Consumer Research • Choice Models
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Choice Models
Fit Models for Choice Experiments
Use the Choice platform to analyze the results of choice experiments conducted in the course of market research. Choice experiments are used to help discover which product or service attributes your potential customers prefer. You can use this information to design products or services that have the attributes that your customers most desire.
The Choice platform enables you to do the following:
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Use information about subject (customer) traits as well as product attributes.
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Analyze choice experiments where respondents were allowed to select “none of these”.
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Integrate data from one, two, or three sources.
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Use the integrated profiler to understand, visualize, and optimize the response (utility) surface.
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Obtain subject-level scores for segmenting or clustering your data.
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Estimate subject-specific coefficients using a Bayesian approach.
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Use bias-corrected maximum likelihood estimators (Firth 1993).
Figure 4.1 Choice Platform Utility Profiler
Contents 
Overview of the Choice Modeling Platform
Examples of the Choice Platform
One Table Format with No Choice
Multiple Table Format
Launch the Choice Platform
Launch Window for One Table, Stacked
Launch Window for Multiple Tables, Cross-Referenced
Choice Model Report
Effect Summary
Parameter Estimates
Likelihood Ratio Tests
Bayesian Parameter Estimates
Choice Platform Options
Willingness to Pay
Additional Examples
Example of Making Design Decisions
Example of Segmentation
Example of Logistic Regression Using the Choice Platform
Example of Logistic Regression for Matched Case-Control Studies
Example of Transforming Data to Two Analysis Tables
Example of Transforming Data to One Analysis Table
Statistical Details for the Choice Platform
Special Data Table Rules
Utility and Probabilities
Gradients

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Help created on 10/11/2018