Maximum Difference Scaling (MaxDiff) is a statistical exercise wherein respondents score multiple features and attributes such as product features, product preference and usage etc based on the most important and least important feature or attribute to help obtain importance scores. This exercise provides different preference scores showing the relative importance of attributes compared to a standard rating scale exercise. Hierarchical Bayesian technique is used to derive the importance scores at the respondent level.
Case Study : Max Differential Analysis on survey data for a large utility vehicle manufacturer in the US
Objective : To collect opinions from current or potential consumers on several new product concepts and to better understand customer needs in a utility vehicle product.
Process & Methodology: Each respondent was given a set of questions containing some utility vehicle attributes (below) and asked to indicate the most and least important attribute.
- Analysis and summary plots were obtained for responses from EACH of the questions.
- Primary analysis was performed using multinomial logit model to obtain the Importance Value of each attribute in percent-shared utility scale (add up to 100). These are the easiest to interpret and were obtained by probability based rescaling procedure of the raw utility scores.
- Count analysis starting from simple proportions of least and most important attributes was also presented as a supportive analysis to the primary model based analysis.
Outcome: Our analysis helped the Utility Vehicle manufacturer better understand their target audience and helped them devise need based strategies based on customer feedback on the features the had the highest importance value for the customer.