User Action Tracking in Matching Systems
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Solution Overview
Problem
Current online dating platforms lack effective tracking and analysis of user interactions to evaluate the effectiveness of matching algorithms and user engagement, making it difficult to identify successful introduction methods and improve user experience.
Innovation Solution
A system and method for detecting user actions in a computer-implemented matching system, storing data on these actions, filtering it based on administrator-defined criteria, and presenting the data in user-friendly formats like logs, charts, and graphs to create a user action log, which helps administrators analyze user interactions and improve matching processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If user interaction data is tracked and stored in detail, then analysis capability and user engagement insights are improved, but data management complexity and storage requirements increase
Solution Approach 1:
The patent extracts specific user interaction data elements (profile views, messages sent, matches made) from the overall system operations and stores them separately in a dedicated data store. This extraction allows detailed tracking of user interactions without requiring the entire system to be redesigned for data management, thus improving information retention while controlling complexity.
Solution Approach 2:
The patent introduces an intermediary matching system that acts as a mediator between users and the data management infrastructure. This intermediary layer processes and structures user interaction data before storage, making the data more manageable and analyzable while reducing the direct complexity burden on the storage and analysis systems.
2Measurement precision
If comprehensive user action logging is implemented, then matching algorithm effectiveness can be evaluated, but system resource consumption increases
Solution Approach 1:
The patent implements partial logging by selecting and tracking only specific user actions that are most relevant to matching algorithm evaluation (profile views, messages sent, matches made). This partial action approach provides sufficient measurement precision for evaluating matching effectiveness while avoiding the excessive resource consumption that would result from logging every possible user interaction.
3Productivity
If user interaction data is aggregated and analyzed, then user experience improvement insights are obtained, but data processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary structuring and organization of user interaction data as it is being collected and stored. By pre-organizing the data in a structured format during the logging phase rather than attempting to organize it during analysis, the system reduces the computational burden and processing time required for later analysis, thus improving productivity while minimizing time loss.
Data Source
AI summary
A method is provided in one example embodiment and includes detecting actions taken by users in a computer-implemented matching system and, for each of the detected actions, storing data indicative of the detected action. The method further includes filtering the stored data in accordance with at least one filter selected by an administrator of the computer-implemented matching system and creating a user action log from the filtered stored data. The user action log includes all of the stored data that matches the selected at least one filter. The at least one filter may include log start time, log end time, type of action, user ID, target user ID, and/or site type. The detected action may include viewing another user's profile, changing the user's own profile, sending a message to another user via the computer-implemented matching system, and/or performing a matching search using the computer-implemented matching system.