved revenue rather than merging them immediately into one opaque LTV field. That lets an analyst explain whether a ranking changed because players behaved differently or because a data stream arrived late. It also prevents the updated report from rewriting the evidence available during an earlier budget decision.

A usable next check

Take a permitted internal cohort and calculate its ranking using purchase revenue alone, then using reconciled hybrid revenue at the same cohort age. Preserve both results and record the data cut-off. If advertising data changes after that cut-off, issue a new version instead of quietly replacing the old result. Use the exercise to identify decisions sensitive to missing revenue.

Download the populated case worksheet. Its control, variant and decision rules are a proposed experiment, not an account of results already measured. Keep the source URL with the worksheet when circulating it so reported findings cannot become unattributed team benchmarks.

Evidence boundary

MoPub is named only as part of the historical source account, not as current implementation guidance. No universal ad-revenue share or profitability gain is inferred, and no advertiser dataset was inspected for this draft.

For background, see reading an mmp dashboard without fooling yourself and cohort quality checklist ua spend. These are existing archive discussions, not independent certification of this case. No first-hand campaign result is asserted.