What’s Stopping Brands from Anticipating Customer Needs?

Richter believes the numbers are a wake-up call for marketers. The data she is referring to is SAP Emarsys’ Customer Loyalty Index, where consumers are be mapped across five key types of customer loyalty: 

• Incentivised Loyalty: This type of loyalty is developed by offering customers cost-saving or value-adding incentives like discounts and rewards. 
• Inherited Loyalty: This loyalty is based on a brand’s tradition or longstanding heritage, or can be built through associations with other brands. 
• Silent Loyalty: Silent loyalty occurs when a customer demonstrates loyalty to a brand that they would not endorse or advocate for publicly. 
• Ethical Loyalty: This loyalty occurs when a customer is loyal to a brand that aligns with their individual values or stance on strong social issues. 
• True Loyalty: True loyalty is unwavering, unshakeable loyalty built on trust, love, and devotion to a brand—the holy grail of customer loyalty, and what 

“To rebuild loyalty, brands need to go beyond transactions and deliver relevance, recognition, and reward – in real-time. That starts with first-party data and platforms like SAP Emarsys, which enable personalised, meaningful experiences across every touchpoint,” says Richter.

To close the personalisation gap between what marketers are delivering, and customer needs, brands must engage more intelligently. But what does this mean? 

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Brands like Krispy Kreme are partnering with omnichannel customer engagement solutions like SAP Emarsys to bridge this gap. In this particular case, the brand wanted to unify customer journeys across its ecommerce and retail operations. SAP Emarsys provided the tools to integrate data from various sources into a single platform. With a comprehensive view of their customers, Krispy Kreme ANZ could analyse behaviours and preferences holistically, and tailor communications to reflect each customer’s journey, whether they were buying in-store, ordering online, or picking up a box at a grocery store. 

Next, the donut brand gained access to advanced analytics and segmentation tools, enabling them to deliver more relevant and personalised experiences. SAP Emarsys’ platform provided a centralised view of customer data, highlighting patterns such as purchasing frequency, favorite products, and engagement across channels. Armed with these insights, the Krispy Kreme team could craft targeted campaigns, such as personalised emails that recommended products or offered exclusive rewards based on individual buying habits. 

“It is why we recognise them as one of an elite group of brands who have entered their ‘engagement era.’ With this foundation in place, brands can build loyalty programmes that meet current needs, deliver content that resonates, and earn genuine emotional connections – turning indifference into advocacy,” says Richter. 

So, why aren’t all retailers digging into the data to find actionable insights, and leveraging predictive analytics to understand customer needs? It’s an old challenge, and as Richter puts it brands are still struggling to establish a ‘strong foundation of high quality, integrated and connected data’. According to SAP Emarsys’ The Global Consumer Products Engagement Report while consumers needs are increasingly about relevance and timely experiences, only 44% of marketers believe their campaigns are effectively personalised. Just 32% of consumer products brands have a connected data strategy, and 58% say their data is too unstructured to use effectively.  

“This is where AI can have a transformative impact. SAP Emarsys, has long used predictive AI to anticipate behaviour and surface previously hidden customer segments, unlocking new growth opportunities. Now, with generative AI, we empower marketers to produce personalised content and campaigns at speed – scaling omnichannel relevance without increasing complexity.” 

As the tech stack that powers customer engagement for leading brands gets taller, brand leaders are looking at artificial intelligence as a way to simplify, rather than add to the complexity. If marketing teams are able to outsource some of the large and repetitive tasks to machine intelligence, that frees up human intuition to reframe future actions that the business needs to focus on. 

One such recurring challenge is an evolving privacy landscape that brand leaders need to stay on top of across diverse geographies. Strategies driving personalisation and omnichannel are heavily dependent on data so changes in privacy laws impact business continuity. The debate on the demise of third party cookies, and the EU AI Act are evolving stories.  

“Strong security and compliance are essential, but trust is just as critical. Marketers must clearly communicate the value exchange: how customer data is used, and what customers get in return. Yet our research shows a disconnect – while 73% of marketers believe they’re transparent, only 45% of consumers agree, and 46% feel brands collect data without meaningful use. The problem is compounded by “dark data” – 52% of data collected is never acted on.”

The takeaway? Customer trust is earned, not assumed. Brands that use data intentionally, transparently, and visibly to enhance the customer experience will be the ones that maintain relevance and resilience as the ecosystem evolves.

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