Conjoint Analysis with pandas and Statsmodels
Conjoint analysis is a multivariate technique used to evaluate customer responses and preferences towards specific combinations of product attributes that simulate potential products.
Just asking customers what they want is not enough. Customers usually want everything, but they are not willing to pay for everything. Conjoint analysis avoids this problem by asking customers to choose between two or more product bundles that differ in the levels of the product attributes. It can also be used to evaluate customers’ willingness to pay for different product attributes.
In this chapter, you will cover the following topics:
- An introduction to conjoint analysis
- Setting up a conjoint study
- Conducting conjoint analysis in Python
By the end of this chapter, you will understand the steps needed to conduct a conjoint survey, the fundamentals of the regression model, and how to do the analysis in Python.
