Device Attribute Testing
Our client wanted to determine the optimal new blood glucose monitoring device – one that would best retain their current customers and also attract new ones. They also wanted to be able to rationalise the strengths of their existing portfolio against their competitors. The patient evaluation needed to reflect real life as much as possible, so that it truly reflected patient preference and could predict the future market impact of any new device.
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.
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.
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