An introduction to conjoint analysis
Conjoint analysis provides analysts with insights into customers’ product preferences and allows them to identify the most important product attributes and attribute combinations most appealing to customers.
It is based on customer feedback data on a select number of products that are each designed around different levels of the same product attributes (known as product bundles). The product bundles are designed to represent the full range of possible product attribute combinations.
Regression analysis decomposes these product bundles such that the utility (also referred to as value or part-worth) customers assign to the various levels of each of the product attributes can be derived.
Rather than asking directly about their product preferences (“How much would you like to pay to purchase a mutual fund?”), conjoint analysis asks customers to choose between two or more product bundles that differ in the levels of the...
