Digital marketing is more complicated than ever. But it gets even more challenging for financial services marketers, thanks to regulatory and privacy issues related to how brands can deploy data to hone their targeting and messaging surrounding certain financial products. To help make sense of the finserv-marketing landscape, Quad Insights spoke with two experts at Quad’s digital agency, Rise Interactive: Adam Krawiec, Senior Director, Account Management, and Doug Durkalski, Group VP, Account Management.
Over the past couple of years, how has Rise been evolving the solutions you’re offering to finserv marketers, such as banks and credit card issuers?
Adam Krawiec: I’d say there’s been an evolution of the adoption of marketing automation. You know, two or three years ago it could be treated as a differentiator — and now it’s treated as table stakes. So, where we’ve evolved our media strategies more recently is to convey that the power of automation is only as strong and as effective as the data signals that you’re sending it.
In the financial services world, we’re talking about a lead that then needs to get nurtured into being an active customer. There are a lot of steps that go into that journey. The path of least resistance is to have the algorithms optimized to the lead form — the initial point that somebody interacts with the brand. But if you’re solely basing your decisioning off that initial interaction point, well, so are other brands. If every brand is operating the same way, there isn’t really a differentiator in strategies. There might be a differentiator in creative or messaging or brand recognition, but there isn’t really a differentiator in strategy.
So, in other words, if every finserv marketer optimizes toward people who are willing to fill out a form, everybody gets a lot of people who filled out forms — but these are not necessarily the people who will ultimately, say, open a checking account or formally apply for a credit card.
Adam Krawiec: Exactly. So, where we at Rise have separated ourselves is really championing the idea of optimizing further down the funnel — optimizing to take in stronger signals, including offline activities, that are going to indicate that an individual is going to ultimately take the final actions that you want them to take.
It’s all about identifying the right kind of indicators that are the true signals for the health of a lead — by taking into consideration a lead-scoring model, for example. And then, pushing those signals back into the engines and using that as your optimization framework.
Let’s talk a bit about that — the engines and the optimization framework.
Adam Krawiec: The newest and most cutting-edge component of that is what we refer to as value-based bidding. What value-based bidding takes into consideration is that there is an intrinsic value of an individual as they hit each milestone along a journey. So, for a simplistic example, they fill out a lead form, then they complete an application, then that application gets approved, then they agree on terms, and then they become an active customer.
Each one of those milestones has an intrinsic value associated with it, based off of, say, the lifetime value of a customer or the value of whatever product or policy is being sold. So, what we do is work with brands to create an ecosystem where we’re understanding and basically putting a value parameter toward each one of those different milestones.
There’s a lot of backend data analysis that needs to be done to understand the value of a specific customer and the conversion rates through the funnel and how to assign appropriate values to different customer milestones. But ultimately, that is a huge differentiator at Rise — we work with our partners to kind of build out that ecosystem.
Using data analysis to reach higher-quality prospects also, of course, heavily factors into Quad’s direct mail solutions. You’re talking about digital marketing solutions, but your colleagues across Quad are having similar conversations with clients — for instance, advising brands that are deploying direct mail to print less, but print smarter, by using data to market to better leads.
Adam Krawiec: Yes, same idea.
Doug Durkalski: Yeah, you need fewer higher-quality leads to have bigger business impact.
And then, once you use data to winnow down to better leads, you also use your data to optimize and personalize your outreach to those better leads.
Doug Durkalski: Right. So, everything we’ve been talking about relates to optimization framework and closed-loop reporting. But we should also talk about targeting and messaging.
From a targeting standpoint, when you asked earlier about what’s changed over the past couple of years — the deprecation of the cookie and losing third-party data signals have obviously been big issues. So, the necessity of using first-party data signals for targeting is crucial, and because of that we’ve been plugging into our clients’ CRMs [customer relationship management systems].
Now, with financial services marketers, there are regulatory and technical constraints. For instance, for certain mortgage or home-ownership products, you’re not allowed to exclude Zip Codes. But what you can do is use first-party data to do a few things.
The first is remarket to people. So, if we already know something about a current customer and we want to upsell or cross-sell, we can do that and give them specific messaging.
The second is lookalike modeling. So, if we know the attributes of a good customer, we can go out and find more customers out in the world with those attributes.
The third is suppression. If we know someone is already a client and they already have all the products — or they’re not a good fit for other products — let’s not continue to market to them and spend money and invest in them. Let’s suppress them from marketing.
Let’s back up to lookalike modeling and get more specific with that. Let’s say you’re a marketer at a bank that has a specific set of first-party data from 100,000 customers. Perhaps those people form-filled at some point. You can market and remarket to those 100,000 people, but if you need more reach for a particular campaign, you can also find a lot more lookalikes in the wider world.
Doug Durkalski: Yep. Exactly.
Those lookalikes never had direct interactions with the bank — the bank doesn’t have first-party data from those customers — but they have behavioral attributes that match up with the behaviors of the core group of 100,000 customers who actually did share their data with the bank.
Doug Durkalski: Precisely. It’s not just who we, as marketers, think our customer is, it’s actually taking our real customers and saying this is what they look like. Find more of these people. It’s about going deeper than just targeting age, demographics, household income.
And then once you find more of these people, what’s next? Let’s talk about the messaging process.
Doug Durkalski: AI increasingly factors into the messaging. In search advertising, for example, we commonly use dynamic creative or responsive text ads. Google and Bing have automated processes where you can give them a pool of headlines and description lines, and in a real-time basis when someone is searching for something, they can pick and choose which headlines to pair with which description lines based on that user. So, based on the time of day and the device and exactly what that person is querying and the search behavior of that particular person, they’re served a particular message. An ad is made and served in real time.
But again, with finserv marketers, there is the regulatory piece, so we have to go through an arduous compliance process. We’ll work with their compliance department and say, here are the four possible headlines and the eight description lines, and here are the 120 different combinations that might be output for any given user based on the algorithm.
We’ve gotten down in the weeds here — the regulatory weeds that are particular to finserv marketers — but to come full circle, what we’re ultimately talking about is conceptually pretty straightforward. Basically, Rise works with financial services marketers — and, of course, all kinds of different marketers as well — to map out how different audiences are likely to go from prospect to customer, and then you create personalized messaging across different channels to optimize that journey.
Doug Durkalski: Yeah, at Rise we call that mapping process a Connections Plan. Connections planning, at the heart of it, is pairing up the right messaging with the right audience based on where they are in the funnel.
Let’s continue the conversation. To learn more about Quad’s full suite of solutions for financial services marketers, please contact Erin Slater, Head of Strategy – Financial Services.