By Mark Gibson and Michael Wallach
Pretty much everyone in banking understands that data and marketing analytics can add tremendous value to an organization and its customers. But far fewer can agree on the immediate path forward. While some industry pundits preach real time analytics and artificial intelligence for personalization, many banks find themselves struggling to reach more basic levels of prowess. This creates a disconnect akin to showing a video of a high performance sports car to someone who doesn’t know how to drive. There is no discernable path forward.
In this article, we will illuminate that path forward and provide a GPS for how to navigate it. Whether you still find yourself “without a driver’s license” or you’re meandering along a winding road, you can learn to use AI and personalization analytics to reach your destination.
Start your engine: understanding how to use data at every stage of the customer journey
Why is it so important to move down this path? Because using analytics and insight can significantly improve the effectiveness and ROI of your marketing efforts, as illustrated by the classic customer development funnel.
Consider the new insights that marketing analytics can add at each stage of the funnel, creating a predictable revenue growth engine. Let’s take a look at each stage.
- Prospecting – Applying analytics to prospecting replaces cold calling with precision targeting that is scalable and repeatable. This can be especially true if you analyze your most profitable existing customers first, then focus your marketing efforts on attracting people like them.
- Acquisition – Now that you know who you are targeting, data analytics can inform what their needs are, what will motivate them to switch and even when they are in the market for a new product.
- Onboarding – Most banks have adopted some variation of the branch-based “2x2x2” onboarding process—that is, following up with new customers after two days, two weeks, and two months. This definitely adds value. However, some basic analytics can dramatically enhance the onboarding process, delivering more value to your customers and increasing revenue and retention for your organization. For example, when you understand who has and has not signed up for mobile banking, you can customize your communication, significantly increasing your success rate.
- Activation/Utilization – Once customers sign up for something, many marketers assume their job is done. Actually, it’s just starting. Think about checking accounts and how many of them sit dormant or with low balances and little usage. The strongest marketing programs set the goal of making the bank the customer’s primary financial institution, and use data to understand where each new customer is in fully adopting the checking account and related services. A combination of email, alerts to the sales force and even direct mail and incentives is used to convert as many customers as possible to primary users and lifelong loyal customers.
- Relationship Expansion – Each customer is different, but most people follow similar paths through life: they graduate, get their first job, buy a car, get married, buy a house, have kids, pay for education, and retire. Understanding where each customer is in his or her life journey can make your customer dialogs much richer and more valuable. Combining that knowledge with specific triggers like a marriage or new baby can improve the effectiveness of your marketing even more. All this data is readily available from third parties your organization may already be working with for other purposes.
Check the steering: clearing the obstacles in your way.
Once you have a solid understanding of how analytics can make marketing more productive and predictive at various stages, it’s time assess the potential bumps in the road:
- A very small marketing department
- Lack of access to data analysts
- Limited budget for business intelligence
None of these obstacles are insurmountable, but your marketing analytics efforts will come to a halt without three basic elements. The first is executive alignment. The C-suite must understand that data driven marketing adds value to the organization—and they must be willing to fund it. That leads to the second ingredient—infrastructure. You’ll need the systems and tools used to store, analyze and deliver data and insight. That will enable the third ingredient—the data analytics activities themselves, including targeting, modeling, analysis and reporting.
Once you have those elements in place, you’re ready to roll. It can be helpful to think of marketing analytics as falling into three levels: basic, advanced, and expert.
Take the first turn: mastering the basic level of marketing analytics
Most financial institutions are either working toward or working at the basic level of analytics. The milestones of this stage are the ability to:
- Determine which data will be useful for improved marketing
- Obtain and house the data somewhere
- Employ basic data access and analysis skills (Be able to answer: Who needs this product? How do I find and reach them?)
- Enable execution and measurement of marketing programs using this insight
The following diagram illustrates how these pieces begin to fit together into a system.
Many banks have come to the critical realization that you don’t have to do all this with your internal staff. There are direct mail and digital marketing firms that do this kind of basic analysis all day every day. However, it is up to you to understand what you want to do, what your critical goals are, and what specifically you hope to achieve. Then you need to manage the third party to make sure they are focused on those things, not just on what pays their bills.
Pick up speed: moving up to the level of advanced marketing analytics
If that all sounds pretty basic, you’re ready to master the advanced level of analytics. The key differences here are:
- Being able to target individuals using digital media, not just segments or personas
- Relying extensively on third party data
- Using marketing automation to deliver relevant content to individuals based on their previous interests and behavior
Additional infrastructure such as a data management platform (DMP), content management system (CMS), and marketing automation (MAP) are needed to fully deploy advanced marketing analytics—but again it is very common to rent rather than buy these capabilities. In other words, there are many marketing services providers including digital marketing and media agencies that have invested in these tools so you don’t need to. The earlier caveat still holds: you need to know what you are buying and how specifically you want to use it. Otherwise, you will end up paying for things you don’t need, and possibly even not accomplishing your business goals. The following diagram illustrates the advanced marketing analytics ecosystem.
Pedal to the metal?
Beyond the advanced level of analytics, there’s also an expert level. This is where a variety of cutting-edge analytical tools are integrated with a host of internal and external systems to achieve the real-time personalization we’ve read so much about. It’s likely that only about 10-20 of the largest banks have reached this level.
Pulling it all together
Wherever you find yourself and your team on the marketing analytics journey, taking that next step can make all the difference in your marketing efforts. It could mean, for example, beginning to use look-alike modeling to find your best prospects. Or it could mean using third-party data to identify prospects who are in the market for your product. And the more you are able to link your activities with actual sales results, the better your chances of repositioning marketing from an expense to be minimized to an investment that should be optimized. Good luck!
Mark Gibson and Michael Wallach are senior consultants at Capital Performance Group, a strategic consulting firm that provides advisory, planning, analytic and project management services to the financial services industry.
