Summary
In this chapter, we have learned how to perform conjoint analysis, which is a statistical tool that allows us to undercover consumer preferences that otherwise would be difficult to determine. The way in which we performed the analysis was by using OLS to estimate the performance of different combinations of features and try to isolate the impact of each one of the possible configurations in the overall perception of the client to undercover where the consumer perceives the value.
This has allowed us to create an overview of the factors that drive users to buy a product, and even be able to predict how a new combination of features will perform by using ML algorithms.
In the next chapter, we will learn how to adjust the price of items by studying the relationship between price variation and the number of quantities sold using price elasticity.
