Case Study: World’s Leading Equipment Company achieves better pricing recommendations and higher margin with LTIMindtree

Harnessing the Power of Azure Machine Learning to Improve Pricing Recommendations on New Equipment

World’s Leading Equipment Company, a global manufacturer of elevators, escalators, moving walkways, and related equipment, needed a better way to set equipment discounts. Sales reps were relying on experience to recommend discounts, which was hurting margin and revenue. LTIMindtree helped the company address this challenge with Azure Machine Learning.

LTIMindtree designed a model to recommend minimum and maximum discount ranges, using feature importance to identify key drivers such as rise, speed, load, installation area, and sales category. Built with Azure Auto ML and deployed as a real-time REST API on Azure Kubernetes Service, the solution delivered measurable gains including a 3% margin improvement and 45% revenue increase in France, plus a 4.5% increase in booked units sold and a 23% revenue increase in Germany.