Apple Ads recently updated its data metrics for app installations, introducing changes like Installations (Click Through) and new metrics such as Installations (View Through). This article explores these updates and their implications.
Which Data Has Been Updated?
In this update, previously installation-related data has been changed to: Installations (Click Through), CPA (Click Through), and Conversion Rate (Click Through). These are merely changes in the data metric names, and the actual ad behavior represented by these metrics remains the same as before. Additionally, new data metrics have been added: Installations (View Through), CPA (View Through), and Conversion Rate (View Through).
Detailed explanations of the data metrics can be found in the official documentation:
https://ads.apple.com/cn/help/reporting/0023-reporting-options-and-definitions
I have also created a simple comparison table for the new and old data:

How to Understand Click Through/View Through?

As shown in the image above:
- User sees the ad, clicks on it, and installs the app within 30 days:
- Before the update: Recorded as an installation.
- After the update: Recorded as an installation (Click Through).
- User sees the ad, clicks on it, but does not install the app or installs it after 30 days:
- This update does not affect this behavior, and it will not be recorded as installation data. In other words, the user is lost.
- User sees the ad but does not click on it, yet installs the app within 1 day:
- Before the update: This installation would not be recorded as ad installation data.
- After the update: This installation will be recorded as an installation (View Through).
- User sees the ad, does not click on it, and does not install the app or installs it after 1 day:
- This update does not affect this behavior, and it will not be recorded as installation data.
The key change in this update is the third part: users who do not click on the ad but still install the app shortly after will now be recorded as an installation (View Through).
Which Users Install the App Without Clicking the Ad?
- Top Ranked Keywords in Natural Search ResultsAs shown in the image, when a user searches for a keyword, the ad is displayed at the top, followed by the top natural result. Users are likely to click on the natural result and then download the app.
- Users Seeing the App AgainPossible scenarios include:
- A user searches for “translation software”, sees the ad for “TranslateABC”, does not click on it, but later cannot find a better app in the search results, searches for another keyword “AI translation tool”, and finds “TranslateABC” again, deciding to install it.
- Another user searches for “scanner software”, sees the ad for “ScanABC”, does not click on it, exits the App Store, and later sees an ad for “ScanABC” on another platform, which convinces them to install the app.
- Another user searches for “securities software”, sees the ad for “SecuritiesABC”, does not click on it, exits the App Store, and later a friend recommends “SecuritiesABC”, prompting the user to install it.
Why Do Users Install the App After Seeing the Ad Multiple Times?
There are many reasons, such as users not liking to click on ads, finding the ad content less attractive than the natural result, seeing better benefits in the ad on another platform, or trusting a friend’s recommendation more.
What Does Installation (View Through) Represent?
Even if we ignore the reasons like user preferences or ad content, seeing an ad leaves an impression on the user. When users see the product again, the likelihood of choosing it increases.
- Product A: The user has seen this product before and remembers it but did not install it.
- Product B: The user has never seen or heard of this product.
When both products are shown to the user, Product A will have a higher conversion rate. This is what Apple Ads emphasizes: its ads not only have a direct conversion effect but also a brand effect, enhancing user impressions and helping conversions in other channels (including organic traffic). In other words, even if users do not click on the ad, the exposure contributes to their installation decision within a short period (24 hours).
Most effective advertising channels have similar brand effects. Exposing the product to users leaves an impression. Apple has a unique advantage as a smartphone manufacturer: it knows which users saw the ad and which users downloaded the app without clicking the ad. Other channels can only track users who saw the ad but cannot accurately identify users who downloaded the app without clicking the ad.
What Is the Impact on Attribution?
In fact, there is little impact.
Apple Ads’ attribution is based on user tokens. When users activate the app, the AdServices framework obtains the user token and requests data from Apple. If Apple returns attribution = true
, it means the user clicked the ad. If attribution = false
, the user did not click the ad.

Currently, whether it’s MMP’s third-party attribution or developer self-attribution, click behavior is more recognized. A user clicking on an ad means they came from that channel. If the user did not click on the ad, claiming the user came from that channel is not recognized.
In my opinion, Apple adds Installation (View Through) data to highlight the brand effect of its ad channel, not to compete for attribution data. In the future, it should not return attribution = true
for users who only viewed but did not click the ad.
What Is the Impact on Advertising?
There is no significant impact.
The new data does not change Apple Ads’ bidding algorithm or user installation statistics (it’s just a name change).
The only point worth discussing is that Apple Ads now provides Installations (Click Through), Installations (View Through), and Installations (Total). Which one should we use when evaluating ad performance?
I still believe that click behavior has a direct effect on user installation, so we should use Installations (Click Through). The data for Installations (View Through) should be considered supplementary and counted towards other channels. Apple Ads’ data only provides an auxiliary function in this context.
Conclusion
Understanding and adapting to changes in data metrics is essential for optimizing advertising strategies. With Apple Ads’ recent updates, it’s clear that the platform is emphasizing not only direct conversion but also the brand effect of its advertisements. By recognizing the impact of both click through and view through installations, advertisers can gain a more comprehensive view of their campaign performance. As the digital advertising landscape continues to evolve, staying informed and agile in response to these changes will be key to maintaining and enhancing ad effectiveness.