Dividing a market into unique segments makes sense. But the statistical methods we rely on for segmentation often result in segments that are strongly differentiated in useless and misleading ways. A recent analysis of Facebook data by The New York Times illustrates this perfectly.
Segmenting customers into subsets that have unique needs, interests, and priorities makes a lot of sense. The more obvious the segments are, the more it makes sense, so a priori segments are best. Big companies in one segment, small companies in another. Retirees in one segment, college students in another. You don’t need fancy K-means…
Doing “statistics” strikes fear in the hearts of many, so how about if we talk about “algorithms” instead? It’s a safer word because most people in the worlds of business and market research never have to take (or fail) a course in algorithms. Algorithms are central to the work that we do in business and…