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Retail Store Clustering

K-means Hierarchical Clustering Clustering Retail Store Clustering Retail Store
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This workflow uses a fictional retail company dataset to cluster stores for grouping them into Pre-Season Planning Markets. Fictional dataset includes : Stores : 1000 stores from all around the world with Country-City-Coordinates information. Category Sales % : Contains 5 different product category and their relative sales pcs % per store. Store Capacity: Divides stores into 3 capacity groups.. Big-Medium-Small Customer Profile: Divides stores into 3 customer group : Type 1 - 2 - 3 Based on this dataset, this workflow enables users to assign weight to each of these parameters and run 2 different clustering methods and analyze the results on this platform with insight sparking visuals. This workflow is created by BI-FI Blogs. Check our blog for detailed guide of this workflow.

External resources

  • Click here to download the sample data for this project
  • Check our blog for Detailed Guide for this Project

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Created with KNIME Analytics Platform version 4.7.0 Note: Not all extensions may be displayed.
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    KNIME AG, Zurich, Switzerland

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    KNIME AG, Zurich, Switzerland

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    KNIME Open Street Map Integration Trusted extension

    KNIME AG, Zurich, Switzerland

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    KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.0

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