Attribution
Expert: with sources and numbers. Plain: the same, without them, for beginners.
AdServices, AdAttributionKit and SKAdNetwork, what each is for, and why Apple Ads is measured differently.
Three frameworks with overlapping names. The distinction that matters: AdServices is for Apple Ads; AdAttributionKit and SKAdNetwork are for everyone else.
AdServices: Apple Ads only
A The AdServices attribution API gives developers insight into how their Apple Ads campaigns perform, supporting campaign, placement, ad group and keyword-level attribution. It uses Apple’s first-party data only and has no information about whether a user viewed or clicked an ad outside the App Store. (Ad attribution overview, verified 2026-09-18)
Keyword-level attribution is the significant part. No other iOS ad measurement gives you that, and it is what makes the keyword harvesting loop possible (90-10). It works because Apple owns both the ad and the store. It is first-party measurement, not cross-party tracking.
AdAttributionKit and SKAdNetwork, everyone else
A SKAdNetwork was Apple’s first privacy-preserving attribution framework, powered by crowd anonymity. (AdAttributionKit and SKAdNetwork interoperability, verified 2026-09-18)
A AdAttributionKit lets registered ad networks and developers attribute installations and re-engagement to a campaign via a signed signal from Apple, limiting the data in the attribution postback, and builds on SKAdNetwork’s functionality. Same source. It is Apple’s newer framework, built on SKAdNetwork fundamentals.
A For ads on third-party advertising platforms, Apple offers AdAttributionKit. (Ad attribution, verified 2026-09-18)
Both deliberately limit what comes back: delayed, aggregated, coarse postbacks rather than user-level data. Covered further in 97-03.
They are complementary
A Apple Ads customers can use two freely available and complementary methods: the AdServices attribution API and measurement in AdAttributionKit. (Ad attribution overview, verified 2026-09-18)
So for Apple Ads you can have both, rich first-party data through AdServices, and the privacy-preserving postback path through AdAttributionKit. They will not agree, because they measure differently over different windows. That is expected, not a bug, and it should be stated in any report that quotes both.
The windows
A Apple Ads reporting attributes tap-through installs within a 30-day window and view-through installs within a one-day window, and both include new downloads and redownloads. (Reporting options and definitions, verified 2026-09-18)
These windows are not what your MMP uses, and neither matches AdAttributionKit’s postback timing. Three systems, three answers, all defensible. Pick one as the number of record, say which, and stop reconciling.
What this means practically
Apple Ads numbers will exceed MMP numbers, usually. Different windows, redownloads included, view-through counted. The gap is structural.
Do not average across systems. Choose the system of record per decision: AdServices for keyword and campaign optimisation inside Apple Ads; MMP for cross-channel comparison; AdAttributionKit for networks that cannot see inside the store.
Say which one a number came from. Every time. An unlabelled install figure starts an argument that cannot be resolved.
What goes wrong
Expecting Apple Ads and MMP figures to reconcile. They cannot.
Comparing Apple Ads CPA to another network’s CPA without noting the frameworks.
Treating AdServices as available for non-Apple ads. First-party only, Apple Ads only.
Mixing view-through and tap-through in one figure across placements. One day versus thirty.
Reporting installs without separating new downloads. Redownloads are included (90-09).
In short
Every fact on this page in one line, with its evidence tier, source and verification date, 4 A. Generated from the claim register, so it cannot drift from the page above.
Three tracking systems with genuinely overlapping names. The distinction that actually matters: one system is only for this centre's own paid billboard; the other two are for every other kind of advertising.
The centre's own first-party system, billboard only
This centre's own attribution tool gives you real insight into how your own paid billboard performs, down to the order, the location, the group and even the individual word. It uses only the centre's own first-party data, and it has genuinely no information at all about whether someone saw or tapped an advertisement anywhere outside the centre itself.
Word-level credit is the significant part. No other measurement on this platform gives you that at all, and it's exactly what makes the whole word-harvesting loop possible in the first place. It works because the same centre owns both the billboard and the shopfront. This is genuine first-party measurement, not tracking someone across separate parties.
The two systems for everyone else
One was this platform's first privacy-preserving attribution system, built on the anonymity of a large crowd rather than tracking any one individual.
A newer system lets registered ad networks and shop owners credit a real walk-in or a return visit to a campaign, through a signed signal from the centre itself, deliberately limiting what comes back in that signal. And it builds directly on the older system's own foundations.
For advertising running on outside platforms entirely, the centre offers this newer system specifically.
Both of these deliberately limit what actually comes back to you: delayed, grouped-together, deliberately coarse signals rather than anything at the level of one individual person.
They work together, on the billboard specifically
For its own paid billboard, you can genuinely use both of the first two systems at once: the centre's own first-party tool, and its own newer, privacy-preserving system.
So for the billboard specifically, you can have both: rich first-party data through the centre's own tool, and the privacy-preserving signal path through the newer system. They will not agree with each other, because they measure things differently, over different windows of time. That's expected, not a flaw, and it's worth stating plainly in any report that quotes numbers from both.
The windows
The billboard's own reporting credits a tap-based walk-in within a genuinely generous window, and a glance-based one within a much shorter window, and both of those include people coming back as well as brand-new visitors.
These windows are not what your own outside measurement partner uses, and neither one matches the newer system's own signal timing either. Three systems, three genuinely different answers, all individually defensible. Pick one as your official number, say clearly which one it is, and stop trying to force the others to agree with it.
What this actually means in practice
The billboard's own numbers will usually come in higher than your outside measurement partner's. Different windows, people coming back included, glance-based credit counted too. The gap between them is structural, not a mistake.
Don't average across the different systems. Choose whichever system is your official record for each specific decision: the centre's own tool for optimising words and orders inside the billboard itself; your outside measurement partner for comparing across every channel at once; the newer signal-based system for any network that genuinely can't see inside the shopfront itself.
Always say exactly which system a number actually came from. Every single time. An unlabelled walk-in figure starts an argument that can never actually be resolved.
What tends to go wrong
Expecting the billboard's own numbers and your outside partner's numbers to match. They genuinely cannot.
Comparing the billboard's own cost figure to another network's without noting which system measured each one.
Treating the centre's own first-party tool as available for advertising that isn't the centre's own billboard. First-party only, and billboard-only.
Mixing glance-based and tap-based credit into one single figure across different locations. Genuinely different-length windows.
Reporting walk-ins without separating out brand-new ones. People coming back are included in the total.