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  • Writer's pictureMMR Research Associates



Choice methodologies are a powerful, frequently used tool in market research. Because they compare lists of key attributes/features to each other, they are particularly useful when attempting to understand what attributes or features are driving preference; the impact that changes in attributes or features might have on overall preference; or how well hypothetical offerings might affect preference. Choice questions are relatively easy and efficient questions for respondents to answer and provide a clear picture of what offering a person would select, if all other variables could be held constant.

Despite broad use of Choice approaches in market research, MMR believes there are opportunities to expand even further the use of this tool to answer critical questions effectively and efficiently at both the simple and complex ends of the Choice methodology spectrum.


Choice methods can be used as a segmentation tool to understand how a market segments itself based on what offerings and associated features attract each customer. A good example of leveraging a robust choice method (e.g. discrete choice) for this purpose arose when an MMR client wanted to do a traditional segmentation study to identify white space in the market regarding customer needs and priorities. The client believed that its premium brand was limiting its ability to capture a very large “value” oriented part of the market. We probed further and determined that there were a limited number of product attributes that customers use to compare products in this category (e.g. material, warranty, price, brand name, channel availability).

Rather than conduct a segmentation study (a lengthy and costly process), we were able to shortcut the process by developing a list of attributes / features that could be modeled in a discrete choice design. We created a simulator that allowed our client to measure the precise impact that various new hypothetical branded products would have on the company’s overall share potential, including:

–          Improvement in company’s overall preference share;

–          New customers that the new brand / product would likely attract;

–          The degree of overlap with current branded products; and

–          Impact among difference channel customers.


On the opposite end of the spectrum, when the competitive offerings are known, and a company is aware of and has the ability to improve key attributes, a Simple Choice Approach is a quick and cost effective tool at both ends of the study because it is simple to set up, and easy to interpret.

As an example, an MMR client asked us to do a conjoint study to determine what the impact on product preference would be if they changed several product attributes. MMR learned that there were only about three variations of their potential new product replacement. With this learning, we were able to develop multiple choice sets that accommodated the client’s potential new products. We were also able to construct scenarios with the new product as both a replacement, and as an addition, to the current product (a scenario with an altered competitive product was also added as a distraction).

What we learned just a few days after the close of data collection is that while both the current and replacement client product had similar shares when only one was present, the combination of the two significantly increased the client’s overall preference share. Additionally, there was limited overlap in respondents selecting each of the client’s products where only one was available. The client was able to use this information to convince a major retailer to carry both SKUs, and the result was a much greater share / profit for the client, and better margins for the retailer, by expanding the client’s brand.

While traditional segmentation analyses are used to identify and/or differentiate brand targets, MMR understands that segmentation analysis may not be the most effective or efficient avenue to achieve a client’s business objectives. A choice based approach to effectively fine tune brand characteristics can effectively help to optimize brand portfolio reach, and determine what combination of attributes will minimize cannibalization of current brand offerings, while maximizing the conquest of competitive brands.


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