Data Evolution: Harnessing Intelligent Data to Improve the Customer Experience & Uncover Growth Opportunities

It’s undeniable that the pace of digital transformation has accelerated. The pandemic sped up the creation and adoption of digital platforms across a number of industries, including financial services.

More than ever, banking customers are using mobile apps and online platforms to handle financial transactions. This increased use of digital tools has created a wealth of valuable data that financial institutions can leverage to pursue customer intelligence initiatives, but only if the right next-generation banking solutions are in place.

Taking Advantage of Customer Intelligence

Customer intelligence involves the gathering and analyzing of customer data to get a better understanding of their behaviors and activities in order to strengthen customer relationships, provide greater customer value and enable data-driven decision making. For banks, customer intelligence can be an incredibly valuable predictor of growth and profitability, especially given increased adoption of digital service channels and the untapped data sources that go along with it.

However, deriving key data insights to better understand evolving customer needs and respond to them with precision, speed and efficiency requires intelligent data solutions.

Leveraging the Right Tools to Deliver Smart Data

By using next-generation banking solutions, financial institutions can glean meaningful data to learn what their customers value most, and better determine how to give them what they want. This not only benefits the customer by improving their experience, but benefits the organization by helping to attract and retain customers while increasing revenue.

According to McKinsey, “A survey of US retail banking customers found that at the banks with the highest degree of reported customer satisfaction, deposits grew 84% faster than at the banks with the lowest satisfaction ratings.” In addition, “Research shows that the stronger the experience and the more satisfied the customer, the more likely it is that the bank will generate higher revenue: a more satisfied customer typically accounts for approximately 2.4 times more revenue than a neutral customer.”

https://www.mckinsey.com/industries/financial-services/our-insights/reimagining-customer-engagement-for-the-ai-bank-of-the-future

This is where harnessing intelligent data comes in. With the right technology in place, banks can assess transaction data in real time to deliver personalized insights to customers and uncover upsell and cross-sell opportunities for new products and services based on customer actions. In this way, data takes the burden off the customer when it comes to figuring out how to navigate a digital banking app or determine what next steps to take. An easy and intuitive experience equals a positive one.

But, before useful data aggregation can occur and actionable insights can be realized, financial institutions must overcome two pervasive issues: integration of legacy systems and breaking down silos.

This takes a solution that can, in effect, stitches different experiences together, from front-end user interfaces to back-end data applications. Many financial institutions use an array of digital platforms and databases that aren’t necessarily aware of each other or able to communicate with one another. With the right solution in place, legacy systems can seamlessly share information and overcome fragmentation by aggregating siloed data—so that all an end user ever realizes is a great, engaging experience.

5 Ways Intelligent Data Can Improve the Customer Experience

Bank customers have come to expect relevant, personalized digital experiences that match their digital experiences in other aspects of life. A financial institution that deeply understands their needs will win out over one that offers generic, cookie-cutter experiences.

For a financial institution to grow and thrive in modern times, it must cater to the customer experience. Here are 5 ways the use of intelligent data can inform customer offerings.

• Streamlined account openings. Account opening is typically a complex event. And often sets the stage for the customer experience. Leveraging intelligent data can help financial institutions better understand attribution that occurs during this process, get a better sense of problematic parts of the process, and see how it can be made better for future customers.
  
  
• Budgeting tools. In today’s current financial climate, every penny matters. Intelligent data capabilities allow banks and credits unions to offer convenient digital tools that help customers budget for specific goals or for everyday bills, and to adjust payments or receive alerts when certain limits are reached.
  
  
• Holistic view of everyday finances. This goes hand-in-hand with budgeting. Smart data aggregation lets customers see a real time, complete picture of their financial state. And it lets financial institutions recommend certain actions or products to better manage day-to-day banking based on this information.
  
  
• Financial wellness programs. These programs can be one of the recommendations based on a customer’s daily financial health. They’re designed to help improve budgeting, spending and future planning, and use intelligent data to produce accurate, meaningful steps, processes and tips.
  
  
• Complementary products. This refers to products recommended based on customer actions outside of a financial institution’s platform. For instance, if they apply for a car loan or get a credit check for a mortgage, that data can be processed by a bank and used to reach out with offerings the customer may be interested in.

Final Thoughts

Leveraging customer intelligence and smart data can help financial institutions foster greater connections with customers and create a more meaningful, thoughtful experience. But as banks make the move to invest in technology that makes this possible, it’s important to remember to be deliberate in how it’s rolled out.

Many financial institutions have data that goes back decades, and not all of it is useful. It might be repetitive, incorrect or simply outdated. It’s best to ensure only quality data is used. It’s also crucial to achieve multiple integrations via varying data sources. This includes data generated via chat or with a voice assistant, and even via social media, in addition to CRM systems and credit systems. But, to get there, start by mining just one data set and widening the net from there. It will help to cut down on errors while simplifying the data aggregation process.

Achieving data aggregation is where banks need to be. To set the stage for future growth and success, financial institutions must embrace data and analytics to transform the business in a way that exceeds evolving customer expectations. That will require a digital makeover across all touchpoints within the organization.

By Marc Jones, CTO, Alkami