Conjoint analysis
Conjoint analysis is a statistical technique used in market research to determine how people value different attributes (feature, function, benefits) that make up an individual product or service.
Overview[edit | edit source]
The objective of conjoint analysis is to determine what combination of a limited number of attributes is most influential on respondent choice or decision making. A controlled set of potential products or services is shown to survey respondents and by analyzing how they make preferences between these products, the implicit valuation of the individual elements making up the product or service can be determined. These implicit valuations (utilities or part-worths) can be used to create market models that estimate market share, revenue and even profitability of new designs.
History[edit | edit source]
Conjoint analysis was developed from mathematical psychology and psychophysics. Around 1970 marketing professor Paul E. Green at the Wharton School of the University of Pennsylvania suggested the use of conjoint analysis as a tool in determining consumer behavior.
Methodology[edit | edit source]
Conjoint analysis techniques may also be referred to as multiattribute compositional modelling, discrete choice modelling, or stated preference research, and are part of a broader set of trade-off analysis tools used for systematic analysis of decisions. These techniques are also used in econometrics, political science, environmental studies, health care and many other areas.
Applications[edit | edit source]
Conjoint analysis is used in many of the social sciences and applied sciences including marketing, product management, and operations research. It is used frequently in testing customer acceptance of new product designs, in assessing the appeal of advertisements and in service design.
See also[edit | edit source]
References[edit | edit source]
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Contributors: Prab R. Tumpati, MD