公开(公告)号：US20230394509A1

公开(公告)日：2023-12-07

申请号：US17805460

申请日：2022-06-05

Applicant: Apple Inc.

Inventor： Nicholas Kistner ,  Andrew T. Maher ,  Artem Kirillov ,  Daniela S. Antonova ,  Mahesh Molakalapalli ,  Matthew Tan Teik Hoe ,  Maxim Martynov ,  Rajiv J. Krishnamurthy ,  Vivek Krishnan ,  Yogesh V. Padte

IPC: G06F21/62

CPC classification number: G06F21/6254

Abstract: 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.

公开(公告)号：US20240103998A1

公开(公告)日：2024-03-28

申请号：US18167406

申请日：2023-02-10

Applicant: Apple Inc.

Inventor： Jae Hyeon Bae ,  Kurt M. Fredericks ,  Nicholas Kistner ,  Andrew T. Maher ,  Nihar Ranjan Hati ,  Mahesh Molakalapalli ,  Srivas Chennu ,  Jamie J. Martin

IPC: G06F11/36

CPC classification number: G06F11/3608

Abstract: This application sets forth techniques for variant testing at scale. In particular, the embodiments set forth provide systems and methods for testing, on a large-scale software application store, visual aspects of one or more variants of representative data associated with an application available through the software application store. According to some embodiments, a method may include using a subset of conversion data associated with a control object and a subset of the conversion data associated with at least one variant object to compute at least one conversion metric for the control object and at least one conversion metric for the at least one variant object. The method may also include generating a performance measurement by applying at least one statistical hypothesis testing function to the at least one conversion metric for the control object and the at least one conversion metric for the at least one variant object.