When you use both conjoint analysis and competitive product market research for your new products, you are less likely to overlook product dimensions that are important to your customers or constituents, and more likely to successfully meet their needs.
- Generate designs easily – use Orthoplan, the design generator, to produce an orthogonal array of alternative potential products or services that combine different product/service features at specified levels
- Print “cards” to elicit respondents’ preferences – use Plancards to quickly generate cards that respondents can sort to rank alternative products
- Get informative results – analyze your data using Conjoint, a procedure that’s a specially tailored version of regression. Find out which product/service attributes are important and at which levels they are most preferred. You can also perform simulations that tell you the market share of preference for alternative products.
- Operating systems supported: Windows, Mac, Linux
Conjoint analysis is a technique pioneered by market research analysts to determine how people value the different features that make up an individual product or service.
Conjoint analysis can be used to discover the optimal combination of product/service attributes in terms of the combination that is most influential on customer choice or decision making.
Conjoint works by showing respondents a particular set of products (or services) and by analysing how they make preferences between these products. By mapping the different features or aspects of the products to the choices that the respondent makes, the Conjoint technique is able to infer the ideal set of characteristics for a product or service.
There are three stages to running a conjoint analysis procedure in SPSS:
- Firstly generate an orthogonal array: this is basically a sample of cases (or cards) where each one represents a product with different combinations of attributes.
- Secondly, collect the responses: this is a practical process whereby respondents are asked to rate cards containing different combinations of product features.
- Lastly, a conjoint analysis is performed with a view to calculating a utility (preference) score for any combination of product features.