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With loyalty professionals facing increased competition in the customer loyalty space, it is critical to understand the right direction to place energies and resources while taking advantage of technologies and ideas that can elevate the customer experience, making a brand stand out. Certain hot trends in customer loyalty tempt marketers with seductive solutions, but which are worth pursuing? How do brands keep and build momentum, tapping into the best fit and low-hanging fruit consisting of high perceived value and the lowest cost?
Helping clients design and enhance customer loyalty programs worldwide, Brierley — a Capillary company — works with brands seeking to understand which ideas to pursue and how to improve marketing and communications strategies by leveraging financial modeling, data and analytics, research, and customer engagement mapping.
Mark Johnson, CEO of Loyalty360, spoke with Don Smith, EVP, Chief Consulting Officer at Brierley, about defining and measuring success, trends Brierley notes for 2024, and what generative AI means for brands.
A Healthy Loyalty Evolution
Many brands faced customer loyalty challenges in 2023. As a result, some brands revamped their customer loyalty efforts and restructured programs, adding functionality and changing benefits. For some brands, new initiatives and restructured tiers were rolled out and were well received. A few brands did not fare as well, like Delta.
Brierley witnessed the same, and Smith believes it’s part of healthy loyalty evolution.
“We believe that if your loyalty program is going to stay fresh, you have to continually inject new elements, experiences, and features to revitalize it,” affirms Smith. “It stays ‘brand fresh,’ and the member is more likely to stay engaged in the program.”
In its consulting practice, one of the things Brierley focuses on in redesigns for some clients is determining the most desired behaviors that need to happen for the brand. With clients, they ask, what are the highest margins, highest growth, or stickiest categories? Can you find ways to recalibrate the program formally or informally to drive those desired behaviors and guard against dilution?
A lot of time is spent on changing the program structures. The company also discusses gamification with clients.
“Gamification sometimes gets a bad name because people think, ‘Oh, that’s spin to win. That’s playing a game.’ That can be one element of it, but done correctly, gamification is about putting a challenge out there and trying to drive people to stretch their behavior, move to their next best action, and appeal to their sense of accomplishment and competition,” explains Smith.
Smith advises letting consumers believe they are gaming the system, as they might perceive they’re “getting hooked up” or “double dipping.” Done correctly, it’s a win-win. Brierley continuously auditions different augmented reality (AR) solutions where it makes sense, such as a virtual mirror in cosmetics and fashion industries.
“I’m big on leaning into biometric solutions, whether that’s facial recognition, optical, or other. They are the future of how customers will securely do business, and loyalty programs would do well to innovate and adopt those,” asserts Smith.
Every program Brierley works on involves zero-party data. Discussions with customers emphasize the importance of collecting profile data from customers and honoring a social contract to use it in a meaningful way.
“If you do that, you’ve got something special,” says Smith.
The Challenges of Defining and Measuring Success
At times, when brands add iterative technologies into their technology stack, employ gamification, or begin to leverage zero-party data opportunities, they struggle to measure the ROI of their efforts and how it impacts the ROI of the program.
Smith acknowledges that many clients with existing programs come to Brierley not knowing what is working and what is not. They want to know the ROI, but more importantly, they want to know if they’re moving the needle on desired behaviors.
“Our first rule of thumb before you even worry about an ROI model or try to go deep is to focus on the theory of action that underlies the program changes you made,” says Smith. “In other words, if you made structural changes or enhancements to the program, it was probably to drive certain desired behaviors.”
Brands should then quickly start making comparisons, pre- and post-change. If new features were introduced, are customers using them? What’s the take rate? What’s happening for those customers who are using them? Do they try it once and drop it, or does it contribute to stickiness? And finally, should the brand be propagating those features and adopting more?
The low-hanging fruit is the opportunity to see if desired outcomes happened. After that, brands can make adjustments. For Smith, the number one reason to make changes to a program should be to recalibrate it in a way that enhances the member experience. Brands may want to fix profitability — which is valid — but if they’re not doing it in a way that creates a more impactful and engaging experience for the member, it’s probably not going to work.
“One of the first things we recommend doing is measuring your rational and emotional loyalty,” says Smith. “Look at whether customers trust the product and the brand, what they’re saying, and what the net promoter score (NPS) is. That’s rational. Then, go deep on emotional loyalty. If you’ve changed your program, you want to ask questions to determine how much customers love your program.”
Brierley developed the Brierley Loyalty Quotient (BLQ), a framework that captures and analyzes both rational and emotional loyalty. It’s the first pulse that the company takes pre- and post-program changes for brands. Brierley needs to see emotional loyalty tick upward as a result of program changes without undermining rational loyalty.
After these actions, brands can delve into customer loyalty program ROI. It takes time to get a clean measurement of ROI change.
“Brierley-Capillary is a big believer in triangulating the research design,” says Smith. “We want to do cohort analyses — preferably with member and non-member data where possible, nearest neighbor algorithms, and match it up with econometric approaches that do the best of modeling to track those changes and treat it like an interrupted time series from pre- and post-program change. This is what we want to do to truly measure that effect, but brands can’t expect it to happen overnight. It requires patience and a methodology to consistently measure and track ROI.”
To Measure Efficacy, Focus on Metrics
Brands can have difficulty in measuring the efficacy of customer loyalty programs, and Smith sees a customer or member-centric component, as well as indirect indicators that can point to how well a program is working. The first step Brierley asks clients to take is to do the BLQ and measure rational and emotional loyalty. This is crucial to learn where a brand may be over- and under-indexing relative to its competitive set.
“Contextualize emotional loyalty with the competitive set with which your current customers are splitting,” directs Smith. “And they’re almost always splitting — understand that and what you have because you should be trending upward and using your loyalty assets to shore up your program.”
Smith’s second number one metric is the BALO — the “becoming active to lapsing out” ratio. When a brand thinks about the cost of acquisition, it should be looking at the health of its funnel — who’s coming in and joining versus who’s dripping out. Brands need to know if they are “hiring” and sourcing more profitable members than they’re losing due to attrition.
“My third metric would be retained member velocity of the customers that are sticking with you period over period, year over year, quarter over quarter,” says Smith. “Are they spending more, or are they spending less? Are they going deeper into your product and service hierarchy? Or are they becoming one-trick ponies? Getting a pulse on what happens in that retained member audience is essential to understanding the health of your program.”
Lastly, Smith observes a profitability and ROI piece that is critical. A focus on customer profitability is one of the things Brierley emphasizes. Too often, the company sees programs labeling people as high value, but they are contributing the lowest margin behaviors and, in many ways, gaming the system or program.
Every Year Brings New Requests
Brierley sees an increased focus on truly understanding share of wallet and potential for share shift. The company spends time going through Voice of Customer (VoC) data to get a representative sample of members and customers to understand where else they shop and why. What’s the brand’s true right to win for share shift and conversion? Modeling helps make those determinations.
“We’re seeing a lot of emphasis on non-transactional engagement rates to understand all the ways a customer can interact with a program or a brand without spending money,” shares Smith.
This includes taking advantage of features in a brand’s app, looking at product reviews, going on the website, watching videos, and playing games. Brands must understand how those non-transactional engagements are working and which ones are the most appealing so that they can lean into them or come up with a strategy around them.
Brierley emphasizes product and service indexing, and Smith believes those reports and views are becoming essential to narrow down to the stickiest products and services a brand is selling.
“They are the gateway to a greater customer relationship and understanding what satisfied customers are buying, compared to what less satisfied customers may have purchased,” says Smith. “This is critical to understanding how you can recalibrate relationships and lean into best products.”
At the end of the day, brands are going deeper into the metrics. They’re not simply looking at retention. They want to see retention broken out within their product category and hierarchy.
Trends for 2024
Certainly, experiential rewards and experiences, in general, are big trends for 2024, but reward choice is significant — customers want more control over how they earn and redeem as well as how they are rewarded.
“An outshoot of this is digital wallet propagation,” says Smith. “Even when I’m in an airline program, and I’ve already hit my status for the year, I love that they’re depositing new things into my wallet that I can consume at different milestones.”
Smith acknowledges that generative AI is critical, and it impacts generative loyalty as well — leveraging AI to make programs better.
“If you do not have a clear path for incorporating artificial intelligence into your loyalty program, you’re going to be left behind,” warns Smith.
Phygital continues to increase in importance, and brands need to find ways to take digital assets and reinforce physical goods and in-store experiences. There needs to be synergy. Programs are becoming increasingly app-based and hyper-mobile. Smith also predicts a rise in coalition loyalty.
“Brands are approaching it in a much more consumer-centric and friendly way. It’s win-win; the rising tide of loyalty across brands lifts all boats,” says Smith.
He sees more suppliers and CPG brands as wanting to be a part of loyalty programs. They’ll be willing to sponsor and fund programs to gain data insights and build customer relationships. Loyalty professionals should prepare for a whole new world ripe for authentic partnerships enabled by coalitions.
Furthermore, adopting an idea, practice, or technology simply because it is a trend is a poor choice. Brands need to produce a business case for the adoption that’s tied to a financial model. Desired behaviors must be defined alongside what outcomes will result. Testing and engaging in VoC research are critical. Low-hanging fruit consists of high perceived value actions (on trend) that will ultimately be the lowest cost. A high perceived value and a low cost could indicate a winning trend.
Standing Out with Differentiated Member Experiences
While a “sea of sameness” in customer loyalty can persist, Smith explains that when Brierley first partners with a client on design, they look at the brand and the program structure, as well as the consumer experience. Using a spatial map, the value proposition versus how many experiential, fun, and engaging elements are present are scored.
“It’s no surprise that in a particular vertical, there’s one leader and many copycat programs,” explains Smith. “What truly sets a program apart is offering the most differentiated member experiences.”
Loyalty programs set up data assets and enable relationships with members and consumers. The true mark of a good program is consuming those data assets and facilitating special opportunities — talking to the customer, giving the person a chance to try something new, mapping in additional benefits and perks that are truly tailored to proclivities and what the customer wants and needs. Brands can have a similar-looking program structure but offer a completely different member experience — constantly pulsing with new opportunities.
“Creating better experiences will produce better outcomes for your business,” finishes Smith.
Leveraging AI in Customer Loyalty
For Smith, AI represents the science of producing machines that can think like humans. They can be smart, recognize patterns, and exercise decision-making and judgment skills. AI can ingest massive amounts of data that humans cannot.
“Generative AI is the buzzword that’s capturing the lion’s share of attention right now,” says Smith. “Generative AI is using AI to create text and images — media content — using generative models.”
Generative models are simply algorithms that learn the structure and pattern of input or training data — similar to the way predictive models were manually built. However, generative AI means that brands can generate new models and constantly cast new data. This enables brands to look at response rates and what is happening while algorithms continuously adapt and build new data sets, fine-tuning and optimizing parameters and results. They can audition multiple methods for looking at it.
“It’s a constant evolution in perfection,” adds Smith. “As loyalty marketers, we’ve got something almost no one else has. We have the best set of data assets tied to a customer. Customers are increasingly sharing what they love. We have first-party data from transactions and zero-party data from profile attributes. There are third-party data and contextual variables. All of this is tied together.”
When it comes to leveraging AI, everything needs to start with theory and strategy. A marketer’s AI focus needs to be driven by what they’re trying to do for their brand and understanding what is needed to do to grow a customer — making them more profitable and more involved in products or services, creating true lifetime loyalty. Everything invested into that mix will be amortized over an extended customer lifetime value.
“Sitting down and asking, ‘What are the desired behaviors? What are the outcomes those behaviors will lead to as we go forward?’ That’s probably one of the most important things that we work on when we do this with clients,” says Smith. “Laying that theory of action out is absolutely essential.”
Looking for Opportunities
Brands have much to consider when looking for opportunities to leverage in the field of customer loyalty — strategy, technology, organizational buy-in, etc. In more fortunate cases, sometimes a brand can uncover a quick win to improve the efficacy of its programs.
Listening to customers and taking a recalibration are key. Brands must understand quickly what a customer likes about the brand and its program. That’s where opportunities can be discovered.
“I counsel clients to not boil the ocean with loyalty — don’t assume that you can do everything overnight,” asserts Smith. “Focus on some things that will have a clear impact on your business, lean into them, optimize them, get them into market, and see how they work. Then, fix them, recalibrate them, get better, and learn what you can rule out. Simple adoptions and experiences are often what gets moved into client programs.”
While leaning into personalization and hyper-personalization is a priority for almost all brands, exercising restraint in messaging is crucial. Multiple emails sent daily clutter a customer’s inbox and can get lost in the shuffle. Spray-and-pray marketing is not going to work.
A little bit of restraint and discipline will enable what brands really want to do, which is hyper-personalization. Done correctly, hyper-personalization is the next thing that happens, and this leads to “clienteling.”
“Clienteling is the in-person connection with the store associate or the customer service representative,” explains Smith. “Combined with AI and hyper-personalization to understand what the next best action is for the customer — what they like, or any problems they’ve had — and serving all that up empowers an associate at the point of human interaction. That’s the sweet spot.”
This is what the brands Brierley works with are embracing as they seek to become more phygital. Brands want to get people back into the stores, and they need to empower the people who are the true face-to-face brand representatives.
Engagement Opportunities Beyond the Transaction
As the economy ebbs and flows and buying patterns adapt, keeping customers involved and engaged without always pushing a sale can be challenging for many brands. Brands can evolve strategies to encompass what matters most to customers through sustainability measures, messaging, and corporate social responsibility (CSR) initiatives. Still, sales need to be optimized. There must be a balance, and brands need to determine how to best navigate customer engagement.
For Smith, it comes down to relevance and a commitment to creating a good customer or member experience.
“It can’t always be about the next sale. If a customer comes in and makes a big purchase, we ought to be empathetic and understand that was probably a big deal for the customer,” begins Smith. “They made a decision to do something with you. The next communication should not be, ‘Hey, here’s a coupon for 10% off. Come back again.’ Maybe they just made a big purchase.”
Instead, a more authentic dialogue might be a message sharing how other customers are using the product. For example, if the product was a sweater or a belt, perhaps the brand might suggest ways to produce a certain look through styling. Smith sees AI as helping brands identify need state — taking advantage of what customers need when they need it and knowing that buying patterns may change.
“If you’re doing AI right, along with smart marketing, those things should be synergistic, identifying patterns and recalibrating,” says Smith. “You cannot just set course on one channel and assume the best route is hammering home the discount. It’s a path to dilution, and it often feels tone deaf.”
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