Store segmentation using SAS clustering

1. Store segmentation using SAS clustering Baofu Ma Merchandising AUTOZONE ANALYST,MERCH RESEARCH

2. Introduction • Motivation: • Need to create similar business model for stores with either similar product sales or customer GBB brand preference. • And explain these clusters in terms of demographic variables. • Challenges: • Business rule requires that the store cluster size has to be greater than certain number. Enforce a minimum cluster size with proc cluster. • Explore the relationship between the clusters and demographic variables.

3. Overview of hierarchical clustering • Each observation begins in a cluster by itself. The two closest clusters are merged to form a new cluster. • Using Proc cluster to get the tree. • Using Proc tree to get the desired cluster. 4 1 2 3 5 6

4. Solution • Get the history of the clustering process using ODS. ods output ClusterHistory=history; proc cluster data=indatatemp METHOD=ward outtree=Tree; • Search clusters which satisfy the minimum size criteria from top to bottom.

5. Example • Classify autozone stores based on market share of 2 oil brands, high mileage and blends. • Business rule requires minimum cluster size is 300.

6. Example • Even borders. • Find centers of each cluster. • Calculate distance between store and each cluster center. • Reassign store to the closest cluster .

7. Example Relationship between clusters and demographic variables. Blue-positive Orange- negative

8. Thank you!