Global Startup Parcel Perform Collaborates with Amazon Web Services (AWS) to Improve E-Commerce Delivery Experience with Machine Learning

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shoppers' satisfaction, but arrival date predictions by logistics carriers are often not available, inaccurate, or outdated, leaving consumers frustrated with the online shopping experience.

Parcel Perform is leveraging machine learning to predict more precisely when customers will get their online shopping items.

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.

Source: https://www.parcelperform.com/

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Parcel Perform Pte Ltd. (2020, September 22). Global Startup Parcel Perform Collaborates with Amazon Web Services (AWS) to Improve E-Commerce Delivery Experience with Machine Learning. AZoRobotics. Retrieved on April 16, 2024 from https://www.azorobotics.com/News.aspx?newsID=11638.

  • MLA

    Parcel Perform Pte Ltd. "Global Startup Parcel Perform Collaborates with Amazon Web Services (AWS) to Improve E-Commerce Delivery Experience with Machine Learning". AZoRobotics. 16 April 2024. <https://www.azorobotics.com/News.aspx?newsID=11638>.

  • Chicago

    Parcel Perform Pte Ltd. "Global Startup Parcel Perform Collaborates with Amazon Web Services (AWS) to Improve E-Commerce Delivery Experience with Machine Learning". AZoRobotics. https://www.azorobotics.com/News.aspx?newsID=11638. (accessed April 16, 2024).

  • Harvard

    Parcel Perform Pte Ltd. 2020. Global Startup Parcel Perform Collaborates with Amazon Web Services (AWS) to Improve E-Commerce Delivery Experience with Machine Learning. AZoRobotics, viewed 16 April 2024, https://www.azorobotics.com/News.aspx?newsID=11638.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.