Promotion Response Tracking via Treatment Instance Segmentation
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Solution Overview
Problem
Managing promotions across various industries, such as financial services and retail, is challenging due to the diverse types of promotions and contact entities, leading to complex tracking and analysis requirements.
Innovation Solution
A computer-implemented method for response tracking that attributes responses to treatment instances within a marketing campaign, using a response table with entries based on attribution rules, including direct and inferred responses, to generate a response tracking report.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If promotions are tracked and logged for future analysis across various industries and contact entities, then the ability to analyze and improve promotions is enhanced, but the complexity of managing and tracking diverse promotion types increases
Solution Approach 1:
The patent segments promotion tracking into distinct treatment instances, each representing a specific promotion version assigned to a group of contact entities. This segmentation allows for granular tracking of responses to individual promotions while managing complexity through structured organization of promotion data into actionable units.
Solution Approach 2:
The patent introduces treatment instances as intermediary entities that bridge promotions and responses. Treatment instances serve as mediators that capture the relationship between promotion versions and contact entities, enabling precise attribution of responses to specific promotions without requiring direct complex mappings between all promotion types and all contact entities.
2Measurement precision
If multiple attribution rules are applied to credit treatment instances for responses, then the accuracy of campaign performance assessment improves, but the complexity of response tracking and analysis increases
Solution Approach 1:
The patent implements dynamic attribution rules that can adaptively credit treatment instances based on response characteristics. The system dynamically determines which attribution rule to apply (first, second, or third rule) based on the specific response data available, allowing for flexible and accurate attribution without requiring a static complex rule set for all scenarios.
Solution Approach 2:
The patent changes the parameters of attribution based on response types and available data. Different attribution rules adjust the credit distribution parameters among treatment instances depending on whether the response is direct or inferred, and what tracking information is available, optimizing attribution accuracy for different scenarios rather than applying a single complex rule universally.
3Measurement precision
If direct and inferred responses are differentiated and tracked separately, then the precision of campaign analysis is improved, but the difficulty of detecting and measuring response types increases
Solution Approach 1:
The patent performs preliminary classification of responses into direct or inferred types before applying attribution rules. By pre-categorizing responses based on the presence of tracking codes and response data, the system simplifies the subsequent attribution process, making detection and measurement more manageable while maintaining precision in distinguishing response types.
Data Source
AI summary
A computer implemented method for response tracking is described. The method includes obtaining one or more responses to one or more promotions, attributing the one or more responses to one or more treatment instances, with the one or more treatment instances correspond to a promotion version assigned to a group of contact entities at an execution of a computer implemented marketing campaign, and generating a response table, the response table including one or more entries, the entries in the response table being in accordance with attribution of the one or more responses to one or more treatment instances.