Summary

• Calibrating a CDP for banking sector enterprises requires a concise approach from top to bottom
• Breaking down data silos and consolidating online and offline data are key steps to be taken in a smooth onboarding process
• A robust CDP is crucial for moving past legacy systems and towards an omnichannel approach

Every minute of every day, customer interactions throughout a bank’s outbound, inbound, and owned media generate huge amounts of data—static and dynamic, structured and unstructured. With the right customer data platform (CDP), banks can harness this trove of customer data gleaned from sources and systems within and outside the bank to create highly personalized, conversion-focused customer engagement.

Breakdown data silos and create a singular view of the customer

Customers have come to value personalized offers and experiences by other digital-first businesses, where stringent rules and regulations protect a bank’s customer data. A CDP can ensure the security of financial data and personally identifiable information (PII) and adherence to privacy norms and security standards. Other data management tools lack the capability to hold the customer’s PII secure while deploying robust encryption mechanisms to share data points with other systems.

A CDP helps consolidate, integrate, and process all of this demographic, behavioral, and transactional data to create a singular, unified view of the customer. This record is updated every time the customer interacts with the bank, offline and online.

With all of this valuable intelligence about existing customers’ needs and behaviors available on-demand, bank marketers can develop and deliver highly personalized, contextually relevant marketing campaigns and interactions at the segment-of-one level.

Use case: Offline and online data consolidation

Harness data for personalization

A powerful CDP provides a single perspective relative to a bank’s customer data, enabling personalization, real-time decision-making, and prescriptive product and content recommendation. With easy access to a holistic view of each customer’s data, banks can send individualized communication that will resonate with the individual customer or prospect.

The extent of personalization depends on the amount of good, clean data available. Tracking online data is the first step toward personalization, but by integrating offline interaction data, such as branch visits and ATM transactions, the personalization experience becomes even more compelling.

Among the most valuable additional perks of a CDP is the advanced data management capability that enables the marketing team to mine data more optimally without having to rely on IT or business intelligence teams at every turn.

Use Case: Location-based personalized offer

Actionable insights, advanced analytics

A good CDP provides insights into existing customers’ behaviors, and also reveals changing behavior and preferences based on signals received from real-time interactions.

Given the sheer magnitude of data readily available to most banks, a robust CDP can extract valuable insights using predictive and prescriptive analytics with machine learning. For example, machine learning can help identify which customers are likely to churn out, those who will likely purchase a new product, and those who would prefer a competitor’s product.

Other examples include: 

• Predicting a customer’s ability to repay a loan based on credit and risk propensity scores and cohort analysis
• Determining which customers are likely to default on a loan
• Identifying how to mitigate the risk of non-payment

Use Case: Lookalike targeting based on AI insights

Process data in real time

Customer data platforms can ingest and process data in real-time, helping to keep marketplace intelligence fresh and usable for data-driven marketing campaigns. Once the data is ingested, it is deduped, validated, and cleansed to ensure quality. It’s then ready to be segmented based on the campaign needs of the bank marketer and activated across the bank’s marketing systems.

Data attributes are standardized so the data is utilized uniformly across the multiple systems within the bank. CDPs can create unique identity graphs and build a singular profile ID for each customer. This data is continuously augmented with each interaction, and as an individual’s demographic data changes—for example, phone numbers, addresses, and more—a CDP can update it across all banking systems in real time.

Use Case: Credit card limit enhancement in real-time

Use Case: Real-time intervention for loan application

Making the right choice

Bank marketers must confront not only a growing volume of customer data but also the multiple systems where data is collected and stored. This isn’t limited to the legacy systems the bank owns. As banks continue to acquire new SaaS products to address emerging uses and issues, the siloed data problems can worsen.

The right CDP can help solve the data silo problem, while also dealing with the full gamut of data management requirements. 

When evaluating a customer data platform, banks should keep in mind the key use cases a CDP can address, both long and short-term, to make sure it will stand the test of time and whether it is a worthwhile investment with a healthy ROI. 

To see the extraordinary results Resulticks delivered for a leading private sector bank in India and to understand our solution for the banking industry.

With our deep understanding of the myriad challenges faced by banks today, Resulticks can help you explore these and many more examples in depth.

You can request a personalized demonstration here.