Case Study: Conjoint Analysis Helps Medical Equipment Supplier Assess Gap In Current Product Portfolio


  • The client’s planned product would not likely be successful at the originally targeted price.
  • The estimated penetration of the product would be less than 10%.
  • The client would need to modify the product features and price the instrument at approximately 15-25% less than originally thought to be sucessful.


The study determined:

  • Many labs were currently looking for new equipment.
  • Three features were critical for market success
    • Reduced hands-on time
    • Additional approved menus
    • Improved runtime
  • Original product would receive very low penetration (<10%)

Business Challenge

A leading diagnostic instruments supplier to the medical laboratory market had a gap in their product portfolio. They had a highly automated product that fit perfectly for medical labs that performed a high volume of tests. In addition, they had a less automated version that could be used by labs and physician practices that conducted a much lower test volume.

The problem was their competitor had recently launched a product that fit the medium-volume test market. Without a competing product, the client was allowing a key competitor an opportunity to carve out market share.

Research Objective

To assist the client in determining whether current products could be modified to meet the requirements for medium test volume labs and, if so, what specific changes would be needed. In addition, the study needed to determine at what price point the new product would need to be offered to be successful.



Adaptive conjoint analysis (ACA) was used to understand the relative value of seven different product features relative to price and to simulate the new product against competing products already in the market.

Why AMG Research was Chosen

AMG Research was selected to conduct the research study due to our experience in the healthcare and laboratory industries, our proven ability to reach the audience effectively, and our experience in utilizing conjoint analysis.