The focus on implicit drivers of brand/product preference continues to gain momentum within the Marketing Science realm. In no specific area has this been more apparent than in the field of Conjoint Studies. Objectively different than A&U and Satisfaction studies, conjoint studies focus on the direct evaluation of a brand or product as a whole. As such, individual attributes or factors of the brand/product are not explicitly rated or ranked by the respondent, instead, they are “considered jointly” (hence the derivation of “conjoint”). Yet, through a thoughtful research design and the application of the appropriate conjoint estimation method, we can derive the relative importance of individual attributes or factors to affect desired outcomes.
At MWI, we continually keep abreast of the latest advances in Conjoint-related techniques. Statistical techniques for seeking out awareness of and insight into these implicit factors continue to evolve, and both the accuracy and uniqueness of the information gleaned from these techniques has improved drastically over the last 20-30 years. Furthermore, we fully understand that no one conjoint technique is “lightening in a bottle”, instead, the pros and cons of different conjoint techniques are to be considered carefully. Appearing below is a graphic generalization depicting the conjoint analytic approaches available to the market researcher:
A number of different factors play into the decision of which general conjoint technique to use, and then specifically how it should be customized to suit your study’s objectives. Before choosing a market research vendor to fulfill your conjoint analytical needs, ask the vendor the following key questions:
- “What conjoint technique is appropriate, based on the number of attribute and attribute levels I want to evaluate?” : This decision impacts appropriate research design and resulting data more than the back-end estimation methods used by the techniques; careful thought should be given to “information overload” experienced by the respondent processing too many attributes and levels. Additional complexity is added with consideration to whether respondents are anticipated to have a low vs. high level of involvement with all attributes, during decision/rating processing.
- “How do the restrictions of my budget impact my selection of a conjoint technique?” A smaller budget typically means a smaller sample size, and the threshold of when to move from one technique to another based on sample size limitations must be considered.
- “What conjoint technique is appropriate based on my study objectives?” Are you looking to gain a fundamental understanding of consumers’ preferences for attributes? Predict customer behavior in the marketplace? Simulate customer response to various product designs? Or, just understand the respondent’s decision making process? Each of these scenarios favors use of one technique over others, as well as whether aggregate, group or individual-level conjoint models will be required for sufficient accuracy.
- “Will the chosen conjoint technique allow for none of the products/brands being desired?” With respect to this condition, which allows for an estimation of market contraction, there are definitive differences in recommended techniques.
- “Can the conjoint technique you recommend be implemented administering the survey the way we plan to?” As previously mentioned, the choice of the technique impacts the research design and how questions are prompted to the respondent. Only certain survey administration types allow for dynamic question prompting.
MWI can also provide a customized Share of Preference Simulator, reflective of the individual attribute level utilities scores calculated for respondents’ (as opposed to aggregate utility estimates for the attribute levels). Use of individual level utilities is a more choice-based approach to generating simulation shares, which in turn we believe produces more realistic results. A hypothetical example of our Simulator interface (which is Excel-based, and hence is completely customizable by either MWI or our clients), for a hypothetical hardwood flooring client, appears below:
Exhibit A – Share of Preference Simulator for Hardwood Flooring Client
Additionally, MWI stays on top of the latest advances in conjoint-based methods. One advance we are following closely and beginning to test is Adaptive Choice-based Conjoint techniques. The technique reflects an exciting development in the field of discrete choice conjoint studies, whereby respondents’ conjoint choices are analyzed on the fly, to determine whether any particular attribute criteria are indicative as a “must have” requirement for the respondent. Subsequent conjoint exercises are then re-defined to reflect whether a “must have” requirement does indeed exist for the respondent.
To learn more about Brand/Product Conjoint Study & Share Simulation Capabilities click here to request more information.
