In this Data Point, Frank visits the new Barnes and Noble location in Rockville, MD which is the first store in the US to sport the book retailer’s new design.

Oddly enough, it looks a lot like the Amazon brick and mortar bookstore just down the road in Bethesda.

With less space and a revamped layout, you have to think that the store’s design is much more data-driven. (Pun somewhat intended.)

Data is the oil that’s lubricating the sales machines at huge online retailers like Amazon.com and is exploring user behavior for tech giants like Google and Facebook.

According to Amazon Web Services (AWS), its payments data engineering team alone is responsible for data ingestion, transformation and storage of a growing dataset of more than 750 TB.

That enormous volume will dwarf that of most other organizations, but this doesn’t mean that their data is any less valuable or that there isn’t room left to compete.

The insight that a retailer can gain from good quality data isn’t determined by how much there is of it, but rather by how it’s collected, analyzed and used to meet customers’ requirements. Where will demand be particularly high next weekend? How much influence will the weather have on online sales? Under what circumstances is the probability of fraud or returns particularly high? Why does the customer behave like this and not differently? The answer to all of these questions is in the data.

Learn how Microsoft is simplifying IoT with the evolution of Azure IoT Central.

Step through a live demo of the new IoT Central retail application template with Avneet Singh, Senior Program Manager, IoT Solutions team.

Learn how this IoT app platform keeps devices connected with built-in device management.

Understand IoT Central makes it easy to integrate into business applications to deliver insights to business decision makers.

Siraj Raval built a demo app called SmartSneaks that lets a user convert a song or image into a generated shoe design.

This is an example of how AI can be used to transform retail by giving users a more personalized experience. The tools he used to build this are the Flutter framework for mobile development and the Flask framework for web development. There are 3 learning objectives in this video including how to build a deep learning API for your mobile app, how to generate images with a generative adversarial network, and how to calculate image similarity with OpenCV.

In the post-Amazon economy, all brick and mortar retailers are struggling. Some have outright failed and others on the brink. However, there are a few outliers that refuse to go down without a fight and are actually innovating.In this DataPoint, Frank notes one that has actually turned physical location to its advantage by helping Amazon process returns! 

Press the play button below to listen here or visit the show page at DataDriven.tv

It’s been nearly a year since the end of the road for Toys R Us. I recorded a Data Point last year about the mixed feelings of getting good deals on stuff from the store vs picking clean the bones of an old friend. (Listen here).

CNBC has an interesting video from last March about the rise and fall of an iconic American retailer. I disagree with the assertion that “no one saw” the big box retailers coming or the rise of Amazon. I was at the forefront of the dot com boom at Barnes & Noble in the 90s and had friends who worked at Toys R Us’ early efforts to create an online store.  They saw this coming – senior management just couldn’t believe they could be bested by anyone.