Survey Distribution System Propensity Scoring
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Solution Overview
Problem
Conventional survey methods often result in inaccurate representations of user preferences and opinions due to broad population selection and variable response rates influenced by timing and surveyor factors, leading to low response rates and disrupted accuracy.
Innovation Solution
A survey distribution system that selects a subset of users based on specific attributes, calculates propensity scores to determine exposure likelihood, and uses these scores to identify and engage a control group for comparative analysis, ensuring accurate representation and response rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If surveys are distributed to a broad population, then the survey coverage is increased, but the accuracy of representing user preferences deteriorates
Solution Approach 1:
The patent segments the broad population into distinct groups based on propensity scores calculated from user attributes and behavior data. This segmentation allows the system to identify and survey specific subsets of users who are most likely to respond, thereby maintaining survey coverage while improving the accuracy of representing user preferences through targeted sampling.
2Adaptability or versatility
If surveys are conducted at different times and by different surveyors, then the operational flexibility is increased, but the response rate accuracy deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors survey response rates and adjusts survey distribution strategies based on performance data. By analyzing which time periods and surveyors yield better response rates, the system can optimize future survey distributions to maintain operational flexibility while improving response rate accuracy through data-driven decisions.
3Measurement precision
If propensity score calculation is implemented to identify target users, then the survey accuracy is improved, but the system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating propensity scores for users based on their attributes and behavior data before survey distribution. This pre-processing step creates a ready-to-use scoring system that simplifies the actual survey selection process, improving survey accuracy while managing system complexity through advance preparation of user segmentation data.
Data Source
AI summary
A survey distribution system receives a selection of a first subset of a user population. For example, an administrator of the system may select one or more user attributes of the users among the user population. In response, the survey distribution system identified the first subset of users based on the selected attributes. In some example embodiments, the administrator of the system may additionally define a maximum or minimum number of users to be exposed to the content, as well as targeting parameters for the content, such as a period of time in which to distribute the content to the first subset of users, as well as location criteria, such that the content may only be distributed to users located in specific areas.