Conjoint analysis is one of the techniques we use that comes closest to pure mathematical models of human behavior, and it can lend amazing insight.  With conjoint techniques, we create working models of consumer preferences for different types of products.  It works by presenting people with scenarios that are more like the real-life trade-offs they always make.  For example, instead of just knowing that price is important, the data from a conjoint study lets us assign a value to price relative to other important attributes, and then model how preferences change as we modify each attribute.

Conjoint is a powerful tool because it helps us understand not only which configuration of product features is optimal, but also why. It shows us how each component is being valued to drive overall preference.

Consider using conjoint if you want to understand:

• The tradeoffs that people make when evaluating their options
• How to bundle features to optimize your product or offering
• Needs-based segments among the people you are targeting
• Drivers of behavior that people themselves may be unaware of
• How your new product may affect product choices and market share

While conjoint analysis relies on a complicated set of mathematical algorithms, its beauty is that it ultimately tells a compelling story about humans, how they behave, and why they behave.

–Joe Hopper, Ph.D.