In a competitive marketplace crowded with a constant barrage of brand messaging, traditional customer loyalty programs are no longer going to cut it. As customer expectations for more customized rewards, experiences, and communications continue to grow, brand marketers are challenged to shift their efforts from what once worked to what has come to be called next generation customer loyalty. While there is not yet a common definition within the loyalty industry, the evolution of consumer behaviors and demands, alongside remarkable new technologies, has made it clear: a transformation across the loyalty landscape is happening.
Brands unwilling to step forward and embrace the mechanisms and strategies fueling next generation customer loyalty will soon be left behind.
To provide guidance, Loyalty360 spoke with supplier members and loyalty strategy experts about the technologies and strategies that will play a key role in the future of customer loyalty, how artificial intelligence (AI) can be leveraged to impact personalization, and why it’s critical for brands to build adaptability into their programs.
Stephanie Meltzer-Paul, Executive Vice President, Global Loyalty, Mastercard
David A. Hamel, VP Strategy, CX and Design, nventive
Kelli Hobbs, VP Business Development, US, Valuedynamx
Jean Perez, Data & Analytics Director, Valuedynamx
Key Technologies and Strategies Shaping Customer Loyalty
In an increasingly competitive customer loyalty landscape, brands need to determine where investments and efforts must be placed to better ensure success within the next one to three years. This includes zeroing in on the right technologies and strategies that will play a key role in the future of their customer loyalty programs.
Brierley’s Stirling believes the top technologies shaping customer loyalty include advanced data analytics for personalized insights and AI-driven predictive modeling to enhance customer experiences.
“Supermarkets like Tesco have invested in predictive analytics to personalize promotions and offers based on individual shopping patterns, enhancing customer loyalty through tailored incentives,” he adds.
Stirling’s Brierley colleague Wickens sees three key areas that will play a major role in shaping the future of customer loyalty in the next one to three years:
Online communities, branded forums, and social media groups built around shared interests and values to foster deeper customer connections and brand loyalty
Moving beyond the transaction — evolving past points and discounts to become more dynamic and personalized
Regarding the third point, Wickens acknowledges that hyper-personalization is one way to achieve this, but brands should also look at how they can optimize reward structures, focusing on the experiential or “surprise and delight” moments that go beyond the traditional program models and focus on delivering customer satisfaction through a true understanding of what that individual consumer considers of value. Building a robust data infrastructure and customer data platform (CDP) will be a necessity, both for customer experience and servicing.
Leveraging AI to stay competitive is also advised by Valuedynamx’s Hobbs, who explains that there must be a right balance of personalization and automation.
“One-size-fits-all marketing doesn’t cut it, so it’s important to leverage data and AI to better understand your customers, using those insights to drive positive brand engagement on a regular basis,” says Hobbs.
Engaged Nation’s Epstein agrees that artificial intelligence has emerged as a linchpin for future loyalty programs, especially as related to AI-driven personalization. He also highlights experiential digital engagement platforms and proactive customer engagement systems.
“Investing in interactive, experiential digital engagement platforms and prioritizing seamless omnichannel integration are pivotal strategies for shaping the future of customer loyalty,” says Epstein. “These approaches provide immersive, interactive experiences and ensure a consistent, unified customer journey, fostering deeper connections and exceeding customer expectations on a continuous basis.”
He also looks to interactive engagement systems as taking center stage. A focus on continuous digital engagement that elevates the brand, enhances the customer connection and experience, and creates an emotional bond that quantifiably drives incremental revenue and lifetime customer value (CLV) is key.
Marigold’s William’s looks to contextual engagement as a trend. “I want to walk and see personalized AR offers overlayed on physical locations in my Meta Ray-Bans. Nothing stops brands from allowing customers to scan items with a mobile phone and instantly get personalized pricing in local currency or points. Think about compelling strategies around spatial technology as it takes hold and becomes more affordable.”
nventive’s Hamel directs brands to focus on these core areas to revolutionize customer loyalty:
Capture “intent and interest” data — especially from omnichannel sources, enabling AI to generate insights and deliver offers precisely when they’re most impactful.
Prepare systems for third-party conversational AI integration to remain at the forefront of customer engagement.
“Investing in these areas will not only bridge the current implementation gap but also position brands to lead in the evolving landscape of customer loyalty,” says Hamel.
“At the risk of sounding biased,” begins CataBoom’s Lobliner, “investment in a gamification, promotions, and prizing platform that integrates with an existing loyalty platform and client tech stack is key. I have a deep belief, based on seeing this work for dozens of brands, that moving beyond transactions and driving relevant, deeper, and more fun engagement matters — A LOT!”
Giving customers new ways to engage dramatically impacts the value exchange between the brand and the consumer, where consumer perceived value skyrockets. To this, Lobliner nods to hyper-personalization.
“Finding ways for customers to tailor how they engage with your brand — from types of games, how deep to engage, to choosing the prizing they prefer — can create meaningful and sticky experiences for customers that will keep them coming back to your brand and/or products time and time again,” emphasizes Lobliner.
Hobbs also sees gamification as another strategy for enhancing customer engagement and loyalty, especially among younger generations. Gamification can provide an interactive and immersive way to motivate and reward customers, boosting awareness and driving higher engagement levels. Rewarding points, miles, or cashback for completing certain actions, such as making purchases, referring friends, or engaging with their favorite brands on social media, fall under gamification strategies.
“Custom rewards can take this strategy a step further — like providing discounts on frequent purchases or allowing customers to choose from a list of rewards that cater to their specific interests,” says Hobbs.
When aligned with a brand’s loyalty objectives, a well-executed gamification strategy can facilitate high levels of engagement and emotional connection, leading to greater customer loyalty and advocacy.
Mastercard’s Meltzer-Paul believes gamification can generate meaningful interactions and allow for crucial “surprise and delight” moments. She sees brands as moving beyond basic tactics toward a more holistic and gamified strategy, differentiating themselves from competitors while getting to know their consumers better.
“Capturing data through gamified elements allows you to learn more about the consumer’s wants and needs, and then link those insights to conversion actions,” she explains.
However, Meltzer-Paul reports that top of mind at Mastercard is enabling flexibility and choice, two things that are less trends and more requirements. Consumers want exciting ways to maximize their rewards and benefits, but they also want to control how that comes to life. Part of meeting those standards means innovating around real-time redemption at every single point in the purchase journey down to SKU-level specials.
“In an inflationary environment where consumers are balancing prices with priorities, they turn to their loyalty programs and offers to help offset direct wallet impact. It’s crucial that when the consumer turns to those benefits, they not only have the freedom to decide what shape that redemption takes, but that it’s also easy and seamless to complete,” asserts Meltzer-Paul.
AI and Next Gen Customer Loyalty Strategies
In Loyalty360’s Next Generation Customer Loyalty: 2024 Loyalty360 Brand Marketer Research, results revealed the majority of brand marketers surveyed indicated artificial intelligence was one of the technologies they’re most interested in and planning to invest in as part of their next generation customer loyalty strategies. Loyalty360 asked its supplier member experts about how they believed AI could be effectively integrated into customer loyalty programs to enhance user experiences and drive engagement.
Epstein believes that AI is pivotal in reshaping customer loyalty programs, particularly through its ability to analyze extensive datasets and unveil profound insights into individual preferences. He sees this transformative power as enabling brands to segment customers dynamically in real time, moving beyond static categories to create fluid, evolving segments that align with changing preferences.
“Leveraging AI for personalization allows brands to deliver tailored experiences at scale, providing personalized recommendations and promotions that enhance user satisfaction and fortify emotional connections with the brand,” says Epstein.
For Epstein, AI’s predictive capabilities enable proactive engagement, anticipating customer needs and offering timely incentives. With adaptive design for loyalty incentives and continuous learning, AI ensures that loyalty programs remain compelling and optimized, marking a significant shift towards more personalized and engaging customer experiences.
To this, Meltzer-Paul adds that AI can help unlock more predictive engagement on the front end, where relevant offers, products, and content can be dynamically curated at scale. On the back end, marketers can set up campaigns and manage loyalty offerings more easily, and AI can enable better financial predictions around point earn/burn, ensuring more clarity around the economics of the brand’s strategy.
“With consumers more likely to frequent a brand that knows who they are and what they like, AI-enabled personalization enables more accurate predictions, better recommendations, and more satisfying experiences overall,” Meltzer-Paul shares. “And because loyalty is an outcome and not a program, those more satisfying experiences keep consumers coming back for more.”
While adding new technologies to an organization’s martech stack — like AI — can be an exciting opportunity for marketers and brands, understanding the methods in which to successfully leverage AI into loyalty programs can be challenging. Hamel suggests that brands start with the low-hanging fruits by using AI to generate better metadata for their offers, enhancing personalization engines.
“Brands can boost these engines with AI capabilities to process the ever-growing data available and serve offers, activators, or accelerators that truly match a unique person rather than a segment or a persona,” explains Hamel. “Augmenting search functionalities within digital platforms with AI will also yield more pertinent results.”
Looking ahead, Hamel sees virtual assistants transitioning from being brand properties to personal assistants owned by the user — with the key differentiator being the assistant’s ability to interact seamlessly with a brand’s data sources. He believes brands already providing personalized experiences that are equipped with the infrastructure to support AI through web services will adapt more swiftly and effectively.
“These brands will stand out as AI’s capability to process substantial data rapidly transforms the engagement landscape,” he finishes.
Valuedynamx’s Perez reminds brands that good, clean, relevant customer data is essential for any AI, or machine learning model to be successful.
“The success of any AI-powered solution should be measured based on what the customer does next,” she adds. “Do they interact? Do they open the email? Do they make a recommended purchase? If not, a good model will learn and apply those learnings on the algorithm to achieve a different outcome next time.”
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