By Mark Gibson
The marketing discipline has been rapidly evolving over the past decade, moving from what was once largely driven by experience, intuition and broad demographic targeting to a function increasingly powered by data, analytics and advanced decision-making technologies.
This is just as true in banking as in other industries. A recent ABA survey of bank marketers chronicles the speed of this evolution and how it is benefiting consumers, marketing and the organization as a whole. This article explores what successful data-driven decision-making looks like in bank marketing, the critical benefits it generates and the organizational and compliance considerations. A future article will explore the most common use cases for data-driven decision-making within marketing and how banks are successfully leveraging it to enhance revenue growth.
The importance of data-driven decision making
Data-driven decision making refers to the organized use of data, analytics and experimentation to inform marketing choices — what to offer, to whom, through which channel and at what time. Unlike traditional marketing analytics, which often focuses on reporting and performance measurement, DDDM emphasizes decision intelligence. The goal is not just to understand what happened, but to guide future actions in a consistent, scalable, and measurable way.
In a banking context, data-driven decisions may include:
- Determining the next-best product or service for an individual customer
- Identifying customers at risk of attrition before they disengage
- Optimizing marketing spend across channels while maintaining regulatory compliance
- Timing communications to coincide with meaningful customer life events
By informing and optimizing these and other marketing decisions and actions over time, banks typically observe that their response rates rise, the cost of acquisition falls, and as a result, marketing efforts become more efficient and productive.
While the data and analytics function is typically located in a department other than marketing, most often finance or IT, respondents to the ABA’s recent survey indicate that marketers make extensive use of that information: 88% of respondents are using data to inform marketing decisions, up from 66% in last year’s survey. In fact, the frequency of their usage has accelerated over the past year, with 24% indicating respondents use data to inform decisions weekly, and 14% saying they use it daily.
This substantial increase in bank marketers using data analytics to inform their programs is likely driven by senior management’s growing expectation that marketing can measure and demonstrate value from its programs and expenditures. While not all sales are easily attributable to marketing efforts, data analytics are essential to both demonstrating that correlation as well as improving the performance of programs over time through data-driven learnings.
Customer data is the “crown jewel”
Customer data is the foundation of most data-driven bank marketing and banks have a huge advantage over most industries because they hold tremendous amounts of customer data. Most banks have data on which products a customer owns, the balances in those products, transaction histories, payment patterns and even branch and digital channel usage. Almost no other industry has that treasure trove of insight!
So, while many companies are forced to segment their customers into broad categories, banks can leverage all their data to create a dynamic, behavior-based view of customer groups or even individual customers.
Another category of data that is useful to marketers is how customers react (or do not) to marketing programs. Email open rates, click-throughs, call center interactions, branch visits and digital advertising performance all provide feedback loops that inform future decisions. This type of insight allows marketers to continuously optimize audience targeting and the media mix to enhance campaigns over time. This type of optimization can improve campaign success rates dramatically over time, with 50% improvements not uncommon.
The third and final category of customer data is ‘third-party data,’ meaning it is not held within the bank, is available externally and must be purchased. The most common and familiar data of this kind is credit bureau data regarding borrowing habits and creditworthiness. But there are many other types of data available that can inform a specific customer or prospect’s likely need for a given deposit or loan product, as well as which key benefits or appeals are most motivating. While this information needs to be used carefully from a compliance and privacy standpoint, it can significantly improve both the audience targeting, the relevancy of product and message and the response rate.
How banks are leveraging DDDM
According to ABA’s survey, customer relationship deepening was the most frequent use case being deployed by bank marketers, with nearly 80% of respondents leveraging data insights to inform these programs. Other top applications include customer communication, customer experience and measurement of marketing results.
The ABA survey also asked bank marketers about their top use cases for DDDM over the next 24 months. Three that rose significantly in importance were more effective new customer acquisition, segmentation and targeting strategy and customer retention.
Organizational considerations
There are several important implications for organizational structure, both within and outside the marketing department, as data-driven decision-making becomes more prevalent and embedded. Within Marketing, as the focus broadens from campaign development and media execution to actual decisions about which customers get what marketing treatment at what time, marketing staff become nearly as fluent in data interpretation and analytical techniques as they are in creative development. Outside of marketing, several other departments are integrated into DDDM development and implementation.
Data-driven marketing depends on timely access to high-quality data, scalable infrastructure, and integration across systems. This means that marketing is aligned with other critical departments, such as IT and Data Analytics, so it can gain timely access to data and technology platforms. Marketing is also aligned with Product Management and Customer Experience because many of the insights gleaned by DDDM have equal applicability to products and channel experiences as to marketing programs.
Build compliance into the program
A data-driven decision-making program needs to be designed from the ground up to be fully compliant with bank regulations. In addition, as with any highly analytical practice, DDDM can introduce unintended bias. As a result, bank marketers have found it best to work closely with their Compliance counterparts from the beginning to design models, processes, and governance standards.
The scope of this work usually includes the following:
- Data availability – clear guidelines defining who can access which data for what purpose, under what controls. Role-based access, audit trails, and approval workflows are typically part of this process.
- Model and decision governance — As marketing decisions become increasingly automated, governance shifts from campaign-level approvals to decision-level oversight. This includes documenting decision logic, monitoring model performance and periodically reviewing outcomes for fairness and compliance.
- Data, model and decision transparency – As with any advanced analytics, banks find it essential to have transparency into which data is used and how it is used to make decisions about individual customers. This upfront work in process design ensures that no unintended bias occurs during DDDM execution.
Turning insight into advantage
ABA’s survey makes clear that more bank marketers are using customer data to make decisions, and doing so more frequently. Marketers are finding that data analytics is enhancing the productivity and predictability of their campaigns while improving efficiency. Critical success factors cited by the group include: collaboration with other departments such as IT, business intelligence, and compliance; ready access to clean customer data; and data analytics fluency within the marketing team.
The primary use case and benefit is deepening existing customer relationships, driven by a better understanding of their needs and behaviors. But it is also expanding into new customer acquisition. Integrating data within marketing automation is increasing the scale and impact, but automation is not necessary for an institution to reap the benefits of data-driven decision-making. The only essential ingredients are organizing an institution’s customer data and having the cross-functional ability to harness that data to produce smarter, more impactful marketing programs.
Mark Gibson is co-leader of the sales and marketing practice at Capital Performance Group, a strategic consulting firm that helps financial institutions maximize the ROI of their marketing efforts. He can also be reached on LinkedIn or at [email protected].
