A regular cadence of deposits, withdrawals, balances and statements make up a large part of a retail bank customer’s monthly activity and their relationship with the bank. But while the number of transactions, average monthly balance, credit scores and loan activity all contribute to understanding a customer and metrics such as lifetime value, transactions alone tell only part of the story.
Because customers now attach value to the personalized experiences they receive, knowing a customer almost exclusively through transactional data is no longer enough. This limited view doesn’t translate into the seamless, consistent personalization customers expect across both physical and digital channels.
Of course, none of this lessens the importance of maintaining clean, accurate transactional data. But to truly understand each customer, banks must also connect all available signals, including behavioral, demographic and contextual, into a unified, living customer profile. Only by blending transactional accuracy and a broader data foundation can banks meet customers where they are, with relevant and timely experiences.
The Dynamic Bank Customer
According to a recent ABA Banking Journal survey, only about half of retail banks utilize a CRM system, despite its foundational role in equipping bankers and marketers with a full picture of each customer across deposit, loan, wealth, and digital channels – which in turn leads to effective needs assessment and added revenue.
It’s important to note that while powerful, a CRM serves best as the frontline for managing customer relationships and interactions, provided it’s fueled with the right data. Yet CRMs weren’t designed to aggregate large volumes of raw data from multiple systems, resolve identities across channels or devices, or continuously refresh profiles in real time. For that, banks need a data readiness engine working behind the scenes to power the CRM’s unified customer profiles.
There’s also a social revolution under way. Banks now rely on Instagram, Twitter, LinkedIn, and Facebook to deliver the kind of personalization that used to be the exclusive domain of bank tellers, such as helping first-time homebuyers understand mortgage options through video content.
AI-driven experiences are a newer but common way for customers to interact, carrying their own expectations for personalization via a chatbot or other natural language applications. Customers may start with account balance checks or other transaction questions, but pivot to product and services inquiries, or help with forms, tax returns, and other guidance.
A Complete Customer Understanding
For an AI interaction or social media interaction to be relevant in the moment (e.g., when the customer is scrolling Instagram, or starting an online chat) banks must treat these channels as not just engagement channels, but as important data sources that help enrich a deep, personal understanding of each customer.
Take the video snippet for first-time homebuyers: the more signals the bank gathers about a customer or their household, the more relevant that video can be. Those signals can also reveal which products to recommend or what images to show to a first-time website visitor.
Has a customer been searching for mortgage information? Are there multiple devices linked to the same household conducting similar searches? Is that second device linked to a different profile? Did a customer reach out to customer service asking for mortgage information to be mailed – and is the physical address linked to a unique profile?
These insights create situational awareness – but only for the retail banks that have an ear to the ground. Being relevant in the moment requires a complete understanding of the customer, which depends on data readiness.
Data quality is central to that readiness. A unified customer profile must be accurate – but accuracy on its own doesn’t reveal a customer’s journey, life stage or retirement goals. Context, such as household relationships and financial milestones, transforms clean data into actionable understanding.
The Benefits of (Really) Knowing Your Customers
A complete customer understanding that transcends transactions delivers measurable benefits. Reduced churn, better retention and stronger loyalty all stem from matching customer context with personalized offerings. Understanding needs and behaviors triggers the switch from personalization being a guessing game to a data-backed strategy with hyper-relevant product recommendations.
Banks that maintain a real-time, consistently updated unified profile provide better customer service, both human and AI-driven alike, and align every interaction and product recommendation around the customer’s current situation. When a chatbot has the full picture, misguided recommendations and repetitive questions become a thing of the past.
According to Gartner, a primary objective for bank CIOs this year is to grow revenue through customer experience excellence, driven in large part through advanced data capabilities. Achieving that requires data readiness – the ability to maintain a complete, accurate and contextual understanding of every customer.
For information on how the Redpoint Data Readiness Hub can help you achieve that unified customer understanding – using your own data – click here.
