What is conjoint? What is maxdiff? how are they different? When should they be used? The family of discrete choice experiments is an important one for market researchers. While more advanced analytically, it is a simple survey technique that mimics real world choices. In this course, you will learn different use cases for conjoint and maxdiff, how to design a study, and how to analyze the data using R.
You should take this course if:
You are currently working or will work with product innovation teams
You want to learn advanced survey design
You want to know what “add-ons” will make a product package more enticing
Follow a Structured Curriculum
The problems with traditional survey questions
Conjoint and MaxDiff were created because of flaws in tradition survey questions, asked on likert scales. In this section will show you what those flaws are, and how discrete choice overcomes them.
In this section you’ll learn the theory behind MaxDiff and how to execute it in R.
Maximum difference and best-worst scaling
The basics of conjoint design
In this section you’ll learn the theory behind conjoint and how to execute it in R.
In this section you’ll learn what else you can do with conjoint, such as product simulators, segmentation, sensitivity plots, among others.
Executing and analyzing a choice-based conjoint
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