Ethnic makeup of the neighborhoods in which the stores reside is often very important. While it is somewhat obvious that an ethnic staple such as rice may sell better in Hispanic or Asian communities, the effect that ethnicity can have on customer demand in the dairy aisle may not be so obvious. Other important demographic factors include income and age. In the past, it would have been uneconomical to consider making assortment recommendations for more than a handful of store clusters within a chain. Today s consolidated retailers cover multiple geo-demographic segments.
Aggregated analysis misses the unique buying characteristics inherent in a customer group.
Consider at least three geo-demographic variables to narrow a customer base to unique groups that have the same purchasing behavior. It is only by overlaying geographic and consumer variables such as region, climate, income, age, ethnicity, and household size that we can optimize assortment across the entire fabric of a chain s geo-demographic consumer base. Remember that a store is not just a product of its geography, but of the people within that geography. When we make assumptions about a store s product mix based strictly on geography, we lose touch with the essence of ECR the consumer. There is little inherent benefit to simply accumulating data.