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In this second installment, Loyalty360’s supplier members and loyalty strategy experts continue to discuss the technologies and strategies playing a key role in the future of customer loyalty, how AI — leveraged correctly — enhances personalization, and why adaptable programs are vital for success.
If you missed part one of Next Generation Customer Loyalty: Experts Discuss Options, Trends, and Technologies, you can read it here.
Chatbots, Virtual Assistants, and the Human Touch
With the rise of chatbots and virtual assistants being employed by many brands, the question of how AI technologies can be utilized to improve customer interactions within loyalty programs. While brands are often eager to embrace exciting new technologies, they must balance technology with the customer’s need for a “human touch.”
Loyalty programs seek to accelerate customer lifetime value, achievable only through active use and optimization. And, to increase CLV, customers must understand how the program works. Hamel believes chatbots are pivotal for this instruction, with AI technologies acting as round-the-clock guides, helping customers grasp and utilize a program’s benefits to the fullest.
“AI-driven chatbots can facilitate accessible support, promote effortless interactions, and ensure customers feel capable, not daunted,” shares Hamel. “In turn, this maximizes the program's effectiveness and enables brands to extract meaningful insights into consumer behavior.”
To preserve the human touch, Hamel clarifies that AI tools must detect and respond to emotional cues, providing assistance or escalating to a human colleague when a situation demands that personal nuance.
“This balance of technology and human interaction is crucial for customer satisfaction and enduring loyalty,” he adds.
While Perez acknowledges customers have experienced “clunky chatbots” and “useless virtual assistants,” she sees considerable improvement over the last 12 months, with Generative AI playing a significant role in reshaping the customer loyalty industry.
“Generative AI is like a dynamic AI brain, which consolidates various knowledge sources — the most well-known version of this technology being ChatGPT,” she explains. “It can assist a chatbot by consolidating knowledge about various topics, like member information, company business models, options, prices, etc. and using large language models to summarize and translate that knowledge into generated, predicted responses that mimic human-like conversation.”
Perez believes Generative AI will allow brands and marketers to move away from pre-programmed answers on chatbots to a truly dynamic conversation. She adds, “This technology also holds the potential to significantly improve customer service wait times and provide a more seamless customer experience by delivering a human-like experience and reducing the need for customers to explain their problem to different agents repeatedly.”
Meltzer-Paul agrees that brands must strike a balance between smart technology and human input, especially in consumer-facing applications like chatbots. “Conversations with virtual assistants must be equally frictionless and effective, or else the tool can have the unintended consequence of disengaging the consumer.”
Building off Meltzer-Paul’s sentiment, Williams sees the current efficacy of virtual agents as unable to meet the high expectations that brands have positioned them for, and readily available human touchpoints are critically needed.
“Stop making chatbots and virtual assistants the sole gatekeepers of progress,” cautions Williams. “There is rarely a way to circumvent a virtual agent for a human expeditiously, especially for complex issues where it is obvious the virtual agent will not provide a solution.”
Indeed, chatbots and virtual assistants can add value to a loyalty program when the technology is supporting quick query resolution and personalized recommendations. In less complex cases, Stirling recommends that brands balance technology by integrating human-centric elements, and natural language, ensuring a more harmonious blend of efficiency and a personalized touch that customers prefer. He notes that airlines are utilizing AI-driven chatbots to provide instant assistance to loyalty program members, offering real-time flight updates, tailored recommendations, and issue resolution in efforts to elevate overall customer satisfaction.
Personalization and Next Generation Customer Loyalty
Personalized offers have been a part of the loyalty ecosystem for decades, but the deprecation of the cookie in 2024 will put them more into focus. And for good reason — according to Mastercard research, more than half of consumers make buying decisions based on the offers that are available to them. Meltzer-Paul notes that as cookies get phased out, merchants will look for a stronger channel to reach their consumers in an attributable way, which makes personalized offers a win/win: The consumer gets a relevant offer that provides access to a unique experience or helps them save money, and the brand can easily track how effective their efforts are.
“Many brands we work with are shifting away from static tiers and benefits in favor of personalized programs and offers. What we call ‘loyalty lite’ empowers brands to take a more modular approach to engagement that enables greater agility and customization,” says Meltzer-Paul.
Personalization also demands a delicate balance with discoverability.
“It’s not enough to mirror past behaviors; brands need to introduce customers to new, curated experiences that broaden their horizons while remaining relevant,” adds Hamel. “This means moving beyond the echo chamber of a customer’s previous choices and adopting algorithms that introduce novelty and serendipity into the mix.”
As brands leverage AI to understand individual preferences, craft tailored rewards, and deliver personalized content, Stirling sees innovations in technologies as creating a unique and engaging experience for each customer.
He offers an example. “Banks use virtual assistants to improve customer interactions by using AI to answer queries about loyalty program benefits, account details, and even financial advice, mixing human touch with technological efficiency.”
For most loyalty programs, Williams finds that the seamless delivery of personalization has yet to fully materialize. He’d like to see a return to the basics of maintaining a dialogue with customers while incorporating zero-party data into journeys with clear win-win outcomes for the brand and customer.
Looking through the lens of personalization and customer loyalty when trying to reach a multi-generational audience of buyers, Hobbs sees Gen Z and Millennials as seeking the most value from their loyalty programs. “They may benefit more from a gamified rewards offering as compared to other generations,” she says.
Lobliner notes that systems and tools are now equipped with sophisticated algorithms that can analyze vast amounts of first-party (1P) and zero-party (0P) data, which allows for incredibly precise segmentation of audiences.
“The part of the equation that must not be forgotten is acquiring that data,” asserts Lobliner. “Traditional forms and surveys don’t get much traction. Gamification is a well-proven strategy to capture this in fun and often unobtrusive ways.”
Moving beyond more targeted messaging, Lobliner explains that linking user data to gamified experiences can deepen engagement and interaction, leading to stronger emotional connections with the brand or product. Users become active participants rather than passive recipients of messages. Rewards, challenges, and storylines can be dynamically adjusted to each user's interests and engagement patterns, supporting a brand’s personalization efforts. Further, gamification can improve loyalty program effectiveness — by tracking user behavior within the gamified experience, data can be used to optimize game mechanics, rewards, and overall design for maximum impact.
Like Hobbs and Lobliner, Epstein looks to interactive and gamified elements, such as personalized challenges or reward structures, to add an engaging layer to the customer experience, fostering a deeper connection between the brand and the consumer.
“Overall, personalization is not just a trend; it’s a strategic imperative for brands aiming to thrive in the evolving landscape of customer loyalty,” says Epstein.
Marketers: Is adaptability built into your customer loyalty program?
In the face of rapidly changing customer preferences and expectations, adaptability is paramount in loyalty program design. According to Epstein, conventional approaches lose their effectiveness over time, and customers are increasingly seeking personalized and innovative loyalty experiences. Understanding the ever-changing landscape of loyalty and the role technology plays is critical.
“Retention can be fleeting, but in more recent years, the competition to break through the clutter to create more mind share for any individual brand continues to become a bigger challenge,” explains Epstein. “Creating a differentiator is increasingly more difficult as consumers are inundated and overwhelmed by the sheer volume of marketing messages and offers. Forbes cited that consumers are exposed to more than 5,000+ brand messages per day.” (See also Thinking vs Feeling: The Psychology of Advertising from the University of Southern California’s Master of Science in Applied Psychology Program.)
Stirling agrees that due to evolving customer expectations, adaptability is crucial in loyalty program design. Flexibility to incorporate emerging technologies, respond to market trends, and adjust reward structures ensures the continued relevance and success of loyalty initiatives.
“Amazon Prime has continued to add more services like Prime Video and Prime Music to meet changing customer preferences. This adaptability ensures that the loyalty program remains relevant and attractive to a diverse customer base,” says Stirling, offering an example.
His colleague Wickens, adds, “By focusing on flexibility, brands can cater to dynamic customer needs and wants, and foster long-lasting loyalty. Whether it’s offering flexibility of reward choice, adding new features and benefits that align with a consumer’s changing priorities, or personalizing rewards based on individual purchase history or preferences, a program that can continuously evolve and adapt demonstrates a commitment to a customer’s evolving journey and expectations.”
Comarch’s Favaloro sees adaptability as a key aspect of loyalty program design, and, indeed, any customer engagement initiative. Brands must be nimble enough to pivot quickly with program mechanics and marketing campaigns as needed.
“Sometimes, this is required due to changing member sentiment, but adaptability also comes into play when unexpected local or national events occur. In these unique circumstances, adjustments to certain promotions may be necessary to reevaluate program messaging while at the same time supporting the affected communities,” says Favaloro.
Williams contends that adaptability has traditionally been reactive to vulnerabilities of a loyalty program — e.g., too many members taking advantage of a benefit like lounge access. “This results in perpetual dilution of the value proposition. Program design should plan around contingencies and avoid the need for future benefits clawback.”
Adaptability in loyalty program design is critical for Lobliner, and he sees segmentation and distribution powered by richer data as enabling a focus on intrinsic motivation. “Moving beyond extrinsic rewards to create experiences that foster genuine interest and engagement will help brands to better connect with their customers.”
To that, Hobbs adds, “Different target audiences may want different rewards or ways of engaging with your brand. Knowing your customers is the best way to stay on top of the trends that are most important to implement within your brand’s loyalty program.”
AI can help brands identify those trends by recognizing patterns across different customer segments. However, to put those learnings into effect, a loyalty program must be nimble enough to cater specific offers to different audiences based on preferences.
Insights derived from data, particularly from underutilized but significant digital contact points, fuel adaptability. Hamel points out that adaptable brands go beyond transactional data, tuning into customer “intents” and life contexts. They don’t just look at purchases; they interpret intent and interest through proxies such as searches, content interactions, and the depth of these engagements to construct robust and relevant customer profiles. This enables them to refine and adjust their loyalty programs dynamically.
Meltzer-Paul advises brands that the best way to keep up with rapid change is to build business experimentation into the organization’s DNA — this means getting comfortable with testing and learning and using those data-driven insights to inform decision-making.
“Loyalty isn’t something you set and forget; your KPIs and metrics of success shouldn’t be either,” finishes Meltzer-Paul. “Every brand defines success differently, but the key is being clear about the objectives up front and reflecting them in how you evaluate success at the end of the day.”
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Did you miss part one of Next Generation Customer Loyalty: Experts Discuss Options, Trends, and Technologies? Find it here.
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[ad_1] Customer expectations continue to evolve, and when considering a purchase — a big ticket item or even a smaller one — they often look for flexibility in payment options. […]
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