Cross-Device User Engagement Tracking via Signal Aggregation
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Solution Overview
Problem
Current computing devices lack the ability to track user engagement across multiple activities and devices, leading to an incomplete view of user activity, making it difficult for users to resume interrupted tasks and increasing energy consumption due to manual re-initiation of applications.
Innovation Solution
A method that combines signals from various sources, including application states and user interactions, to create a user engagement log, which is then stored and synchronized across devices, allowing for a unified view of user activity and enabling seamless resumption of tasks across platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple computing devices are used to perform various tasks, then user productivity and task completion capability are improved, but the ability to track user engagement across devices and activities deteriorates
Solution Approach 1:
The patent implements a universal user engagement tracking system that operates across multiple computing devices and software applications. The system uses a common identifier (such as a user profile or device identifier) to aggregate engagement data from diverse sources including different operating systems, applications, and device types, creating a unified view of user activity that maintains productivity benefits while solving the tracking fragmentation problem
Solution Approach 2:
The patent introduces an intermediary component (engagement tracking service or intermediary software layer) that sits between the user's interactions with various applications and the tracking system. This intermediary captures engagement signals from multiple sources, normalizes the data, and consolidates it into a coherent user engagement profile, enabling cross-device tracking without interfering with user productivity
2Adaptability or versatility
If users switch between different activities and locations, then task flexibility and user experience are improved, but the ability to resume interrupted tasks deteriorates
Solution Approach 1:
The patent implements preliminary action by continuously tracking and recording user engagement state in advance before interruption occurs. The system maintains a current engagement profile that is updated in real-time as users interact with applications, so when users switch devices or activities, the engagement data is already prepared and can be immediately retrieved to resume tasks without requiring users to manually re-navigate or re-initiate applications
Solution Approach 2:
The patent employs feedback mechanisms where the system monitors user engagement patterns and provides information about current and previous activities. This feedback loop allows the system to understand user behavior patterns, predict which tasks are most likely to be resumed, and pre-position engagement data for quick retrieval, thereby maintaining task flexibility while improving ease of task resumption
3Loss of energy
If manual re-initiation of applications is required after interruption, then system resource consumption during tracking is reduced, but energy consumption increases due to manual intervention
Solution Approach 1:
The patent applies partial action by implementing engagement tracking at a selective level rather than continuously monitoring all system events. The system tracks key engagement signals (application focus, user interactions, session state) at strategic points rather than every possible event, reducing the computational overhead and energy consumption of tracking while still maintaining sufficient data to enable automatic task resumption and reduce user time loss
Data Source
AI summary
Technology related to determining a user engagement with software programs is disclosed. In one example of the disclosed technology, a method can include receiving a plurality of signals indicating states of the computer and a software application executing on the computer. The method can include combining the signals to determine a user engagement with the software application. The method can include storing a user engagement log based on the determined user engagement with the software application.