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SINGAPORE, Sept. 22, 2020 /PRNewswire/ -- Parcel Perform, the leading carrier-independent delivery experience SaaS platform, today launched a unique Machine Learning (ML) algorithm to reliably predict date of arrival of any e-commerce delivery. The solution was developed in collaboration with Amazon Machine Learning Solutions Lab. The underlying machine learning 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 percent of logistics carriers don't provide this information to the recipients. With 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 fulfillment and shipment data, and convert it to a specific, time-bound promise 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 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.
About Parcel Perform
Parcel Perform is the leading global carrier-independent delivery experience platform for e-commerce merchants and their customers. It integrates with 600+ carriers worldwide and is used by leading Australian brands including Nespresso, Catch Group and MECCA Brands to create exceptional delivery experiences.
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