Retailer Achieves Improved Gross Margin and Quicker Inventory Turnover by Using Big Data Analytics

Sep 23, 2016

Business Challenge

Challenge with implementing store level product pricing strategy.

A retailer wanted to accurately determine the prices of products in relation to the varying demand at an individual store level.

Situation: Traditional methods not yielding expected returns.

The client was following traditional methods for price setting which was not providing profitable returns. This also resulted in adverse effects such as standing stock inventory, expired stock etc.

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Markdown optimization for dynamic pricing strategies.

We used markdown optimization strategy to determine the right time for price cuts and the most optimal price levels. This was implemented at a store level, making use of historic data at an individual product level, for accurate demand forecasting. Our solution also helped the client with better inventory planning.

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Improved gross margin and quicker inventory turnover.

The client was able to implement a dynamic pricing strategy at an individual product category level across stores. This helped in improving sales and also gross margins by achieving a better average unit retail price. We also helped the client achieve a much-improved inventory turnover.

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