Customer Intelligence

Personal, white glove service has always been a competitive advantage for community banks and credit unions. Therefore, a customer-centric mindset is vital. While a customer may be just another number at a large, national bank, community-based financial organizations can get to know people on a more personal level—and they may in turn feel a larger sense of connection and loyalty to a bank or credit union that has a history within the community.

But, as banking moves to be more digitally-focused, a familiar, friendly face at the bank counter is not enough, especially as younger generations embrace the convenience of online and mobile banking. Customer touch points are increasingly digital—which isn’t necessarily a bad thing. Financial institutions now have a wealth of data about each individual. Large, national banks are already using this to their advantage.

Many large financial institutions have invested billions in technology, including data and AI-based solutions that allow them to fully embrace customer centricity in their business practice. This allows them to foster relationships based heavily on digital interactions.

But without ample resources that can be focused on developing data-backed solutions, how can a smaller, community-based institution compete?

• Are your products and services what your customers really want and need?
• Are recommendations and advice being tailored to each unique individual?
• Are customers experiencing seamless interactions across all touchpoints?
• Are you using direct feedback and data to inform decision-making?
• Are you able to provide customers with “unexpected value,” beyond what they would normally expect from their financial institution?

In order to reach these lofty goals, organizations must first get buy-in across the organization and actively work to shift goals and mindsets.

Once a bank or credit union has determined that it is on its way to cultivating a customer-centric mindset, it is time to start taking action. One of the most powerful ways to become more customer-centric is to rely on insights from data. But the first step is to organize data into a 360-degree view of each customer—breaking down data silos in order to capture the entire customer journey.

Once data has been aggregated, cleansed, and organized around each customer, it can be used to make data-driven decisions, personalize the customer journey, and increase the effectiveness of marketing campaigns, and optimize operations. With the power of AI and predictive analytics, organizations can:

• Enhance digital interactions with chatbots;
• Enact offer relevant product suggestions;
• Determine which customers or members are most likely to churn;
• Identify potential new customers who look the most like their current best customers;
• Optimize loyalty programs to increase customer satisfaction; and more.

If all of this sounds like a lofty goal, that is because it is. This undertaking can be a huge challenge for most midsized banks and credit unions. In many cases, it could take several months—or even years—to get to this point. That is why many organizations are looking outside their own walls to work with experienced partners to guide them through the process along with pre-built technology solutions that can reduce the time to implementation.

To meet the unique challenges of community banks and credit unions, Aunalytics has developed the Daybreak Analytics Database—an end-to-end data and analytics platform using AI and machine learning to enrich a bank or credit union’s existing data and create a customer-centric view. This ultimately allows midsized financial institutions to more effectively identify and deliver new services and solutions so they can increase wallet share and better compete with large financial institutions.