Conjoint Analysis

One of the increasingly popular techniques being used in new product development is an analytical technique called conjoint analysis (CA). The early academic work on CA was done by Paul Green in the 1960s and since then it has widely been used in various contexts and applications. In essence, conjoint analysis is a marketing technique for predicting how developed or redesigned products or services would perform when taken to the market. By selecting the right features (attributes) of a product or service and setting the right price for a given product, companies can “win over” consumers and maximize sales. In practice, if one asks consumers what features they want in a product they would probably indicate that they wish for everything, but this is often not feasible in the real world. In complex real-world situations, one has to make compromises between various features composing a product. Because it is impossible to have absolutely everything requested by consumers, Green suggests a technique in which consumers are faced with pairs or groups of products that are composed of a combination of various features (attributes) and are asked directly which one they prefer the most. Conjoint analysis facilitates gaining key insights into consumer choice and allows companies to target distinct market segments by making more than one version of a product. From a social scientific standpoint, CA differs from common survey approaches that ask respondents what is important in a product and how much they are willing to pay. Instead, respondents choose from realistic product options as they would in the real world. The most commonly used applications of CA approach include, but are not limited to the following areas:

• Consumer electronics
• Automobiles
• Consumer packaged goods
• Insurance and banking services
• Telecom and Internet service providers
• Health care decisions
• Environmental impact
• Job selection and workplace loyalty
• Travel and tourism industry

This entry discusses various issues relevant to CA and in the following sections explains procedures that need to be conducted in every CA study. It also discusses the basic steps in performing CA. It further explains the importance of attributes selection by choosing a smartphone case for illustrative purposes. Moreover, this entry outlines the statistical techniques being used in CA to deal with situations in which there are many conjoint profiles to be assessed. Finally, it explains how to perform the reliability and validity tests in CA research and presents some of the advantages and disadvantages of CA.