Identifying patterns or opportunities in various and diverse segments to bring about the best strategies for each cluster
Most business have a fragmented customer base, i.e customers could be of different socio-economic backgrounds, spread across geographies, have variable product choices etc. Dynamic clustering helps the retailer identify patters or factors that drive store performance. They could be similar local patterns across stores in different locations. Product and consumer attributes are important for in-season store sales performance.
Identifying of patterns and opportunities in diverse segments/clusters to formulate the best strategies for each cluster, for productive growth, innovation and competitiveness is called dynamic clustering. Another reason for the ever growing emphasis on dynamic clustering is globalisation; the reason for increased exposure of local economies to heightened global competitiveness. Clusters draw their rationale from the concept of “external economies of scale ” developed by Marshall (Marshall, 1920).
Here’s an example of dynamic clustering:
Say you’re an apparel chain that operates stores in 7 states across India. By using Dynamic Clustering, you are able to identify similar patterns in four different states, let’s assume, Tamil Nadu, Andhra Pradesh, Karnataka and Kerala. This then enables you to make better and more relevant sales, purchasing, or marketing decisions for this cluster of states.