Optimizing content item delivery for installations of a mobile application

US11151603B2 · kind B2 · utility

Assignee

• MICROSOFT TECHNOLOGY LICENSING, LLC · US

Inventors

• Samira Tasharofi · Sunnyvale, US
• Christopher D. Erbach · Palo Alto, US
• Pei Yu · Bellevue, US
• Nirav Nalinbhai Shingala · Santa Clara, US
• Alexandros Ntoulas · San Jose, US
• Rohan Rajiv · Santa Clara, US

Key dates

• Filing date: Dec 31, 2018
• Grant date: Oct 19, 2021
• Expiry date: Jun 22, 2039

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q30/0267
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

Techniques for optimizing content item delivery for installations or activations of a mobile application are provided. In one technique, a machine-learned model is trained based on multiple training instances that individually indicate whether an entity performed a particular action relative to a mobile application. In response to receiving a content item request from a third-party content delivery exchange, it is determined whether a client device that initiated the content item request has activated a particular application. In response to determining that the client device has not activated the particular application, multiple feature values of the content item request are identified. Based on inputting the feature values into the model, a score is generated that indicates a likelihood that an entity of the client device will perform the particular action relative to the particular application. Based on the score, a content item is transmitted over a network to the client device.