Providing the latest delivery date of online purchases is a crucial driver for online shoppers’ satisfaction, but arrival date predictions by logistics carriers are often not available, inaccurate, or outdated, leaving consumers frustrated with the online shopping experience.
Now, Parcel Perform is using machine learning to predict more precisely when customers will get their online shopping items.
The company has launched a unique machine learning algorithm, developed with Amazon Machine Learning Solutions Lan, which can reliably predict the date of arrival of any e-commerce delivery. The algorithm trains on delivery pattern data from millions of past orders to predict the date of arrival for any e-commerce shipment. This allows consumers to receive predictions of when their parcel will arrive, which is critical for improving the customer experience.
Today, 95% of logistics carriers don’t provide this information to the recipients. With more consumers shopping online, providing delivery predictions before and after checkout is essential, and offers opportunities for retailers to differentiate their delivery experience.
The solution was born out of the business challenge; Parcel Perform’s e-commerce customers want to leverage their fulfilment and shipment data, and convert it to a specific, time-bound delivery date. Having started the cloud-native business on AWS infrastructure, Parcel Perform turned to AWS to help build a solution to this challenge. Parcel Perform and Amazon Machine Learning Solutions Lab collaborated closely to build a flexible, scalable solution, combining AWS’ expertise in ML and ML services like Amazon SageMaker, with the specific requirements of the logistics domain to build this unique product.
“With our Date of Arrival prediction, consumers now know when their parcel will arrive, instead of just where it is at the moment. This date of arrival prediction truly makes the difference to their delivery. The experts in Amazon ML Solutions Lab team have been working closely with our development teams in advising and improving the machine learning algorithms that drive this service to make it a real value add for our customers,” said Dr. Arne Jeroschewski, Founder and CEO, Parcel Perform.
“Our work with Parcel Perform enhances the customer’s post-purchase experience by using machine learning to predict when a customer will receive their items. Combining our expertise in machine learning with the power of Amazon SageMaker, we were able to help build a solution that can scale to meet the needs of Parcel Perform’s e-commerce customers around the world,” said Michelle K. Lee, VP of the ML Solutions Lab at Amazon Web Services.