Lemnisk hosted a Customer Data Platform (CDP) Virtual Summit for the North American region on June 29th, 2022. The CDP Summit’s aim was to make enterprise marketers understand how they could create exceptional customer experiences using CDP-led hyper-personalization and increase their digital engagement and conversions. It comprised insightful fireside chats and a panel discussion with leading industry leaders. This article focuses on the first fireside chat with Adam Bell, Senior Vice President of Digital Marketing, Customers Bank.
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The major takeaways from the insightful chat are as follows:
Fireside Chat with Adam Bell
1. How is data becoming a source of differentiation in the context of customer experience?
From a traditional bank moving into a practice of a much stronger digital play, there’s a seismic shift happening. Everything has become digital-first and that becomes tricky. It’s a problem for everyone across the bank to really get to know the customer.
And our bank was born on a tradition of being high-tech and high-touch. So understanding the customer and traditional customers that used to walk into the bank are no longer walking into the bank. So how do you meet them in the middle and how do you keep that tech-forward yet still have that high-touch mentality and ability is really what creates the problem.
The pandemic put a different strain on people working from home, being at home, and having to go toward a contactless society. And that creates issues where the next phase of that becomes a data thing. It becomes data understanding and data sourcing at the root of being able to service customers better. And that’s I think where the path for data as a differentiator is critical to not just the bank, but any business.
2. How do you really understand the customer data that’s coming in, organize it, and effectively use it to activate customer insights and produce value for that entire funnel?
Most banks are siloed with one division doing one thing with regard to the data that they collect, the data that they look at, and the data that is in all of their dashboards. So the key to all of it is first looking at the data sets, and understanding what’s in a warehouse or to be warehoused. And then, what’s the difference between what’s warehoused and what becomes critical to understanding how to manage that data. There are plenty of steps and the way I always talk about it is when looking at data is two sides of the fence, it’s exploratory versus explanatory.
On the exploratory side, it’s pulling that data, understanding, and getting everything in one place to look at it from a hypothesis standpoint and say, this is what we know of a customer. And to be able to experiment with that data to understand a little bit more about why customers are doing X activity with you.
From there, it’s even more critical, and this is really the data differentiator. It is the presentation layer, the explanatory side. It’s getting to the point of understanding the hypothesis to the insights, but then being able to present that not only internally, but present that back to an audience so that the data is actually used to tell a story and then the story becomes critical to what the customer experience is and to the customer retention of what that data means.
So I always go back to exploratory versus explanatory, and that’s typically how I approach data, play, and understand the background to just pull it all together.
3. Are there any best practices or learning pitfalls that you have with respect to managing customer data?
When we really look at that data in its totality, we can experiment and ultimately find results that might not be the same as what we set out for. Then that becomes a new store and it becomes a new action to take a new relevance.
That might actually change the face of the company and the story that you originally knew about your customer. So the hypothesis side is equally as important as the collection of that data and then ultimately out to telling that story back to the customer and building a customer experience that is much more relevant to the customer, for sales, positioning, and awareness. All those critical factors come into play pretty quickly when those insights start to take shape.
4. Can you give us an end-to-end example of how to understand data, get to the insight and actually produce value?
Customers bank set out in 2020 as the pandemic was increasing. And the government through the SBA program was offering PPP checks and forgiveness to the small business sector to help them get through the worst of times so that they can stay afloat. Our bank made a tremendous commitment. Knowing our customers and knowing that the small business sector was a place that we could help. And for all the right reasons, this bank got involved in the PPP program to help usher along that forgiveness and those checks for protection for that sector.
And it was just an absolutely phenomenal move to keep millions of jobs open across the country. So for all the right reasons, our bank was heavily involved and became one of the top servicers of loans across the country. Well, that’s something that wasn’t an original program. It was something that came along fast that forced a bank to react. And our bank, in particular, had to treat it like we were a FinTech program, which meant that we had to hook up and start to connect to other companies and act like a FinTech and be FinTech forward in a digital space.
Whereas that created a lot of problems for the bank to overcome, it also created a lot of opportunities for us. We were taking in hundreds of thousands of loans and helping people get to the next place and to keep their businesses afloat. And the need for speed and the need for understanding the customer truly became a new story.
Coming back to the exploratory, explanatory side. The exploratory side was pretty much seeing all the stuff that was happening from a data perspective, to understand what customers were active to receive a check, and then it moved quickly into now. As we kept on servicing these through the previous two years here, all of a sudden, you have that other aspect of how you communicate to the customer. How do you understand their story? How do you know what they should be receiving and when they should be receiving it to keep them active?
Then a huge problem is that the data set we started with in 2020 or 2021 doesn’t work anymore. You have companies that couldn’t keep afloat or you had companies that were barely scraping to get by. The dataset changed overnight and it continually changes as the length of this pandemic, and other activities, the economy starts to shrink this small business community.
That’s where we really look at that data and we try to offset it by buying data and overlaying transaction information to try to understand, are these customers even in business anymore? Do they have their lights on? Are they at a place where there’s something else that we could offer them or be active to help them get to the next place so that they can stay afloat or more than afloat and actually thrive through these worst of times?
So that changing data story, I don’t think most people expect data to change. When you get a customer record, you expect they’ll be in business forever. Well, with the small business community, that is not the case anymore. That’s a critical moment for us. We have to continually refine and cleanse our data to make sure that we really understand the customer so we can share the plight of what they’re going through in a much better way that works for them.
And then there are other offers, opportunities, and things that we can do to help them along their journey. And that really for us is that story and where we’re at with the bank. We think we’ve helped out this community quite a bit and there’s still plenty more to go. We’re not going to stop there and rest on our laurels.
5. What kind of datasets did you use here? Was it website behavioral data or the kind of data that you tried to use to enrich custom profiles? Can you just talk us through some of that?
When we started this, it was really about communication. Telling the customer that they have this opportunity available to them and to welcome them as a customer of the bank – that we’re servicing these loans on behalf of the SBA and some of the other originators and lenders that we worked with to help them out.
The starting point was always communication. Did they receive communication from us? Do they understand what they need to do in order to receive payment? And then ultimately that story shifted to a forgiveness story. Could they be forgiven of the loan? Do they qualify? And then what are those steps along the way? All of those things were changing on the fly. The first sample data set really came out of what was happening around a fixed point of that loan activity. And then off of that is really a communication aspect.
Then once you have those stories and you start to understand what they’re going through, what these customers are going through, you start to paint a picture and say, what else can we do? And that means that you have to start looking at all the communication channels and website traffic, website information, and anything you can see about what’s driving that community.
Because what happened in the beginning, was nobody knew about it. What did website traffic look like? Help. Help, help. FAQs, FAQs, FAQs. And most of the companies that were in this business and most of the banks that were dealing with what we were doing, had a tremendous amount of traffic. Well, if the traffic told a story, it means we needed better FAQs or better communication that had information upfront so that they didn’t have to go back to the website to look for more information.
So that’s an ongoing thing that becomes the basis for how you start to look at this as a data play. And then you’d get into a lot more of the specifics about that personalization and understanding what the customer is going through. And that’s where overlaying data and transaction data and other things become very critical because you don’t want to go into an addressable market or make an addressable market that isn’t there.
In the end, you wind up wasting your time by trying to hit customers that might not even be active anymore. It’s about qualifying that data in full. With every type of source, you can actually start to overlay on top of each other to paint an addressable market.
6. Are there any regulatory aspects of using data that you’ve encountered that people need to keep in mind? And how have you worked through all of that?
Let’s start with the word empathy. You can’t say any more than what this bank felt for our customers. And for communities of people that we didn’t even know. And it starts with the traditional banking that we were doing and having really solid relationships with a lot of our customers where they were telling their story of “I don’t think I’m going to make it.”, “I don’t think I can do anything here.” “I heard about this SBA information, but I don’t really know what to do.” It was a lot of hand-holding. It was a lot of people working through talking to customers and reaching out by the thousands. And that’s what really starts that story of really, truly understanding your customer.
And I take that back to when I was in Texas for a crypto conference. A small business owner came up and said, “Hey, I saw Customers Bank at this conference. I had to say hello. I just wanted to let you know that your bank kept us afloat during the pandemic and we’re still here and we’re trying new, different spaces with our business.” That to me was the icing on the cake. That meant that we understood what the customers were going through, helped them along as much as we could, and now here they are, they’re thriving.
With that comes the other side of the house which is “Behind the scenes.” When you’re trying to get to that personalization and you’re trying to get to a form factor where you can reach that customer at any given moment, “When it’s right for them?”. That cliche of Right channel, Right time, Right message becomes tricky and for a bank, it’s more than tricky. Regulation is probably one of the hardest things that I’ve seen as a marketer to understand fully and be able to get personalization to a customer.
The word target is like a nasty word in the sense that you never want to target a customer. That means that data becomes more like a lookalike model of creating segments and audiences that are like those people that you have to start to truly figure out. And to get to that point where you’re doing this in groups and you’re doing this in lookalikes. Then you really have to know and understand, and no one understands that information as tight as you can to help them along and to reach them at that moment.
So regulation obviously is there for a good reason, entirely valid. And we as marketers live by it and then try to get to those audiences in segments that really work that is more anonymized to a background instead of going direct to a person. So it represents a lot of problems. And I’d say going to another topic of a cookie-less future is yet another problem. When GDPR and regulations start to hit in the US like what we saw in Europe, these things start stacking.
It makes a marketer either that much more critical or that much more responsible for the data that’s coming in and out of properties like especially digital channels, web, email, and others. Therefore, responsibility becomes a stronger word here in the next phase of what marketers have to really understand.
7. What you’re saying is that the potential performance loss or the CTRs, etc. that you might lose out on is something that you figure is okay. It’s not as bad as people perceive it to be?
Yes, it feels bad that you can’t get to personalization. But that just means that your data pool and the aggregate of your data have to be that much stronger and that much bigger. And when you start to get into volumes of data and petabytes of data, then your warehouse becomes critical.
Where are you storing all that? What are the tools and services and platforms like yours that become so much more? I use the word critical a lot here, but they are critical to controlling that data and understanding how it all comes together. And then ultimately being able to report back and report on it so that the presentation layer back to the customer is equally strong.
8. How should marketing leaders look at some of the MarTech adoption decisions for the next 12 to 18 months and potentially longer and how is that going to pan out?
When you see cross-border volume and transactions becoming lighter because of what’s happening in the world, small business sectors just keep taking hit after hit and it doesn’t end.
Looking at the economy, inflation, and the macroeconomic view, it is very difficult to foreshadow what’s going to come. Spends have become more complex for anyone to truly understand and work around.
Hence, it still goes back to understanding the customer in full and what they’re going through. This is because we as marketers are going through the same thing. We need to have that empathetic approach to really get to know the customer better so that we can get to a point where we can market or bundle opportunities for them around what they’re already doing, which, in our case, is our bank.
There is no question that you have to look at things differently and this is the time to do it. This is the point where selling has to come secondary to what the need is and the understanding of the customer all the way. It has to be much more about the experience that customers are driven to and where they are in their path. And that means building personas and lookalikes and that understanding really becomes a much bigger approach that has to be done.
So for us, Customers Bank, we put that “Customers” name in our name for a reason. We have experience working with customers as well as an understanding of what they’re going through with a boot-to-the-ground approach.
By Bijoy K.B | Associate Director – Marketing at Lemnisk
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