17805460. APP STORE PEER GROUP BENCHMARKING WITH DIFFERENTIAL PRIVACY simplified abstract (Apple Inc.)

APP STORE PEER GROUP BENCHMARKING WITH DIFFERENTIAL PRIVACY

Organization Name

Apple Inc.

Inventor(s)

Nicholas Kistner of Cupertino CA (US)

Andrew T. Maher of Cupertino CA (US)

Artem Kirillov of Cupertino CA (US)

Daniela S. Antonova of York (GB)

Mahesh Molakalapalli of Fremont CA (US)

Matthew Tan Teik Hoe of Cupertino CA (US)

Maxim Martynov of Cupertino CA (US)

Rajiv J. Krishnamurthy of Cupertino CA (US)

Vivek Krishnan of Cupertino CA (US)

Yogesh V. Padte of Cupertino CA (US)

APP STORE PEER GROUP BENCHMARKING WITH DIFFERENTIAL PRIVACY - A simplified explanation of the abstract

This abstract first appeared for US patent application 17805460 titled 'APP STORE PEER GROUP BENCHMARKING WITH DIFFERENTIAL PRIVACY

Simplified Explanation

The abstract describes a method for providing peer group benchmarking with differential privacy in app stores. Here are the key points:

• The method involves obtaining app store metrics for a first application.
• An application peer group is determined for the first application based on common traits.
• Peer group app store metrics are obtained based on the metrics of the application peer group.
• A user interface is displayed to show the relative placement of the first application's metrics among the peer group metrics.
• The user interface element identifies the peer group metrics without revealing the performance of individual apps within the group.

Potential Applications

• This technology can be used in app stores to provide developers with benchmarking information about their apps compared to similar apps in their peer group.
• It can help developers understand how their app is performing in relation to their competitors and make informed decisions for improvement.

Problems Solved

• This technology addresses the problem of obtaining benchmarking information in app stores without revealing sensitive performance data of individual apps.
• It provides a way to compare app performance while preserving privacy and confidentiality.

Benefits

• Developers can gain insights into their app's performance compared to similar apps without compromising privacy.
• The method allows for accurate benchmarking without revealing specific app performance, protecting sensitive information.
• It provides a fair and standardized way to evaluate app performance within a peer group.

Original Abstract Submitted

Providing peer group benchmarking with differential privacy obtaining one or more app store metrics for a first application, determining an application peer group for the first application, wherein the application peer group is determined based on a plurality of common traits, and obtaining one or more peer group app store metrics for the application peer group based on the one or more app store metrics. A user interface is displayed to indicate a relative placement of at least one of the one or more app store metrics for the first application among the peer group app store metrics, and the user interface element identifies the application peer group metrics with a minimum level of accuracy without revealing the performance of individual apps within the peer group.