Using Loyalty Data to Drive Sales

Convenience store shopping behaviors shifted dramatically during the pandemic, upping pressure on brands to discover new ways to drive traffic and revenue in their stores. Those with robust loyalty programs had a leg up, mining this data to gain quick visibility into these new needs and buying trends, and applying those insights into their businesses. Others moved quickly to introduce or level up loyalty programs of their own. Nearly two-thirds of U.S. c-stores (64 percent) had a loyalty program in 2020, according to PDI, and at least 60 percent planned to invest in them moving forward. Those experiences reinforce the growing importance of loyalty data in helping c-store brands better understand their customers. Loyalty data is increasingly seen as an essential tool to develop insights to drive decision-making across the enterprise. “If you’re getting into loyalty because you think it’s going to be a big win for you, you’re not getting into loyalty for the right reasons,” said Daniel Kahan, loyalty lead for W. Capra Consulting Group, a Chicago-based consulting firm. “Loyalty at its heart is a way to collect data.” A DATA-FUELED STRATEGY Convenience retailers leading the way in loyalty are upping their game by using this data to not only drive revenue, but also reap greater margins from those sales. Here’s what they’re doing differently: 1. Approaching Loyalty Data Strategically For loyalty leaders, leveraging data well is core to their enterprise-wide plan for meeting revenue goals. They set clear objectives for what they want to accomplish and then put the resources in place to make continual, incremental improvements in their ability to collect, unify, cleanse, analyze and apply loyalty data. Quality data is essential for activities such as segmentation and personalization, says Perry Kramer, managing partner at Retail Consulting Partners, a Boston-based consulting firm. “Anybody that’s going to put it in a loyalty program really wants to have a strategy around their data analytics and data cleansing, and then execution in the stores.” These resources include not just selecting a loyalty platform capable of taking them from where they are now to where they want to go, but also hiring loyalty and analytics talent to make the most of that data. Among the top items on this team’s to-do list is ensuring they are collecting the right data to support their goals. Loyalty leaders also make sure their loyalty data is distributed widely across the organization in ways that make it easy for non-data scientists to understand and apply it in their own domains. 2. Personalizing Based on Individual Behaviors Loyalty leaders’ continual push to refine their personalization capabilities has been key in sustaining them through fast-evolving pandemic behaviors. Personalized promotions delivered at the right time through the right channel with the right offer are the most effective. Applying artificial intelligence to loyalty data is proving key to unlocking new opportunities by recognizing subtleties in individual behaviors, such as establishing what defines a lapse in personal visit cadence for a specific customer to correctly time “We miss you” offer messaging. “Loyalty data is key for us because it is the broadest amount of data we’re able to collect on customers. It’s not just transactional. It’s item by item, seeing what’s selling, what’s not,” said Chris Hartman, director of fuels, forecourt and advertising for Rutter’s, a convenience store chain operating in Pennsylvania and West Virginia. “Considering they are our most frequent shoppers, they’re the ones that we want to make sure are seeing the value that we offer and we’re able to keep them happy and keep them coming back.” Those insights also help Rutter’s understand what might attract non-loyalty members to become more loyal, Hartman added. 3. Leveraging Location Data to Fine-Tune Offers Location data is proving an invaluable data point across retail to help put customer behavior in context. RSR Research found that an overwhelming 82 percent of retailers call the ability to combine geographic and demographic data for better business decisions very valuable, up from 71 percent just a year ago. The Greater Ohio area’s Duchess convenience store chain, for example, is gaining deeper insight into customer behavior and marketing effectiveness by using geofencing data to correlate when and where a customer is when a message is opened, such as reading a text just after pulling into the parking lot. Soon, the brand will start matching that data with purchase behavior. “We’ll be able to know if we send a specific offer as a geofencing message and a push notification, do they actually purchase that exact item in the store?” explained Nathan Arnold, director of marketing at Ohio-based Englefield Oil Co., which operates Duchess stores. In the future, Duchess hopes to use location data to tailor offers to specific store locations. 4. Tapping Into Consumers’ Appetite for Fuel Discounts Consumers are highly sensitive to fuel prices right now, and increasingly expect to be rewarded for fuel purchases. PDI found that fuel savings are the leading reward driver in loyalty program participation for c-store loyalty members (36 percent). Smart c-stores are leveraging this trend together with loyalty data to drive sales at the pump and in-store. “When you get fuel loyalty, then you get in-store loyalty,” says Retail Consulting Partners’ Kramer. Duchess is leveraging its loyalty data to apply learnings from past redemption patterns around when fuel prices are high vs. low. Now that fuel sales are up from early pandemic lows, the brand replaced references to points in its loyalty reward messaging with cents off per gallon — as in, buy two sandwiches, earn five cents off a gallon. “We find that it’s very important for our marketing efforts to give away this free gas because it’s increasing the rings, but it’s also increasing the sales of individual products,” noted Arnold. 5. Putting Profitability at the Center Loyalty leaders leverage deeper insights into individual customer behaviors to ensure offers are highly targeted while optimizing profitability. For example, they know offers sponsored by a CPG partner, such as a soft drink brand, lower their own costs. But leaders take it a step further. They use vendor funding prescriptively to drive sales that make sense for the business, leveraging those dollars to increase purchase frequency of an occasional buyer, while skipping customers who would have purchased a two-liter bottle anyway. Rutter’s, for example, relies on input from its product vendors to suggest items to bundle with a customer’s loyalty offer based on correlations gleaned from across their customer base. “Customers look for resources,” said Rutter’s Hartman. “You’re already convenient because you’re on the corner and you have fuel. But do you have the value proposition inside the store that’s going to make me come in and get the products that I need and then pick up products maybe that I didn’t know about or didn’t know I needed?” Other high-profit strategies include placing emphasis on a brand’s market differentiators in loyalty offers, such as private label and prepared food items, and coupling loyalty data with first-party online ordering. By moving ordering in-house, the brand owns the guest experience and can delight their best loyalty customers with surprise offers, customized menus, and preferential treatment. RETAILING IN THE AGE OF LOYALTY In this era where customer expectations are both elevated and constantly-evolving, c-stores continually leveling up their loyalty analytics capability are gaining a competitive advantage. “The loyalty program allows a very concise way to view your consumer in a single portfolio and package all their data and transaction history in one place,” says W. Capra’s Kahan. “No matter what you want to forecast, you can look to your loyalty data.”

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