Marketers are familiar with the adage that “good marketing combines both art and science.” While there is no substitute for creativity and intuition, savvy marketers know that the “science” part of the equation is becoming ever more important. Data-driven decision making related to customers and prospects is required to compete in today’s banking environment.
The science of bank marketing centers on a well-understood and targeted customer profile, a solid marketing strategy to attract and retain such customers, and efficient use of a sometimes limited marketing budget to get the most value from each dollar invested in the marketing strategy.
Timely, accurate data and solid analytics drive implementation goals, results-tracking, and improvement plans.
Sources for marketing data and analytics abound—from marketing automation tools and web analytics to social media analytics and ad platform reporting. These technologies have evolved significantly in recent years, clearly helping marketers recognize and nurture prospects, as well as identify cross-sell opportunities with current clients.
So where does the bank’s finance team fit into the picture? Let’s take a look at how a great relationship with finance can support the science of marketing to customers and prospects based on customer profitability.
1. Let’s start with the big picture. How can finance help marketing?
The finance team does not simply crunch numbers. The team consolidates information across the institution, analyzes it, and provides the right information to the right people to support informed, timely business decisions. Analyses related to customer profitability are of particular interest to marketers as indicators of marketing needs and campaign efficacy, which contribute to overall institutional success.
2. How has the analysis of customer profitability changed?
Customer profitability involves both art and science as well. Years ago, the value of an institution’s customer was commensurate with the dollars under management for that customer. This mindset did not consider the scope of the customer’s influence—the art side of customer profitability. Nor did it consider the profitability and risk associated with the customer’s loans and deposits—the science side of customer profitability. Dollars managed and profitability may not have a high correlation.
The finance team’s measurement of customer profitability and scope-of-influence helps finance and marketing executives understand which groups of customers—and even which individual, high-value customers—contribute most to their institution’s bottom line.
3. What’s the best way to partner with the finance team on a topic such as customer profitability?
First work as a marketing team to understand the types of decisions to be made, and then develop a sequence of questions to determine the data required from finance and other teams to make such decisions.
For example, appropriate questions related to customer profitability include:
- What types of decisions are going to be made? For example, does the institution want to make loan pricing decisions, reduce or waive customer fees, adjust customer service levels, or support marketing campaigns for specific customer groups?
- Who is accountable and how? Will branch managers, region managers, front-line employees (such as relationship managers and loan officers), and/or marketing managers be making these decisions? Will the profitability associated with these decisions and marketing campaigns become part of performance reviews or compensation plans?
- What metrics are needed to make decisions? Applicable metrics may include net interest margin, fully allocated profitability, return on equity, risk-adjusted return on capital, and profitability rankings.
- What calculation/methodologies are needed to derive those metrics? For customer profitability analysis (as well as analysis of product, channel, office, or branch profitability), finance may use methodologies such as matched-term funds transfer pricing, and activity-based costing, including calculations for overhead cost allocations, product/unit costs, and other items.
- What tools are needed? To support these calculations and methodologies, work with finance to determine whether necessary tools are in place. Beyond Excel spreadsheets, are new tools needed? Can desired information be derived from separate tools, or is a single platform required?
- What data points are needed? Desired information may include data types such as general ledger, loan or deposit/share accounts or other instrument-level data, transaction history, customer information files, credit information, demographics, and statistical data.
With the answers to these questions, finance should be well equipped to provide marketing with solid customer profitability metrics and analytics to better inform their strategic marketing decisions.
4. Once marketing has this customer profitability information, how can it be put to good use?
One idea is to create a ranking system that classifies customers based on their profitability level—for example, platinum/gold/silver, or some other system. The marketing team plays a key role in developing an approach to reward and retain the most profitable customers by offering them different service levels or exclusive benefits. Profitable customers who often hold large deposits or take out jumbo loans have historically earned better rates and been charged reduced fees. Other perks suggested by the marketing team for more profitable clients might include assignment to a relationship officer, or exclusive access to a premium credit card.
Customer profitability information also can be used by the marketing team to compare different metrics for “engaged” vs. “non-engaged” customers. For example, customers might be categorized based on the number of products they have overall, the variety of product categories they use, their account activity levels, or some combination. Financial metrics for engaged versus non-engaged customers also can be compared, including net interest margin, loan loss, non-interest income and expense, and profitability ratios such as risk-adjusted return on capital.
All of these data points can inform the marketing team as it develops and implements different marketing strategies that might be appropriate for different “slices” of engaged and non-engaged customers.
Additionally, it can be informative to layer on data points such as demographic information (e.g., age, income level or geographic location)—and information about products used—to help tailor campaign messaging. Correlating these additional data points, and combining them with an analysis of which products are the most profitable, can help institutions identify existing profitable customers for cross- or up-sell campaigns on social media outlets, such as LinkedIn or Facebook, or on advertising platforms. These channels can also attract new customers with a propensity to be profitable.
5. How frequently do you recommend analyzing customer profitability data?
Customer profitability analysis is definitely not a one-and-done exercise, or even an annual process. Instead, consider a monthly reporting cadence for regular analytics. The more timely the data, the more accurate the institution’s decision-making process related to products and customers.
Originally published in the ABA Banking Journal.