Discrete Choice Analysis

Discrete Choice Analysis (DCA) is an analytical technique used to simulate real-world consumer purchasing behavior. DCA is ideal for the following types of research challenges:

  1. Products where only one purchase is made over a longer period of time (for example, durable goods, cars, cellular phones, etc.)
  2. Complex products, with many different possible features, where you are trying to determine which feature is most important in the purchase decision.
  3. Questions about price sensitivity and the impact of price changes.
  4. Product categories where the brands are well-known and impact the purchase decision.

Through an experimental design, consumers are given a series of product choices, varying by features and levels. These features generally include brand and price. For each choice set, consumers are asked to choose the one bundle of features and attributes that they would most likely buy or none of the choices. The decision that the respondent makes mimics real-world purchasing behavior without respondents being aware of being measured on the relative importance of each product feature.

For example, a typical choice set for a project to measure interest in smartphones could look like this:

Please CLICK inside the box of your preferred choice below and click “NEXT” to continue.

✅ Select Choice 1, 2, or 3.
✅ If you don’t want any or those, select Choice 4.

DCexample

A respondent may see up to a dozen of these choice sets, each one varying the levels of each feature. Through this exercise, we identify what feature is most important in driving the purchasing decision, the relative importance of each product feature or attribute and the impact of each possible level of feature or attribute on purchase likelihood.

Most significantly, the technique provides an Excel-based Simulator that can calculate the forecasted share of market for any combination of features, attributes, and levels to determine the optimal combination of attributes for a potential product. The true power is the Simulator’s ability to test an endless array of scenarios to identify the most effective marketing strategies and tactics for a new product.
Discrete Choice Analysis can be a powerful tool developing and evaluating new product concepts to increase the probability of market success. The technique provides marketers and product developers with three important pieces of information:

  • The product features and attributes that would have the greatest positive impact on consumer choice.
  • The relative impact of each variation within a feature or attribute.
  • The impact of various combinations of product features or attributes on competitive market behavior.

For more information and examples, read our blog articles on the topic:

Lessons Learned from the Edsel: How Using Discrete Choice Analysis Might Have Saved This Car

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