Case study: How conjoint was used to determine the optimum features for a BGM device

The solution
We applied a hybrid qual-quant methodology, which combined face-to-face in-depth interviews with a quantitative conjoint exercise. The face-to-face setting allowed us to present a number of explanatory vignettes and real devices to patients so they could make fully informed decisions around each of the attributes they were assessing. This approach also allowed the moderators to probe patients further on the reasons behind the performance and preference ratings they gave to each product.   

Next patients were asked to complete a simple and engaging paired online exercise, which used choice-based-conjoint to determine relative utility of each attribute and preference share. As a result, we were able to see what the most compelling devices would look like across each patient group and gained a complete understanding of the motive behind each choice. 

The outputs
We were able to provide our client with clear recommendations for the optimal features for a BGM device. We also created an excel-based simulator which, after comprehensive training, allowed the client team to calculate expected preference share for each possible device according to attribute sensitivity and relative importance.