In Banking, Big Data Is Great… But Right Data Is Better

How can banks and credit unions market more effectively? Segmenting consumer groups by behavior, preferences, even political leanings makes it easier to parse the right groups of people to maximize sales. The deeper marketers dig, the more likely they'll find the right ore.

Today’s consumers have more options than ever before, so they expect the financial service providers that they’ve selected to truly know them. On the other hand, consumers worry about privacy.

How do banks and credit unions provide the customized service that consumers increasingly expect?

The stakes are high. If consumers don’t perceive value in a relationship with their financial institution, they’ll look elsewhere. The smarter the financial sector becomes about data and technology advances and how to deploy personalized communications through segmentation, the greater the level of customer retention and loyalty will be. In turn, this will drive preference and increase market share.

Drill Deep to Mine for Prime Data

Many industry resources provide demographic and purchase data to help financial marketers better understand who their customer is, at least in general terms. Often, however, such data fails to clarify a specific customer’s needs and how to best reach them.

Understanding who your customer is at a granular level, and how to reach them most effectively across channels — and in compliance with fair lending laws and regulations — is the sweet spot. With an enhanced level of detailed targeting, the right segmentation can deliver a 5%-7% lift in ROI.

Specificity improves the focus of your marketing. Rather than aiming at a vague target, such as non-Hispanic white women ages 18 to 49, you can market with laser precision. For example, you can segment to a 20-something mother who shops at Whole Foods, has a 529 educational savings account, holds a mortgage, banks online, uses Apple Pay, reads Parenting Magazine, maintains an umbrella insurance policy, drives a Volkswagen, contributes to education causes, and votes Republican.

You begin to get to know your target as a person and, through this detailed picture, you begin to see her life and needs unfold. Further, understanding how cultural differences can impact the customer’s language and media preferences is critically important when your goal is relevance.

Segmentation also offers marketers the tools to plan media buys and deliver campaigns across all channels, including digital and social. Knowing its top segments, a regional bank can purchase a list by segment, or select digital audiences across platforms to reach more prospects that look like their best customers. This provides scale in a privacy-friendly way that isn’t possible with other methods.

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Fresh Data Revises Longstanding Segmentation Boundaries

To further help marketers understand consumers, an original financial behavior research study was conducted over three years. The largest undertaking of its kind in the financial services industry, this research tapped into 250,000 households to create income-producing assets (IPA) data.

This permission-based, anonymized consumer data measured liquid wealth and savings and investment vehicles. This data was then married with property-level home value data and increasing IPA to over $3 million to create greater distinctions among the high-affluent segments, providing marketers with a more detailed view of wealth and prospective financial behaviors.

Using affluence and household age and composition, three lifestage classes have been identified: Younger Years, Family Life and Mature Years. These are further distilled into 12 groups classified as Upwardly Mobile, Mass Middle Class and Retirement Blues, among others.

These groups have been further refined into 60 segments like McMansions & Merriment, Value Seekers and Leisure Land, for example, to provide marketers with a detailed snapshot of who their consumers are, how they manage their money and spending, and where they tend to spend their leisure time.

 

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Webster First: Identifying the Best Customers

Now one of the largest credit unions in Massachusetts, Webster First began as a single-office credit union in 1928. As a regional banking player, Webster, like other smaller financial institutions, has limited staff, analytics, and marketing resources. Accordingly, making the most of each customer relationship is crucial.

To do so, Webster has become savvy at converting customer insights into action. Webster First recently leveraged powerful household demographic and behavioral data enhanced with big data insights that embrace more accurate correlations to net worth. These two key big data insights center around property-level home value and property characteristics and technology usage and behaviors.

The addition of this new data reflects changes in U.S. consumer demographic and financial composition, fostering a higher level of precision in determining the most relevant products and offers for Webster’s existing and prospective customers, personalized at scale.

Having a deeper understanding of not only customer life stages, but defined household segments, has helped transform for how Webster First reaches and talks to consumers across channels. Webster First has been able to refine its marketing approach at an individual level. In addition, it has refined its go-to-market strategies and, in turn, gained a competitive advantage and built its business by better understanding specific customers and segments.

For example, tapping cultural insights, Webster First discovered that Hispanic customers often went to a specific bank branch that lacked Spanish-speaking tellers. The bank brought in Spanish-speaking staff, which resulted in a better relationship with those customers. It also allowed Webster to expand this personalized service to additional Hispanic prospects — thus discovering new, untapped audiences.

Having a window into consumers’ technology usage has changed how Webster communicates with customers and prospects as well. Access to insights from 95 million U.S. households and 400 million devices across 100 technology-related behaviors, including use of specific devices as well as specific activities engaged in by households, helps illustrate how individual households embrace technology in their daily lives.

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Enhancing Omnichannel Engagements at Webster First

These insights have empowered Webster and its marketing agency to be more strategic about their paid media planning, buying and refining their media spend to more accurately reach the right customer at the right time through the right channel. Knowing that a particular customer segment tends to watch traditional TV while others stream movies on their digital devices, for example, has helped Webster more accurately place relevant ad messaging and creative.

Using customer lifestyles and product preferences, they’ve also personalized digital landing pages for such products as money-market accounts and changed ad placements in a variety of media channels based on more clearly defined customer segment data.

As a result, Webster has seen increases in product growth and targeted website traffic during campaign timeframes, leading to paid media savings as a result of greater channel efficiencies.

The credit union also identified new areas of opportunity in products, services, and optimizing digital and bank branch customer experiences. Because of this strategic approach to leveraging precise segmentation data, while Webster is driving less overall online traffic, the people arriving on the credit union’s site are more qualified and therefore more valuable.

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