Conjoint Analysis is a procedure for measuring, analyzing, and predicting customer’s responses to new products and to new features of existing products. It enables companies to fester customer’s preferences for products into part-worth utilities associated with each option of each attribute or feature of the product category. Companies can then recombine the part-worth to predict customer’s preferences for any combination of attribute options, to determine the optimal product concept or to identify market segments that value a particular product concept highly.

Factors and their values are defined by the researcher in advance. The various combinations of the factor values yield fictive products that are being ranked by the interviewed persons. With Conjoint Analysis it is possible to derive metric partial utilities from the ranking results. The summation of these partial utilities therefore results in metric total utilities.

Conjoint Analysis

· Independent variables: Object attributes.

· Dependent variable: Preferences of the interviewed person for the fictive products.

· The utility structure of a number of persons can be computed through aggregation of the single results.

Conjoint Analysis

· Factors and Factor Values

o Important for the choice of factors and their values are

§ Relevance

§ Interference

§ Independence

§ Realisable

§ Compensatory relationships of the various factor values

§ They do not constitute exclusion criteria

§ Terminable

Conjoint Analysis

Possibilities of rating of the incentives

· Ranking

· Rough classifications into groups of different utility with succeeding ranking within these groups.

· Aggregation of these results leads to a total ranking. Used when there are a large number of incentives.

· Rating scales

· Paired comparison

Conjoint Analysis

Estimation of the utility values

Conjoint Analysis is used to determine partial utilities (partworths) for all factor values based upon the ranked data. Furthermore, with this partworths it is possible to compute the metric total utilities of all incentives and the relative importance of the single object attributes.

Individual Conjoint Analysis: For each person utility values are computed.

Combined Conjoint Analysis: Only one value for each factor category.

Conjoint Analysis

Estimation of the utility values of target criterion for the determination of the partial utilities:

The resulting total utilities should yield a good representation of the empirically ranked data. Related procedure for the determination of the partial utilities: monotonous analysis of variance.

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