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      2. APPROACH

        We took a four-phased approach to this challenge:

        • Data from disparate?sources were consolidated into a single data warehouse, improving the usability of data
        • The analytical data layer was then prepared after carrying out data treatment procedures and applying business rules that were appropriate for the client’s business
        • Elementary data analysis helped classify stores based on potential products they could house
        • A regression model was then applied to identify the impact of changing assortment quantities on the top-line sales and the correlation model helped identify the af?nity between different products
        • The combined insights from the models helped us arrive at the optimal assortment strategy for the client.

        KEY BENEFITS

        • Our easy-to-use solution enabled the client to identify closely related products and plan assortments accordingly
        • It included recommendations on the mix of products that a store should carry and store-level revenue prediction based on the assortment mix

        RESULTS

        Our collective efforts paid off when the client’s Stock Keeping Unit (SKU) level prediction enhanced the weekly sales by 6%.

        亚洲 欧洲 日韩 综合在线