A statistical technique which keeps the track of how people react on various features of individual product and service is defined as conjoint analysis. In market research the objective that conjoint analysis carries is to be certain about what combination should be in attributes that has impact on decision making or respondent choices.
- The technique is most widely used quantitative methods in marketing research, it carries the information on how the price changing is affecting demand-supply in market, it consists the data how well response is for a new product among consumers. This design shows how consumers are making their choices among new products, how they are deciding on certain depending on its special attributes.
- The origin of conjoint analysis is born from the mathematical psychology, marketing Professor Paul Green at the Wharton School of the University of Pennsylvania and Data Chan established existence of this concept.
Books on Conjoint analysis
Book 1 –
Linking Conjoint Analysis and QFD: Analyzing and Extending Conjoint Analytical Methodologies to Support Large Industrial Applications By Bernd Österreicher (published by diplom.de, 1999)
Book 2 –
Analyzing Decision Making: Metric Conjoint Analysis By Jordan J. Louviere (published by SAGE, 1988)
How Conjoint Analysis works?
- There are several activities in conjoint analysis, with which company analyze the situation.
- First and foremost should be choosing product attributes as example, outer impression, price or size.
- Then comes the values or options of each attributes, for example, on the subject of size, there may be options of 5”, 10” or 20”, it is seen that the higher number of options used for each attributes, it enlarges the burden on respondents too.
- After that, description of products depending on the combination of attributes options.
- then, choosing the form of combination in which the attributes are going to be presented to the respondents, verbal presentation pictorial presentation and paragraph description are used form in this criteria.
- On the next step, the decision is taken in what mode responses will be taken, there are three choices, individual responses, bundle all responses in one utility function, and categorize the similar responses.
- Lastly, selection of the technique how the collected data will be used, there are three different model by which the raw data is transmitted through a useful data, like the Part worth model, Vector (Linear) model and Ideal-point model.
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