Case Study
Digital Transformation with Machine Learning
Overview
U.S. based Fortune 300 global industrial distribution and inventory management services company with 15,000 employees, 330 branches, 19 distribution centers, and 41 regional contact centers serving 3 million customers. Annual revenues are $10 billion, 41% online.
Problem
- The client was in a first-mover battle for Digital revenues.
- They sought innovative ways to serve customers and increase revenues.
- Increasing competition from “big box” retailers moving into B2B space
- Increased M&A to achieve economies of scale
Action
- Analyzed the architecture of the customer experience, interviewed customers, devised options, and developed customer journeys.
- Wrote and sold business case recommending placement of personalized ad tiles to increase customer affinity while promoting products they are most likely to buy.
- Designed personalization engine using Big Data approach, which captured keystrokelevel data, analyzed for pattern of product combinations, and combined with purchase history to display products most likely to purchase.
- Created functional specifications and contract documents to streamline customer acquisition and order-to-cash.
- Led the implementation and change management teams.
Outcome
- Exceeded new Digital Platform goal of $100 million in annual sales in six months.
- Customers felt client understood them by suggesting products they wanted to buy, saving them from having to remember and eliminating the need to search for them.
- Popular product pairings were made available to sales and marketing for promotions.
- Marketing Promotions went from a 3% hit rate to 43% hit rate in six months.
- Innovative bundles with external partners were being weaved into customer journeys for future waves of releases – not possible with old approach.