The brick-and-mortar retail industry is finally embracing its digital transformation moment. After years of lagging technological adoption, retailers are exploring their options when it comes to improving the retail experience on all levels.
This seismic evolution hasn’t gone unnoticed by some of the world’s leading digital giants. Recently, Mastercard and Verizon Business announced a joint venture to revolutionize shopper payments, contactless exchanges, and consumer personalization by leveraging 5G-powered technologies. The partnership promises to bring innovative thinking to retailers and enable them to scale up their services and solutions.
But 5G tech is just the tip of the retail digital transformation iceberg. Yet another powerful component already being considered by brands is retail analytics. In fact, the analytics landscape is booming — and in North America, it’s expected to exceed $8 billion in revenue by 2027, according to Global Market Insights. Regardless, nearly three-quarters of companies surveyed by Deloitte admit they don’t use “a single, common set of tools and methods across the enterprise for accessing and analyzing data.” This hampers their ability to form data-driven insights, even if they’re adept at collecting it.
What’s the cause of this glaring gap? There are many. First, plenty of brands don’t feel like they have the resources to make sense of the analytics they accumulate. Second, some leaders haven’t learned that mined data can unlock brilliant ideas that can help with everything from operational efficiencies to consumer habits.
A final reason for not using predictive analytics in retail falls on a lack of internal cheerleaders and supporters. Without upper management and store-level digital champions, team leaders don’t understand how to integrate data insights to boost the in-store experience — and they often fall back on old models. After all, if the people above them aren’t invested in analytics, why should they be?
The good news? Each of these obstacles to improving the retail customer experience by leveraging retail data analytics is far from insurmountable. And if you’re in the retail field and are eager to use the data you already assemble, you have choices. Below are some strategies that will help you offer a fresh and modern in-store experience with help from data:
1. Evaluate data to shed light on consumer buying habits
Customers often behave in predictable ways. For instance, they might gravitate toward certain shelves regardless of what’s on them. Or they might make purchases cyclically — but not necessarily on a cycle that would be obvious to you.
Data analytics helps you understand what’s happening beyond simply the buy-sell process. The more you understand about your customers (think basket sizes to ordering trends), the better your ability to forecast revenue. And you can often collect the data you need through point of service software that’s already integrated into your checkout process.
2. Use retail data analytics to map out your staff scheduling
It’s a tough job market for retailers. Many promising candidates are opting out of part-time and full-time work as a part of the post-pandemic “Great Resignation,” as well as other factors. Consequently, your ability to staff your store precisely is more critical than ever.
Data can help you understand your customer traffic flows to avoid both overstaffing and jams. As an example, you might realize your meat counter is busiest between 4 p.m. and 6 p.m. on Mondays and Thursdays. This small bit of information can allow you to pinpoint where to put your people and the hours they should be working. Additionally, counters and beacons can feed you real-time information on customer dwell times and foot traffic counts to ensure your team members are always where they’re most needed.
3. Let data inform your personalized shopping campaigns
Buyers love to feel like they’re getting a one-of-a-kind retail experience. You can make them feel unique by using analytics to construct recommended journeys that feel intuitive and individualized. At Sephora, for instance, personalization has become a brand mainstay. Through the beauty store’s app, customers can book appointments, virtually experiment with products, and receive customized recommendations.
Here’s the bottom line: Don’t underestimate the powerful advantages of hyperpersonalization. There’s a reason the process has been associated with increased sales across the retail sector. Plus, personalizing customers’ experiences might decrease sales and marketing outlays by up to 20%, increase conversations by up to 15%, and improve worker engagement by nearly one-third, according to McKinsey.
Digital transformation is blossoming in the retail sphere. Retail analytics can help companies effectively expand their customer relationships and revitalize a sense of consumer trust. All it takes is a willingness for retailers to learn how to better use the data that’s already at their fingertips.
Scott T. Reese is CTO at Harbor Retail
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