Heuristic-Based Message Testing System for Discriminating Scores
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Solution Overview
Problem
Conventional message testing methodologies, such as choice-based message selection models, are limited in testing a large number of messages, produce non-discriminating scores, and do not account for individual respondent-level choice drivers, leading to inefficient and inaccurate results.
Innovation Solution
A heuristic-based system and method that identifies language in messages, determines associated heuristics, generates modified versions of messages, and uses machine learning and artificial intelligence to optimize message bundles and selection processes, allowing for personalized message testing and optimization across various communication channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional choice-based message selection models are used to test messages, then message testing can be conducted, but the number of messages that can be tested is limited and scores are non-discriminating
Solution Approach 1:
The patent segments the message testing process into multiple independent choice exercises, where respondents evaluate different sets of messages across multiple rounds. This segmentation allows testing of a larger total number of messages while maintaining score discrimination through aggregated response patterns across segments.
Solution Approach 2:
The patent presents only a subset of messages to each respondent in each choice exercise, rather than all messages simultaneously. This partial action approach enables testing of many more messages overall by rotating different message subsets across multiple exercises and respondents, while the aggregation of partial responses produces discriminating scores.
2Measurement precision
If conventional choice-based message selection models are used, then message testing can be conducted, but individual respondent-level choice drivers are not accounted for, leading to inefficient and inaccurate results
Solution Approach 1:
The patent implements feedback loops where respondent choices in each exercise inform the selection and presentation of messages in subsequent exercises. The system learns from individual respondent preferences and adjusts message presentation accordingly, accounting for respondent-level choice drivers while maintaining manageable system complexity through iterative refinement.
Solution Approach 2:
The patent creates a dynamic testing system where message sets, respondent assignments, and exercise configurations adapt based on accumulated response data. This dynamic adjustment allows the system to account for individual respondent characteristics and choice drivers without requiring a completely complex predetermined structure.
3Adaptability or versatility
If conventional methodologies test only original messages, then testing can be conducted, but opportunities to improve messages are limited
Solution Approach 1:
The patent performs preliminary analysis of message performance data to identify patterns, strengths, and weaknesses before finalizing message bundles or making optimization decisions. This preliminary action enables systematic message improvement while keeping the testing process straightforward by preparing optimized message sets in advance based on accumulated evidence.
Solution Approach 2:
The patent creates and tests multiple variations and copies of messages with different wording, framing, or presentation while maintaining the core message intent. This allows optimization of message effectiveness by comparing variants without requiring entirely new message creation, balancing adaptability with ease of testing.
Data Source
AI summary
A plurality of messages are received and for each respective one of the received plurality of messages: a series of steps can be performed, including identifying language in the respective message, determining at least one heuristic, generating a first modified version of the respective message and generating at least one second modified version of the respective message. The second modified version(s) include language not in the respective message and not in the first modified version of the respective message. Further the at least one second modified version represents the determined at least one other heuristic. A device can be prompted to respond to a survey that includes the respective message(s), at least one first modified version, and/or at least one second modified version. A second survey can be generated of the respective message(s), modified version(s), and/or second modified version(s).