Manhattan Associates Pioneers the Use of Machine Learning to Help Retailers Guarantee Accurate Delivery Promises

Manhattan Associates Inc. (NASDAQ: MANH) today announced the latest infusion of machine learning into its Manhattan Active® Omni suite to significantly improve the accuracy of delivery date calculations when fulfiling online orders from stores. Manhattan’s testing found that this new technology can decrease late deliveries by between 30% and 50%.

Today’s connected consumer is demanding accurate and aggressive delivery dates and fulfilment options during the purchasing process. To get orders to consumers more quickly and at a reduced cost, omnichannel retailers are increasingly choosing to fulfil orders from their stores. However, given the dynamic nature of the store environment, it is significantly more challenging to provide precise ship and delivery date calculation when fulfiling from stores versus warehouses. As a result, many retailers revert to vague or overly conservative delivery date estimates, which can negatively impact sales conversion.

Manhattan has enhanced its Interactive Inventory offering, part of its industry-leading order management solution, with machine learning to give online shoppers the most accurate and optimized delivery dates in real time. The solution uses the latest technologies to dynamically calculate delivery dates with a precision that is simply not possible using configuration methods. 

“In this latest update to Interactive Inventory, we have significantly improved what was already the industry’s most robust order promising solution with machine learning that helps retailers make better delivery promises and execute on them with confidence,” said Amy Tennent, senior director of Product Management for Manhattan Associates. “This improved accuracy will reduce cart abandonment, decrease late deliveries and increase customer satisfaction.”

Media Contacts

Daniel Osborne

Director, Marketing APAC

Deliver On Your Promise to Customers

Contact the Manhattan team to learn more.

Contact Us

Related Information