Conjoint analysis is mainly used to identify the most desirable combination of features to be offered in a new product or services.
In Conjoint analysis, respondent are told about the various combinations of features under consideration and are asked to indicate the combination they most prefer, to indicate the combination that is their preference and then in Conjoint analysis uses such preference data to identify the most desirable combination of features to be included in the new product or service.
Conjoint analysis applies a complex form of analysis of variance to the preference data obtained from each respondent. This analysis calculates a value for each feature. Features with the highest values are judged the most important to respondents.
Variables used in Conjoint Analysis:
Conjoint analysis is applied to categorical variables, which reflect different features or characteristics of the product or service under consideration. For example some new product if we take asset manager preference characteristics of interest to researchers could include i.e. Past performance of manager, his portfolio, his company, his way of investing or many other things.Conjoint Analysis Identifies Interdependencies among variables: Conjoint analysis differs from cross tabulation or regression in that it is not concerned primarily with a single dependent variable. Rather, conjoint analysis is like cluster and factor analysis in the sense that these methods try to identify the interdependencies which exist between number of variables.
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