Banks have good reason to value their clients. The average banking consumer can be worth $2,000 to $4,000 over the course of a lifetime. With online-only upstarts poised to snatch up any customers feeling dissatisfied with their current institutions, modern banks have been forced to double down on retention. Consumer banking loyalty, however, is a sophisticated problem. With multiple customer touch points and a contrasting portfolio of products and services, understanding what drives customer loyalty is a multifaceted challenge with cross-departmental implications. Some banks have found a solution in data science. Advancements in analytics and business intelligence have allowed for a deeper understanding of consumer behavior at scale. Engagement solutions built on top of these systems are helping banks sell more financial products and deepen their relationships with existing customers. While customer service fundamentals and legacy technologies remain relevant, those pulling ahead are doing so thanks to insights afforded them by new data technologies. While many consider these to be the early days of data-driven loyalty solutions, many banks have already made great strides.
Investing In Mobile
A 2017 report by the Mobile Ecosystem Forum found that 61% of consumers in developed markets are regularly accessing mobile banking. Experts expect adoption rates to reach as high 80% among youth demographics by the end of 2017, which is good news for banks. They know that what happens on mobile can be measured. Part of this uptake is due to the aggressive rate of innovation that modern banks pursue. Automated alerts, no-charge fund transfers, and photo-capture check cashing are among the latest features offered by most mobile banking providers.
Integrated Call Centers
As tech brings new levels of sophistication to customer service, some solutions are too entrenched to go quietly. Studies suggest that as many as two-thirds of banking customers still prefer talking over the phone. Forward-thinking banks are bridging new and old by optimizing their call centers for efficient data ingestion. Kirsten Jepsen, director of global marketing at Sykes, outlines the four requirements of a data-friendly call center.
- Successfully capture and use customer information to increase service value and experience.
- Employ a voice of customer program that invites customer feedback to help identify those at risk of attrition for proactive engagement.
- Continuously evaluate employee performance based on defined customer service standards.
- Analyze down to the root cause of customer dissatisfaction to inform the creation of new programs and services.
Between digital solutions and data-friendly legacy technologies, modern banks are poised to offer the personalized service that modern customers expect.
Modern data solutions let banks see the future of their customer base. As consumers use more online and mobile banking tools, their behaviors are more easily quantified. Properly analyzed, this data allows banks to forecast behavioral patterns. “Understanding the data across the customer lifecycle enables banks to create more actionable segments and take targeted action tailored for each segment,” explains Steven J. Ramirez, CEO of customer experience firm Beyond the Arc, Inc. “Once a bank gathers their data and generates the insights into how customers are likely to behave, the final step is to act on those insights.”
With data in hand, banks are investing in scalable sales solutions that leverage these behavioral insights. Heavy adopters have deepened commercial relationships on all fronts. “Product win rates (the share of products bought by respondents at their primary bank) range from 38% at the worst performer to 63% at Huntington National,” explain Gerard du Toit and Maureen Burns, partners with Bain & Company’s financial services department. “(Huntington National) replaced its manual sales process with an automated one that made it easier for employees to manage cross-selling and upselling opportunities.” Automated sales solutions have helped Huntington National become one of the 40 largest banks in the United States.
Adaptive Retention Strategies
Sales aren’t the only function to benefit from automation. Customer experiences are optimized using real-time analytic data. “There are many different bank customer retention strategies but to maximize their effectiveness you need to match them with their position in the customer life-cycle,” says Adam Ramshaw, a Net Promoter score and customer feedback consultant, in an article with Genroe. Ramshaw describes how analytics let banks identify customers at risk of churn, and how they “… must determine why they are no longer using your product (are you are their ‘back of wallet’ card) and create initiatives to change their behavior.” For those matching the behavioral profile of a mid-churn customer, he says banks ”need to understand the product drop cycle, i.e. the order in which customers drop your products before leaving.”
Every industry has felt the continental shift towards scalable, data-driven solutions. While many B2B markets still rely on white-glove service to close deals, evidence is mounting to suggest that technically-mediated relationships have become the gold standard for consumer markets. For the time being, embracing data continues to be the best way forward for financial institutions.