How Community Banks Should Use Big Data to Become Better, Faster and Stronger

Today, consumers live in a world where anything and nearly everything they want is at their fingertips. Understanding and retaining customer data is becoming critical for community banks to prevent their customers from turning to retailers and competitors at decision-making moments. According to iAcquire, a digital agency specializing in inbound marketing, social media  and search engine optimization, 70 percent of mobile searches lead to action on a website within one hour of when the search was conducted. That leaves banks with precious little time to serve customers before a retailer can offer a new credit card or a just-in-time solution to replace the bank’s services.

The quest to personalize offers for “segment of one” marketing is a daunting task for any business, but a big data solution can help by quickly analyzing more and more diverse data than ever before, predicting customer behavioral patterns, and producing real-time services opportunities just before a consumer makes a financial decision. For example, big data analytics can analyze customer information like financial and transactional data to predict a customer’s future purchasing decision. For example, a bank could recognize that a customer has been saving more money than usual in the past three months, has rented two cars from a local rental business, and has commented on three types of vehicle reviews on a used car website. Through this information, a bank can anticipate that its customer might be in need of an auto loan to purchase a car soon. In order to capitalize on such an opportunity before a customer receives a loan from a car dealership, a bank could send its customer an auto loan offer and the option to speak with a loan representative.

Once a customer has purchased the vehicle, the bank can recognize the transaction and guide the customer in archiving his vehicle’s warranty policy and contract while prompting him to enroll in auto-pay for his monthly car payments. When the customer logs into his account, the bank can also suggest that he enroll in overdraft protection. This example demonstrates how a cloud analytics solution can use historical, social and contextual data to help banks offer relevant services that align with their customers’ lifestyles while cross-selling effectively.

Ultimately, a cloud analytics solution’s anywhere, anytime access, natural language capabilities and automatic quality audits make it possible for community banks to spend more time understanding trends and insights versus finding and mining the actual data itself. These capabilities can enable a bank to create new revenue streams, build personalized offers and maintain customer loyalty. For these reasons, community banks should consider investing in a big data solution in order to extract information efficiently and precisely to meet their business objectives and solve complex problems faster than their competition.

For more information, visit ICBA Strategic Technology Solutions or call Brandy Smallbrook at (320) 352-7320.