In our last blog, we discussed how the research community’s experience with Max/Diff and related choice-based models has led to the realization that not all consumers (respondents) make choices based on the full spectrum of attributes. In fact, our experience reveals significant variation in the number of variables that drive an individual’s choice.
Across a wide spectrum of categories — likely most categories — segmentation of choice drivers is at play. There are significant differences between consumers in terms of what attributes they care about when considering choices. Depending on the study, 30%-70% of consumers have been found to be making choices on just one attribute, while the choices of others can be driven by just a handful of variables. So within a single category, consumer choice strategies are not uniform. Further, the type and number of variables that drive an individual’s choice can vary by category.
Our collective choice-based modelling experience repeatedly shows that consumers are segmented in their brand choice strategies, and therefore, how they think about brands! The implications for brand attribute/benefit evaluation methodology are major. Assessment of brand imageries/equities via traditional “laundry list” check offs of benefits, flavors, advertising claims, etc., now seems blunt and unrealistic because it does not take into account how a given respondent thinks about brands and makes brand choices.
Max/Diff modelling is a far better method for determining attribute value/importance at the individual consumer level than via lengthy lists of benefits that may not be relevant to the given respondent. Another key strength of Max/Diff modelling is that brand attribute imagery metrics for each respondent are obtained on the dimensions specifically relevant to them. That is accomplished by first identifying which attributes are driving brand choice for each respondent and then matching the brand attribute assessment exercises to align with each respondent’s brand choice drivers.
Are your organization’s brand imagery/equity strengths fully optimized and leveraged? If your brands are still relying on brand delivery based on stated importance and benefit rating “laundry lists”, it might be time for a new approach to opportunity assessment.