How to Use Customer Analytics to Break Down Silos and Build Stronger Customer Relationships

As the retail industry rebounds in 2018, brands must make a concerted effort to build meaningful customer relationships in order to maximize their piece of the pie.

By most metrics, 2017 was hardly a banner year for brick-and-mortar retailers. A record high rate of store closures paired with the expanding market share of ecommerce-only retailers cast a dark shadow over some of the most formidable shopping mall mainstays of decades past.

But while the store closures aren’t expected to stop anytime soon (Business Insider estimates that 2018 will see nearly 4,000 big box locations close up shop), recent forecasts suggest that a retail renaissance may already be underway. According to the National Retail Federation (NRF), July retail sales were up 0.4 percent over June and 4.9 percent over July 2017. In light of these figures, the NRF bumped up its 2018 year-over-year retail sales growth projection to 4.5 percent — a sizeable increase over the 3.8 percent it projected earlier this year.

Much of this growth has been concentrated among big box retailers like Target, which recently reported its strongest same-store sales numbers in over a decade. “There’s no doubt that, like others, we’re currently benefiting from a very strong consumer environment — perhaps the strongest I’ve seen in my career,” says Target CEO Brian Cornell.

Target’s success can be attributed in part to its robust investment in its digital presence. Early in 2017, the retailer unveiled a plan to pour $7 billion into a number of initiatives designed to help it adapt to the modern retail era — foremost among them, a dramatic expansion of its ecommerce platform. According to CNBC, this investment has already paid tremendous dividends, with Target’s digital sales increasing by over 40 percent during the second quarter of this year alone.

“I think you’re seeing winners and losers right now in retail,” Cornell concedes. “We took a path that said we are going to invest in the long-term.” This, ultimately, is the salient point of Target’s success story. If retailers want to take advantage of the budding retail renaissance, they must consider the long-term implications of their short-term decisions, beginning with how they utilize data to build meaningful customer relationships.

Retail Marketing Teams Seeing More I-to-I than Eye-to-Eye

With the abundance of data at retailers’ fingertips — purchasing data, CRM data, email engagement data, etc. — it would seem that marketers have all the tools they need to pivot to a customer-centric approach. Unfortunately, while the customer data needed to craft engaging, personalized brand experiences certainly exists, it’s often plagued by the scourge of responsive retail marketing: siloing.

For a retailer to build — let alone maintain — a meaningful relationship with a customer, it must have access to a holistic view of who that customer is. For instance, imagine a retailer’s customer, Miguel, makes half of his purchases in brick-and-mortar stores and half of his purchases online. This 50/50 split means that Miguel will be just as responsive to messaging related to his physical interactions with the brand as he is to messaging related to his digital interactions with the brand. As such, if the retailer sends Miguel a promotional email that only addresses one type of his brand interactions, it’s missing out on a great deal of potential engagement.

Because many retailers house their in-store purchasing data in a point-of-sale (POS) system and their online purchasing data in an ecommerce system, scenarios like these play out surprisingly often. This disconnect is only exacerbated by the fact that the typical retail marketing team is divided into numerous subteams, each of which is tasked with managing a specific channel or data source.

When ecommerce teams are only concerned with ecommerce data and in-store teams are only concerned with in-store data, it’s not hard to see why retailers so frequently fail to deliver consistent, unified brand experiences to their customers. Indeed, a recent survey conducted by the Harvard Business Review found that data silos and organizational silos are the second and third biggest obstacles preventing marketers from leveraging real-time analytics in an effective manner, respectively.

That’s one of the reasons why a fully-integrated customer analytics platform is so valuable, as it automates many of the data centralization processes that are laborious, if not impossible, to do by hand.

How to Dismantle Organizational Silos

Breaking down organizational silos is a two-step process. First, a retailer must figure out a way to bring all of its data together. In many ways, the digital age has been both a gift and a curse to retail marketers. On the one hand, retailers have access to previously unfathomable volumes of data on each of their customers. On the other hand, they now face the unenviable task of aggregating millions of data points drawn from dozens of sources — all in close to real time. That’s one of the reasons why a fully-integrated customer analytics platform is so valuable, as it automates many of the data centralization processes that are laborious, if not impossible, to do by hand.

Once a retailer has stitched its data together, it must export this integrated dataset to its various marketing tools. Since raw data isn’t particularly illuminating in and of itself, retailers typically utilize dozens of marketing tools — many equipped with sophisticated AI and/or predictive analytics capabilities — to find actionable insights into what their customers want from their brand.

The Benefits of Getting It Right

Using customer analytics to break down data and organizational silos and build stronger customer relationships is no small task, but the benefits are well worth the effort.

Strategic insights can help a retailer figure out which customer personas it should be pursuing, which product lines it should be investing in, and how it should be positioning itself to provide its customers with the best brand experiences possible. They can also provide answers to some of the most pressing questions retail CMOs face, from “Which of our customers have the highest lifetime value, and how do we acquire more of them?” to “What gets customers excited about engaging with our brand?”

Ultimately, access to — and proper utilization of — these kinds of customer insights plays a significant role in determining whether a brand is a “winner” or a “loser” in today’s hypercompetitive retail landscape. Retailers that are able to use customer data effectively can expect both an immediate lift in revenue and, more importantly, sustained long-term growth.

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