Customer Data & Analytics Blog

NRF Takeaways—AI to Rescue the Customer Experience

Ed Wolf | 4 minute read

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From Jan 15-17 in New York City over 30,000 attendees—analysts, journalists, and other thought-leaders—gathered to attend NRF’s Big Show 2017, the largest retail technology event of the year. 

Each year, this show is the perfect venue for retailers to discuss the latest trends in the industry, and to talk about the technology providers at the heart of creating these innovative solutions. Between the keynotes, sessions, the exhibit halls, and the impromptu discussions, NRF highlights the key topics and issues all retailers must deal with today and in the future. 

This year’s event was the largest ever, and the packed sessions, crowded halls, and meeting rooms seemed to indicate an industry going through a massive transformation—the ever-increasing digitization of their business—and an audience eager to learn how to best maximize the opportunities brought about by this change. 

Some of the topics at the show were cool and cutting edge—AR/VR, Robotics, Location Beacons, and various IoT (internet of things) applications. But those seemed indicative of what was coming in the future—the “meat” of the content centered around how retailers can address their challenges and leverage opportunities NOW. 

Improving Customer Experience in an Omni-Channel World

One of the major “NOW” topics of discussion at the show was the need for retailers to improve the customer experience, which is increasingly challenging in today’s omnichannel, highly competitive environment. This typically involves personalization; the idea that the customer feels the retailer understands them and speaks to them as if they know their needs, wants, and preferences.   

Most brands agree that, if they can communicate in an emotionally intelligent way with their customers, they will receive a higher level of engagement, loyalty, and ultimately revenue in return.  Many retailers spoke of a “new mindset” or a “100% personalization strategy” 

In practice, however, brands struggle with this—they have difficulty knowing exactly how to communicate.  It’s difficult to understand what message or offer to which customer, through what channel, and at what time.  It is so difficult, in fact, that they default to mass emails or give every customer the same discount, thereby cannibalizing profits and delivering generic communication. 

The reason for this is centered around data.  In theory, retailers have more customer data than ever before.  This includes preferences, purchase history, spending habits, demographics, intent, and other attributes. In theory, a large amount of data should make it easy for retailers to truly understand their customers and deliver the best, most personalized experience, whether online, in store, via email, or on a customer support call.  We say, “in theory”, because the reality is that shockingly few retailers are able to take advantage of the benefits that “big data” provides. 

The problem for many of these retailers is that this data lives in silos. The e-commerce data is stored in one area, the in-store data lives somewhere else, the email team has campaign results data, and someone else is in charge of social media data. You get the picture. So, when marketing tries to execute a really personalized, segmented campaign, they can’t do it without calling someone in the IT group, or a marketing data analyst, to pull a report. Then they must wait for that report, plug it into a marketing execution tool of some kind and fire away. By that time the data might be days or even weeks old and is probably incomplete, leading to outdated promotions or irrelevant offers. 

AI to the Rescue

Most retailers understand that, due to the huge volume of data coming from a wide variety of sources ,machine learning and AI is needed to wrangle all the data into one consistent view of the customer. 

Another topic of concern at the event was the quality of the data itself.  Because of the siloed state of the customer information, most retailers don’t feel confident that they really have a true understanding of each customer.  They feel like they are missing key information on their customers’ behaviors in their various channels. Also, because some of the legacy systems being used are antiquated, more than a few retailers remarked that they couldn’t identify the same customer in different channels, which often leads to multiple messages to one person—the quickest way to get unsubscribed. 

So, these topics were at the heart of many of the sessions and informal conversations at NRF.   The challenge practically all of these retailers face is how to ensure they are getting ALL of their customer data clean, and in a timely fashion, and then how to best use that data to analyze their customers and produce the insight needed to personalize communication.  And, this must be done automatically and in a continuous, near real-time manner, with insights into how to adjust execution based results.  It’s a daunting challenge indeed, but one that is crucial to solve. The stakes are tremendously high, as the battle for customer loyalty is fierce. 

Interestingly, most of the retailers speaking in the NRF sessions had a good understanding of all these roadblocks, yet they can find few technology providers who deliver a robust and comprehensive solution. 

The good news for customers is that both retailers and technology providers understand and are committed to fixing this problem. If that happens, we’ll be entering a golden age of emotionally intelligent personalization. Perhaps that will be the key topic at NRF 2018.

Having worked for, and with, numerous leading edge retail companies, and having a background in AI/machine learning, and data management, these massive data quality, personalization, and customer intelligence challenges are exactly why our founders started DataXylo. To learn more about how DataXylo mitigates these issues, please visit www.dataxylo.com

Topics: Customer Intelligence