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The loyalty industry is a complicated space. Navigating it can be difficult, which is why Loyalty360 engages in discussions with brand and vendor representatives: to learn how to address its challenges and take advantage of its opportunities. Recently, we sat down with Don Smith, Senior Managing Director and Strategy & Chief Analytics Officer at Brierley+Partners, and his team to get a general idea of how loyalty has changed, what it will look like in the future, and what brands should do about it.
How has customer loyalty changed over the last few years?
Simply having a loyalty presence with a traditional do-get value proposition is no longer sufficient. Customer expectations have evolved so that the user experience must be seamless and cohesive as members move, in real time, from channel to channel without knowing where one begins and another ends. This frictionless experience has improved the flexibility in earning and redeeming rewards and enjoying member benefits. It has also boosted customer engagement. This increased interaction with the program, and the overall brand, reinforces the importance of cultivating emotional loyalty. Knowing and acknowledging your customer across channels allows you to surprise and delight them in ways that are authentic and on brand.
What is the biggest challenge that your clients face in driving deeper customer loyalty?
Not trying to boil the ocean. Brands feel a legitimate pressure to fulfill their end of the loyalty contract: leveraging customer data to deliver highly personalized marketing reflective of customer interests, preferences, and need states. A top priority in this mission is anticipating and guiding program members to their next best actions, but this focus on data-driven prescription can quickly become unwieldy, with marketers attempting to propagate too many recommendations, offers, experiences, and calls to action. Focusing on myriad objectives can result in marketing paralysis, leaving personalization on the future roadmap, with short-term focus being on disproportionately generic, discount-driven offers.
If you could recommend one thing to a client to help them with this challenge, what would it be?
Leverage data analytics to winnow down the next best action marketing matrix, allowing marketers to focus on a small set of manageable but highly strategic business objectives. Consider the case of product recommendations. Data scientists can deploy recommendation engine logic and adaptive learning algorithms to populate a seemingly endless array of specific products mapped to specific customers. Unfortunately, marketers wishing to action these recommendations may be unable to pull together the massive visual assets, offer sets, and personalized copy corresponding to these prescriptions. But if we can help marketers identify those (preferably high margin) products or services that are stickiest (i.e., ones that increase lifetime value, shift share, and habituate shopping cadence), we can identify a minimum winning constellation of products that become the focus of a practical and effective marketing regimen.
What can we do as an association to help bring simplicity and efficiency to the industry?
Simplify the marketing narrative. Many brands feel the pressure to move their marketing vehicles from zero to 100 miles per hour right away. Not only is such a trajectory unreasonable. It also leads these practitioners to adopt advanced tech solutions without first developing the solid theories of action and strategic plans that are enabled by the shiny new tools of data science. Industry practitioners benefit most from concise, straightforward case studies and best-practice vignettes. Marketing literature presently resembles a sea of hyperbole, dominated by ambiguous and overwrought buzz words: artificial intelligence, augmented reality, real-time customer journey maps, etc. A series of thoughtful A/B tests positioned as “quick wins” may move the ROI needle more effectively than a loftier, unproven, “holistic” solution.
What is “next big thing” for customer loyalty?
Hyper-personalization. Historically, loyalty programs have relied on data-driven initiatives that look at behaviors that have already occurred, such as transactions. Prescriptive analytics provide brands with a forward-looking approach to loyalty by understanding customers’ intentions and anticipating their future needs. Facilitating this level of hyper-personalization becomes a powerful tool in engaging with a brand’s most loyal and valuable customers in ways that delight them without feeling intrusive and disconcerting.
How sophisticated are most brands’ customer experience and customer loyalty initiatives?
Most brands’ loyalty programs are simple. The basic value proposition is primarily focused on rewarding transactional loyalty, with limited integration into the broader customer experience. When it comes to enhancing CX and loyalty, efforts to make them more sophisticated are often thwarted if they are planned and executed in silos. The owners of the loyalty program and customer experience reside in different departments, and initiatives are developed and managed independently, an approach that leads to a disjointed and underwhelming experience for the customer. The brands who understand that these initiatives must be intertwined and integrated across multiple touchpoints are the ones who have successful and sophisticated programs.
Should all brands strive to have the brand recognition of Apple or Amazon? Why or why not?
Recognition is only one measure of a brand’s value to its customers and the organization. While most marketers would love to have the brand recognition and market dominance of an Apple or Amazon, few organizations will ever have the resources necessary to get to that level. And to paraphrase PT Barnum, although there may be no such thing as bad publicity, there is such a thing as bad brand recognition. On balance, most organizations would be better served investing their limited resources in ensuring their products and services are consistently delighting their customers and making sure potential future customers know just how great they truly are. Your brand doesn’t need to be known worldwide or nationwide. It just needs to mean something very positive and valuable in your corner of the world: where your customers and potential customers are.
How should brands manage data?
The two guiding principles for data management are proactive security and democratization. Regarding the former, brands must be vigilant stewards of their customers’ data, maintaining a security regimen that rises above the formal regulations (e.g., those conferred by GDPR, CCPA, PCI, etc.). Customer data should be used with a customer-centric focus, delivering a better and more relevant experience for the consumer. Data should never be sold or brokered, and affiliate marketing efforts should be done sparingly, with individuals explicitly consenting to participation.
Once anonymized, these secure and protected data assets should be modeled and made available to stakeholders across the brand. In far too many organizations, marketing data is the province of marketers only, and decision makers in other areas (e.g., merchandising, store operations, supply chain, finance, etc.) do not benefit from the rich customer-centric data curated through programmatic loyalty and structured CRM. Democratized data strategies should include the creation of a semantic metadata layer that enables quick queries and visualization by non-technical users, with permissions carefully governed. Propagating a single source of customer data truth is a rising tide which lifts all stakeholder boats.
What strategies should they adopt in relation to stricter data regulations?
The primary strategy we advocate is proactive security, comprised of multiple elements/tactics:
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