Banks and credit unions have a significant challenge. According to research published in the Raddon Report, a measly 32% of the average financial institution’s account holder households are profitable, while the remaining two thirds negatively affect the institution’s bottom line.
Let’s say that again: Two thirds of account holders are dragging down the industry’s bottom line.
It’s a problem across the board. Even some of the nation’s top-performing banks and credit unions don’t make a profit from the majority of their customers and members. But it also represents significant opportunity. Financial marketers need to comprehensively reevaluate their retention and acquisition practices to more effectively use actionable data.
People Don’t Buy What They Don’t Need
At any given time, it’s estimated that only 4% of checking account customers are in the market for a loan. And most financial institutions find that less than 10% of those account holders shopping for a loan end up borrowing from their primary bank.
Instead, they turn to competitors for credit products, whether it’s credit cards, mortgages, auto loans or even personal loans. Why? Timing and relevance. They tend to use whoever is reaching them at right time with the offer they need. Data-savvy marketers in acquisition mode are stealing your potential profitability.
Missed Opportunity:
Less than one in ten checking account customers needing a loan turn to their primary financial institution.
Even a financial institution’s best customer won’t book a loan if they don’t need one. The key to profitability is gaining the ability to see what account holders need, when they need it, and making a personalized and compelling offer at the right moment. But the question is: How do you pinpoint those moments of need? A three-step process does just that.
The Three Steps to Perfectly Timed Offers
Step 1: Convert customer data into actional consumer insights
To improve the profitability of your account holders, you first must be able to harness your data to build real consumer insights that you can act upon.
Start with your first-party data. Gain a picture of your current account holders. Identify the mix of products that profitable households have with you.
Bring third-party partner data into your mix to build a much fuller picture of consumers that includes demographic and financial attributes, previously purchased products and services, and the scenarios in which they have engaged with you in the past.
Model your target list after your most profitable customers. Work with a data partner to create high-quality propensity models that identify the consumers like your most profitable ones based on a data append of demographic, financial, and purchasing behavior.
A propensity model is a statistical scorecard that is used to predict the buying behavior or needs of your account holder base. Propensity models are used to identify those most likely to have a specific need or to respond to an offer. Putting a multifaceted propensity model in place — one that can predict what account holders will buy or do — gives you the ability to capture the intent signals that make your insights actionable.
Intent signals are points of data that indicate that an account holder or prospect is showing interest in your brand or in something that will impact their purchase behavior. An intent signal could be an online search, or it could be connecting with the brand on social media, or even downloading information or filling in an online form. For example, if you see intent signals that indicate an account holder is downloading information about home buying, you know they are also very likely to be shopping for a mortgage.
And when you know what account holders intend to do before they do it, you can begin marketing earlier in the customer journey. If you can get there before competitors, with exactly the right offer at precisely the right time, you are more likely to get that business.
Step 2: Have a system to act on consumer insights
Consumer insights with intent signals, are very powerful — but only if you have the program to act on those signals quickly and effectively. Intent signals tell you what consumers are shopping for and when, so they give you the power of timing. But the ability to put an offer in front of the consumer at exactly the right moment requires a comprehensive campaign program, channel tools, and personalized messaging.
Agencies such as Amsive have platforms to orchestrate omnichannel campaigns across digital and traditional channels. You need to be able put messaging in market that speaks directly to your target with a personalized offer, and you need to do it quickly.
Digital marketing can reach your customers where they are and where they spend their time, while direct mail can put a very specific, relevant offer in hand. The combination can be a powerful tool to drive conversion and profitability across your account base.
Step 3: Measure results and capture attribution
One of the greatest challenges in marketing analytics today is capturing true attribution, particularly in omnichannel campaigns. When you reach across all channels, you made a great impact, but in the interplay of these channels, attribution can get lost.
Analytics across multiple channels can be misleading because the analytics of many digital platforms are siloed off. To build a repeatable omnichannel campaign program, you need to understand how the complex mix of reach and conversion impacts performance throughout the customer journey.
For instance, can you identify the first-touch channel? Do you have a clear picture of how subsequent touches across multiple channels move your target audience further down the funnel? Do you know which channel and tactic created the conversion point?
Mixed Signals:
With an omnichannel campaign, keeping track of attribution is a big challenge because of siloed analytics.
A combination of advanced analytics and machine learning gets you much closer to clarity on this process. When you understand what is working, you can replicate it more effectively.
Profitability Starts With Better Management of Data
Today, only the most astute financial institutions are using data to successfully build deeper and stronger relationships with existing customers while also attracting new ones. Data gives them the power to understand which customers are truly unprofitable—and which ones show the potential for greater profitability.
Download our eBook to learn more about how to use next-level campaign intelligence across the online and offline media landscape to achieve higher levels of performance and profitability.