Conjoint analysis is a tool that allows a subset of the possible combinations of products features to be used to determine the relative importance of each features in the purchasing decision. It is based on the impact that the relative values of attributes considered jointly can better be measured that when considered isolated. Conjoint analysis is perfect for answering questions such as "Which should we do, build in more features, or bring our prices down?" or "Which of these changes will hurt our competitors most?"
This technique was developed in 1970s which allows to work out the hidden rules people use to make trade-offs between different products and services and the values. By understanding precisely how people make decisions and what they value in the products and services, we can work out the optimum level of features and services that balance value to the customer against cost to the company.
The steps which are involved in developing conjoint analysis which are as follows:
· First we choose the product attributes.
· Then choose the values or options for each attributes.
· After valuing the attributes define product as a combination of attribute options.
· Then choose the form in which the combination of attributes is to be presented to the respondents.
· To decide how responses will be aggregated. There are three choices- use individual responses, pool all responses into a single utility function, or define segments of respondents who have similar preferences.
· At least select the technique to be used to analyze the collected data.
There are different types of conjoint analysis which are expressed below:
· Adaptive conjoint analysis: it is one of the most common methods carried out in conjoint analysis. The benefits of ACA are that it allows for a large number of attributes upto 30 and levels upto 7 per attribute to be used. This method is used for larger more marketing focused work.
· Choice based conjoint analysis: CBC can show more than just two "products" at the same time, together with a none-of-these option enabling more realistic choice decisions to be evaluated. Choice-Based Conjoint (CBC) is favored academically and widely used for pricing and brand value studies
· Discrete choice analysis: A more advanced form of choice-based conjoint is Discrete Choice Analysis (also known as "stated preference research"). are particularly popular for transportation studies looking at modal choice - the preference between a train, car and airline for instance.
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