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How to Use Data to Acquire New Account Holders

Sep 12, 2016 9:39:59 AM

Screen_Shot_2016-09-12_at_9.38.17_AM.pngRetail banking is at an impasse. Fintech startups are poaching bank service channels left and right, providing strong competition for new and current customers. While fintech firms are able to innovate more quickly than banks, banks maintain a large strategic advantage — large customer bases. Banks own huge quantities of customer data but few have successfully analyzed it and put it to use to attract new customers.

What does that mean? For many banks and credit card issuers, “the data they already have in their vaults is the most valuable, and now is the time to leverage it.”

Do The Basics Well (And Track Usage Behavior)

A Bain & Company survey of 14,812 retail bank customers revealed that mundane, everyday banking interactions matter just as much as complex transactions. Yet, customers across the world continue to be underwhelmed by basic product delivery. Perhaps accustomed to higher service standards in shopping, restaurant, and courier services, customers now expect the same standards to apply to their banking services.

Known in some circles as omni-channel banking, it is now common to expect flawless, quick and free bank services such as in-person consultations (branch office), ATMs, online payment and money management tools, live phone support, and automated phone and mobile services.

What does this have to do with data and customer acquisition? Providing solid free basic services is the easiest (and cheapest) way to communicate your brand to current and potential customers. If the service is good, word-of-mouth will attract new account holders. On the other hand, if the service doesn’t deliver, expect customers to leave for hungry competitors. With each service transaction, banks collect user behavior data. Banks that learn from their usage statistics will be able to shift offerings quickly to meet customer demands.

Target Marketing and Segmentation Efforts

The average person receives 121 emails and five pieces of snail mail per day. Research done at Stanford says that bank mass mail campaigns are less than 1% effective but targeted direct mail campaigns can be much more effective.

In addition, “Banks that apply analytics to customer data have a four percentage point lead in market share over banks that do not.” A lead like that adds up over time — enough to spell the difference between institutions that remain competitive and those that don't.

The research also found that "the average response rate for community bank direct mail pieces is between 0.3% and 6%, with an average of 3.4%. If you include the cost of time, design, mailing list management, postage and execution, the cost per lead for banks works out to between $19 and $55 per lead, or about $169 per sale."

High lead generation costs and cost of sales means that customer segmentation efforts must be far more detailed and targeted. Fees for basic banking products are being squeezed out of the marketplace (by competition and regulation) making return on direct marketing even tougher. This is where big data management and analysis can help you win. Building IT systems, online products, mobile products, and in-person/high touch products that track existing customer/user demographics/behavior and test retention initiatives and scenarios, banks can target higher fee products more appropriately and generate a more attractive lead base.

Internet of Things & Big Data Analysis

In addition to tracking bank user data, banks are increasingly being incorporated into the Internet-of-Things (IoT). As smarter houses and machines report usage statistics and metrics, banks can capitalize on this emerging technology space by providing data analysis and integrated payment solutions.

For example, smart utility readers can communicate water, electric, and gas bills, to banks which can set up auto-pay features to transact with utilities directly and eliminate monthly utility bill headaches. In another example, a smart fridge might know when you have run out of milk or a smart car could know when it is about to run out of gas...payment features could be integrated directly into the fridge or car so that a user could place the replacement order from home or on the road.

While the future of banking technologies can be fun to think about, banks can (and should) take action now and use their data to retain and attract new accounts. Using data that has already been collected from current customers, banks can, as Harland Clarke writes, “gain key insights from customer portfolios, identify opportunities and risks in those portfolios, and perform product analysis for deposit, loan, electronic and other lines of business.”

Finally, banks can leverage current customer data to segment and target potential customers with similar demographics/behaviors and bring them into the fold offering products and services that match those needs. 

Taken together, these suggestions to better use data can add up to enormous gains.

Banker's Guide to Big Data

Kenneth Dabkowski

Written by Kenneth Dabkowski

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