Solution Criteria

Episode 06

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Market Segmentation: Episode 06 Transcript

Hello, I’m Beth Horn, head of the Advanced Analytics Group here at Decision Analyst, and I’m here to discuss how to choose the best segmentation solution.

Some general criteria for useful segments include: segments should share more commonalities with each group than they do between groups, segments should also be large enough for organizations to mount cost-effective campaigns, and segments should be reachable through most media avenues.

Market Segmentation Criteria

I also suggest that segmentation solutions should consider linking those segments to important market outcomes. It is vital to understand which key metrics are important to stakeholders and craft a plan to include those metrics. Such results can help a company determine which segments to target first (groups who are likely to purchase the product for instance), and how to communicate with them.

So, when deciding upon a final solution, companies often wonder how many segments should I have, 5, 6, 10, 15, 20? There’s not a magical number, I’m sorry to say. Companies that advertise using mass media, for example, will lean toward fewer segments. Companies that use direct mail or email marketing may use many, many, many segments, because it is relatively inexpensive and easy to market to all of them. A service-oriented industries, such as hospitality and foodservice, tend toward many segments as well, because not only do they have to account for the consumer, but they must account for the day part, the usage occasion.

Successful Segmentation

So, although there can be a great deal of sophistication in the analysis stage, segmentation is not a purely scientific pursuit. Sadly, there are no magic buttons to press to generate the best segmentation solution. So, given that the data have been modeled the most appropriate way and the basics are addressed, category experience and expert judgment are the final guides to selecting the best segmentation solution.

So, thanks for watching and please be sure to check out our next video: “Uncovering Motivations.”


Elizabeth Horn

Elizabeth Horn

Senior VP, Advanced Analytics

Beth has provided expertise and high-end analytics for Decision Analyst for over 25 years. She is responsible for design, analyses, and insights derived from discrete choice models; MaxDiff analysis; volumetric forecasting; predictive modeling; GIS analysis; and market segmentation. She regularly consults with clients regarding best practices in research methodology. Beth earned a Ph.D. and a Master of Science in Experimental Psychology with emphasis on psychological principles, research methods, and statistics from Texas Christian University in Fort Worth, TX.