Understand and measure purchasing decisions

IBM® SPSS® Conjoint helps market researchers increase their understanding of consumer preferences so they can more effectively design, price and market successful products. It enables them to model the consumer decision-making process so they can design products with the features and attributes most important to their target market.

SPSS Conjoint includes procedures that can help researchers:

Orthogonal design

The output for the orthogonal design has one row for each profile, with the factors displayed as columns. A footnote lets the experimenter--but not the other test subjects-- know which cases, if any, are holdouts.

Orthogonal design

Results table

This table gives the predicted probabilities of choosing each of the simulation cases as the most preferred one, under three different probability-of-choice models.

Results table

Simulation cases

The real power of conjoint analysis is the ability to predict preference for product profiles that weren't rated by the subjects. These are referred to as simulation cases. Simulation cases are included as part of the plan, along with the profiles from the orthogonal design and any holdout profiles.

Simulation cases

Utility scores

This table shows the utility (part-worth) scores and their standard errors for each factor level. Higher utility values indicate greater preference.

Utility scores

Design an orthogonal array of product attribute combinations

Produce and print cards

Analyze research data

SPSS Conjoint resources

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Understand and measure purchasing decisions

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