Conjoint Analysis is concerned with understanding how people make choices between products or services or a combination of product and service, so that businesses can design new products or services that better meet customers’ underlying needs. A key benefit of conjoint analysis is the ability to produce dynamic market models that enable companies to test out what steps they would need to take to improve their market share, or how competitors’ behavior will affect their customers.
To understand how conjoint analysis works, we need to be able to describe the products or services consistently in terms of attributes and levels in order to see what is being traded off. Conjoint analysis is a sophisticated technique and there are technical issues that need to be considered. In particular, the design of attributes is a crucial step in a conjoint project as choices between poorly defined levels can render the exercise meaningless. You should also be aware that there are different flavors of conjoint analysis depending on the application. Adaptive Conjoint Analysis (ACA) is the most common, but there is also Choice-based and Full-profile Conjoint Analysis.
Conjoint analysis proves to be extremely helpful since estimates psychological tradeoffs that consumers make when evaluating several attributes together. Also conjoint analysis is known to measures preferences at the individual level.
On the flipside conjoint analysis has several disadvantages such as respondents are unable to articulate attitudes toward new categories, or may feel forced to think about issues. Conjoint analysis also is said to have a major flaw that it does not take into account the number items per purchase so it can give a poor reading of market share.