How Analytics-Driven Store Clustering Can Drive Sales And Profits In Retail

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Personalisation is the new mantra for retailers today. However, that should not be limited only for the customers but also be adopted as a strategy towards growing store sales. ‘One-size-fits-all’ approach would no longer work for achieving strong store-level growth and it is important to customise a strategy for each store. Clustering of stores based on characteristics beyond store sales or region will enable retailers to identify a cluster of stores that would match each other closely on multiple dimensions. Brick-and-mortar retailers can begin their store level personalisation journey in three steps: Identify variables for clustering: Variables that define variation in-store performance should be identified to create clusters. Business validation of emerging clusters: St
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Sulabh Jain
Sulabh Jain is the Executive Director at Impact Analytics. He facilitates the data analytics decision making for IA's clients in the US. He is an experienced business consultant with expertise across retail, IT services and business improvement projects. He has worked with BCG in India and has ran a startup in the B2C domain.
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