Machine-learning models to facilitate user retention for software applications
US11188840B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 29, 2017 |
| Grant date | Nov 30, 2021 |
| Priority date | — |
| Expiry date | Oct 1, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L67/535
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An ordered combination of machine-learning models may be used to identify users who are likely to abandon use of an application, predict the reasons why those users are likely to abandon, and identify intervening actions that the application can perform to reduce the probability that the users will abandon the application. For example, a first machine-learning model determines a retention-prediction value indicating a probability that the user will complete a target action in the application before a session terminates. If the retention-prediction value satisfies a threshold condition, a second machine-learning model determines a reason why the session is likely to terminate before the user completes the target action. A third machine-learning model determines an intervention action for the application to perform to increase the probability that the user will complete the target action before the session terminates.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.