Discrete Choice/Conjoint Methods


Conjoint and MaxDiff analysis are used to determine the implicit values placed on a large set of features or product options. Conjoint analysis simulates ‘real-world’ decision-making by asking people to choose between complete product packages. It helps untangle the complex tradeoffs people subconsciously make when selecting one product over another (for example, weight, battery life, screen resolution, and cost for a laptop). MaxDiff analysis, also known as best-worst scaling, is used to determine the relative preferences for a large set of features. Since people are better at judging items at extremes than at discriminating among items of middling importance, MaxDiff studies repeatedly ask respondents to pick the most important and least important from different sets of features.

  • Make informed product design and therapy formulation decisions, based on research that reflects the real way people weigh the pros and cons of different features and think about their product preferences.
  • Understand how key patient or HCP segments differ in the importance they place on different features and attributes.
  • With conjoint analysis, a ‘what-if’ simulator translates the utility scores into a predictive model. Adjust the attributes and levels to understand the impact of feature trade-offs on share of preference.
  • Prioritize CGM user-interface features to direct product software development.
  • Uncover the relative importance different patient segments place on a new drug’s benefits and risks and estimate share of preference in taking the therapy.
  • Determine the differentiating features for the design and ergonomics of a new CGM.

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