In your eagerness to stay on the leading wave of the digital transformation, is your bank sacrificing power for speed? Big data has the potential to help financial institutions create customer experiences that are meaningful, relevant and engaging on an individual level. But if you homogenize your use of digital channels and treat all your digitally engaged customers as if every one of them fits neatly into a handful of pre-defined segments, your financial institution is failing to maximize the power of your technology.
The importance of segmentation
Financial institutions are vast repositories of customer information, and they know more about their customers today than at any other time in history — even if many of them still don’t seem to realize it. That data is integral to creating the kind of personalized experience digitally indoctrinated customers crave, but it’s not the only ingredient you need. Segmentation right down to a granular level is also critical.
Segmentation, the act of dividing customers and their information into like groups for the purposes of marketing to them, has been around about as long as people have been selling things to each other. A fruit vendor in an ancient Roman marketplace would move the choicest, costliest fruits to the front of his wares when a rich senator walked up to his stall. Had he left them out front the whole day, he would have disenfranchised the common folk who couldn’t afford the premium product. Had the vendor tried to sell the senator the common stuff, he would have angered a powerful customer.
Banks today are in much the same situation as that ancient fruit vendor. Miscalculating a customer’s interest can be a costly mistake, especially in a marketplace where consumers have too many options to waste time sticking with a financial institution that doesn’t understand them. Target them with offers and information that are not relevant to them, and customers will take their business elsewhere.
“(Customers’) daily digital interactions with firms have already created the expectation that any desired information or service will be available on any appropriate device, in context, at their moment of need,” Forrester analyst Alyson Clarke writes in her report Trends 2016: North American Digital Banking. “But now those expectations are escalating, and customers are growing accustomed to companies anticipating their needs and offering what they’re looking for — sometimes before they even know what that is … Your understanding of your customers’ context will make or break your ability to succeed in their moments of need.”
Technology and big data can be the solution to depersonalization and resulting disengagement, but only if that “hardware” is paired with the “software” of customer segmentation analysis. In this digital environment, only adroit segmentation analysis can help you understand your customers’ context at any given moment in their lives.
What segmentation can tell you
Good segmentation processes customer information through multiple filters, until you achieve a granular level that optimizes your understanding of customers. The basics are easy to grasp — you divvy up customers based on commonalities such as age/generation, income levels, occupation, education attained, geography, life stage, marital status, parents or non-parents, etc.
But not every 20-something is exactly like every other. Not all college-educated 40-plus married couples are earning the same amount, or saving for retirement at the same pace. Some millennials are paying off college debt, and may not be ready to hear about mortgage opportunities — in which case that text alert you just sent pushing your low-interest mortgage products might be downright unwelcome. Others may be caring for an aging parent with money problems, and thinking about their own need to save for retirement.
Within broader segments, differentiators emerge. Big data, paired with customer segmentation analysis, can help you understand how those factors might influence interests and behaviors. Smart segmentation can mine a wealth of information, like which customers have been searching online for information about products you sell. It can also help you identify niches where opportunities may be emerging.
Neglecting to refine segmentation is one of the saddest, most wasteful kinds of failure for financial institution marketers. It can result in content that’s irrelevant at best and inappropriate at worst going to customers and prospects who just aren’t interested in it. Worse, it sends the message to consumers that you don’t really know them, and maybe you don’t really care to.
Adding up to a better experience
“Retailers and travel companies are using predictive tools and algorithms to exceed expectations with highly personalized experiences,” Clarke writes. “Digital teams at financial firms have been slow to re-engineer websites and apps to enable highly personalized digital experiences.”
Clarke recommends banks use analytics and location-based information to improve the relevancy and context of their marketing and offers. Integrate data on customer spending patterns, geolocation, social media and more to create a clearer picture of who your customers are, and what offers might be of interest to them at any given point in their day, not just during a certain stage of life.
By now you’re either wondering why anyone wouldn’t invest time, money and effort in customer segmentation analysis — or, you’re saying “Do you know how hard that is?” You don’t have to go it alone. Segmentation analysis software and services exist to help. “Outsourcing” your segmentation efforts in this way can help ensure your financial institution maximizes the power of your big data, and delivers the highly personalized experience customers have come to expect.