What Conversion Value Mapping Is
Conversion value mapping is the rulebook behind Apple's privacy-preserving iOS attribution. SKAdNetwork and AdAttributionKit let an app report one fine conversion value from 0 to 63 and one coarse conversion value of low, medium or high per window. Apple does not care what those numbers mean. The mapping is where the advertiser decides.
A good mapping is short enough to fit in the space Apple allows, ordered so that higher values mean better users, and built from events that actually happen inside the measurement windows. A weak one encodes events most users never reach in time, so most installs report the same value and the signal disappears.
The Building Blocks
Every mapping is made of four decisions:
- Events. Which in-app actions count: registration, tutorial complete, trial start, add to cart, first purchase, a level reached.
- Priority. When a user does several mapped events, which one sets the value. Usually the event closest to revenue wins.
- Revenue ranges. Which purchase or subscription amounts fall into which value, so value-based bidding gets a revenue signal.
- Windows. What the fine value captures in days 0 to 2, and what the coarse values capture in days 3 to 7 and 8 to 35.
Common Mapping Patterns
Funnel mapping gives each value to a step in the onboarding or activation funnel. It works when revenue comes late, as in many subscription and fintech apps, because the network still learns which campaigns bring users who progress.
Revenue mapping splits the 64 values into revenue ranges. It suits shopping, food delivery and games with early in-app purchases, where first-session revenue is common and predicts long-term value.
Hybrid mapping uses low values for funnel events and high values for revenue ranges. Most mature apps end up here, because it gives non-paying users a signal without wasting the top of the range.
For coarse values, mirror the same logic in three levels. Low for basic engagement, medium for strong intent, high for revenue. In the second and third windows, use coarse values for slower signals such as trial-to-paid conversion or repeat purchases.
Designing for Ad Networks
Ad networks read conversion values directly, and the two largest have their own expectations. Google and Meta each support conversion value schemas for SKAN campaigns, and each needs the mapping shared in the format it understands so its bidding can tell good installs from weak ones. Keeping one mapping and translating it per network is easier to maintain than separate mappings that drift apart.
Check three things before you ship a mapping:
- Most installs should not land on a single value. If 80% report 0 or 1, the events are too late or too rare.
- Higher values should mean better users in your own data, such as higher D30 revenue.
- The SDK should write values for every mapped event on a real device, which you can confirm with a test build before launch.
Conversion Value Mapping in Linkrunner
In Linkrunner, you set the mapping once in the dashboard: choose the events, set their priority and define revenue ranges. Linkrunner generates the fine and coarse values for Google and Meta from those rules, with setup guides for Google and Meta SKAN campaigns. The iOS SDK writes the values as users complete events, through SKAdNetwork and, on iOS 17.4 and later, through AdAttributionKit.
The SKAN dashboard then decodes postbacks back into those events and revenue ranges, so a campaign review shows which campaigns drove registrations, purchases or revenue rather than a list of raw numbers.
Mistakes to Avoid
- Encoding too much. Packing many events into 64 values leaves each combination with too few installs to read.
- Ignoring the first window. Fine values are only reported for days 0 to 2. Anything that happens later belongs in coarse values.
- Changing the mapping often. Each change resets network learning and splits your trend lines.
- Treating null as zero. A null value means Apple withheld data for privacy, not that the user did nothing.