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The expression "a model is only as good as its inputs" is well-founded.

Chances are you would agree with our belief that people make choices by comparing what they want (desires) to what they believe is available to them (beliefs).

Unlike traditional models such as conjoint, discrete choice, and regression analyses, our choice model leverages existing market perceptions by collecting desires (what you want) and beliefs (what you believe you can get). It predicts choice by integrating desires and perceptions at the respondent level.

By contrast most conjoint and discrete choice models treat products and services as objective bundles of attributes (price, features, etc.) supplemented with brand attributes. They do not allow for respondent-by-respondent differences in how products are perceived at the attribute level.

We have learned that a company may be perceived as expensive (a weakness) but offering great service (a strength). It may be perceived as offering high quality products (a strength) but having too narrow a product line (a weakness). More simplistic treatments of "brand" make it difficult to identify perceived strengths and weaknesses, let alone leverage this vital information when predicting choice.
Modeling Characteristics: scope
Modeling Characteristics: measuring systems
"The best way to predict the behavior of an animal is to suppose it has beliefs and desires."

Daniel C. Dennett
(author of 8 books on cognition and Director of Cognitive Studies at Tufts University)
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