Global fashion retailer personalizes online shopping with AWS

Dan Berthiaume
Senior Editor, Technology
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Germany-based Zalando is running its machine learning workloads on Amazon Web Services (AWS) to reduce time-to-market of new online customer experience features.

Zalando, which sells lifestyle and fashion products across 17 countries, has selected AW as its preferred cloud provider. In addition to machine learning, Zalando is using AWS cloud technologies in analytics, compute, database, networking, serverless, storage, and more to transform itself into a more data-driven organization. As a result, it intends to optimize critical business functions such as supply chain management, pricing, marketing, and customer care.

Leveraging AWS’s machine learning services, Zalando seeks to continuously improve the customer experience by reducing the time it takes to design, launch, and scale new features for its e-commerce platform. Employing Amazon SageMaker to build, train and deploy machine learning models quickly, and Amazon EMR to capture, store, and analyze large volumes of data, Zalando’s engineering teams are using customer purchase data to create personalized shopping features like individual product and size recommendations, as well as predicting a customer’s future outfit preferences. 

Zalando is also using AWS machine learning to offer more personalized recommendations based on style preferences or a brand’s ethical practices, predict when items are in-stock for more accurate package delivery and return times, and forecast real-time availability of the latest fashion trends. Working with AWS, Zalando can develop and implement new customer applications faster, such as creating digital avatars that allow customers to virtually try on clothes, and delivering a customer experience that enables shoppers to see how outfits fit without trying them on physically.
Zalando is using a wide portfolio of AWS services. For example, the retailer deployed AWS Lake Formation to create a data lake running on Amazon Simple Storage Service (Amazon S3) to securely enable its developer teams to collaborate more effectively on projects across different service lines. 

In addition to its data lake, Zalando also combines data from its internal SAP workloads, including accounting, supply chain management, and e-commerce platforms, with AWS’s analytics portfolio, with modules such as AWS Glue, Amazon Redshift, and Amazon Athena, to produce transactional and analytical data reports that track business performance in real time. 

These insights help Zalando’s size & fit team to reduce size-related returns by predicting how a garment’s fit is impacted by the material or stretch and making size recommendations that match the customer’s fit preferences. Additionally, by migrating its SAP workloads to AWS, Zalando has reduced IT management time by more than 30%.
“Working with AWS, we’ve created a next-generation machine learning platform that enables all of our data scientists and developers to collaborate better and work more efficiently with teams across the company,” said Rodrigue Schaefer, VP digital foundation at Zalando. “This platform is enabling us to continuously improve the customer experience by rapidly reducing the time it takes to design and implement state-of-the-art personalization tools and new product features. From better stock management to a quicker returns process, we’ve also used a range of additional AWS services to drive operational efficiencies at all stages of the customer journey.”