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This post will walk you through how to format your respondent-level conjoint data when programmed using your survey platform of choice. There are many survey…

In a standard choice experiment, respondents are presented with alternatives which have a common set of attributes. Alternative-specific designs relax this requirement and are designed to…

Choice-based conjoint (CBC) studies usually specify a fixed number of levels for each attribute. The resulting attribute then becomes categorical. But that doesn’t mean you…

Modern tools for analyzing conjoint analysis, such as hierarchical Bayes, produce rich data showing preferences for each person in a market. The main deliverable from…

Indifference curves are a way of showing relative preferences for quantities of two things (e.g., preferences for price versus delivery times for fast food). This…

In this blog post, I describe the Efficient algorithm for generating choice model designs. This algorithm is used for generating choice model designs with partial profiles,…

While choice-based conjoint analysis represents one of the more sophisticated techniques used in market research, presentation of its results commonly consists only of a simulator,…

In a stated preference discrete choice experiment, respondents are asked a number of questions. Each question asks them to choose between a number of alternatives…

Today, you can produce a wide range of choice model experimental designs with numerous different algorithms. But with all this design diversity, how do you…

Choice experiments, also known as choice-based conjoint (CBC), are widely used for predicting the performance of new products and changes to products’ designs and portfolios.…

This post introduces the key concepts in designing experiments for choice-based conjoint analysis (also known as choice modeling). I use a simple example to describe…

Working out the sample size required for a choice-based conjoint study is a mixture of art and science. What makes it tricky is that the…

The hard bit of designing a choice-based conjoint analysis (choice modeling) study is creating the experimental design. However, there are a few others parts of…

Ready to dive further into conjoint analysis? In this post I describe the main applications of choice-based conjoint analysis (choice modeling; CBC). If you haven’t…

Choice-based conjoint analysis is a technique for quantifying how the attributes of products and services affect their performance. It is used to help decision makers…

In this article I will go through the basics of fitting a choice model to discrete choice experiment data in Q. I’m going to assume…

D-error is a way of summarizing how good a design is at extracting information from respondents in a choice experiment. In other articles I provide…

Running a survey can be expensive and time-consuming. Luckily you can use simulated data to check and compare your survey design, saving you time and…