Reengagement Notification Filtering via Dynamic Scoring
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Solution Overview
Problem
Computing devices often produce notification alerts for reengagement type notifications without considering the user's likelihood of engagement, leading to unnecessary alerts and resource inefficiency.
Innovation Solution
A computing device determines whether to output reengagement type notification alerts based on a reengagement score threshold, which is dynamically set based on contextual information such as user activity, location, and consent, ensuring alerts are delivered only when the user is likely to engage, thereby optimizing alert output and resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If notification alerts are output for all reengagement type notifications, then the user is informed of all new notifications, but the user experiences unnecessary alerts and resource inefficiency increases
Solution Approach 1:
The system dynamically changes the notification output parameter based on the reengagement score. When the reengagement score exceeds the threshold, the notification is output; when it does not exceed the threshold, the notification is suppressed. This parameter-based filtering resolves the contradiction by selectively delivering notifications based on user engagement likelihood.
Solution Approach 2:
The reengagement score acts as an intermediary mechanism between receiving notification data and outputting alerts. The computing device calculates the reengagement score based on contextual information and uses this intermediate metric to decide whether to suppress or output the notification, thereby resolving the contradiction between informing users and conserving resources.
2Loss of energy
If notification alerts are suppressed based on reengagement score threshold, then device resources are conserved, but the user may miss important notifications
Solution Approach 1:
The system uses the reengagement score threshold as a dynamic parameter to control notification suppression. By adjusting the threshold based on contextual information, the system ensures that important notifications (those with high reengagement scores) are delivered while suppressing less important ones, thus preventing information loss while conserving resources.
Solution Approach 2:
The system uses contextual information about user behavior as feedback to dynamically adjust the reengagement score threshold. This feedback mechanism ensures that the suppression decisions are adaptive and context-aware, preventing important notifications from being missed while maintaining resource efficiency.
3Reliability
If reengagement score threshold is dynamically adjusted based on contextual information, then notification effectiveness is improved, but device complexity increases
Solution Approach 1:
The system dynamically changes the reengagement score threshold parameter based on contextual information such as user activity, time of day, and device state. This dynamic parameter adjustment improves notification effectiveness by adapting to user context while maintaining a relatively simple computational model for calculating the threshold.
Data Source
AI summary
In general, techniques of this disclosure may enable a computing device to defer output of a reengagement type notification until the computing device determines that a user is likely to engage with the application or service that generated the notification, as opposed to ignoring or dismissing the notification and/or the application or service. In this way, by precisely controlling its output, the described techniques may enable a computing device to increase a likelihood that a reengagement notification will succeed in reengaging a user with the application or service associated with the notification.