Three strategies to make QSR loyalty more personal

For quick-serve restaurants, loyalty programs are now table stakes. More than 82 percent of QSR brands already have a loyalty or rewards program and 60 percent of brands plan on prioritizing retention strategies in 2025. The question in this climate is, how do marketers stand out when everyone is offering a lot of the same?

The brands that invest in and prioritize meaningful 1:1 personalization can build relationships that generic marketing simply cannot. Brands that excel at personalization generate 40 percent more revenue from marketing campaigns compared to the average company. 

It’s easy to understand why. Consumers see roughly 5,000 ads a day, with adults seeing roughly two million marketing messages a year - but only 44 percent of consumers say the offers they’re receiving are relevant. 

Personalization cuts through the noise, creating unique experiences for every customer. Here are three ways marketers can infuse 1:1 personalization into every aspect of their loyalty programs and strengthen relationships with customers in the process. 

Personalizing the onboarding experience

After a customer signs up for a loyalty program, marketers must create a lasting first impression. Yet too many brands send batch-and-blast emails and notifications that may not capture a customer’s interest. QSRWeb reviewed the marketing communications of top brands after a consumer signs up for a loyalty program. One leading QSR sent no notifications or emails in the first two weeks post-sign up. Another sent emails everyday, but the emails weren’t personalized to the customer’s location or previous orders.

From the point of a customer's first order, marketers can leverage first-party data to 1:1 emails tailored to a customer’s location and menu preferences. If a customer orders a meatless entree and sides, marketers can send notifications about new vegetarian items and use geolocation data to suggest the closest restaurant. If a customer routinely orders lunch during the work week, marketers can tailor content, suggesting online ordering to beat the lunch rush. 

Marketers don’t get a second chance to make a good first impression. The first few weeks of loyalty communications are pivotal to creating lasting relationships with customers. By going beyond standardized welcome emails and loyalty messages, marketers can show customers that the brand understands the unique cravings of every single diner. 

Gamifying loyalty points to encourage dining

Gamification helps marketers enhance their loyalty program with a sense of urgency. It also encourages customers to see their points and rewards as a competition–the more points the better rewards and the more valuable the prizes. Most of all, gamification adds some fun to the digital dining experience, enhancing “messaging engagement by making emails and SMS messages fun, interactive, and rewarding, which leads to higher open and click-through rates.” 

Gamification can also collect valuable zero-party data. Marketers can offer fun quizzes and surveys which can enhance 1:1 personalization and better understand the unique needs of every customer. As QSR magazine notes, “Offering valuable benefits in exchange for personal data can inspire participation and enhance personalization.”

Loyalty programs are ultimately a give-and-take relationship. Whether it’s free coffee, a discount on large orders, or secret menus, customers want rewards in return for their loyalty. Marketers can create loyalty tiers to offer exclusivity and enhance emails and notifications to show the number of points customers need to jump to the next tier. Brands can offer task-based rewards as well, creating non-purchase engagement that strengthens relationships. 

Defining value at a 1:1 Level

When inflation struck the QSR industry, brands started defining value by going beyond price and convenience. Brands are showcasing benefits like ingredient transparency and wellness, new and exotic flavors, or family-style meals, which shift the way the customers think about the value proposition of a QSR meal.

Consumers also view value differently. They want experiences that are catered to their unique needs, whether that’s the way they shop, their family size, or their income level. Loyalty programs allow brands to meet customers where they are, understanding how, when, and where they dine through first- and zero-party data.

Marketers can harness the power of artificial intelligence and machine learning to create 1:1 personalization across every loyalty touchpoint. If a customer responds well to new menu items, brands can send exclusive looks at exciting new flavors and menu items. Customers who often buy dinner for the whole family can receive family bundles to make ordering easier and customized to their needs.

Loyalty programs can strengthen the bond between guests and brand, building lasting relationships while increasing customer lifetime value. For customers to remain loyal, they must know that their favorite restaurant understands their unique needs and rewards them. Infusing 1:1 personalization throughout the loyalty journey does just that while also offering fun and unique experiences. 

1:1 personalization with AI decisioning 

As QSR marketers create 1:1 personalization strategies, they will inevitably wonder how AI can help achieve their goals. Customers expect their favorite restaurant to understand their needs across every channel. New tools like AI decisioning are bringing marketing into a new era, allowing brands to meet customers wherever they are with unique, individualized experiences no matter how they order. 

AI and machine learning (ML) have rapidly evolved as essential tools in a marketer’s arsenal. One common method of using AI models to personalize are so-called next best action (NBA) models, which combine predictive models and manual testing to predict a customer’s “next best action,” and encode the result as business rules. 

These “predictive models” have their limits. They’re slow, static, and can only find “winners for segments” – they cannot understand customer behavior at an individual level. AI decisioning agents rely on a different type of ML, reinforcement learning, which is best-fit for making 1:1 decisions. An AI decisioning agent chooses the best action to take for each individual, and then autonomously experiments and continuously learns from future customer actions. 

To learn more about AI decisioning, read our whitepaper on personalization trends for QSR marketers.