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One of CPG companies in emerging markets saw 8% uplift in sales. Impact S-Reco: SKU recommendation engine to suggest CPG account manager what other SKUs they need to accommodate in a store Expertise / Capability Used Global CPG majors that are actively looking to grow top-line in their pursuit to win market share Industry Focus Step1: Store segmentation Dynamic segments based on interpretable factors – Wallet size, Value and Variety of SKUs purchased (WVV) Identify lookup stores in each segment. Lookup stores are the ones that have consistently purchased new SKUs Look-up store behavior is what we want to encourage for other stores Step2: Store similarity BRIDGEi2i algorithms identify stores that are similar to look-up stores based on certain predefined attributes Stores most similar to a look-up store are likely to buy the same set of SKUs that a look-up store purchased Step3: New SKU recommendation Looking at similar stores in similar geographies, BRIDGEi2i algorithms discover which SKUs would be an ideal match to be sold in a store that has high sales lift potential based on sales in lookup stores Step4: Base SKU recommendation Based on historical point of sale data and shipment data from business warehouse, the tool identifies SKUs that are required in the store Step5: Recommended order Based on business rules and running machine learning algorithms, S-Reco recommends quantity of SKUs that are recommendable to a store Identify weightage mechanism for success metrics to develop final set of recommendations Value weightage encourages higher, but relevant, value SKUs to be recommended Expected quantity of SKUs for both base-order and recommended orders are computed based on likelihood distribution CPG companies continuously look to increase revenue through different avenues. One of the avenues is to store the right SKUs in stores. In this journey, company can’t afford to store all SKUs and find out the right mix but should know what needs to be there that most customers look for. BRIDGEi2i went out to solve the problem using machine learning/artificial intelligence to provide the sales representatives with store level intelligent recommendations at the point of sale. Based on data analysis, we feel this could have considerable impact on revenue uplift for CPG companies. In fact, BRIDGEi2i worked closely with a large CPG company in one of the emerging markets and recommendations from tool resulted in revenue uplift of 8%. Summary One of the major challenges that CPG companies face is that ordering systems used by the sales representatives are based on replenishment model that doesn’t give enough scope to the companies for identifying sales growth opportunities through other SKUs. In a way, what other SKUs should be stored in that store to increase sales. Even if CPG companies want to add a new SKU to store aisle, they are usually not in a position to justify why a store manager should add a particular SKU. Business Challenges Approach/Methodology BRIDGEi2i provides Business Analytics Solutions to enterprises globally, enabling them to achieve accelerated business impact harnessing the power of data. These analytics services and technology solutions enable business managers to consume more meaningful information from big data, generate actionable insights from complex business problems and make data driven decisions across pan-enterprise processes to create sustainable business impact. BRIDGEi2i has extensive experience in Price and Promotions modeling, Market Mix Modeling and Data Visualization to support CPG clients. About BRIDGEi2i “Wouldn’t it be wonderful to know what your customers are looking for but is not available in the store?” Customer looking for a product Product not available in the store Customer leaves to find another store BRIDGEi2i’s proprietary decision engine S-Reco leverage advanced statistical and machine learning techniques to make intelligent, localized and personalized sales recommendations. Sales personnel use S-Reco from a simple internet-enabled device to make SKU recommendations to store manager and become a thought leader in recommending appropriate SKUs for stores. Our Solution POS + Shipment Data Only POS Data POS Data Shipment Data Base Recommendations New Recommendations Mashup data into Hadoop System 2 Final Recommendation through online tool 4 1 Development POS and Shipment data mart 3 BRIDGEi2i recommen- dation engine © 2016 BRIDGEi2i Analytics Solutions Pvt. Ltd. All Rights Reserved - www.bridgei2i.com For more details contact us: [email protected] | India: +91-80-67422100 | US: +1-650-666-0005 http://www.twitter.com/bridgei2i http://www.twitter.com/bridgei2i http://www.twitter.com/bridgei2i http://www.twitter.com/bridgei2i http://www.twitter.com/bridgei2i http://www.twitter.com/bridgei2i http://www.twitter.com/bridgei2i http://www.twitter.com/bridgei2i http://www.twitter.com/bridgei2i http://www.twitter.com/bridgei2i http://www.twitter.com/bridgei2i http://www.twitter.com/bridgei2i Maximizing revenue for CPG companies through store level intelligent SKU recommendations