How useful to your customer is a particular feature of a product or service? Conjoint analysis helps you find out.
Conjoint Analysis is a multivariate technique that captures the exact levels of utility that an individual customer places on various attributes of the product offering. Conjoint Analysis enables a direct comparison, for example, between the utility of a price level of $30 versus Rs.$50, a delivery period of 1 week versus 2 weeks, or an after sales response of 24 hours versus 48 hours.
Once we know the utility levels for each attribute (and at individual levels as well), we can combine these to find the best combination of attributes that gives the customer the highest utility, the second best combination that gives the second highest utility, and so on. This information is then used to design a product or service offering.
If Conjoint Analysis is done segment-wise across a sample of customers,
it can be used to predict market-share. The response of customers to changes in the competitive strategy through changes in the marketing elements can also be predicted.
Conjoint Analysis is extremely versatile, and the range of applications includes virtually any industry. New product or service design, including concepts in the pre-prototyping stage, can specifically benefit from conjoint applications.
Some examples of other areas where this technique can be used are -
Do you have a product or service concept which needs fine-tuning? Contact Outsource2india for Conjoint Analysis.
Design attributes for a product are first identified. For a shirt manufacturer, these could be Checks or Solid Colors, Price of 6 dollars versus 10 dollars, and exclusive versus mass distribution. All possible combinations of these attribute levels are then listed out. Each design combination is ranked by customers, and used as input data for Conjoint Analysis. Then the utility of the products relative to price can be measured, and because attributes are included (but not varied), some component utility (’part-worth’) could be mined from the data.
The output is a part-worth or utility for each level of each attribute. For example, Checks may get a utility level of 5 and Solids, 7.5. Similarly, Exclusive Distribution may have a part utility of 2, and Mass Distribution, 5.8. We then put together the part utilities and come up with a total utility for any product combination we want to offer, and compare that with the maximum utility combination for this customer segment.
This process clarifies for the marketer of the product or service, the attributes that he should focus on in the design.
If a retail store finds that the height of a shelf is an important attribute at a particular level, a well-designed shelf may result from this knowledge. Similarly, a designer of clocks will benefit from knowing the utility attached by customers to the dial size, background colors, and price range of the clocks. Similarly, a designer of clocks will benefit from knowing the utility attached by customers to the dial size, background colors, and price range. Manufacturers would then produce clocks that are closer to a customer’s expectations - and sell more clocks!
Which attributes of your product are really important to your customer? Find out with O2I’s Conjoint Analysis.
Through a discussion with the client we identify the design attributes to be studied and the levels at which they can be offered. We then build a list of product concepts on offer. These product concepts are then ranked by customers. Once this data is available, we use Conjoint Analysis to derive the part utilities of each attribute level. This is then used to predict the best product design for the given customer segment. We use the SPSS (Statistical Package for the Social Sciences) Conjoint procedure to analyze the data.
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