qualitative analyses

conjoint analysis / discrete choice

(Our forte! ABR specializes in this high-end set of analytical techniques.) A way to quantify consumers’ values associated with different product attributes using multivariate techniques.

Every customer making choices between products and services is faced with trade-offs. Is high quality more important than a low price and quick delivery? Is good service more important than design and looks? By understanding precisely how people make decisions and what they value in your products and services, you can work out the optimum level of features and services that balance value to the customer against cost to the company.

Conjoint analysis is a powerful statistical technique that allows the researcher insight into the consumer choice process. By having consumers “trade-off” or choose between products or services with different characteristics, it becomes apparent which features/attributes have the most influence on decision-making. You are able to work out the hidden rules people use to make trade-offs between different products and services and the values they place on different features.


There are several conjoint analysis tools and approaches:

  • Choice-based Conjoint (CBC) – The term “choice-based” means the respondent chooses among derived product alternatives. This type of research yields optimal results when evaluating price elasticity across many different product features, such as warranty or other options (including an opt out option called “no-buy”). This approach most closely mimics the dynamics of a competitive market and is therefore the one used most often.
  • Ratings-based Conjoint (RBC) – Ratings-based Conjoint involves rating individual product alternatives or rating two product alternatives simultaneously. No-buy options are not easily accommodated in Ratings-based Conjoint. Ratings-based Conjoint may be more appropriate for non-competitive markets, such as oligopolies, monopolies or emerging categories.
  • Hybrids (e.g. ACA) – Hybrid techniques are generally most appropriate when a large number of attributes must be included. ACA is the best-known and most widely used example of a hybrid technique. [www.macroinc.com]

When you want to know…

  • What combination of product features, preferences and values is most likely to lead to purchase?
  • How do product features interrelate to increase consumer interest?
  • How will a change in price affect overall preference?