Conjoint Analysis is a statistical tool that has its origins in mathematical psychology. It is also called ‘multi-attribute composition model’ or ‘stated preference analysis’ and is widely used in marketing, market research, operations research and product management. Its purpose is to determine how people perceive and value different features or attributes of a particular product or service.
Conjoint Analysis was developed by mathematics professor Paul Green at the University of Pennsylvania and Data Chan. Today it is one of the most popular quantitative research tools in market research to test consumer’s acceptance of product design, packaging, advertising and so on. Conjoint Analysis is also widely used in mathematical approaches like evolutionary algorithms, rule developing experimentation; other applied sciences and social sciences.
Say, you are a consumer goods company wanting to find out the brand preference for similar products based on your customer’s brand perception. You could study the available sales transaction data and analyze it to create a perceptual map using conjoint analysis. This would provide you a better understanding of the customer’s perception of different brands. This would in turn lead to better customer profiling and more targeted and successful marketing campaigns.
There are various benefits of using a conjoint analysis. Most importantly, the consumer himself does a trade-off analysis between the desirability of various features in a comparable scenario. Secondly, it may reveal hidden factors that we were not even considering in our study. Thirdly, it uses realistically possible choices and considers preferences at an individual level. Further, it can also help in segmentation based on different desired features in different consumer groups. Conjoint analysis not only helps us in deciding the features of planned products but may also reveal which of the existing products consumers prefer most and why. On the other hand, conjoint analysis may sometimes be too complex and may confuse the respondents who might provide overly simplistic answers instead of doing a real comparison.
On the whole, conjoint analysis is an extremely useful tool that can be used effectively to decide among various available options. Its popularity as a tool is because it is based on the assumption that every consumer purchase decision is taken after simultaneous consideration of multiple attributes. Conjoint analysis often offers the best way to decide what to choose in difficult trade-off situations like quality vs. cost, quantity vs. quality, brand vs. price, richness of features vs. time to market and so on.
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