Solution Criteria
Transcript
Hello, I'm Beth Horn and I lead the Advanced Analytics Team at Decision Analyst. Today I want to talk about something we get asked all the time. How do you choose the right segmentation solution?
When we're looking for segments that truly work, there are a few must-haves. First, people within a group should have more in common with one another than they do with people in other groups. Second, the segments need to be large enough to make your marketing campaigns cost effective. And third, you need to be able to reach them through your usual media channels.
I always recommend linking your segments to the market outcomes that matter most to you. By understanding the key metrics your stakeholders care about, you could build a plan that targets the right people first, like those most likely to buy, and figure out exactly how to talk to them.
One of the most common questions is, "How many segments should I have? Is it five, 10, maybe 20?" I wish I could tell you that there's a magic number, but it really depends on your business. If you rely on mass media, you'll probably want fewer, broader segments. If you're using direct mail or email marketing, you can afford to have many more segments because it's easy to personalize. Industries like hospitality and food service often have the most segments because they have to account for both the person and the specific occasion, like a quick lunch versus a fancy dinner.
Even though there's a lot of complex math happening behind the scenes, segmentation isn't just statistics, there's no magic button that spits out the perfect answer. Once the data is modeled correctly and the basics are in place, the real secret ingredients are category experience and expert judgment. That's what ultimately leads you to the best solution.
If you'd like to learn more, please check out our other episodes on segmentation. Thanks so much for joining me.
Presenter
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.