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Tagged: big data

Customer Segmentation in the Big Data Age: Where Banks Find Value

February 8, 2017

Customer segmentation helps banks get to know their customers on a more granular level. Segmentation reveals specific intelligence that could otherwise be obscured by the sheer volume of data. These insights, in turn, inform messaging strategies for marketing and customer service strategies. Segmentation can also help banks better understand the customer lifecycle and predict customer behavior.

Examples of common customer segmentation criteria:
  • Customer value – How many products & services customers purchase and what kind of revenue that generates for the bank – past, current, and predicted for the future
  • Demographics – Age, geography, gender, generation (e.g. Millennials and Baby Boomers), income level, marital status, and other “vital statistics”
  • Life stage – Slightly different from age, focused instead on customers’ journeys through various milestones and markers; for example, graduating college or starting a family
  • Attitude – Customers’ subjective stances on things like the financial industry as a whole, online and mobile banking, the economy, and their satisfaction with their bank
  • Behavior – Interactions and transactions between customers and their bank, which channels they use and how often, and which products they adopt

Similar criteria can be applied to banks’ business customers – profitability, number of employees, “life” stage (start-up, established, legacy), and so forth.

These are the traditional ways that customers have been segmented for decades. However, relying just on these categories is not going to yield many actionable insights.

In the age of Big Data, you sometimes have to think small. The real power of segmentation is not the quantity of data you can collect – which, with today’s technology and methods, is virtually infinite. It’s in the ability to drill down to the information that actually teaches you something about your customers.

Often it’s not the segments themselves, but where they overlap, where you’ll find the most valuable intelligence.

customer segmentationSome examples: unmarried, home-owning, degree-holding women under 45; middle-income married parents of high-school-age children in a particular school district; and minority Millennials who are starting their own digitally driven businesses.  Any of these micro-segments may prove valuable customer niches for banks to prioritize. But first, you have to conceive of their existence. Second, ask the right questions. And third, conduct the relevant research to answer those questions.

To understand how this can come in handy for banks, just think about the sometimes bizarre categories that show up in your Netflix queue based on what you’ve been watching lately. Vintage sci-fi with a strong female lead? Critically acclaimed British nature documentaries? Criminal investigation murder mysteries based on books? The more they know your tastes, the more likely you are to keep using their service based on their recommendations.

The options for how segments can overlap are nearly limitless.

Nearly. There is a bell curve to the usefulness of segmentation. Too broad, and the results are less than insightful. Too narrow, and the value of the insights gained will have minimal bottom-line impact.

This is where it helps to have experienced data scientists on your side. The purpose and advantages of segmentation are easy to enough to grasp, but the farther you get into analytic methodology, the more highly technical it becomes, and the more you need to understand about mathematical models and formulas. If things like our guide to data visualization make your eyes glaze over, chances are that the nuances of segmentation will put you right to sleep, too.

But you’re in luck, because CSP’s customer experience & research experts are passionate about getting you the insights you need out of the wealth of data we can gather. So if you are interested in getting to know your customers down to the niche level that segmentation empowers, give John Berigan a call at (800) 841-7954 ext. 101 or contact us by email to start a conversation.


More articles on using data to your advantage:

Release the Customer Intelligence Trapped Within Data Silos

February 25, 2015

Big Data is a big topic. In all the conversation about the potential for data to reveal key customer insights, broad statements and big promises are far more common than specific examples of the real-world answers a business might hope to gain.

There’s a reason that the word “data” is plural. An individual datum reveals very little on its own; it’s the connections, intersections, and overlaps of data that form the actionable patterns and trends.

Yet customer data is often still “siloed” into separate sources: direct customer feedback, employee performance measurements, web and mobile analytics, customer service interactions, standardized reports and evaluations, and social media impressions, to name a few.

Together, all of these data points can shed an entirely new light on the customer experience, but businesses are still learning how to effectively and efficiently connect the dots. Customer data is hardly self-explanatory, and legacy systems weren’t designed with this kind of interconnectivity in mind, leaving those insights trapped in silos.

transaction dataFor an example, consider financial service institutions. An article in BAI’s online edition rightly points out how these businesses are flush with transaction data generated by customers using credit cards, debit cards, checking accounts, ATMs, and mobile payments on a day-to-day basis.

This resource alone can tell the institution the number, types, locations, and frequency of transactions; the devices being used to complete these transactions; the breakdown of service and card types; and withdrawal/deposit amounts on a real-time basis.

Not only does this summarize the customer experience, there’s a direct connection to daily operations like cash inventory and technical support for digital tools (think: error code reports from a malfunctioning ATM).

Without systems in place to gather all of this customer data and deliver it in a digestible and useful format, to the correct teams, and in real time, valuable customer intelligence stays trapped in the Transaction Data silo.

Data is a living organism.

It consumes, it grows, it morphs and takes on new shapes, dimensions, and patterns. Each source of data depends on the others; by keeping customer data in silos dictated by their sources, a business risks starving itself of the vital information it seeks to gain by gathering data in the first place.

At CSP, we believe in the indispensable value of customized data delivery solutions designed around each business’s unique goals and customer experience. Don’t miss out on trapped data – talk to our customer intelligence experts today.

CSP can be reached by phone at (402) 399-8790 ext:101, via our website, or on Twitter @csprofiles.