Conjoint Analysis

Conjoint analysis is a very popular method used in Marketing Research and price origination. Its primary goal is to identify preferred features of a good and to measure how change in price influences its demand.

Instead of conducting a direct customer survey which asks which particular feature they would prefer conjoint analysis is asking potential customers to measure various combinations of product features. Each combination is contained of numerous conjoined product attributes (hence "conjoint").

There are various ways to measure these preferences. One of the most frequently used applications is Choice-Based Conjoint. In CBC surveyors are given different product concepts and then are asked to identify the variant they would prefer. Before CBC technique, the conjoint analysis was presenting products to respondents one at a time. However, consequent variants of conjoint analysis was presenting goods in pairs (CVA or ACA for Adaptive Conjoint Analysis), or different combinations at a time (for CBC or ACBC for Adaptive CBC).

During the analysis respondents complete roughly 10 to 25 conjoint questions. These questions are crafted, to make the features of the product most optimally balanced. Showed independently and evaluating the variety of responses a statistician can infer which particular attributes are most impactful and deciding the final choice. This is different from more basic techniques which ask consumers about their preference of an individual feature because it shows the propensity for a tradeoff.

The output is a combination of scores (frequently referred as "part-worth utilities") for each feature included in the study.

What makes conjoint analysis so useful is that it allows ranking the products instead of simply knowing how good they are bringing it to the common denominator. This common denominator, of course is the price the customer (in theory) should be willing to pay.