Targeted Offer Delivery via Composite Scoring
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Solution Overview
Problem
Conventional advertising methods often result in low return on investment as offers are directed to a general audience, with many recipients having no interest in the product, especially when targeting digital wallet users, leading to inefficient use of resources.
Innovation Solution
A method and system that utilize a processor to determine whether to provide targeted offers for digital wallet products by assigning values to demographic and transaction history parameters, applying algorithms like logistic regression, decision tree, or support vector machine models to calculate a composite score, and deciding on offer delivery based on this score compared to a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If conventional advertising methods are used to direct offers to a general audience, then the coverage and reach of advertising is improved, but the return on investment deteriorates due to low customer interest
Solution Approach 1:
The patent segments the general audience into targeted customer groups based on demographic parameters (age, gender, location) and transaction history parameters. This segmentation allows offers to be directed only to relevant segments, improving ROI while maintaining adequate coverage through multi-channel delivery (email, SMS, mobile alerts).
Solution Approach 2:
The patent applies local quality by tailoring offer parameters and selection criteria to specific customer segments rather than using a uniform approach. Different parameter combinations are used for different customer groups, making the advertising quality locally optimized for each segment's characteristics and behavior patterns.
2Device complexity
If offers are directed to a general audience, then the simplicity of the advertising system is improved, but the effectiveness of the offer delivery deteriorates
Solution Approach 1:
The patent performs preliminary actions by pre-calculating composite scores for potential recipients based on their demographic and transaction parameters before offer delivery. This advance scoring and filtering ensures that only high-probability candidates receive offers, significantly improving delivery effectiveness while automating the complexity through processor-based algorithms.
Solution Approach 2:
The system uses self-service by automatically selecting offer recipients based on predefined parameter criteria and composite score calculations, eliminating the need for manual audience selection. The processor-based system autonomously evaluates parameters and makes delivery decisions, improving effectiveness without proportionally increasing operational complexity.
3Ease of manufacture
If traditional advertisement techniques are used, then the ease of implementation is improved, but the productivity of customer acquisition deteriorates
Solution Approach 1:
The patent replaces manual mechanical selection processes with automated processor-based systems that calculate composite scores and select recipients algorithmically. This substitution maintains ease of implementation through standardized computational procedures while dramatically improving customer acquisition productivity by efficiently processing and evaluating large numbers of potential recipients.
Data Source
AI summary
A method for providing an offer to a potential recipient is provided. The method includes obtaining first information, such as demographic information and/or shopping history information, that relates to the potential recipient; assigning a respective value to each of a plurality of first parameters based on the first information; assigning a respective value to each of a plurality of second parameters based on second information that relates to the offer; determining a composite score based on the assigned first parameter values and the assigned second parameter values; and determining, based on the composite score, whether to provide the offer to the potential recipient.