Learn how we optimized a vast number of SKUs using competitive intelligence and machine learning analytics to provide our customer with a data science toolkit to make informed decisions at speed and scale.

Client:

A global distributor of industrial and electronic products.

Challenge:

The client needed to optimize their extensive stock-keeping units (SKU) portfolio to maximize margins by deciding which products to retain, remove, add, or improve. With operations spanning 32 countries and over 50,000 daily shipments, managing and optimizing SKUs was a complex and time-consuming task. Variations in sales volumes and market demand across multiple channels added further complexity. The client required a scalable solution to analyze the competitive landscape, identify market opportunities, and make informed decisions quickly and efficiently.

Solution:

eClerx implemented a data-driven SKU rationalization solution using advanced analytics and competitive intelligence. The approach automatically assessed the optimal SKU range based on factors such as digital interactions, customer data, transaction history, competitor ranges, and marketplace demand trends.

Performance was measured across five dimensions—traffic, sales, content, conversion, and demand transfer—using indices to identify opportunities and guide decision-making. This analysis was powered by technologies including eRange, Merchandiser+, and eCube, which provided insights into product performance and opportunities for improvement.

Our solution equipped the client’s category management teams with a robust data science toolkit to make strategic decisions at speed and scale. It offered actionable recommendations for optimizing the SKU portfolio and aligning product assortments with customer demand.

Impact:

By leveraging eClerx’s expertise in analytics and technology, the client transformed their SKU rationalization process, enabling them to enhance category performance, meet customer needs effectively, and drive sustained growth.

“We partnered with eClerx Digital to help us streamline our product offer, taking a data-driven approach to removing, adding, retaining, and improving the assortment of SKUs based on demand. Their ability to quickly formulate an analytics framework to address the problem at hand and leverage data science and technology to develop a scalable solution enabled our category teams to spend less time trawling through data and more time strategizing their range mix according to customer needs.”

RS Component, Product Manager

How We Did It: A holistic data-driven approach for
speed and scalability.

The inputs from the data scraping were modeled using an ensemble of technologies and tools to bring out insights on product performance and opportunities for supplier brands and  product changes.

• NLP & machine learning algorithms
• Text matching
• Substitutability
• Assortment intelligence
• Clustering
• Forecasting

Experts & advisory used:

6 subject matter experts

eClerx Digital won ISG’s 2021 Digital Case Study Award for its proprietary SKU Range Optimization for RS Components. ISG showcased the year’s best provider and client partnerships.