There are a variety of attributes that signify a profitable customer in banking. Age, industry, loan balance, deposits, number of products used and fee income generation are all well understood as it relates to finding a more profitable customer. However, in this age of big data, there are a variety of other attributes that, when assembled, resemble, in some way, your existing group of profitable customers. For banking, attributes like email response times, international travel, ESPN, college, family size, credit card and hundreds of other characteristics commonly point to a profitable banking customer. This is called a “Lookalike audience” and the use of which will change bank customer acquisition.
Why This Is Significant
Utilizing a lookalike methodology to find customers is a radical departure from traditional bank marketing. Historically, bank marketing has either been done via one-to-one engagement or mass “spray and pray” marketing where a message is broadcasted in hopes that the right customer will hear or see it. As can be seen by our recent response rates (2015), lookalike marketing is impressive by targeting both the customer and the message.
Lookalike marketing is so effective because of the three-dimensional aspect to it. Not only are you gathering a population that you want, but a population that is likely to use a particular loan or deposit product AND you are delivering them ads/emails that are relevant to them. This is a massively powerful combination of methods that have only recently been available to banks.
Lookalike Targets Are Not What You Would Expect
The part that many banks have failed to realize is lookalike marketing isn’t matching similar demographics, but quantitatively matching behaviors and thought patterns. If you ask most bankers to draw a customer persona of their most profitable customer, you will likely get a picture of a 62-year old, white male that reads the Wall Street Journal. The reality is that if we are talking checking, it is more likely a 32-year old, college educated African American woman that identifies with Bernie Saunders, plays the piano and likes to run.
Putting Lookalike Analysis Into Action
The easiest way to put this into action is to leverage social media. Twitter, Google and Facebook all have lookalike functionality where you upload a set of target clients (at least 100) that you want to mimic and then let the algorithm run its course. Once you see the output, you realize the power of social media and Presidential preference, level of volunteerism, number of Likes, pet ownership and much more.
The other way to handle it is to use a prebuilt statistical tool. We use Watson and Emcien but there are many other tools that will do the job.
There is also a long list of third party marketing firms such as Amadeus Consulting and others that can do the hard work for you and crunch your data to return an ideal set of attributes.
When you get done, you should have a set of attributes and a roadmap to go get new customers with greater effectiveness. Our graph below maps lifetime value of core checking customers with the number of correlated attributes. Understanding those attributes of customers around the green line now allows us to find other customers that match up. Target a city the size of Jacksonville, FL with the right campaign and you are likely to get an engagement rate of 20%. Of these, you should be able to convert 0.5% into an elite-tier checking account. That is a potential cumulative marketing lift of close to $1mm from a campaign – not a bad return on investment.
If your bank is looking to be more effective in its marketing, applying the concepts of lookalike marketing is a way to improve your efforts and make better use of your resources. It is not a magic bullet to getting new customers, but it is the most quantitative way possible to build a portfolio of profitable customers.
Submitted by Chris Nichols on February 23, 2016