Determine What Really Creates Satisfied Customers
Measuring scientists’ satisfaction with a product or service is tricky. Customers are often not clear on what they like—or what they’re willing to pay for. (They will often say they want it all.) In BioInformatics’ Derived Importance Modeling, we extract those attributes that are most closely linked to customer satisfaction, so suppliers can identify where their performance falls below buyer expectations. By mapping these results, it is easy to assess attributes that under-perform, and conversely, those that consistently make a scientist smile.
Case Study: Customer Satisfaction with Product Features of Antibodies
In the market for pre-made antibodies, BioInformatics evaluated and compared nine product features in order to answer two questions. How much does a particular product feature influence perceived quality? And how much does that perception of quality influence customer satisfaction? The analysis revealed areas where product improvement would increase satisfaction, as well as features where product differentiation could be obtained. Improvements to features rated as "highly important but not highly satisfied" were identified that would result in increased overall satisfaction levels. Likewise, avoiding investments to improve those features rated as "not important, but highly satisfied" would prevent futile marketing and product development efforts related to customer satisfaction.
Solution: Deriving Product Feature Importance and Influence on Satisfaction
We measure each respondent's level of satisfaction with the specific product features the you select. We also assess the respondent's overall level of satisfaction with the product or service. The analysis requires key pieces of data be collected:
- Level of satisfaction with specific features of [product X] from [supplier X]
- Overall satisfaction with [product X] from [supplier X]
Using a statistical technique called bivariate correlation, each product attribute is plotted on a quadrant map. Quadrants are a useful tool for visualizing the relative importance of various product attributes and the relationship of the attributes to satisfaction. The example displays the results of a commonly used product in the antibodies market.
Adding a Customer Segmentation to this analysis provides even more detail and can be performed by almost any variable, whether demographic, firmographic, primary supplier, etc. For industrial life scientists, we found that antibody form is more important than purity, yet the reverse is true for academic life scientists.