Segmented Impact Analysis for User Action Valuation
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Solution Overview
Problem
Existing methods for determining the value of user actions on websites are inaccurate because they do not consider specific user information, leading to 'like-to-like' comparison issues and inaccurate representation of action values.
Innovation Solution
Implementing segmented impact analysis that compares users based on demographics, purchase history, search history, and other characteristics to determine the value of actions by identifying similar users and calculating the difference in spending patterns between those who perform and those who do not perform specific actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If anonymous data from overall population is used to determine action values, then data availability is improved, but measurement precision deteriorates due to inapplicability to specific users
Solution Approach 1:
The patent segments the overall user population into distinct groups based on demographics, purchase history, search history, and device characteristics. By dividing users into segments (e.g., new users vs. returning users, mobile vs. desktop, different demographic groups), the system can calculate action values for each segment separately, making the values more applicable and accurate for specific users while still utilizing data from multiple users within each segment.
2Measurement precision
If user-specific information is incorporated to improve action value accuracy, then measurement precision is improved, but device complexity increases due to additional data processing requirements
Solution Approach 1:
The system pre-segments users into groups based on their characteristics and calculates action values for each segment. This segmentation approach simplifies the complexity by organizing user data into manageable categories rather than processing individual user data separately, while still maintaining accuracy through segment-specific calculations.
Solution Approach 2:
The system performs preliminary segmentation and action value calculation for common user scenarios and segments. By pre-calculating action values for typical user segments and scenarios, the system reduces the complexity of real-time calculations while maintaining accuracy through the use of pre-computed segment-specific values.
3Measurement precision
If segmented impact analysis is implemented to improve recommendation relevance, then measurement precision is improved, but loss of time increases due to additional processing steps
Solution Approach 1:
The system pre-segments users and pre-calculates action values for common segments and scenarios. By having segmentation and baseline action values ready in advance, the system minimizes the time required for real-time recommendation generation while maintaining high relevance through segment-specific calculations.
Solution Approach 2:
The system applies segmented impact analysis selectively to high-value decisions and scenarios where precision is most critical, rather than uniformly to all recommendations. This partial application of segmentation reduces overall processing time while maintaining recommendation relevance for the most important cases.
Data Source
AI summary
Devices and methods are provided for used segmented impact analysis to determine high-valued computer-based actions. The device may determine a first user account associated with performance of a first computer-based action and a second computer-based action associated with a network-accessible resource. The device may determine a second user account associated with performance of the first computer-based action, but not with the second computer-based action. The device may determine a first value for the first user account, the first value based on the performance of the second computer-based action. The device may determine a second value for the second user account, the second value based on the failure to perform the second computer-based action. The device may determine a third value, wherein the third value is a difference between the first value and the second value. The device may send the third value with a product recommendation.