Conjoint analysis

Conjoint analysis is a survey-based statistical technique used in market research that helps determine how people value different attributes (feature, function, benefits) that make up an individual product or service.

Conjoint analysis originated in mathematical psychology and was developed by marketing professor Paul E. Green at the Wharton School of the University of Pennsylvania.

Other prominent conjoint analysis pioneers include professor V. "Seenu" Srinivasan of Stanford University who developed a linear programming (LINMAP) procedure for rank ordered data as well as a self-explicated approach, and Jordan Louviere (University of Iowa) who invented and developed choice-based approaches to conjoint analysis and related techniques such as best–worst scaling.

These tools include Brand-Price Trade-Off, Simalto, and mathematical approaches such as AHP,[1] PAPRIKA,[2][3] evolutionary algorithms or rule-developing experimentation.

Using relatively simple dummy variable regression analysis the implicit utilities for the levels could be calculated that best reproduced the ranks or ratings as specified by respondents.

Originally, choice-based conjoint analysis was unable to provide individual-level utilities and researchers developed aggregated models to represent the market's preferences.

With newer hierarchical Bayesian analysis techniques, individual-level utilities may be estimated that provide greater insights into the heterogeneous preferences across individuals and market segments.

Market research rules of thumb apply with regard to statistical sample size and accuracy when designing conjoint analysis interviews.

The actual estimation procedure will depend on the design of the task and profiles for respondents and the measurement scale used to indicate preferences (interval-scaled, ranking, or discrete choice).

Students are segmented by academic year (freshman, upper classmen, graduate studies) and amount of financial aid received.

Using these utility scores, market preference for any combination of the attribute levels describing potential apartment living options may be predicted.

[citation needed] The market research approach, Mind Genomics (MG), is an application of Conjoint Analysis (CA).

[6] Nonetheless, legal scholars have noted that the Federal Circuit's jurisprudence on the use of conjoint analysis in patent-damages calculations remains in a formative stage.