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Potential impact of revenue lift

around 3-4% in developed

markets. 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

ShipmentData

BaseRecommendations

NewRecommendations

Mashup data intoHadoop System2 Final Recommendation

through online tool41 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: enquiries@bridgei2i.com | India: +91-80-67422100 | US: +1-650-666-0005

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Maximizing revenue for CPG companies through store level intelligent SKU recommendations