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

The retail game is the same as it always was: bring customers in and do what you can to make them come in more often and with larger baskets. The difference is the number of people vying for pieces of an increasingly finite pie with increasingly expensive slices.

Let’s not bother with talk of the vicissitudes of retail. If you’re in retail, your eye is specially trained to spot these daily headlines shouting about the apocalypse that’s coming or that’s just passed.

The keys is to build meaningful customer relationships to maximize the pie you get.

By most metrics, the last couple of years have not been kind to brick-and-mortar retailers. A record high rate of store closures paired with the expanding market share of e-commerce-only retailers is casting 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 (they’re already up 23% compared to this time last year), recent forecasts suggest that a retail renaissance may already be underway. According to the National Retail Federation (NRF), retail sales overall (including digital and brick-and-mortar) grew by 4.6% in 2018 and are expected to grow between 3.8%-4.4% this year.

Much of this growth has been concentrated among big box retailers like Target, who have been taking on Amazon by leveraging physical stores to enhance the online shopping experience.

In the fourth quarter of 2018, Target’s brick-and-mortar stores influenced nearly 75% of its online sales; in-store traffic rose 4.5%; in-store sales increased 5.3%; and online sales increased 31%.  

“We’re very pleased with our fourth-quarter performance, which capped off an outstanding year for Target,'' Brian Cornell, Target's chairman and CEO, said in a statement. "We delivered our strongest traffic and comparable sales growth in well over a decade.''

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 e-commerce platform.

“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, the retailer is 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 e-commerce 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 sub-teams, each of which is tasked with managing a specific channel or data source.

When e-commerce teams are only concerned with e-commerce 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 hyper-competitive 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.

To learn more about breaking down organizational and technological silos for holistic business growth, check out our webinar, Jumping the 3 Big Hurdles to Predictive Modeling. 

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