TRC

Product Configurator

By Rajan Sambandam

Consider a person who wants to buy a personal computer. A simple way to do it would be to go to the website of a computer manufacturer and essentially "build" a computer. The firm provides the options for various components such as monitor size and CPU speed along with specific prices. The customer can select exactly the combination desired, subject to a price constraint. When all of the offered options are considered, the consumer is choosing a specific computer that fits the budget from among several thous an d computers. Yet the process can be completed quickly, efficiently and can be almost enjoyable for the customer. Would it be possible to use such a process for research? How would it work and what kind of results can we expect? This article deals with these issues through the use of a product configurator for research.

Product configurators in various forms have been historically used by firms to help their salespeople sell the right products to customers. With the improvement in computing power and the high level of Internet access in the general population, firms are increasingly allowing customers to "design" the products they want to buy. The same factors can be useful for researchers trying to understand consumer behavior.

A product configurator based approach to research is most appropriate when the product (or service) has multiple features with varying options. Conceptually this is very similar to the basic design requirement in a conjoint analysis. [For a more detailed explanation of conjoint analysis, please refer to Deriving Value from Research: The

Use of Conjoint Analysis for Product Development]. In conjoint analysis, products or sets of products are evaluated by respondents and the answers are analyzed to understand the importance of different features and options. This means an experimental design often has to be used to create the products and there are rules on how to construct the products and sets. Violations of rules can have a strong impact on the quality of the results.

On the other hand, a product configurator has virtually no rules. In the most basic version of the configurator, respondents choose the options they like and assemble a product that best meets their needs. Studying the choices they make allows us to understand what is important to them. Often a price constraint is included along with each option so that respondents do not automatically select the best option in each case. For example, in configuring a personal computer, respondents may face a choice between a 17-inch monitor priced at $100 and a 19-inch monitor priced at $150. As they keep making choices a running total of the amount of money they have "spent" is provided. Thus a respondent who wishes to spend less than a specified amount (say $1000) for a personal computer will have to make choices of features, such as monitor size, where price will have to be traded tradedoff with more desirable options of that feature.

Sometimes the nature of a product is such that a price constraint cannot be imposed for every feature or option. In such cases, respondents can be asked what price they would be willing to pay. Alternatively, a Van Westendorp pricing approach can be used to understand the willingness of people to pay for the product.

Are there any advantages to using this method over conjoint analysis? The primary advantage is in terms of flexibility.

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