Analysis of clustering solutions
First Claim
1. A method comprising:
- determining, by a computing system, incremental values associated with a plurality of clustering solutions, wherein each of the clustering solutions groups stores of a retailer into clusters in a different way, wherein for each clustering solution in the plurality of clustering solutions, the incremental value associated with the clustering solution indicates a difference between an estimated revenue associated with the clustering solution and revenue associated with a baseline clustering solution, wherein determining the incremental values associated with the plurality of clustering solutions comprises, for each respective clustering solution from the plurality of clustering solutions;
determining, by the computing system, incremental values associated with each of the clusters into which the respective clustering solution groups the stores, wherein the incremental value associated with each of the clusters into which the respective clustering solution groups the stores is an aggregation of incremental values associated with the stores in the cluster, and the incremental value associated with each store in the cluster is an estimated change in a revenue of the store if a current assortment of items in the store is swapped with another assortment of items; and
determining, by the computing system, the incremental value associated with the respective clustering solution based on a sum of the incremental values associated with each of the clusters into which the respective clustering solution groups the stores;
determining, by the computing system and based on the incremental values associated with the plurality of clustering solutions, an appropriate number of clusters into which to group the stores of the retailer, wherein the appropriate number of clusters corresponds to a turning point of a best fit curve through a plurality of points, each respective point of the plurality of points corresponding to a respective clustering solution of the plurality of clustering solutions, the respective point having a first coordinate corresponding to a number of clusters associated with the respective clustering solution and a second coordinate corresponding to the incremental value associated with the respective clustering solution;
selecting, based at least on part on the appropriate number of clusters, a particular clustering solution in the plurality of clustering solutions; and
distributing, based at least in part on the particular clustering solution, merchandise to the stores.
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Abstract
A computing system determines incremental values associated with a plurality of clustering solutions. Each of the clustering solutions groups stores of a retailer into clusters in a different way. For each clustering solution in the plurality of clustering solutions, the incremental value associated with the clustering solution indicates a difference between an estimated revenue associated with the clustering solution and revenue associated with a baseline clustering solution. The computing system then determines, based on the incremental values associated with the plurality of clustering solutions, the appropriate number of clusters. The clustering solutions that group the stores into more or fewer clusters than the appropriate number of clusters tend to be associated with incremental values that are the same or lower than the clustering solutions that group the stores into the appropriate number of clusters.
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Citations
14 Claims
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1. A method comprising:
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determining, by a computing system, incremental values associated with a plurality of clustering solutions, wherein each of the clustering solutions groups stores of a retailer into clusters in a different way, wherein for each clustering solution in the plurality of clustering solutions, the incremental value associated with the clustering solution indicates a difference between an estimated revenue associated with the clustering solution and revenue associated with a baseline clustering solution, wherein determining the incremental values associated with the plurality of clustering solutions comprises, for each respective clustering solution from the plurality of clustering solutions; determining, by the computing system, incremental values associated with each of the clusters into which the respective clustering solution groups the stores, wherein the incremental value associated with each of the clusters into which the respective clustering solution groups the stores is an aggregation of incremental values associated with the stores in the cluster, and the incremental value associated with each store in the cluster is an estimated change in a revenue of the store if a current assortment of items in the store is swapped with another assortment of items; and determining, by the computing system, the incremental value associated with the respective clustering solution based on a sum of the incremental values associated with each of the clusters into which the respective clustering solution groups the stores; determining, by the computing system and based on the incremental values associated with the plurality of clustering solutions, an appropriate number of clusters into which to group the stores of the retailer, wherein the appropriate number of clusters corresponds to a turning point of a best fit curve through a plurality of points, each respective point of the plurality of points corresponding to a respective clustering solution of the plurality of clustering solutions, the respective point having a first coordinate corresponding to a number of clusters associated with the respective clustering solution and a second coordinate corresponding to the incremental value associated with the respective clustering solution; selecting, based at least on part on the appropriate number of clusters, a particular clustering solution in the plurality of clustering solutions; and distributing, based at least in part on the particular clustering solution, merchandise to the stores. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A computing system comprising:
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one or more processors; and one or more storage devices that store instructions that, when executed by the one or more processors, cause the computing system to; determine incremental values associated with a plurality of clustering solutions, wherein each of the clustering solutions groups stores of a retailer into clusters in a different way, wherein for each clustering solution in the plurality of clustering solutions, the incremental value associated with the clustering solution indicates a difference between an estimated revenue associated with the clustering solution and revenue associated with a baseline clustering solution, wherein the instructions cause the computing system to determine the incremental values associated with the plurality of clustering solutions in part by causing the computing system to, for each respective clustering solution from the plurality of clustering solutions; determine incremental values associated with each of the clusters into which the respective clustering solution groups the stores, wherein the incremental value associated with each of the clusters into which the respective clustering solution groups the stores is an aggregation of incremental values associated with the stores in the cluster, and the incremental value associated with each store in the cluster is an estimated change in a revenue of the store if a current assortment of items in the store is swapped with another assortment of items; and determine the incremental value associated with the respective clustering solution based on a sum of the incremental values associated with each of the clusters into which the respective clustering solution groups the stores; determine an optimal cluster count based on the incremental values associated with the plurality of clustering solutions, the optimal cluster count indicating a number of clusters into which the stores are grouped, wherein the optimal cluster count corresponds to a turning point of a best fit curve through a plurality of points, each respective point of the plurality of points corresponding to a respective clustering solution of the plurality of clustering solutions, the respective point having a first coordinate corresponding to a number of clusters associated with the respective clustering solution and a second coordinate corresponding to the incremental value associated with the respective clustering solution; and select, based at least on part on the appropriate number of clusters, a particular clustering solution in the plurality of clustering solutions, wherein merchandise is distributed to the stores based at least in part on the particular clustering solution. - View Dependent Claims (10, 11, 12)
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13. A non-transitory computer readable storage medium that stores instructions that, when executed by one or more processors of a computing system, cause the computing system to:
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determine incremental values associated with a plurality of clustering solutions, wherein each of the clustering solutions groups stores of a retailer into clusters in a different way, wherein for each clustering solution in the plurality of clustering solutions, the incremental value associated with the clustering solution indicates a difference between an estimated revenue associated with the clustering solution and revenue associated with a baseline clustering solution, and as part of causing the computing system to determine the incremental values associated with the plurality of clustering solutions, the instructions cause the computing system to, for each respective clustering solution from the plurality of clustering solutions; determine incremental values associated with each of the clusters into which the respective clustering solution groups the stores, wherein the incremental value associated with each of the clusters into which the respective clustering solution groups the stores is an aggregation of incremental values associated with the stores in the cluster, and the incremental value associated with each store in the cluster is an estimated change in a revenue of the store if a current assortment of items in the store is swapped with another assortment of items; and determine the incremental value associated with the respective clustering solution based on a sum of the incremental values associated with each of the clusters into which the respective clustering solution groups the stores; determine, based on a comparison of incremental values associated with the plurality of clustering solutions, an appropriate number of clusters such that the appropriate number of clusters corresponds to a turning point of a best fit curve through a plurality of points, each respective point of the plurality of points corresponding to a respective clustering solution of the plurality of clustering solutions, the respective point having a first coordinate corresponding to a number of clusters associated with the respective clustering solution and a second coordinate corresponding to the incremental value associated with the respective clustering solution; and select, based at least on part on the appropriate number of clusters, a particular clustering solution in the plurality of clustering solutions, wherein merchandise is distributed to the stores based at least in part on the particular clustering solution. - View Dependent Claims (14)
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Specification