T
THINK Contributor

Why predictive analytics will steal the show at National Retail Federation’s 2017 Big Show

By , January 11, 2017
post_thumb

Predictive artificial intelligence (AI) is changing the online shopping experience and is set to steal the stage at the upcoming 2017 National Retail Federation’s Big Show. Machine learning will help retailers forecast demand and set prices in more sophisticated ways. Our smartphones, tablets, and desktops will integrate better to learn from user habits and adjust based on context to make experiences more predictive. Design and the user experience will become more human-centered, with predictive technologies working within the ecosystem of our devices, holistically considering each touch-point. Ultimately, to retain customer loyalty, retailers will have to deliver true value in exchange for collecting and analyzing data. 

These trends will be at the center of this year’s NRF show, with demos and panels on anticipatory online shopping technologies to more personalized in-store experiences. Here’s a closer look at some of the key trends retail marketers will likely be seeing on the show floor and paying close attention to in the next year.

The Continued Reimagining of the Connected Device

The “connected consumer” is not a new concept, and today’s omni-platform retailer is focusing on developing an integrated platform that provides a consistent consumer experience across all devices.

Just a few recent examples of expanding the connected consumer include Amazon’s Dash Buttons, which allow consumers to order items with the press of a button. BI Intelligence data shows Dash Buttons are growing in both order volume and brand availability. Competitors such as Kwik are working to bring similar functionality to homes for brands like Domino’s, Budweiser and Huggies in a direct-to-consumer move. Hiku lets consumers personalize in-home ordering with partnerships at stores such as Walmart. These technologies will be scaling beyond the biggest players and redefining customers’ relationships with the marketplace.

At this year’s NRF show, there are likely to be new technologies debuting, including virtual assistant shopping technologies, expanded IoT capabilities and deeper customization of in-home shopping options, making it easier to purchase goods across a range of product categories. Top executives from Levi Strauss & Co. and Intel will be delivering a keynote on the future of connected retail, in-store, in-home and beyond, in the session Driving Retail Transformation: How Data and Smart, Connected Technology Deliver Amazing Customer Experiences.

Deeper Store-Level Analytics

The National Retail Federation estimates that online shopping will increase 7 to 10 percent during this holiday season alone. Yet even with the continued shift of shopping activity to online venues, brick and mortar locations are a major part of the retail experience. McKinsey estimates that despite the online shopping push, brick and mortar shopping will still account for 85 percent of sales in 2025. eMarketer released similar research, estimating that just 9.81 percent of sales will occur online by 2019. At this year’s NRF show, companies will be taking in-store analytics to the next level. As retailers have successfully embraced experiments with technologies like iBeacons, which track in-store traffic patterns, the next generation of in-store analytics will make it easier for retailers to customize the experience at each physical location. For users who have downloaded the Macy’s app and have opted in, the retailer uses beacons to determine which products they’re looking at in-store and send customized product information and promotions. Woolworth’s has launched a click and collect program; customers order their groceries in advance, and then beacons signal when they’re within a certain distance of the store so staff can assemble individual orders.

The focus isn’t just on understanding what each customer does in-store, although that remains important. Retailers are looking at each physical location as an opportunity to customize the blueprint of how they do business. For example, the needs of an urban location may vary dramatically from a suburban site in terms of inventory, floor plans, in-store advertising, and much more. Macy’s, for example, is currently testing an AI app that provides personalized guidance on product location, inventory and more for each individual store. Deeper store-level analytics will help retailers dynamically customize the in-store experience for customer segments and individual consumers. Attendees who are interested in this topic can visit the session From Data to Delight: An Insight Driven Revolution of the In-Store Experience.

Nuanced Search Technologies Scale

For online retailers, nuanced search – powered by natural language processing, machine learning and predictive analytics – is bringing consumers to the right products faster. In large part, this is being driven by the rise of mobile and how voice search is changing the way customers search for products, moving from keyword searches to more natural inquiries. Retailers are also dealing with larger inventories and consumers who want to more quickly find specific products without searching through pages of results.

Retailers are investing in technologies to improve the shopping experience. Earlier this year, for example, Etsy acquired Blackbird, which Total Retail reported would play a critical role in helping consumers find unique products amid the site’s more than 40 million listings. And as Forbes reported, North Face has launched the Fluid Expert Personal Shopper which uses IBM Watson’s cognitive capabilities to create a more intuitive shopping experience. A range of tools, from the Watson Conversation Service to Google’s Natural Language API, are providing retailers with the tools to enhance their search technologies. The NRF show will likely feature trends that roll out better search capabilities to a wide range of online retailers, across size and industry categories. 

Improving Big Data Infrastructure

While the high visibility trends in predictive analytics and retail tend to be the consumer-facing innovations and the programs that make new services possible, it’s important to look below the surface. Futuristic shopping experiences are powered by massive IT engines. The Harvard Business Review estimates that companies spend $36 billion in storage and infrastructure for big data, and that number will double by 2020. Sophisticated programs that mine data and help retailers visualize trends in real-time, demanding the latest in computing technology. The NRF show lineup is sure to feature easy-to-scale cloud-based storage, high-bandwidth networking solutions and the computing power needed to drive 2017’s most innovate retail solutions.

The Layers of Data

The hottest trends at this year’s NRF show are going to point to one big idea: There is no single source of truth about the customer. Past purchases, search history, location, integration with calendar events, and social media activity are all facets of a more complex picture of today’s customer.

Yet, no single source tells the retailer everything they need to know for a true 360 view. Customers are expecting their REI app to flag a sale on snow boots after the app sees an upcoming skiing trip in their Google calendar, and for Google Maps to then show nearby store locations and traffic information, for example. Predictive analytics are at the heart of making this vision a reality.

The Post-Purchase Revolution

Retailers aren’t just focused on customer acquisition. There’s an increasing focus on how big data and predictive analytics can help at every stage of the customer relationship. True digital transformation and relationship building with customers focus on delivering great experiences after the sale. This year’s show is likely to showcase how predictive analytics can transform the post-purchase experience.

From smarter upselling and cross-selling, to using AI to deliver the content needed to optimize customer success, retailers are rapidly expanding their use of predictive analytics across the customer life-cycle. For example, companies like Narvar are using AI technology to help retailers provide better service during the post-purchase period, including fulfillment, shipping and returns for brands like DSW, Gamestop, Crate and Barrel and The Limited. Fitness brand Under Armor used IBM Watson to develop a fitness app to deliver more value to customers and deepen their connection. These examples are just scratching the surface of what’s possible for AI after the sale.

Whether it’s improving the consumer search experience or delivering better in-store analytics, predictive analytics stand to shake up every area of the retail experience. For companies interested in using all the data at their fingertips to shape an unforgettable customer experience and streamlined shopping funnel, this year’s NRF show promises to deliver a host of new tools and technologies to make it happen. 

If you’re unable to attend Retail’s Big Show this year, be sure to follow the buzz on Twitter with #NRF17 and #THINKMarketing.

Please note that DISQUS operates this forum. When you sign in to comment, IBM will provide your email, first name and last name to DISQUS. That information, along with your comments, will be governed by DISQUS’ privacy policy. By commenting, you are accepting the IBM commenting guidelines and the DISQUS terms of service.