Network Content Variant Detection and Analysis
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Solution Overview
Problem
Companies face variability in the effectiveness of network-accessible content in eliciting desired user responses due to subtle changes in content design and appearance, making it challenging to determine the most effective variants for user interaction.
Innovation Solution
A compute device and method that obtain samples of network-accessible content, determine the presence of multiple variants, and monitor statistical user interaction tests to detect the final variant and discontinuation of others, providing data on the most effective content configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple variants of network-accessible content are tested simultaneously, then the ability to identify the most effective variant is improved, but the complexity of monitoring and analyzing the tests increases
Solution Approach 1:
The patent segments the content variants into distinct samples that can be independently obtained and analyzed. The monitoring system divides the analysis into separate steps: obtaining samples, determining presence of multiple variants, and monitoring statistical tests. This segmentation allows the system to handle multiple variants without overwhelming complexity by processing them in discrete, manageable units.
Solution Approach 2:
The system performs preliminary actions by obtaining and analyzing content samples before conducting full statistical testing. The compute device first determines whether multiple variants are present in the samples before initiating comprehensive monitoring of user interaction tests. This preliminary detection phase reduces the overall complexity by filtering out cases that don't require full monitoring analysis.
2Reliability
If statistical user interaction tests are monitored continuously, then the reliability of test results is improved, but the time required to complete analysis increases
Solution Approach 1:
The patent implements feedback mechanisms where the compute device continuously monitors user interaction data and uses this feedback to determine when sufficient data has been collected. The system adjusts its monitoring based on the statistical significance of the results, allowing it to stop monitoring when reliability thresholds are met, thus reducing unnecessary time loss while maintaining result reliability.
Solution Approach 2:
The patent replaces continuous manual monitoring with automated computational analysis. The compute device uses algorithms to automatically analyze user interaction data, determine statistical significance, and identify the final variant without requiring continuous human intervention. This substitution maintains high reliability through systematic analysis while significantly reducing the time investment required.
Data Source
AI summary
Technologies for detecting and analyzing user interaction tests for network-accessible content include a compute device. The compute device includes circuitry configured to obtain samples of network-accessible content. The circuitry is additionally configured to determine, based on the obtained samples, whether multiple variants of the network-accessible content are present. Further, the circuitry is configured to monitor, in response to a determination that multiple variants are present, a statistical user interaction test associated with the variants, including detecting a final variant and discontinuation of other variants in the statistical user interaction test. Additionally, the circuitry is configured to provide data indicative of the detected final variant of the network-accessible content.