Why Banks Need Better Customer Data to Deliver Truly Personalized Marketing

By Jim Marous, Co-Publisher of The Financial Brand, CEO of the Digital Banking Report, and host of the Banking Transformed podcast

Retail banks have more marketing technology, customer information, and communication channels than ever before. Yet many institutions still lack the data foundation required to deliver meaningful personalization.

Recent State of Financial Marketing research found that more than half of surveyed financial institutions are already using generative artificial intelligence in marketing. However, none reported having customer data that was immediately available and ready for AI applications.

The research also highlights a major gap between how banks define personalization and what customers experience. In many cases, personalization still means selecting a customer segment and sending it a relevant message. True personalization goes further by recognizing what is happening in a customer’s financial life and responding at the right time.

Key Findings for Bank Marketers

• Targeting is not the same as personalization. Customers judge an interaction by its relevance, timing, offer, and overall experience, not by the audience segment selected behind the scenes.
• Artificial intelligence depends on usable data. More than half of institutions are using generative AI, but none said their customer data was immediately available and AI-ready.
• Marketing budgets may be misaligned. AI-generated content and creative received significant planned investment despite ranking last among the tactics respondents considered effective.
• Existing relationships are being overlooked. Deposit growth is a leading priority, while primary-bank relationships, share of wallet, dormant accounts, onboarding, and customer win-back efforts receive less attention.
• Progress can begin with practical steps. Banks can start by assigning ownership of the customer record, creating a unified daily view of behavior, and using control groups to measure incremental results.

The Difference Between Targeting and Personalization

Hyper-personalization has become one of the most common phrases in financial marketing. However, relatively few institutions are delivering experiences that customers would genuinely describe as personal.

Only about one in 100 institutions surveyed said it was truly providing hyper-personalized experiences. When financial institutions were asked to define personalization, approximately two-thirds described a process focused primarily on deciding which audience should receive a particular message.

That approach is familiar. Traditional bank marketing often relied on data from core systems, geographic information, account balances, and broad customer segments. Marketers selected an audience, created an offer, distributed the message, and measured the response.

Modern marketing technology has made that process faster and more sophisticated. Banks can now reach customers through multiple channels, test different messages, and automate campaigns that once required months of manual work.

Even so, the basic decision often remains unchanged: determining which list should receive which message.

Customers do not experience the segmentation process. They experience the offer, the timing, the onboarding journey, and whether the interaction reflects an understanding of their financial needs.

This distinction is important because many banks have invested heavily in capabilities that customers cannot see. An institution may report strong personalization technology while delivering experiences that feel generic to the people receiving them.

Customer Data Sets the Limits for AI

The quality and accessibility of customer data determine how effectively a bank can use artificial intelligence. Data must be unified, current, accurate, and available when a decision needs to be made.

Approximately two-thirds of financial institutions surveyed said their customer data is either spread across multiple systems or updated in batches. Very few described their data as available in real time, and none said it was immediately accessible and ready for AI-driven action.

This finding should influence how banks prioritize their technology investments.

Generative AI can help produce marketing content. Predictive AI can support decisions about who should receive an offer and when. Agentic AI may eventually take action based on those recommendations. Every one of these capabilities depends on reliable customer intelligence beneath the technology.

One of the most notable findings from the research is that AI-driven content and creative ranked last among the tactics considered effective, even though these areas were expected to receive some of the largest budget increases.

This does not mean banks should abandon AI. Instead, it shows why institutions need to invest in the foundation that allows AI to produce better outcomes.

Why the Data Foundation Matters

Banks do not need perfect data before they begin using advanced marketing tools. Experienced technology providers can help institutions improve targeting and campaign performance even when data remains incomplete.

However, there is a significant difference between using basic customer information and operating with real-time intelligence.

Many banks can identify account balances, product ownership, transaction patterns, and broad demographic details. Fewer can recognize a meaningful financial event as it happens and respond while the information is still relevant.

For example, a bank may be able to identify that a customer recently received a large deposit. A more advanced data environment could determine whether that event signals a need for savings advice, investment guidance, debt repayment options, or a new product recommendation.

The more current and connected the data, the more useful the bank’s response can become.

Marketing Investment Should Follow Customer Impact

The research also shows that banks may be investing more in visible marketing outputs than in the capabilities that create lasting customer value.

Many institutions rely on outside partners for media planning, while roughly half use external support for creative production. Personalization and decisioning are among the capabilities banks are least likely to outsource.

There are valid reasons for caution, especially when customer data, governance, privacy, and fair lending considerations are involved. Still, refusing outside help does not automatically strengthen an internal capability. In some cases, it allows an existing weakness to continue.

The same imbalance appears in many bank growth strategies.

Deposit growth is a leading priority across the industry. Yet efforts designed to turn deposit accounts into deeper, long-term relationships often rank much lower. These include becoming the customer’s primary financial institution and increasing share of wallet.

Banks are putting substantial effort into acquiring customers while devoting less attention to what happens after acquisition.

Dormant accounts and customer win-back programs present similar opportunities. These customers already have a relationship with the institution, and much of their history is already available in bank systems. Nevertheless, these opportunities are often underfunded compared with acquisition campaigns.

Three Steps Banks Can Take Now

1. Assign Clear Ownership of the Customer Record

One individual or team should be accountable for the quality, completeness, and usefulness of the customer record. This responsibility should include measurable goals that make progress visible across the organization.

2. Build a Unified Daily View of Customer Behavior

Banks should connect checking, card, loan, deposit, and digital engagement data into a unified view that is refreshed daily. Daily updates may not deliver true real-time personalization, but they provide a practical foundation for more timely marketing and service decisions.

3. Measure Incremental Lift

Marketing teams should consistently use control groups by holding back a portion of the target audience. Comparing campaign recipients with a control group helps determine whether a marketing action actually changed customer behavior.

Many financial institutions do not use control-group testing consistently. Yet it is one of the most affordable ways to measure the real impact of a campaign and avoid confusing activity with results.

The Future of Personalized Banking

Customers want their banks to understand their circumstances and provide useful guidance at the right moment. The technology required to support that experience is becoming more accessible, but technology alone will not solve the problem.

Better personalization requires connected data, clear accountability, effective measurement, and investment in the infrastructure that supports customer intelligence.

Before the next marketing planning session, bank leaders should compare two areas side by side: spending on marketing activity and investment in the data foundation. The most important question is not whether the institution is funding more marketing.

The real question is whether the bank is funding better marketing.

Jim Marous is the co-publisher of The Financial Brand, host of the Banking Transformed podcast, and owner and CEO of the Digital Banking Report, a subscription publication focused on the digitization of banking.

Source: TheFinancialBrand.com