18350481. BACKGROUND UPGRADE MIGRATION DETERMINATION AND IMPLEMENTATION simplified abstract (MICROSOFT TECHNOLOGY LICENSING, LLC)

BACKGROUND UPGRADE MIGRATION DETERMINATION AND IMPLEMENTATION

Organization Name

MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor(s)

Robert Bradley Gilbert of Kirkland WA (US)

Alison Rachel Wu of Redmond WA (US)

Aamir Rasheed of Lake Forest Park WA (US)

Prakhar Srivastava of Seattle WA (US)

Doru Kesriyeli of Vancouver (CA)

BACKGROUND UPGRADE MIGRATION DETERMINATION AND IMPLEMENTATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18350481 titled 'BACKGROUND UPGRADE MIGRATION DETERMINATION AND IMPLEMENTATION

Simplified Explanation

The abstract describes a method for migrating a user to an updated version of a software feature without friction, by utilizing telemetry data and a machine learning model to predict user acceptance.

• Telemetry data is collected for both the updated version and the prior version of the software feature.
• A machine learning model is trained using external telemetry data to evaluate user behavior.
• A migration acceptance value is calculated to determine if the user will accept the updated version over the prior version.
• The migration acceptance value is compared to a threshold value set by the trained model.
• If the migration acceptance value exceeds the threshold, the prior version is excluded from the user profile.

Potential Applications

This technology could be applied in software development to streamline the migration process for users and improve user experience.

Problems Solved

This technology solves the problem of user resistance to software updates by predicting user acceptance and excluding prior versions seamlessly.

Benefits

The benefits of this technology include reducing user friction during software updates, improving user satisfaction, and increasing adoption rates of updated software features.

Potential Commercial Applications

One potential commercial application of this technology could be in the development of software applications where frequent updates are released to users.

Possible Prior Art

Prior art may include similar methods of predicting user acceptance of software updates, such as A/B testing or user surveys.

What is the impact of this technology on user experience during software updates?

This technology significantly improves user experience during software updates by predicting user acceptance and excluding prior versions seamlessly, reducing user friction and increasing user satisfaction.

How does this technology benefit software developers in terms of user adoption rates?

This technology benefits software developers by increasing user adoption rates of updated software features, as it streamlines the migration process for users and improves overall user experience.

Original Abstract Submitted

Migration of a user of a computing device to accept an updated version of a software feature to the exclusion of a prior version of the software feature is implemented without user friction. Telemetry data corresponding to use of the updated version and of the prior version is stored. The telemetry data is evaluated utilizing a trained machine learning model trained using external telemetry data with respect to use of the updated version and to use of the prior version. A migration acceptance value indicative of whether the user will accept use of the updated version to exclusion of the prior version is calculated. The migration acceptance value is compared to a threshold value determined by the trained model. If the migration acceptance value exceeds the threshold value, the prior version is excluded from the user profile.