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How Nordstrom Utilizes Human Intelligence to Blend Brick-and-Mortar with Online Commerce

Erin Shellman (Nordstrom), David Von Lehman (Nordstrom)
Enterprise Data Grand Ballroom West
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Nordstrom started modestly in 1901 as a small shoe store in Seattle, and has since expanded to 117 full-line department stores and 138 Rack stores across the country. The art of retailing has changed dramatically over the last century and retailers today are concerned with understanding customer behavior and preferences both in the physical world and online. Today’s customers expect a unified, relevant experience across all touch-points: online, in-store, and on mobile devices.

The goal of the Nordstrom Data Lab is to create products that rely on a wide spectrum of data resources from within the company and social media to reinforce a unified face to our customers. This includes emulating aspects of the customer-centric store experience on the web, and applying novel data analyses to augment and enhance the in-store experience.

This talk is for people with large and varied data who are interested in novel applications of data analytics, machine learning, and visualization to influence stakeholders and put the power of data to work for their businesses. We’ll walk through three case studies where we have delivered insights and/or products that blend data and experiences from physical and online commerce:

• A recommender system powered by the collective fashion expertise of our personal stylists
• Engaging, interactive visualizations powered by d3.js
• Clothing color trend visualizer

In the process we’ll discuss the challenges, tools, and techniques we employed along the way. We’ll also cover how the development of rapid prototype user interfaces have proven a powerful tool for conveying insights to and gaining support from business stakeholders. Some of the technologies that will be discussed include: R, Python, Ruby, d3.js, and Node.js.

Erin Shellman


I am a data scientist in the Nordstrom Data Lab and a specialist in statistical computing. I am interested in the development of scalable machine learning methods with applications in recommendation systems, market segmentation and customer engagement. I have a master of science degree in biostatistics and a PhD in Bioinformatics, both from the University of Michigan in Ann Arbor. Big data problems are my passion.

David Von Lehman


David is a full stack developer with 15 years experience building B2B and B2C applications. He spent 6.5 years as a Sr. Application Architect leading the design and implementation of many customer facing features of Recently he joined the Innovation Lab team which focuses on eliminating uncertainty around high risk technology endeavors. Currently he is focusing on partnering with the newly formed Nordstrom advanced analytics team to tackle some of the organizations toughest data challenges.


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