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Banks dependent on attracting customers through demographic information are in for a wake-up call as new customer behaviors, fueled by a rising younger workforce, have quickly antiquated the traditional banking datasets.

Most banks have long viewed customer segmentation based on demographic characteristics such as age, race, gender, education level and location. But the migration of consumer banking activity to digital channels — and the vast volumes of data resulting from it — gives banks a crucial opportunity to do better.

Banks that adapt quickly are finding new ways to segment customers based on their habits, preferences and needs, particularly as the younger generation ages into their careers and acquires more wealth.

With machine learning models well suited to discover new patterns among mountains of data, banks can analyze customers’ historical activity to better understand what they want and need from their bank, rather than assumptions based on demographic profiles.

Additionally, the explosion in digital products and services that consumers use daily means banks can leverage a variety of third-party data sources to supplement their own data; and augment a better understanding of customers’ habits and preferences.

Such analysis can allow banks to segment customers in ways that yield deeper insights, leading to more effective marketing and customer service strategies. For instance, banks can segment customers based on factors like their financial savviness and digital maturity, which likely have greater influence on their financial decision making than gender or race.

Such behavioral factors can also be combined with demographic information for segmentation, as noted by BAI Research Group, which examined the general consumer population and segmented it according to five profiles based on their affinity to digital channels, use of various financial products, satisfaction with their current bank and demographic characteristics.

However, the growth of Generation Z in the workforce — a trend that is already well underway — will mean banks need to market more on behavioral profiles and rely less on demographic information.

Gen Z already has a significant presence in the workforce with roughly the same percentage earning a paycheck now as millennials, who are about ten years older. By next year, Gen Z will make up 20% of the workforce; and an estimated 61 million of them will join the workforce in the coming years.

There are important factors about how Gen Z views the world, which will influence how banks can reach them. Gen Z is more socially aware than prior generations and resistant to traditional definitions of race and gender, making it difficult to apply such traditional demographic factors.

Instead, banks will need to persuade them on the basis of their needs, values and likes. Additionally, this generation grew up with mobile and social media, and are quick to turn their attention away from messaging that doesn't appeal to them.

As today’s young adults grow to become the bulk of the working population, meaningful customer segmentation will shift from a marketing activity to becoming the foundation of banks’ business strategies. Given the younger generation’s short patience for brands that don’t demonstrate an understanding of their needs and desires, banks will need to appeal to them based on refined, personalized messaging and service strategies.

Trying to serve the general population in this manner will become overwhelming for the vast majority of banks, forcing them to focus more on specific customer segments that offer the most promising opportunities. The days of being a bank for everyone will be a thing of the past.

Behavior-based segmentation will offer a path to properly define, select and understand those segments that banks will need to succeed. Those critical customer segments may differ between institutions. One may focus on highly affluent and financially savvy customers, while another may focus on those that are most digitally active, regardless of income bracket.

But the goal will be the same: to build the best bank for those customer segments that the bank needs to win. To do that will require deep familiarity with those customers’ needs, and then redesigning the organization and its services to meet those needs.

Behavior-based segmentation will be at the core of this change, and will put banks on a path to differentiating themselves in the eyes of their most important customers.

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Consumer banking Customer data Fintech Machine learning Predictive analytics People analytics