Note: This is part one in a two-part series on the future of loyalty. The second will get into some examples of how programs are evolving.
One of the realities of today’s inflationary puzzle is discount-focused strategies are increasingly difficult to sustain. Prices aren’t only climbing for consumers; the reason restaurants are charging more is some mix of rising ingredient and labor costs, interest rates, and continued challenges with access to capital. But there’s no question softened foot traffic and a cautious customer will force offer-based deals into the marketplace, as you’re seeing proliferate recently. What’s often happening as well, though, is restaurants are strategizing to get something out of the deal, which is why there’s so much investment put toward cultivating loyalty. That data and relationship, as it often does, outweighs transactional business. Rewards users spend more and come back more often and can be reached through multiple channels. Consumers don’t frequently buy brands on discount they don’t like. But they do return if they discover value past whatever offer got them there in the first place.
According to Paytronix’s 2024 Loyalty Report, operators in the 75th percentile of loyalty transaction share (transactions from members compared to all transactions) achieved 30 percent of their transactions from users, while brands in the 90th percentile saw loyalty penetration reaching 37 percent and beyond.
The highest-performing quick-service brands in their base reached an average 62 percent loyalty member retention rate, while elite full-service chains retained 58 percent of their loyalty program members, month-to-month.
When it came to loyalty member acquisition, the top quick-serves signed up an average of 110 new loyalty members per store each month. Full-service counterparts acquired 70 new members per location monthly.
Below is a look at how some brands stacked up. The metrics were broken out by percentile ranks from median to elite. It’s a blueprint for benchmark performance.
And so, beyond the performance indicators and larger premise that loyalty has emerged into an even more-pressing role than usual, how are programs evolving? In the report, it was clear guests seek brands that recognize and serve individual needs as they decide where to spend their dollars. According to the National Restaurant Association’s 2024 State of the Industry from earlier in the year, guests typically join an average of 3.6 loyalty programs. Gen Z adults, 4.4.
Percentage of loyalty program members who say they’re less likely to try a new place because they prefer to go where they’re a member of a loyalty program (sign them up right away)
All adults: 48 percent
Gen Z adults: 58 percent
Millennials: 50 percent
Gen Xers: 42 percent
Baby Boomers: 41 percent
Percentage of customers who say they’d likely participate in a loyalty program if it was offered (waiting to be wooed)
All adults: 81 percent
Gen Z adults: 87 percent
Millennials: 87 percent
Gen Xers: 86 percent
Baby Boomers: 75 percent
The Association’s report noted 78 percent of current loyalty users were more likely to visit a restaurant where they could earn points, even if it was less convenient. Eighty-one percent added they’d join another loyalty program if it was offered by their favorite eatery.
Another stat to toss in: Per McKinsey and Co., companies (not just restaurants) that excel at personalization generate 40 percent more revenue from these efforts than average players.
Where this brings the industry to is to a need for a higher level of personalization. A Customer Loyalty Executive Survey last year from PwC said the top reason consumers remained loyal was “the experience feels personal and created just for them.” That’s become the expectation as much as the rule, especially as digital ordering invades every corner of our retail lives.
Yet still, just 44 percent of consumers said the offers they get today were relevant, according to PYMNTS. The reported found 83 percent of respondents were receptive to personalized messages and nearly half were likely to switch brands for more relevant offers. Tailoring offers to specific needs and interests doubled the chances the consumer would switch merchants.
There’s opportunity in the gap.
More than 80 percent of brands’ campaigns, according to Paytronix, are segmented versus sent to their entire loyalty database. Less than 10 percent leverage predictive model scores.
Quick service
Segments: 72 percent
Blast: 22 percent
All filter: 5 percent
Full service
Segments: 64 percent
Blast: 30 percent
All filter: 6 percent
The company suggested three tools to tap in:
1. Differentiation. Rewards should fit the brand and match what each individual member craves. That could mean monthly subscriptions or meal passes, early access, or milestone deals (like birthdays), and experiential options.
2. Emotional connection. Paytronix said by analyzing purchase histories and contextual cues, such as location, weather, and device data, and key dates like birthdays or loyalty program anniversaries, operators can develop personalized offers that drive positive sentiment. Say wish members a happy anniversary with a BOGO offer. Welcome them back from vacation with a coupon for a beverage. Thank them when they hit spend tiers by donating in their name to a local cause.
3. Brand Affinity. Customers want to feel recognized and appreciated. That’s how you begin to build symbiotic loyalty. Personalization engines that enable individualized loyalty experiences are key to creating and sustaining win-win experiences, the company said.
Personalization is a process that requires foresight. Paytronix said to consider how to tailor your program’s core structure, earn/spend mechanisms, and reward offerings so they resonate with what each guest segment wants. Leverage unique selling points to differentiate the value proposition.
In that way, especially for a sector that tends to mimic each other, no matter what deal you’re rolling, or if others are, too, it’ll feel unique to the brand and recognizable to the loyalty base.
An example the company gave: A fast casual could implement a points-based system where members earn and redeem rewards for free food, merchandize, and exclusive experiences. A coffee chain, though, might be better suited to take a subscription approach for unlimited beverages coupled with surprise-and-delight rewards. “A great way to get the wheels turning is to assess other brands’ loyalty programs, listing the pros and cons of each one,” Paytronix said.
Here are some considerations to put on the table, from the report.
Define the most effective ways to engage guest segments
Create a flexible structure that allows for brand-aligned promotions
Make program management easy for your staff through training, alignment before revamping programs, and keep software and hardware updated
Identify and use program structures that deliver the highest return on investment
Implement robust data-capture mechanisms for accurate and effective guest segmentation
With those bases covered, then personalization can come into view. An insight from the report is automated feedback with AI. Conversational AI boosts loyalty by responding to reviews and questions. Even automated responses, Paytronix said, show top guests the brand cares and gives lapsed, at-risk diners the attention needed to reengage.
Manually responding to each review, for many, is just not realistic. Large language models and natural language processing, however, can automatically generate personalized, real-time responses to comments at scale. “Whether it’s issuing a sincere apology for a negative experience along with a make-good offer or doubling down on praise with a surprise that delights, AI empowers you to nurture more guest relationships,” the company said.
“Data” as a more general topic is one that’s darted at the industry from both sides, through a fire house, in recent months. Whether it’s loyalty or IoT or some other system gathering information, restaurants have more data flooding in than ever. But what to do with it, or how to stop and make sense of the torrent is a different task.
The Data Quality 2023 Study, from Software Development Times, stated 16.13 percent of organizations consider themselves “data driven,” More than a third added they were at the “data aware” stage, which means they’re just now starting to understand the nature of data integration and how it can help them reach internal goals.
This early stage outlook is the case for restaurants as well, a category that’s historically lagged the field in technology solutions.
Paytronix said operators should ramp up data beyond name, email, and birthday for its guests. “Today’s most successful loyalty programs use real-time transactional and behavioral data to create guest experiences that increase visits, sales, and CLV,” the company said.
Based on years of data, Paytronix noted that adding a basic loyalty program creates an 18–30 percent increase in spending and visit frequency among program members. And it only grows from there. Adding a team of strategy and analysis experts who can interpret data, the company said, increases visits and spending among loyalty users by an additional 5–10 percent. And layering on tech, like an app and online ordering, boosts visit frequency and spend by another 5 percent.
The rise of data
First-party data is the road to hyper-personalization. Every guest interaction generates data that can be deployed toward program curation.
Incorporating one-to-one targeting based on first-party data, Paytronix found brands could boost year-over-year loyalty spend by 16.5 percent. Marketable restaurant and C-store users delivered lifetime value 18–24 percent higher than members who hadn’t opted-in to receive loyalty program communications.
Third-party data from partners, however, can also enhance guest profiles with deeper psychographic, interest, and lifestyle insights, the company added. Location data unveils routines and affinities, and demographic information clarifies household dynamics.
Essentially, first-party data is the foundation of personalization. But third-party integration offers an extra level of context on everything from age, gender, lifestyle, interests, and life stages.
In terms of AI and machine learning, Paytronix offered three examples of the growing tech in work.
Intelligent Guest Segmentation. One of the biggest challenges businesses face with their loyalty programs is effectively segmenting customers. This is where machine learning shines. AI-powered analysis can sift through vast pools of customer data in seconds—such as purchase history, frequency, and lifetime value—to automatically surface microsegments like customers who order on Fridays at 5:30pm or those who buy a specific drink on Tuesdays.
Predictive Churn Analytics. Another powerful application is the use of predictive analytics to identify the risk of customer churn before it happens. Sophisticated models can analyze shifts in individual purchasing patterns and engagement metrics like visit frequency. By detecting leading indicators of lapsing behavior, for example, operators can automatically trigger 1:1 win-back campaigns aimed at retaining their most valuable loyalty members. If a guest who previously visited twice a month suddenly goes four or five weeks without a transaction, AI can prescribe a targeted offer or incentive customized specifically for their purchase preferences.
Frictionless Guest Experiences. Upselling and cross-selling are crucial revenue drivers, but making relevant recommendations for individual guests is challenging. Machine learning changes that by automatically grouping menu items based on what your customers like to buy. AI models can analyze each guest’s order history and taste profile to intelligently surface the most appealing items during every transaction. For loyalty programs, this translates into opportunities to showcase members-only menus or bonus-point multipliers for trying new items aligned with preferences. According to eMarketer, 53.9 percent of consumers say brand recommendations make them feel recognized and appreciated.
The post The Future of Restaurant Loyalty Starts with Personalization appeared first on QSR Magazine.
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