Analytics Tracking Depth Based on User Value
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Solution Overview
Problem
Current analytics tracking methods are costly for application and service providers, with previous attempts to reduce costs, such as sampling, resulting in lower accuracy.
Innovation Solution
Implementing a system where user interactions are tracked based on assigned user value thresholds, with tracking calls only executed for users exceeding a predefined monetary or relative value, thereby minimizing unnecessary tracking calls and reducing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If analytics tracking is performed for all users, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent applies local quality by differentiating tracking depth based on user value segments. High-value users receive full analytics tracking while low-value users receive reduced or no tracking, optimizing the balance between measurement precision and cost across different user populations rather than applying a uniform tracking approach to all users.
Solution Approach 2:
The patent changes the parameter of tracking intensity based on user value thresholds. By dynamically adjusting whether tracking occurs (binary parameter change) or the depth of tracking (granularity parameter change), the system maintains high measurement precision for valuable users while reducing costs for less valuable users, effectively resolving the contradiction between accuracy and cost.
2Loss of energy
If sampling is used to reduce analytics costs, then cost decreases, but measurement precision deteriorates
Solution Approach 1:
Instead of uniform sampling that degrades overall measurement precision, the patent applies local quality by implementing selective tracking where high-value users are fully tracked and low-value users are sampled or excluded. This localized approach maintains high measurement precision for the most valuable user segments while still achieving cost reduction through reduced tracking of less valuable users.
3Measurement precision
If tracking depth is increased for all users, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent reduces device complexity by applying local quality - implementing simplified tracking logic for low-value users and enhanced tracking only for high-value users. This segmentation avoids the need for a universally complex tracking system, maintaining high measurement precision where needed while reducing overall system complexity through differentiated tracking depths across user segments.
Data Source
AI summary
In an example embodiment, user interactions with a software component may be tracked in an efficient manner. Specifically, an analytics tracking request triggered by user interaction with a software component is received. Then a value assigned to the user is retrieved. It is then determined if the value assigned to the user exceeds a value threshold assigned to the analytics tracking request. Based on a comparison between the value assigned to the user and the threshold value, an analytics tracking function associated with the analytics tracking request is launched.