Collecting data used to mean a morning conversation between a clerk and a customer buying coffee. Today, mobile apps, loyalty programs and transaction-based data analytics are reshaping that conversation, putting an automated, more scientific spin on an age-old ritual.
That technology won’t necessarily mean radical changes, either. It most likely will merely add tweaks and logical next steps to what already exists.
For Michael Sherlock, vice president of fresh food and beverage for Wawa Inc., Wawa, Pa., it’s a simple new capability the company is about to test in its app that remembers a customer’s previous order and asks if he or she would like to have that meal again. (See story on p. 116.)
“It’s a matter of leveraging technology,” Sherlock said during a session on digital ordering at CSP’s FARE conference in June in Nashville, Tenn. “With a mobile order, you can save an order, push personalized [offers] or engage in a way that’s meaningful to [the customer].”
Driving Customer Feedback
Any consumer-facing technology—from loyalty programs to the point-of-sale (POS) register—already has the ability to collect data that, if used effectively, allows retailers to offer more compelling products and a better experience.
Take a new development from mobile-app provider GasBuddy/OpenStore, which designs responsive apps and websites for retailers. After gathering feedback from customers, the Gaithersburg, Md.-based firm recently developed a Spanish version of its solution.
“We [already] designed our platform to get customer feedback using surveys: what’s important in terms of deals, the location finder, playing games,” says Jeff Peters, product manager for GasBuddy/OpenStore. “Until now, the system could only have that conversation with an English-speaking customer. The change will provide that same survey to Spanish-speaking customers and will show us what features they appreciate.”
In its current format, the app and website solution already asks consumers what their preferences are, such as what brand of soda they like, as a way of allowing the retailer to offer relevant incentives. Adding the Hispanic consumer to the process will provide a new level of demographic information that wasn’t available before, Peters says.
So either by an active “tagging” of a user—which combines information he or she provided with ongoing shopping histories—or through a survey, retailers can make more informed decisions about marketing and affinity strategies, Peters says.
Another data-collection opportunity comes with loyalty programs. Jane Sinn Gabriel, retail solutions product manager for
The Pinnacle Corp., Arlington, Texas, says such programs have built key metrics around frequency, velocity and spend.
“Retailers can use these key measures to identify their most engaged members down to their least engaged members,” she says. “Average spend and market-basket data … can also be compared to the same measures in the general transaction data, [showing] whether loyalty has a real and consistently positive impact on … traffic, sales and average transactions.”
Loyalty systems often capture demographic data, which lets retailers create groupings of customers by age, ethnicity and economic attributes. The data can provide insight into customer behavior, such as when certain groups visit most often, what they purchase and how much they spend. Based on that information, an organization can review its strategy and determine whether changes are needed to be more successful.
Mining Transaction Data
Even the basic POS transaction has become a rich source of business intelligence—a catchphrase often referring to solutions that can turn transaction data into meaningful trends, customer personalization or marketing strategies.
Retailers today most likely feel the pressure to collect POS data as major suppliers have begun to ask for it to better analyze market needs, says Greg Gilkerson, president of PDI, Temple, Texas.
Retailers need the technology to manage data, but that ability has to be simple—and technology suppliers are stepping up. The latest release of PDI’s solution, for example, involved a complete rewrite of the data-collection system, a “ground-up” endeavor, Gilkerson says. The task was necessary to better integrate that data collection, retrieval and analysis into the entire system.
Gilkerson describes the evolution as a “maturing process,” one that results in a lower cost of ownership for collecting data: “These days, retailers don’t need an army of tech guys to drive their business.”
Members help make our journalism possible. Become a CSP member today and unlock exclusive benefits, including unlimited access to all of our content. Sign up here.