NRF16: SAS® demonstrates how retailers put customers at the center of IoT

Retailers create offers that matter, optimize operations by analyzing sensor, beacon data

Learn how Event Stream Processing from SAS can help make the shopping experience more personalized.

A consumer walks into a major department store to shop for new shoes. Her smartphone is on, and she immediately reaps “best offer” benefits based on her previous purchases and enabled by the Internet of Things (IoT). Constantly streaming data from connected devices – the heart of IoT - offers retailers access to unprecedented customer connections, but only if they have the right tools to analyze the data. That’s where SAS shines.

Analytics leader SAS was analyzing device data long before the acronym IoT came into vogue. SAS will interactively demonstrate its IoT capabilities live in Booth 2743 during NRF16, Jan. 17-19, in New York City. Retailers using SAS® Analytics uncover patterns emerging from the downpour of retail data – even while the data is still moving – so they can quickly and confidently take actions that matter to customers. These capabilities represent SAS’ initial offering in the space. To support retailers and other representatives more comprehensively, SAS will release a suite of IoT products in the spring of 2016.

IoT benefits retailers behind the scenes, too

Imagine a grocery store at 5 p.m. on a Tuesday evening. Customers rush in to grab dinner essentials. When that grocery store is equipped with IoT sensors like geofencing and other location-based technologies, it stands a better chance of anticipating operational and customer needs that create a more satisfying, efficient shopping experience. Analyzing IoT data with SAS helps retailers identify patterns so they can confidently take action – such as shifting in-store staff to the checkout lanes, making sure freezer units are operating efficiently or delivering a customized promotional code directly to a customer’s smart device.

“Retailers are more optimistic about IoT than we expected them to be,” said Nikki Baird, RSR Research Analyst. “Rather than operational improvements that save costs, their interest currently lies more with customer engagement and insights that drive growth. Even with existing data – supply chain, merchandising, customer, marketing, etc. – retailers could benefit today from ‘exception management tools,’ but they’ve resisted implementing them in the past. It often comes down to trust that exception management is finding everything that is wrong and not surfacing alerts that turn out to be nothing. Getting that foundation in place is a must-have, because with IoT, exception management is critical.”

SAS Analytics allows retailers to:

  • Sense where customers are and what they’re doing. Advanced analytics and machine-learning algorithms identify relevant information. SAS deciphers signals in data streaming from sensors – in the network and at the edge – so a retailer can confidently make decisions in real time.
  • Understand which customers have been shopping on your website before visiting your store. SAS allows a retail enterprise to share a single, coherent language that can be deployed anywhere – at the sensor device, in data gateways, in cloud aggregators – to consistently share analytically sound information throughout a connected ecosystem.
  • Act by directing store associates to customers in need. By using exception management practices, SAS Analytics for IoT integrates necessary instructions for action based on streaming data indicators. This includes separating what alerts to issue and to whom, what systems need to respond, and which portions of the data should be examined more thoroughly. The continuous analytics cycle gives retailers or consumer goods manufacturers the ability to take control of their IoT environment.

“Without analytics, the IoT is just a bunch of smart sensors sending data into the void,” said Alan Lipson, SAS Global Retail and CPG Industry Marketing Manager. “Analyzing more data from more sources helps companies identify trends faster, respond sooner and connect with customers in a way that’s meaningful.”

SAS offers a foundation of sophisticated streaming technology, mature analytics and proven domain expertise that provides users with meaningful, specific capabilities to make sense of IoT data. SAS provides retail customers a secure path for making real-time personalized offers, predicting maintenance needs and a host of other actions that can deliver concrete business value. SAS IoT analytics delivers intelligence in the connected world. 

This is the 20th year SAS has participated in the NRF BIG Show, one of the most influential retail events of the year. For more about SAS Analytics for retail and SAS Customer Intelligence, visit SAS at the NRF 105th Annual Convention and EXPO in Booth 2743. 

Visit Internet of Things (IoT): What It Is and Why It Matters for more information. To learn more about mastering the nuances of retailing today, read Analytics Are the Power Tools of Retail or download Modern Merchandising: Managing complexity with new tools and techniques. Follow SAS on Twitter @SASRetail and with #NRF16.

Progressive retailers prefer SAS

SAS’ powerful analytics and extensive industry experience empower retailers to anticipate customer desires and advance business objectives. SAS’ portfolio of retail and customer intelligence software is available through several different investment, deployment and growth options.

SAS retail and consumer packaged goods customers include Academy Sports + Outdoors, Aeropostale, Ann Taylor, AutoZone, Bealls, Belk, Best Buy, Brooks Brothers, Cabela’s, Carrefour, Casino, Chico’s FAS Inc., Coach, DSW, Family Dollar, Foot Locker, Fresh Direct, Frito-Lay, Gander Mountain, Godiva, Hudson’s Bay, Kellogg’s, Kohl’s, Levi’s, Macy’s, Mark’s Work Wearhouse, Marks & Spencer, Nestlé, Office Depot, Overstock.com, Procter & Gamble, S Group, Sainsbury’s, Stage Stores, Staples, Tesco, Tractor Supply Company, Waitrose, Wakefern, Williams-Sonoma and Winn-Dixie.

SAS demonstrates its IoT capabilities at NRF16 this week

 

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