How Apple Will Use Your Personal Data
With the recent launch of iOS 12, Apple starts personalized recommendations based on users’ preferences. Changes will also involve the Mac App Store, Apple Music and Apple Books.
How recommendations work
Apple starts reviewing users’ search history: what apps they look for, and when and how often they use the App Store. Information such as type of device, operating system used, and available memory card space will help to make the most perfect fit for users.
This is how App Store notifies users about data collecting:
Recommendations of apps and games are selected from the ones featured before on Today tab.
How to Limit Access to Personal Data
Users are still able to choose whether they want to keep their data secure or let Apple use it for statistic or ads. To manage your data privacy, go to the settings:
Recommendations for Mac App Store and Apple Music
Mac App Store will also use data to make personalized recommendations. This is how Mac Store informs users:
In documentation for Apple Music API, we see that now there are methods for personalized tokens, which means that access to users’ personal data is required. Personalized tokens are needed for many features of Apple Music such as:
- Personal library.
- Rating collections.
Along with App Store, access to personal data can be switched off.
What personalized recommendations mean for app developers
We were extremely interested in how personalized recommendations will influence the conversion rate. As you know, being featured in app stores makes number of installs and views grow (learn more in the article How to get featured on the main App Store page). And we have managed to inform developers if the apps are being featured beforehand (track all the apps from Today, Apps and Games tabs). But is it possible to predict personalized featuring?
We can base our hypothesis on the Search Ads operating process. Here Apple divides users into groups of 5,000 people and use their impersonalized data. It’s possible that personal recommendations will work for groups of users. In this case an app will receive thousands of views daily.
Personalized recommendations will give more opportunities for an app to attract more loyal users. For example, yoga apps will be shown to the group of users who have searched or downloaded similar apps.
Don’t forget to take care of your app page: positive customer reviews, rates, high graphics quality and descriptions will draw users’ attention after seeing it featured.
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