Marketers and marketing researchers struggle to uncover what product and service attributes and features are truly valuable to customers. The long-standing approach of asking customers to rate importance on a five-point scale often does not sufficiently discriminate between the items, leaving marketers with the impression that everything is important! And, if everything is important, then, effectively, nothing is important.
Conjoint analysis is one solution to this dilemma. In conjoint analysis, respondents are presented with products described by a set of attributes and prices. Respondents then choose between “products”, composed of varying bundles of attributes and price, and the analysis show marketers how customers trade-off these different attributes and prices. The outcome identifies the most important attributes in driving interest in the “product”, the optimal level of each attribute, and the impact on potential product demand. Conjoint analysis (also called trade-off analysis) is a very powerful tool, but it can often be difficult to implement. Conjoint is criticized as being tedious for respondents, expensive for researchers, and difficult for marketers to understand and implement. Further, conjoint is dependent on the respondent being able to see the choice options, so it is nearly impossible to administer the technique effectively by telephone interview. For these reasons, conjoint is especially difficult to use with B2B respondents.
Max Diff (Maximum Difference Analysis, aka “poor man’s conjoint”) is often an alternative to conjoint analysis. In Max Diff analysis, respondents are asked a series of questions with four or five attribute choices and asked to select the one they believe to be “most important” and the one that is “least important”. Later response choices are optimized based on earlier questions. The analysis works best for identifying the most important and least important attributes, but does not discriminate well in the middle of the set, and does not reveal how respondents make purchase decisions by trading off among attributes and price.
So what’s a marketer to do? Enter Simple Conjoint.
Simple Conjoint is an alternative to traditional Conjoint and Max Diff approaches for determining preference. The method, developed by Jordan Louviere, can be thought of as a hybrid of traditional Conjoint and Max Diff approaches, as it borrows from, but isn’t exactly like either method. Here’s how it works:
- Each respondent evaluates one “product” at a time, with a number of different attributes and a level for each attribute. Unlike traditional Conjoint, the respondent does not evaluate multiple “products” from which they select the one they like best.
- First, after the product description, the respondent identifies which of the attributes is “most important” and which attribute is “least important.” If the number of attributes is relatively large (e.g., more than six), the respondent may also identify which attribute is “next most important” and which is “next least important” to them.
- Finally, respondents are asked how likely they would be to buy that “product”, providing a baseline measurement of acceptance.
The key difference of Simple Conjoint is that respondents only evaluate one product at a time. That difference leads to many advantages. While Simple Conjoint can certainly be useful for consumer research, it is especially valuable for B2B research because:
- Researchers can evaluate large numbers of individual attributes without respondent fatigue since the exercise is relatively short and easy for the respondent.
- Simple Conjoint can be administered in a phone survey, making it particularly useful with B2B samples when online sample is not available or desirable.
- It can be used with online surveys when the product is too complex to ask the respondent to evaluate multiple similar-sounding products (a frequent B2B research challenge.)
- Simple Conjoint can be completed as a component of other surveys, as it adds only 3 to 5 minutes to the average length of the survey.
Simple Conjoint is a great solution to the challenge of figuring out what’s important to customers, especially for B2B applications and/or telephone survey administration. As a stand-alone technique or added as a component to another survey, Simple Conjoint can provide you with valuable information, making this approach an attractive addition to the marketing research toolkit.