ASO Patents

What This Patent Covers and Why It Matters for ASO

Feature it describes: Peer Group Benchmarks, the comparison figures developers see in App Store Connect.

Most patents on this site describe systems you can only infer from the outside. This one describes a tool you open every week, which makes it unusually checkable.

Three things in it should change how you read those numbers.

1. Your peer group is defined by app type, monetization model and download volume tier. The monetization dimension separates freemium, paid and subscription apps. The volume dimension means your comparison set changes as you grow. A benchmark that worsens after a good quarter may not be a decline at all. You may have moved into a tougher tier.

2. The numbers carry deliberate error. Differential privacy here is not a policy statement, it is injected measurement noise. The system adds controlled inaccuracy to peer group metrics so that no individual app’s performance can be recovered, then checks whether the result is still accurate enough to be useful, and iterates. Small peer groups need more noise to stay private, so the smaller and more specific your niche, the less precise your benchmark. Reading a two percent gap as meaningful is reading the noise.

3. Peer groups must be large enough to hide individuals. Group membership is chosen with a minimum size requirement. That constraint pulls against specificity: the more precisely Apple could define your competitive set, the more it would reveal about the few apps in it.

The metrics named in the description are worth listing, because one of them is not in the developer vocabulary:

• Conversion rate
• Crash rate
• Retention
• Discoverability
• Usage
• Monetization performance

Discoverability appearing as a peer comparable metric is the detail to sit with. It implies Apple computes a discoverability figure per app and considers it comparable across a peer group. That is closer to a public ASO score than anything Apple has ever described elsewhere.

Practical consequence: use benchmarks to detect direction and large gaps, not to tune. If a metric sits inside the noise band of a small peer group, there is nothing there to optimize toward.

Patent Summary

The system lets a developer compare their application’s performance against similar applications without exposing any individual competitor’s data.

A peer group is determined from traits the applications share, including app type, monetization model and download volume tier, with group membership constrained so that the group is large enough to prevent identification of any single member. A privacy mechanism then injects measurement error into the peer group’s aggregate metrics. The system confirms that the resulting accuracy is still sufficient for the comparison to be useful, balancing the privacy threshold against the accuracy requirement iteratively.

It then retrieves the metrics for both the developer’s application and the privatized peer group, and displays the comparison, showing how the app performs relative to its peers without revealing any peer member’s own figures.

The tension the patent is solving is worth naming. A benchmark is only useful if it is precise, and only publishable if it is imprecise. Every figure in App Store Connect’s benchmark view is a negotiated point between those two requirements.

A detailed breakdown of the privacy mechanism, the figures and the full claim language will follow in a later update to this article.

Related reading: US12561221B2 covers how these comparisons are displayed.