If the subject of conjoint analysis is new to you, it would be easy for you to think that there is only onetype in existence. Needless to say that the technology used to conduct these studies have improved over the years and with that, different forms conjoint analysis were created. Depending on the task, you may have to switch between the types and this is why the importance of knowing about more than one cannot be overlooked. With that said, let’s look at a few.

Adaptive Conjoint Analysis – ACA

The ACA is one of those types that is not being widely used anymore, given that there are many variations now available. However, there are many people who still prefer this method, seeing that it tends specifically to cases in which there are several attributes to consider. This could include software products along with a host of others. The ACA uses some of the principles of the CBC concept but it is quite different as it relates to the design, implementation, and calculation.

Choice Based Conjoint Analysis –CBC

This is the most common type being used in today’s market and the CBC uses a full profile strategy, while reducing the work on the part of the different respondents. Normally, it displays more than two products at a time with a “none of these” option available, to facilitate more realistic choices that can be further evaluated. Shelf based displays in one of the many places this feature is used heavily to test pricing strategies for products that may have up to 25 brands to select from in a virtual shopping market.

Discrete Choice Experiment / Discrete Choice Analysis /
Discrete Choice Modelling

This particular type as you see goes by many names, but they all speak to the same thing. It is an advanced form of conjoint analysis, when compared to the CBC and some of the others but it’s still in the experimental stage in a manner of speaking, hence the name - Discrete Choice Experiment. It is mostly used in cases that deal with modal choice in particular. This would refer to a preference between a train, car or jet for example. However, when the Discrete Choice Experiment is comparedto the choice-based type for example, the only notable differences are the inclusion of continuous variables like time and price for instance.

In concluding, there are many other types of conjoint analysis models available, which each one catering to a specific target. Based what you need to explore or confirm, ensure that time spent to review what you target is and how can a particular analysis help you tap into that market.

Author's Bio: 

This article is penned by Lora Davis for Conjoint.Online. The company offers a free service Conjoint.ly (www.conjoint.online), an online tool aimed at product managers wishing to perform choice based conjoint analysis—also known as discrete choice experimentation using conjoint excel.