Full Profile Conjoint
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Full Profile Conjoint Analysis
Conjoint Analysis assumes that consumers may be able to evaluate a range of products/services along some key dimensions. These dimensions are called attributes, i.e. flavor, brand name, color, shape, price etc. Each attribute  may have more than two levels, e.g.  flavor might have levels of "lime", "lemon", "orange", etc. Attributes correspond to key dimensions of the product/service and levels of attributes correspond to points along those dimensions (various types and degrees of functionality).

Conjoint analysis constructs a series of product profiles (concepts), based on design specifications. Each concept, (which may be a card or a real mock-up or a virtual computerized mock-up product, each time depending on the means of collecting the data), represents a possible product or service.  

During the full profile conjoint task,  the respondent rates each of these products on scales, such as likelihood of purchase. We are asking respondents to make judgments on the likelihood of choosing an alternative product/service.

The steps we follow in designing  a full profile conjoint study are the following:

Develop the list of attributes and levels
Generate and select the full profile design
Test assumptions
Modify the design

In some cases, in order to develop a list of attributes we may need the help of Clients' expert judgments, which will be verified through qualitative research with the use of Repertory Grid Analysis.

Conjoint Analysis provides a quantitative estimate of how each level impacts on the decision. The utility function contains these quantitative estimates for each attribute.  For categorical attributes, the utility function consists of Part-Worth estimates for each level of the attribute. For quantitative attributes, there are two models; the Vector model, which assumes linear reaction between the levels of the attribute and the Ideal-Point model, which describes a curvilinear relation between the level of quantitative attribute and its utility.

Market simulations are the bottom line of Conjoint Analysis. After having determined the best way to model our results and cleaned our data, we can model how each respondent would evaluate any product or service, defined by the attributes and the levels in the study. The market simulation models use this information to predict, how each respondent would choose among alternative products. We forecast share of choosing products or services under a wide variety of scenarios.

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