Correlating product sales to store segmentation
AssigneeTarget Brands, Inc.
InventorsPing-Fong Hsieh, Earl S. Sun, Daniel W. Peterson
Life of this patent
Estimating the term…
Abstract
Past sales data for a product sold at stores in a chain of retail stores is received by a computing device. For each segment, the stores in the chain are grouped into one or more clusters. The average sales of the product in each cluster and the average sales of the product in all of the stores are calculated based on the past sales data. A cluster variation and a total variation may be determined for each of the stores based on the past sales data. A correlation indicative of an effectiveness of the segmentation strategy to reduce sales variation between stores in each of the plurality of clusters may also be determined based on the at least cluster variation.
Claims20
A method comprising:
- receiving, by a computing device, past sales data for a product sold at a plurality of stores;
- assigning each of the plurality of stores to one of a plurality of clusters based on a segmentation strategy;
- calculating a cluster average sales of the product for each of the plurality of clusters based on the past sales data for each of the stores assigned to the cluster;
- for each of the plurality of stores, calculating a cluster variation based on a difference between actual sales of the product in the store indicated by the past sales data and the calculated cluster average sales for the cluster to which the store is assigned;
- calculating a total average sales of the product based on the past sales data for each of the plurality of stores and the total number of stores in the plurality of stores;
- for each of the plurality of stores, calculating a total variation based on a difference between actual sales of the product in the store and the calculated total average sales;
- and
- determining a correlation score based on the cluster variation and the total variation, the correlation indicative of an effectiveness of the segmentation strategy to reduce sales variation for the product between stores in each of the plurality of clusters.
The method of claim 3, further comprising:
- comparing the first correlation score and the second correlation score;
- and
- determining which of the first correlation score and the second correlation score is greater based on the comparison.
A system comprising:
- at least one computer-readable storage device that stores sales data associated with a product sold at a plurality of stores, that stores a first segmentation strategy that assigns each of the plurality of stores to one of a first plurality of clusters within a first segment, and that stores a second segmentation strategy that assigns each of the plurality of stores to one of a second plurality of clusters within a second segment;
- at least one processor configured to access the sales data on the at least one computer-readable storage device, and further configured to:
- determine a first correlation score for the first segment based on the sales data, the first correlation score indicative of an effectiveness of the first segmentation strategy to reduce sales variation for the product between stores in each of the first plurality of clusters;
- determine a second correlation score for the second segment based on the sales data, the second correlation score indicative of an effectiveness of the second segmentation strategy to reduce sales variation for the product between stores in each of the second plurality of clusters;
- and
- generate a report based on the first correlation score and the second correlation score.
A non-transitory computer-readable storage medium encoded with instructions that, when executed by one or more processors, cause the one or more processors of a computing device to:
- receive, by a computing device, past sales data for a product sold at a plurality of stores;
- assign each of the plurality of stores to one of a plurality of clusters based on a segmentation strategy;
- calculate a cluster average sales of the product for each of the plurality of clusters based on the past sales data for each of the stores assigned to the cluster;
- for each of the plurality of stores, calculate a cluster variation based on a difference between actual sales of the product in the store indicated by the past sales data and the calculated cluster average sales for the cluster to which the store is assigned;
- calculate a total average sales of the product based on the past sales data for each of the plurality of stores and the total number of stores in the plurality of stores;
- for each of the plurality of stores, calculate a total variation based on a difference between actual sales of the product in the store and the calculated total average sales;
- and
- determine a correlation score based on the cluster variation and the total variation, the correlation indicative of an effectiveness of the segmentation strategy to reduce sales variation for the product between stores in each of the plurality of clusters.
Dependencies are inferred from the claim text.