Conjoint analysis

Consumer preferences for alternative product concepts can be measured through conjoint analysis, a method for deriving the utility values that consumers attach to varying levels of a product’s attributes. Respondents are shown different hypothetical offers formed by combining varying levels of the attributes, then asked to rank the various offers. Management can identify the most appealing offer and the estimated market share and profit the company might realize.

Green and wind have illustrated this approach in connection with developing a new spot removing, carpet- cleaning agent for home use. Suppose the new product marketer is considering five design elements:
Three packages designs (A, B, C)
Three brand names
Three prices
A possible Good Housekeeping seal
A possible money-back guarantee (yes, no)

Although the researcher can form 108 possible product concepts (3*3*3*2*2), it would be too much to ask consumers to rank 108 concepts. A sample of say, 18 contrasting product concepts can be chosen, and consumers would rank them from the most to the least preferred.

Marketing planning, buyer analysis, market segmentation and targeting are concerned with value selection. Product development, manufacturing, service planning, pricing, distribution and servicing, are concerned with value creation & value delivery. Personal selling, advertising, publicity and sales promotion are concerned with value communication. Activities like market research and market control assess the effectiveness of the value delivery process, the level of satisfaction the customer has actually received and how it compares with the firm’s intention as well as with other competing offers for the purpose of enhancing value.

The marketer now uses a statistical program to derive the consumer’s utility functions for each of the five attributes. Utility ranges between zero and one; the higher the utility, the stronger the consumer’s preference for that level of the attribute. Looking at packaging, we see that package B is the most favored, followed by C and then A. the preferred names are Bissell,K2R, and glory, in that order. The consumer’s utility varies inversely with price. A Good House keeping seal is preferred, but it does not add that much utility and may not be worth the effort to obtain it. A money back guarantee is strongly preferred.

The consumer’s most desired offer would be package design B, with the brand name Bissell, selling at the price of $1.19, with a Good Housekeeping seal and money back guarantee. We can also determine the relative importance of each attribute to this customer the difference between the highest and lowest utility level for that attribute to this consumer the difference between the highest and lowest utility level for that attribute. Clearly, this consumer sees price and package design as the most important attributes, followed by money back guarantee, brand name and, a Good House Keeping seal.

When preference data are collected from a sufficient sample of target consumers, the data can be used to estimate the market share any specific offer is likely to achieve, given any assumptions about competitive response. The company, however, may not launch the market offer that promises to gain the greatest market share because of cost considerations. The most customer appealing offer is not always the most profitable offer to make.

Under some conditions, researchers will collect the data not with a full profile description of each offer, but by presenting two factors at a time. For example, respondents may be shown a table with three price levels and three package types and asked which of the nine combinations they would like most, followed by which one they would prefer next, and so on. They would then be shown a further table consisting of trade offs between two other variables the trade off approach may be easier to use when there are many variables and possible offers. However, it is less realistic in that respondents are focusing on only two variables at a time.