Product and Marketing teams are often faced with product/service design problems where decisions need to be taken on different product attribute levels or service levels and the prices at which these are to be offered. A tour operator, for example, may need to decide on a) places and locations b) total tour time (no of days and nights) c) level of hotel accommodation - 2-star, 3-star, 5-star etc 3) type of vehicle to be provided 4) nature and number of meals on tour to be included etc. Customers also make trade-offs while purchasing products and services laying more importance on more important attributes and trading off less important attributes. The other important trade-off is between price and product attribute/service level . A very common such choice is between flying Economy or Executive class in an airline and also, the choice of airline.
Conjoint analysis assists us in understanding the trade-offs customers make and in quantifying the importance that they place on different attributes. It also allows us to compare sets of attribute level-price level comparisons in terms of customer preference share.
In choice based conjoint surveys, respondents face different choice tasks where they select from different product /service profiles. Every respondent gets to see only a subset of the potentially possible product profiles. Sometimes constraints are placed to rule out technologically unfeasible product profiles. Every respondent only gets to see a subset of all the possible product profiles. Different sets of respondents may face different sets of choice tasks based on an experimental design that tries to maximize efficiency. Respondents make choices from sets of 3,4 or more product profiles in a single choice task and evaluate multiple choice tasks. Sometimes, to reduce size of the design, they may only be shown partial product profiles ( sub-set of attributes in a single task) or in online surveys, the choice tasks they face may be adapted to earlier evaluations of the attributes and levels ( adaptive choice based conjoint).
Compilation and analysis of the choices made by all respondents gives us quantifiable relative importance of each attribute and of its levels and the ability to simulate scenarios and predict preference shares for a set of product/service profiles in line with those considered for the survey ( having same attributes and levels or for price, levels within the price range considered). The insights are important for product design.