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Home Retail and Marketing

How to Sell the C-Suite on Advanced Analytics

October 13, 2016
Reading Time: 4 mins read

By Steven Simpson

It’s not just large institutions that stand to benefit from the power of data and advanced analytics—smaller banks have just as much to gain. Yet bank marketers still struggle to make a business case for the bank’s investment in them. In the past, data analytics were custom built, sometimes at the cost of millions of dollars—a luxury accessible only to the largest financial institutions.

Now, with more affordable implementation options available, marketers need to figure out how to get more top-management muscle and C-suite buy-in for these programs. To make the best case possible, here are three points to bring to the table:

  1. Competitive survival depends on knowing your customers.

To successfully keep pace with today’s competitive landscape, you must understand that your best customers are your competition’s best targets.  Can the bank identify these profitable customers?  Do you have the analytic algorithms to measure your strength and retention with them?

Compared to their smaller counterparts, the largest banks appear to have succeeded in deploying data analytics. In 2014, Wells Fargo invested $600 million into a multi-year analytical program, hired a chief data officer and teams of analysts. Wells Fargo’s investment in big data is aimed to make its customers’ lives easier, to enhance customer loyalty, and to mitigate risk. Bank of America, Capital One, Fifth Third, and other mega-banks have figured out how to gain greater market share by becoming more data-centric. The data that drives the bank needs to be captured, sifted, and analyzed to find hidden and valuable knowledge aimed at making these banks more attractive to existing and future customers.

Today, many marketing departments rely on a marketing customer information file (MCIF) to help with customer segmentation. But once all of the account data is in the MCIF database, what next? How will all that data be translated into actionable decision-making that actually brings the bank answers, opportunities, and revenue?

An advanced analytic platform helps financial institutions make better decisions by identifying opportunities based on machine learning and advanced analytics. Banks without these programs are at a competitive disadvantage.

  1. Banks need the tools to validate and deliver return on investment.

When it comes to budgets and marketing programs, the C-suite will always challenge the marketing department to show a return on investment. In January 2016, the Financial Marketing Trends Report released some sobering statistics, reporting that 50% of financial marketing professionals surveyed admitted they struggle to quantify the results and impact of their current marketing programs.

It is very difficult to measure leads and new business derived from broadcast marketing activities such as billboards, radio and print advertisements, and one-off “welcome to the bank” letters and statement-stuffers.

As the industry dives deeper into the digital revolution, banks need to be communicating and marketing to customers and prospects through many different channels such as: email marketing, social media, digital ad networks, text messaging, and more. With a proper analytics platform, the bank can easily uncover the purchasing influences and behaviors that define the most profitable customers, and create customized, personalized messages to these specific audiences.

Advanced analytics generate real-time insights that lead to faster, smarter campaign decisions, which will in turn deliver higher-quality leads to the sales team and lending department. According to Marketing Sherpa, advanced analytics deliver efficiency gains of 30% or more by supporting targeted campaigns and higher conversion rates.

With greater accuracy, data analytics can assess the impact of strategy and campaign execution. In addition, using data analytics, the bank can easily:

  • Track marketing campaign budgets
  • Quantify and measure open, click-through, and response rates
  • Determine which campaigns are the most effective at turning leads into new business

Advanced analytics can assist marketing in quantifying all program activities, which can improve future marketing strategy, plans, and budget allocation. When results are measured, monitored, tracked and repeated for ongoing success, it will help solidify C-level buy-in.

  1. Segmentation only works when it’s followed by timely, specific messages.

Advanced analytic programs help the marketing team identify which product to offer to which customer, and when. Understanding customer behavior, timing, and product trends will help in customer-centric up-selling and cross-selling activities.

The big payoff: an advanced analytics platform offers prescriptive recommendations that allow marketing to create a new action (car loan, mortgage, student loan, checking account) for an identified group of customers (retirees, business executives, etc.). Then it will time stamp and track the impact.

This feedback loop allows marketing to focus efforts on the most promising opportunities. The result is an immediate boost to revenue and business goals. Additionally, the system helps create best practices by comparing performance of different messages, channels, timing, segmentations, and actions against a control group.

With an advanced analytics program, the marketing department can customize each audience segment to receive a customized message. Plus, each additional message will be further segmented and customized. If something changes in account behavior, that customer segment will receive a different message and offering. Advanced analytics allows the bank to pinpoint exactly what message, what segment, what marketing channel, and what pitch worked.

Bank marketers are then able to answer critical questions, such as:

  • How does traditional print advertising and direct mail compare to a message through the digital channel?
  • Which message was best received, by a particular segment, via the digital channel?
  • Did text work better than e-mail versus call center, versus teller delivered message in branch, versus print?
  • Does success vary when you consider how long the customer has been with the bank?

The bank will soon have a proven and repeatable process to track and gain actionable insights on how customers react to product offers and know the return on investment of each channel, message, action and timing.

Financial institutions that are well prepared to harness customer data via advanced analytics stand to drive huge new market share. Today, without a commitment to data analytics, financial institutions will struggle to thrive and survive in tomorrow’s competitive business environment.

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Steven Simpson is senior vice president of Financial Institution Solutions, at Saggezza, a provider of innovative software technology solutions.

Tags: AnalyticsBig dataCustomer loyaltyMachine learningStrategic marketing
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