Market Research Conjoint Analysis Service

Conjoint Analysis is Statistical Analysis technique used in market research to determine how people value dissimilar features that make up an being product or service. Conjoint Analysis presents conception to respondents. However, instead of giving a single concept for each respondent, each of the respondents is showing too many concepts. The goal of Conjoint Analysis is to determine the alignments of limited number of attributes are the most influential on respondent choice or decision making. A controlled set of potential products or services is shown the respondents and by analyzing how they make preferences between these products, the implicit valuation of the individual elements making up the product or service can be determined. This implicit valuation can be used to create a market models that approximate market share, revenue and even effectiveness of new designs.

Conjoint Analysis is originated in mathematical psychology and was developed by the marketing professor Paul Green at the University of Pennsylvania and Data Chan. Other prominent Conjoint Analysis pioneers are professor V. Srinivasan of Stanford University who developed linear programming procedure for rank ordered data as well as self explicated approach. Today it is used in many of the social sciences and applied sciences including marketing, product management, and operations research. It is used to test frequently the customer who acceptance of new product designs, in assessing the appeal of advertisements and in service design. It has been used in product positioning, but there are some who raise problems with this application of Conjoint Analysis.

Conjoint Analysis techniques may also be referred as multi-attribute compositional modelling, isolated choice modelling, or stated preference research, and is part of broader set of trade off analysis tools used for systematic analysis of decisions. These tools are includes Brand Price Trade Off, Simalto, and mathematical approaches such as evolutionary algorithms or Rule Developing Experimentation.

Data for Conjoint Analysis is the most commonly gathered information through market research survey, although Conjoint Analysis can also be applied to carefully designed configuration or data from an correctly design test market research. Market research rules of thumb apply with regard to statistical sample size and accuracy when scheming Conjoint Analysis interviews.

The length of research survey depends on the number of attributes to be assessed and the method of Conjoint Analysis in use. The typical Adaptive Conjoint survey with 20-25 attributes may take more than 30 minutes to complete. Choice based conjoint, by using a smaller summary set circulated across the sample for entire steps completed in less than 15 minutes. Choice exercises may be displayed as store front type layout or in the some other replicated shopping environment.

Conjoint Analysis services from Informatics Outsourcing

• For each action, respondents are required to make hypothetical trade-offs between products.
• Each respondent is forced to make trade-offs between product features, much as consumers are forced to do when they are actually shopping.
• Each respondent answers a series of questions; in each question the combination of features shown together changes. In this way, a large number of product features can be estimated.