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Insightful Marketing through Conjoint Analysis
Every purchase decision is nothing but a series of trade offs that the buyer makes between several attributes to maximize its utility. To be a winner in the market place, Marketers need to get an insight into the consumer’s mind and design/price your product accordingly.
Conjoint Analysis is a powerful research technique which helps to quantify the perceived values of specific product features & determine what attributes drives consumer behavior.
At AbsolutData our deep expertise and pioneering approach to conjoint analysis helps us lend winning edge to our clients. Conjoint Analysis can help to come with an optimal solution for client’s product by answering following questions:
* What is the best possible combination of attributes for my product?
* How price sensitive are the target customers? At what price can client maximize its profitability?
* What services are consumers willing to pay more for in the product?
* How will a change in attributes impact client’s market share?
How Does Conjoint Analysis Work?
* Represents ‘Product’ as a collection of different levels of various attributes
* Respondents choose the most preferred product from a set of products
* The set of chosen products generates preference/utility values at a respondent level, and for every level of each attribute
* ‘What-If Simulators’ exploit this utility information to generate different product scenarios and help explain market behavior at an aggregate level
AbsolutData Conjoint Analysis Expertise:
AbsolutData uses state-of-art conjoint techniques and apply them to answer various business problems:
* Discreet Choice Conjoint - Respondents are shown different products at the same time and are asked to select one of them. This is the most popular type of conjoint analysis today
* Adaptive Conjoint Analysis - The product combination shown are dynamically updated based on previous responses in the survey. This can only be done on a computer based survey.
* Maxdiff Conjoint - Respondents are asked to select the best and worst attribute from the combination shown. Typically used for soft attributes that are not quantified
* Asemap - A relatively new technique to find attribute importance for large number of attribute.
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