Show what an IAP-only ROAS leaves out of a hybrid cohort
A hybrid game can earn purchase and advertising revenue, but a report may include only one stream. A reproducible illustrative example with editable inputs and explicit limits.
A hybrid game can earn purchase and advertising revenue, but a report may include only one stream. This lab reconciles two non-overlapping revenue streams against the same acquisition spend. It shows a scope difference without claiming that either stream is incremental.
Define the calculation before using it
Confirm that the purchase and advertising values represent the same install cohort and observation horizon. Add them only after documenting currency, deductions and whether one source already includes the other. Calculate the purchase-only and combined ratios against identical spend. A stream missing from an export should remain unknown until its coverage is established, not silently zero.
Work through the synthetic example
The teaching example has 3,000 in purchase revenue and 2,000 in ad revenue against 10,000 of spend. Purchase-only ROAS is 30%, while the combined ratio is 50%; advertising supplies 40% of the measured revenue total. These are arithmetic consequences of invented inputs, not a benchmark for hybrid games.
| Output | Worked-example result |
|---|---|
| Purchase-only ROAS % | 30.0000 |
| Combined ROAS % | 50.0000 |
| Ad share of revenue % | 40.0000 |
Use the artifact and preserve its assumptions
Open the editable calculator to change the inputs and inspect the sensitivity view. The CSV records synthetic inputs and expected outputs; the JSON fixture keeps the equations available for reproduction. These calculations have been checked against the stated example. No measured campaign data is included.
The sensitivity rows vary only ads by 20% below and above the entered value. They are scenarios, not confidence limits or a forecast distribution. A row outside the model’s constraints is labelled rather than turned into a plausible-looking result. Save the chosen inputs with the decision so another reader can distinguish a changed assumption from a changed formula.
Evidence and limits
Google’s export schema separates the reporting date, UTC timestamp and event parameters. The worksheet uses simplified aggregate inputs; it does not claim that an export already contains a correctly reconciled cohort. See Google Analytics BigQuery Export schema, especially “event_date, event_timestamp, event_value_in_usd and event_params fields”.
Ad-revenue precision, payout timing and cohort allocation are not verified. The combined figure is still revenue divided by spend, not profit, cash recovery or a causal estimate of advertising value.
Background: UA metrics explained: CPI, ROAS, LTV and payback and Reading an MMP dashboard without fooling yourself. These existing articles provide context; the present calculation does not verify every archived claim.
