Why Your Apple Search Ads Attribution Is About to Spike—And What It Actually Means

Starting March 27, 2025, Apple Search Ads (ASA) is getting a meaningful upgrade: view-through attribution (VTA) will become available via the Apple Ads Attribution API. This change expands how ASA measures ad performance, moving beyond just taps to now include impressions that lead to installs.

If you’re running ASA campaigns this shift could reshape how you measure performance, attribute revenue, and optimize your campaigns.

In this post, we’ll cover:

• What view-through attribution is and why Apple is making the change
• What this means for mobile developers and marketers
• How RevenueCat’s ASA integration helps you make sense of this new model

What Is View-Through Attribution?

Until now, Apple Search Ads relied solely on tap-through attribution. A user sees your ad, taps it, and downloads your app within 30 days.

With view-through attribution (VTA), installs can now be credited to users who saw your ad, even if they didn’t tap, as long as the install happens within 24 hours of the impression.

This update gives advertisers a fuller picture of how ASA campaigns are influencing user behavior, and potentially driving installs.

What’s Changing in the Attribution Payload?

To support View-through attribution, Apple has introduced a new field in the attribution payload: claimType. This field tells you whether an install came from a:

• Click – A traditional tap-through interaction (30-day attribution window)
• Impression – A view-through interaction (24-hour attribution window)

Tap-through attribution is still prioritized if both are present. One caveat: VTA will not be supported for campaigns using age or gender targeting.

Why This Matters for Developers and App Marketers

This might seem like a small technical tweak, but it comes with some big strategic implications.

1. You’ll see more attributed installs

With view-through Attribution enabled, Apple Search Ads may start claiming credit for installs that previously would’ve been considered organic. As a result, the number of new installs and conversions attributed to ASA might spike even if nothing else changes about your campaign strategy.

2. You’ll get a more complete picture of user behavior

Many users don’t tap on an ad right away, but the impression can still leave an impact. VTA helps surface those indirect conversion pathways, especially for high-visibility placements like the Today tab or App Store search results.

3. Your attribution and reporting models may need a rethink

If you’re relying on deterministic, last-touch attribution, now is a good time to revisit your model. With both click and impression-based installs in play, it’s important to track and differentiate them to avoid misreading performance or over-crediting ASA.

4. Understand what’s actually driving valuable conversions

It’s easy to assume every attributed install is high value, but not all impressions are created equal. A fleeting glance at an ad is not the same as an engaged tap. To get real insight, tie attribution back to downstream metrics like trial starts, subscriptions, and LTV—not just installs.

Another key consideration is if you are running ads for branded search terms, where users are already searching for your app by name. If someone sees your ad and installs shortly after (without tapping on the ad), that install could now be attributed to ASA, whereas previously it would only be attributed if a user directly clicked on it. 

But was it really the ad that drove the install? Or just the user’s intent? And most importantly, do you want to attribute the revenue generated from that install to your spend on ASA or not? It’s a nuance marketers now need to account for.

How RevenueCat Helps You Make Sense of It All

RevenueCat’s ASA integration supports view-through attribution out of the box, so you can connect installs (from views or taps) to the metrics that matter most, like conversions, revenue, and lifetime value (LTV).

RevenueCat also allows you to parse through the number of new customers being attributed to ASA from view-through attribution, broken down by the keyword that the ad was served on. This way, you can consider how exactly you want to use the impression attributions in your analysis, for example excluding impressions from branded keywords.

If you’re already using RevenueCat, just click here for your New Customer Chart, filtered by impression and segmented by ASA Keyword.

Beyond supporting view-through attribution, RevenueCat’s ASA integration also fills key gaps left by Apple’s native reporting. While Apple’s attribution frameworks provide helpful data at a high level, they fall short when it comes to answering deeper questions about campaign effectiveness over time.

For example, Apple’s reports do not allow you to track user cohorts or connect subscription behavior back to specific campaigns or ad groups. Data is limited to high-level summaries, often requiring you to export and manipulate spreadsheets manually just to uncover basic trends.

With RevenueCat, you get more than just raw attribution data. You get:

• Clean, visual cohort analysis to follow the subscription lifecycle of ASA-acquired users over time
• Filters and segmentation in Charts by campaign, ad group, keyword, and claim type
• Attribution data tied directly to meaningful downstream metrics like trials, conversions, renewals, and LTV

Here’s how it works:

• We capture attribution data from Apple’s Ads Attribution API, including the new claimType field
• We match that data to subscription events like trial starts, conversions, renewals, and cancellations

By pairing ASA attribution data with subscription performance, RevenueCat helps you see what’s truly driving long-term growth—not just installs.

In summary

View-through attribution is a powerful addition to Apple Search Ads, but it also introduces new complexity in how performance is measured and credit is assigned. With RevenueCat, you can cut through the noise—tying installs (from taps or views) to the metrics that actually matter, so you can make smarter decisions about your ad spend.