Conjoint analysis is a tool that allows a subset of the possible combinations of product features to be used to determine the relative importance of each feature in the purchasing decision. Conjoint analysis is based on the fact that the relative values of attributes considered jointly can better be measured than when considered in isolation.
multivariate statistical technique which analyses preferences for various combinations of attributes: e.g. "Would you rather have a can of cold fizzy soft drink, a glass of claret, or a cup of coffee with cream?' Conjoint analysis (derived from co nsidering joint ly) would separate out preferences for hot vs cold drinks, alcoholic vs non-alcoholic, colour, and container. Related to choice modelling. The information can come from either databases (see revealed preferences) or questionnaires (see stated preferences).
A quantitative market research technique for examining the trade-offs of a products attributes in order to determine a comparison of how potential customers value each attribute.
a broad collection of techniques that use experimental designs to derive the relative worth or value of a product based on respondents' willingness to trade-off each component of the offering. This term typically refers to methods that use rank-ordering or rating scales to evaluate preference of attribute combinations.
A statistical research method that involves the measurement of the collective effects of two or more independent variables (ie product attributes, eg color, size, ease of use, cost, etc.) on the classification of a dependent variable ("overall liking," purchase intention, "best buy," or any other evaluative measurement).
Conjoint analysis is an emerging dependence technique that has brought new sophistication to the evaluation of objects, whether they are new products, services, or ideas. The most direct application is in new product or service development, allowing for the evaluation of the complex products while maintaining a realistic decision context for the respondent (Hair et al., 1995).
A multivariate technique used to quantify the value that people associate with different levels of product/service attributes.
A research technique to determine the relative importance and appeal of different levels of an offering's attributes.
A quantitative market research technique which determines how consumers make trade-offs between a small number of different features or benefits.
A regression-based statistical technique that measures the value customers receive from a product or service. The name "conjoint" comes from the phrase "considered jointly", as in the product attribute trade-off's that consumers make. Conjoint analysis is of value if customers' decisions are rationally based and depend on many factors. It consists of three steps: design, execute, analyze. Design: define customer decision and identify product/service attributes. Execute: evaluate product/service concepts. Analyze: calculate relative importance of attributes, generate segments, simulate behavior.
See also: Conjoint analysis (in marketing), Conjoint analysis (in healthcare)