Segmented Promotion Testing for Consumer Behavior Prediction
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Solution Overview
Problem
Current promotion optimization methods rely on backward-looking, aggregate historical data, which fails to account for unanticipated events and individual consumer behavior, leading to inefficient promotion strategies and potential long-term damage to brand equity.
Innovation Solution
Implement a forward-looking approach by administering test promotions on purposefully segmented subpopulations to gather actual revealed preferences, allowing for iterative testing and validation of promotion variables to optimize general public promotions effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If backward-looking aggregate historical data is used for promotion optimization, then data collection is simple, but measurement precision and reliability of promotion effectiveness are insufficient
Solution Approach 1:
The patent segments the general population into multiple subpopulations and administers different test promotions to each segment. This segmentation allows for more precise measurement of promotion effectiveness by isolating variables and reducing noise from unanticipated events, directly addressing the measurement precision problem while maintaining manageable system complexity through structured experimentation.
Solution Approach 2:
The patent implements preliminary testing with subpopulations before launching general promotions. This preliminary action allows validation of promotion variables and prediction of consumer behavior in advance, improving measurement precision by gathering actual revealed preferences rather than relying on imperfect historical aggregate data.
2Reliability
If test promotions are administered on purposefully segmented subpopulations, then prediction accuracy of consumer behavior improves, but device complexity and testing effort increase
Solution Approach 1:
The patent divides the population into purposefully segmented subpopulations to test different promotion variables. This segmentation improves reliability of consumer behavior prediction by controlling for external factors and isolating promotion effects, while the structured approach to segmentation prevents system complexity from becoming unmanageable.
Solution Approach 2:
The patent systematically varies promotion variables (discount depth, duration, type) across different subpopulations to observe effects on consumer behavior. This parameter changes approach improves prediction reliability by gathering comprehensive data on variable impacts, while the methodical variation keeps the testing system organized and manageable.
3Productivity
If iterative testing and validation of promotion variables is implemented, then promotion optimization effectiveness improves, but loss of time and productivity increase
Solution Approach 1:
The patent conducts preliminary iterative testing with subpopulations to validate promotion variables before full-scale implementation. This preliminary action improves promotion optimization effectiveness by identifying effective variables in advance, while limiting the iterative process to test phases rather than continuous cycles reduces time loss.
Solution Approach 2:
The patent implements feedback loops where test promotion results from subpopulations inform subsequent testing and final promotion design. This feedback mechanism improves optimization effectiveness by continuously refining promotion variables based on actual consumer responses, while structured feedback cycles prevent indefinite iteration and associated time losses.
Data Source
AI summary
Methods and apparatus for implementing forward looking optimizing promotions by administering, in large numbers and iteratively, test promotions formulated using highly granular test variables on purposefully segmented subpopulations. The plurality of test promotions are associated with at least one behavioral economics principles. The responses from individuals in the subpopulations are received and analyzed. The analysis result is employed to subsequently formulate a general public promotion.