Response Attribution Valuation Using Time Delay Regression
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Solution Overview
Problem
Current marketing technologies struggle to accurately attribute responses to multiple promotions across marketing campaigns, especially when responses are not directly identifiable, leading to incomplete credit assignment and inefficient resource allocation.
Innovation Solution
A computer-implemented method using a regression model that calculates response attribution values by retrieving and iteratively updating response rate and time delay distribution parameters, allowing for accurate credit assignment to promotions based on response rate and time delay analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct response attribution is used to determine promotion effectiveness, then each response can be easily associated with identifying information about the promotion, but responses that do not provide identifying information cannot be attributed to specific promotions
Solution Approach 1:
The patent introduces time delay distribution as an intermediary parameter to indirectly link responses without promotion identification information to their causative promotions. By modeling the temporal relationship between promotion delivery and response occurrence, the system can attribute responses to promotions even when direct identification information is absent, thus resolving the contradiction between measurement precision and information loss.
Solution Approach 2:
The patent replaces the mechanical system of direct promotion identification (requiring explicit response data containing promotion IDs) with a statistical modeling approach using time delay distributions and regression analysis. This substitution allows attribution of responses to promotions based on temporal patterns rather than direct identification, overcoming the limitation of information loss while maintaining attribution accuracy.
2Adaptability or versatility
If multiple promotions are run across marketing campaigns, then marketing coverage and reach are improved, but it becomes difficult to determine the contribution of each individual promotion to a response
Solution Approach 1:
The patent segments the overall marketing campaign into individual promotion components, each with its own time delay distribution parameters. By calculating separate response attribution values for each promotion based on their specific temporal characteristics, the system can measure the contribution of individual promotions within multi-promotion campaigns, thus resolving the contradiction between campaign flexibility and measurement precision.
Solution Approach 2:
The patent changes the parameters used for measuring promotion effectiveness from simple response counts to time delay distribution parameters and response attribution values. By incorporating temporal parameters that capture the relationship between promotion delivery and response timing, the system can accurately measure individual promotion contributions even when multiple promotions are running simultaneously, maintaining both campaign versatility and measurement precision.
3Measurement precision
If response attribution values are calculated using iterative regression modeling, then credit assignment to promotions becomes more accurate, but computing resources and time are consumed
Solution Approach 1:
The patent implements feedback through iterative regression modeling, where each iteration refines the time delay distribution parameters and response attribution values based on previously calculated results. This feedback mechanism progressively improves credit assignment accuracy by incorporating lessons from previous iterations, while the iterative nature allows for early termination when convergence is achieved, balancing precision with computational efficiency.
Solution Approach 2:
The patent applies partial action by allowing the iterative calculation process to terminate early when a sufficient level of accuracy is achieved or when convergence criteria are met, rather than always completing the full iterative process. This approach provides adequate credit assignment accuracy for practical purposes while reducing unnecessary consumption of computing resources and time, thus resolving the contradiction between precision and productivity.
Data Source
AI summary
A computer-implemented method is described for determining a response attribution value that represents a credit assignment to a communication, for an associated response received from a recipient during a marketing campaign.