Enhance and Scale Customer Experience with Data

Michael Krigsman: Today, on The Data Economy, we’re speaking with Beth Johnson, the Chief Experience Officer of Citizens Financial Group. She offers a fascinating glimpse behind the scenes relating technology infrastructure, data, operations, and processes to meeting the business needs that are so important to their customers. Beth, it’s great to see you again. 

Beth Johnson: Hi, thanks for having me. 

Michael Krigsman: Beth, so you’re Chief Experience Officer of this large financial services organization. Tell us about Citizens, and about your role. 

Beth Johnson: Yeah sure, so Citizens is one of the oldest and largest banks in the United States. We service customers across the nation. We’re national, particularly in our commercial businesses, and some innovative places like student-lending. And then where people know us very well as in the Northeast and mid-Atlantic, where we have a 14-state footprint. But we do offer a full range of products and help our clients on their financial journeys. 

Michael Krigsman: And as Chief Experience Officer, what does your role encompass? 

Beth Johnson: Yeah, it’s a new role for Citizens. We launched the organization and my role about two years ago. And it’s really focused on the customer. So how do we build the capabilities that are going to enable us to differentiate with our clients, whether it’s a business, a large business, small business, or a consumer to make sure we can help them on their unique financial journey over time? So that specifically includes things like digital, and our digital design teams, as well as delivery teams, data, and analytics– so important for this conversation– our marketing and communications capabilities, our enterprise payments. And then really wrapped in the how some of our agile transformation efforts to deliver faster for our customers across the organization. 

Michael Krigsman: Beth, customer experience is such a broad field. And we’re going to be talking about data specifically. Just briefly, can you give us an overview of what are the components that comprise customer experience? 

Beth Johnson: To me, customer experience is rooted in a couple of things. First, it’s being able to have a deep understanding of your customers. And that can be through asking them, through surveying them. It can also be through how you observe the way they act in your daily life, or how you test things. You know, we talk about user experience design, and the ability to do A/B testing. But to meet customer experiences is first all about that deep insight and understanding of our customers that we can bring to the front line, that we can bring to product owners, that we can bring throughout the organization to just frankly, better understand our customers. And then second, we also think about it is underpinned with those design capabilities that then deliver excellent experiences. So how do we think about human-centered design, and building journeys, and journey maps that are going to enable our customers to better interact in their lives, and in their partnership with Citizens on their financial future broadly? 

Michael Krigsman: So all of this then depends on really understanding who the customer is, what they care about, what’s important to them? 

Beth Johnson: Yes. And it’s interesting, right? I think the mistake people make is sometimes, we think customers know what they care about, and what’s important to them. But you can’t just ask them. You have to really observe the behavior of our customers, how we interact in order to make sure we understand those needs, that we each feel– and I use the word feel intentionally, as well as rationally think about it, so that Citizens can support them in their lives, and in their banking partnerships that they have. 

Michael Krigsman: And now, we come to really what’s the heart of the matter for this podcast, which is of course, The Data Economy. So what is the role of data in helping you understand the customer, as you’ve just been describing. 

Beth Johnson: Yeah, I think data is just foundational at this point into how we think about customer experience, how we think about digital transformation, how we think about designing our products, our services, our interaction models with our customers. And why that’s so important is, there’s just so much of it. So we can understand data from a standpoint of how our customers transact with us. As a bank, we need to understand data from a standpoint of what are our customers able to do from a financial standpoint around their credit profile, and other things surrounding those customers? We need data to better understand their needs. And so there’s just a myriad of ways we look at data to link to our customers, and to design better solutions for them, whether that’s through digital channels, or physical channels, or in-person interaction models in order to serve our customers better. 

Michael Krigsman: Beth, you used the term digital transformation, which I think is fascinating, because I have thought about customer experience as being the next evolution, if you will, of digital transformation. And so I think it makes sense to talk about the role of data in digital transformation more broadly just to help us understand the context even further. 

Beth Johnson: Yes, we’ve thought about the way customers are behaving, the way our daily lives are unfolding is so different today than it was even three, four, or five years ago. I like to use a stat that I recently heard that today, we each make 35,000 small decisions in our lives every day, whether that’s because we get 64 notifications on our cell phone on average, or because we have more choice than ever before, because we can research things in ways we couldn’t do historically in our lives. What we really believe is that digital transformation, customer experience transformation, and data transformation are all very, very, very closely linked. You can’t have one without the other, so that we can understand fundamentally that sort of human need of our customers, and do it through data, through digital channels, through our physical channels by giving information to people, and empowering them with data to know about their customers. So it’s really, really linked in the way we think about better serving our customers. 

Michael Krigsman: Why are customer experience and digital transformation linked so tightly, as you were just describing? 

Beth Johnson: Yeah, I think it’s because digital has just become a part of how we live. And it’s advancing even faster. So we’re all on our phones on average two hours a day now in our lives. It’s how we research content. When my daughter was applying to school, it’s how you think about researching different schools. It’s the first place you go before you do that in-person visit, which fortunately, we’re able to do again following COVID. It’s just become linked to how we manage our lives, whether it’s doing simple transactions, researching content, trying to get things done quickly, scheduling appointments. We’ve really become enabled in our lives through digital. And I think companies have to be willing to respect that as we create our experiences, and then streamline all our operations around it. We also want everything instantly. So best-in-class providers across our lives, we’re just getting things faster and faster. You have to use data. You have to use digital in order to be able to offer those kind of seamless, quick, frictionless experiences that we all want in our lives today. 

Michael Krigsman: You’re really describing data as the glue that brings all of these pieces together that really underpins how we run our daily lives, everything we do. 

Beth Johnson: I absolutely agree with that statement. I think data is the foundation that you can put on top that’s underneath digital experience, other experiences, analytics, how understanding what’s happening in the environment. But you’ve got to have good data flows. And increasingly, that’s real-time data to be able to pin those things together, and to offer great, great outcomes for us, for our customers, but for all of us in everything we do.

Michael Krigsman: You said this magic word, real-time data. Where does that fit into customer experience? Let’s parse that. 

Beth Johnson: Yeah, I’ll give you a great example. I don’t think everything has to be real time. I think it’s something people talk about a lot, which is, is all your data flowing through your systems real-time? But there are other times where it’s really important. A great example at Citizens, we just launched what we call Peace of Mind. So that’s really to prevent those oopses in those that sort of simple tools managing your life as we talked about. So when I overdraft, you have 24 hours to really move money, and correct that before we give you a fee, or any kind of reason for having to consistently use overdraft. And people do that intentionally. But often, it is that that’s oops. But we need to be able to tell you real time that you did it. So if we’re going to give you 24 hours to be able to correct that mistake, we got a text you, email you, pop up an alert in your mobile phone to say, hey, did you know this just happened? And then when you do it, and you move money, so that you’re not in an overdraft situation, we’re going to pop another message that says, hey, you fixed this. And that’s an example of real-time, right? And it’s really relevant in the moment. And we want to be relevant in the moment when it matters. There are other things that aren’t quite so important where maybe if we get information at the end of the day, and we share it with you, that’s OK. So we’re really selective. And we’re starting to build the pipes, and how we deliver those real-time experiences when they really matter to each and every one of us. 

Michael Krigsman: So you’re making very specific choices about the timing of when you present this data to the user, for example, if there’s a security question that needs to be done very quickly. 

Beth Johnson: Absolutely, absolutely. Fraud is a great example in banking of a real-time need. If you’re in the store, and we think you’re charging the credit card, and we’re not sure it’s you, we wanted to get to you right away, so that we can check, is it you? And then we can allow you to use that card if it is. Or if it’s someone that has your information, we can stop that from going through. So another great example of real-time. 

Michael Krigsman: Does the availability of this real-time data change the way that you think about interacting with the customer, and the design of your products and services? How does that ripple through your thought process? 

Beth Johnson: I would say in a couple of different ways we think about real-time, and we think about data. We do have an in communication stream. So our we use the buzzword personalization, like everybody in different ways, but we use it for communication. So how do we think about piping our data in so that we have real-time communications when it’s highly relevant. So we think about data in that. And then on top of that, we do have what I’ll call more curated experiences. So how do we think about for a segment of customers developing an end-to-end experience? And what components of that are outside of typical product or pricing, but may be the tools you can use, or the advice we can give, or the insights we can pop up to as relevant in the mobile app. And we’ll be very thoughtful about how we map that, and how we think about that journey for our customer, and how data and analytics can help underpin that. 

Michael Krigsman: You mentioned a few times that it’s the emotional experience, and the emotional connection to your customers. How do you harness data to address that emotional connection? That seems like a harder challenge. 

Beth Johnson: Yeah, you know, I think the biggest mistake people make, that we, data and analytics organizations, is making it all about the data, or all about the math, or all about the kind of technical components, versus, tapping into those emotional components, and making it real for people both internally in our culture, so they can understand it better, and that in the capabilities, but also for our customers. And so I was just debating this with the head of our home equity business. And we’re using data and analytics to really streamline end-to-end how you can generate a home equity loan with citizens. And we were number one in the US actually in home equity last quarter. And so what we did was, we mapped that data in very sophisticatedly from everything from targeting those customers, to how we price them, to how we talk to them to better meet their needs, to what we can pre-fill for them in the underwriting processes, to how we can get them their money when they book their loan. But frankly, if I’m a customer, what I care about is, I want to remodel my kitchen faster. And when I’ve decided to do it, the fact that I can be ordering those countertops in seven days instead of 32 days, which is the industry average, is a huge benefit. And so the emotional side is, hey, I’m so happy. I get to do my kitchen faster. But that’s all underpinned in the data and technology. So that’s how I think about that emotional connection versus the kind of technical underpinnings that have to sit underneath it. And there are a lot, by the way, to make that whole stream happen. But it’s really that emotional end state for the customer that matters if we’re going to grow our business and continue to be really relevant to our clients. 

Michael Krigsman: So this links back to something you said right at the outset, which is really developing that deep understanding for what the customer wants. And I just think this is fascinating, because folks in data, we tend to focus on the data and the technical technology aspects, and sometimes, can lose sight of the bigger picture, which is, what are we trying to accomplish at the end of the day? 

Beth Johnson: Yeah, at Citizens our brand promise is made ready. And what that really means is if I’m a corporate client, we’re going to help you throughout your financial journey. And that can be in times of stress. That can be when you’re in times of high growth. That can be throughout your lifecycle. And never more than when COVID first launched did we see that. 

And the data we needed then was to provide information to our RMs to go out to our customers, and pick up the phone and call them, and find out how are they doing. But we also had to use data to think about what do we think is going to happen in that industry. What’s going to happen with that company? How are we best prepared to serve them? So I do think you have to just take it back to the customer. That doesn’t mean, by the way, that you don’t have to have the pipes. The other thing I often say to folks, as I think about our ability to have impact with data and analytics, I kind of tease our modelers sometimes, the data scientists that are building AI models, or that are building advanced analytic models. The model can be the easy part. 

If you can’t actually figure out a way to get the data that’s accurate to feed the model, and then get the outputs of that model into the hands of the system, whether it’s a relationship managers I just discussed, or whether it’s directly into the mobile app, or into the hands of a customer, you don’t actually get any benefit from it. So you’ve got to think about the whole infrastructure and piping to then be able to deliver that outcome for the customer. So I don’t want to not talk about how hard that is, and getting that right is critically important. But you got to stay focused on the end game, which are those use cases that are going to deliver impact for the customer. 

Michael Krigsman: It sounds like you’re operating on two levels. One is being ensuring that the data is consistent and supporting the operations you need to express your brand promise, to be true to your brand promise. And then at the same time, you have the technology layer that involves the models, and the technology infrastructure, and the piping that’s necessary to handle, manage, collect data, collect and analyze all of this data. 

Beth Johnson: Yeah, I think that’s absolutely right. I almost think of it usually on three layers when I think about it. There’s the kind of base technology and scaling capabilities that we need around data. So how do we understand how we’re going to move data real-time? There are a couple of different tools to do it. We’ve just selected a new provider to help us. You know, where are you going to put the data? There are providers like Redshift or Snowflake. 

Michael Krigsman: How do you think about that technology? 

Beth Johnson: How do you scale capabilities is critically important. And then think about data strategists. So before you even get to data scientists, or AI, or ML, who are people that really understand the data sources themselves, both first party, second party, and third party, how we can knit them together that can be that kind of an agile speak that product owner for data to say, we want to pipe things this way. We want to understand it this way. I know when we say deposits, what’s that mean. I have a single source of the truth that I can leverage and give to others as they’re thinking about data. And then you have those true data scientists, and analytics, and AI on top of it to think about how do you build sophisticated modeling capabilities that we can utilize in experiences? I probably should have said four levels. Then on top of that, you have the business users, and the business people like me that are just trying to generate great insight from all three of those layers in the company. 

Michael Krigsman: So to what extent are you tracking and focused on the enabling technologies, and how the enabling technologies change and evolve over time, and maybe offer new capabilities as they evolve? 

Beth Johnson: Yeah, we’re absolutely investing in understanding the technologies. And we’ve been investing in moving our data infrastructures into the cloud, and so we’ve made great progress on that. And we’ll continue to use new technologies, both in managing the data, but also in how we can display the data, and for business intelligence tools as well. Actually, at Citizens, I should mention this. We just hired a new chief data and analytics officer on my team that’s going to join in the second quarter this year to really help pull it all together. And we were very intentional about combining the data role, with the analytics role, and the insights roles, so that we can make sure we’re focused on the technology, the scaling, but very use case and customer-driven in how we’re building and why we’re building that data infrastructure. 

Michael Krigsman: What kinds of data are you using? You’re doing so much with data. Do you think about it as different kinds of data? 

Beth Johnson: Banks have a lot of data. So when you ask about what kind of data we’re using, we’re lucky. We’re probably not even tapping into what we could from a customer insight perspective. But the good thing about being a bank is, we have a lot of data. We invest heavily in the security of that data, and ensuring we’re using it for our clients’ benefits, and check in on are they comfortable with how we use it. But that said, we have first party data, so we understand a lot about our customers financial needs. That can include loans and deposits, so credit information around our customers, as well as spending habits, as well as how you manage your money. And then we can add on secondary data on top of that, so how we think about external data through credit bureaus and others that allow us to better understand our customers. And then I would say on top of that is behavioral data. So when you’re on our website, how are you clicking? What are you looking at? How do you think about if I have a child that’s college age, and I start researching student loans, how to pay for college, which we have quite a bit of, how do I make sure I link that together, so I can have the right conversation with you, irrespective of channel, or give you the right offer to enable you to think about financing with Citizen your student loan. And then even on top of that, I have customer feedback data. So we do quite a bit of work. We use Medallia, but we do quite a bit of work from an NPS, net promoter score perspective, to measure sentiment both at the transactional level, as well as the relationship level. So we can feed that in as well to enable us at all those different levels to really understand our customers. 

Michael Krigsman: So you’ve developed really, a set of taxonomies of different kinds of data. And I’m assuming associated with that is this kind of data can help us accomplish X, Y, Z goal maybe in operations. This kind of data can help us with customer experience. This kind of data is foundational. Does that correspond to what you’re doing at all? 

Beth Johnson: Yes, I think that’s right. And that’s why that data strategist role between technology and deep analytics is so important to help think about those different kinds of data, what we need them for, how we can use them effectively, and how we can plug into those business use cases, whether it’s streamlining an operation as you mentioned, or whether it’s providing analytic insights through AI tools on our mobile app to customers. We really need that data strategist as the glue that can hold all those pieces together from a data perspective as a foundation. 

Michael Krigsman: So from a data perspective, there is both efficiency data, or data that helps you run your operations more efficiently. And then there’s what we might call the innovation data that helps you expand, deepen your relationships with customers, those business relationships. 

Beth Johnson: I don’t think about it quite that way, because it can be the same data that does both. So I think about what’s the right data for the use case, but it’s not necessarily the case data that’s driving innovation. And I think innovation is so critically important. I’m glad you mentioned it in banking. Is different than that data that you can use to streamline operations. 

So for example, understanding your income, if I am in banking, we have regulations. We have rules as we think to sort of debt to income ratios in certain products. I can use the data I have to get a sense of what I believe that to be for a client. That can be really important in innovation and growth, and better meeting the needs of clients. But I also can use it to streamline on the back end and streamline operations. If I already have that data, I don’t need to ask you to provide me a pay stub. I don’t need to ask you to fill in certain forms and send them back to me, whether electronic or in-person. So I can use the same data to drive growth that I use to streamline back-end operations. 

Michael Krigsman: So then in other words, you’ve got a body of data. You know what that data consists of. And then the question becomes, where can we apply that data to various use cases that will be beneficial in one way or another? 

Beth Johnson: Yes. 

Michael Krigsman: How has this availability of data changed the way you think about operating a bank? 

Beth Johnson: I think data enables banks to both better meet the needs of our customers. We have a survey where we actually ask our customers are they comfortable using data for insights. And what’s interesting is, for example, over 85% of our business clients say they’d love for us to use their data to serve them better, and better meet the needs of their business over time. So I think we use it to come up with solutions to enable that. So how do I help you predict your cash flow if you’re a business customer, so that you can make sure you can be more efficient in how you run your business? So we have those kinds of tools and innovation. And that’s so critical in banking. But then we also use it as I said on the other side, to streamline operations to make sure we’re effectively managing our credit books, or we’re managing our operations, and we’re pre-filling data when we have it. So I think banks are pretty lucky with the amount of data they have, and have proven to our customers that we’re using the data in their best interest, and we’re investing in the tools to ensure things like privacy, and just having high data standards, and governance within our organization. 

Michael Krigsman: Beth, let’s change gears a little bit. You’ve discussed such a range of skills that need to be brought to bear from understanding, having empathy for the customer, understanding, and being able to express the brand promise down to deep technical expertise relating to ML models, for example. What’s the composition of your team that enables all of this? 

Beth Johnson: So it is the reason we put the team together the way we did was to just enable the holistic view of supporting our customers. I will say, we think it’s really important on the team to stay close to the use cases, and the businesses, and the customers first, so a deep understanding of what’s going to drive value for citizens on the team. And then we really want to couple that. And that’s why we do– we are responsible for customer experience, and those listening posts on that side, as well as some of the deep data and digital expertise that we have. 

But then we had to build talent at all levels. So I have a woman on my team who is working for me now who runs our personalized communications for the bank. But what she’s really helped me understand is, it’s only as good as that data foundation. So it’s critically important to also have that talent who just knows if I need to know your deposits, and I have seven data fields that all say deposits, which one is relevant for my use case? So it’s really knitting together a whole bunch of skills that are all critically important to have a whole ecosystem around data that allows us to deliver the end use cases that we want. 

Michael Krigsman: Has there been an impact on the internal culture at Citizens around creating this data-centric awareness, and even driving a data-centric kind of culture. 

Beth Johnson: We are at Citizens absolutely on a journey around how to drive a data-centric– and I’ll use digital and data-centric transformation and culture. And so it’s one of the mandates of our chief data and analytics officer that’s coming in is, continuing to drive the thinking that enables our business leaders to understand how to create new value propositions foundationally with business insight, and data and analytics at its foundation, as well as to just up-skill. So we’re up-skilling across the bank on different kinds of data and analytics capabilities at all levels with all needs. And so that cultural transformation is really a critical point of how we’re going to innovate going forward. I think we touched on innovation a little bit, and you did, Michael, earlier. But we need that culture of data and analytics to be an innovative company. And that’s a critical component of the culture we want, and our DNA at Citizens. 

Michael Krigsman: To say that transformation is hard really is a cliche, but it is hard. And so how do you manage the culture change aspects as you are really innovating with data, and changing, and transforming the organization, and the products, and the services that you offer? 

Beth Johnson: So I’ve become a very good friend with our HR department as I’ve been leading these transformation efforts. I have a renewed appreciation for what it takes to drive cultural change in everything from how we communicate internally, to what we celebrate internally, to the training and development. We’re doing badging systems around data and analytics that require our training team to help partner with us on just that the constant way you have to be very thoughtful and explicit and how you want to drive the culture, and how you want to move the organization to be more data and analytics-driven. And I’ve really done that in partnership with our human resources team, and our head of learning and development is, as I said, become one of my close friends and go-to people at Citizens. Because I just think you’ve got to stay at it. It’s a constant drumbeat. And it’s one we’re going to continue to make progress on over years. It’s not a [? month ?] of a project. It’s just a shift in the ability of the company to innovate, and leverage data and analytics to do that. 

Michael Krigsman: So this is really a very important issue for you. 

Beth Johnson: Critically important. As I said, we created my team that enterprise experience organization about a little over two years ago with this mission. And we’re willing to invest in it, and think about what capabilities data and analytics being a critical one do we need to drive citizens to the future, including innovation, but also the ability to just deliver excellent experiences at its foundation for our customers. 

Michael Krigsman: Beth, one of the most difficult questions that many business leaders face is, what kinds of data to collect, how much data to collect, and what are we going to do with this data? So how does your organization address these very common challenges? 

Beth Johnson: As we think about data collection, and what data to collect, we do it two ways. There is some basic foundational data that we ensure that we have, and we moved our data lake. We have a data lake foundation that we’ve moved to the cloud, so we have that kind of holistically there. But then we have moved into certain data marts, where we can start to think about what do we proactively want real-time versus end-of-day, versus potentially either even other time periods. We also have a data intelligence platform. That’s our internal data that’s also moving to the cloud, that then brings in some third party data that we can combine with that first party data. And so that gives us the foundation that we have for data. We then take those top down use case driven approaches. So as we add to that foundation, and as we increase our capability, we want to do it starting with how are we going to deliver something better for our customer? Or how are we going to streamline our operations? Or how are we going to improve our risk practices, and our ability to do portfolio management? We start with that, And we go backwards. So if we need to add to that basic foundation, we do it in a very thoughtful prioritized way. 

Michael Krigsman: Is there somebody on your team who is we could say, the steward of all of this data? In other words, how do you know what data you’ve got? 

Beth Johnson: So I think that’s such a great question. We have a couple of people, but that is where I have a head of our kind of town. We call it our data and analytics town in our agile speak. And they’re really required to understand, or have the people that work for them on their team that understand the piping of all these different data sources, where it is right now for the company, and where we need it to get to. And it’s critical to have the knowledge, the history, the talent in place to do that, and to do it well over time, so that you’re using really quality data as you’re driving these use cases. 

Michael Krigsman: So you really have to have at least somebody, if not a team, who is focused on understanding the inventory of data, and what’s available. 

Beth Johnson: Yes. And you’ve got to keep the talent. Because you’ve got to make sure one, you’re documenting it, so that it’s not completely talent-driven, but it’s much more efficient and effective if you have a group of people who really understand our data assets well. 

Michael Krigsman: Do you make a distinction between investing in data for innovation versus data and processes for efficiency? You mentioned earlier that it’s one corpus of data. But how do you think about the distinction between those different kinds of investments? 

Beth Johnson: So we want to use the foundational data we have for both. So we are very use case-driven and financial business case-driven organization. And so we’ll look at as we prioritize what do we think is going to have the biggest impact. But we have things like an Innovation Fund that can say, hey, we want to do some testing and learning around this that can tap into our data intelligence platform for that innovation, as well as places where we are streamlining operations. I talk about we are transforming our consumer bank to be end-to-end digital, to just make it simple and easy to do those everyday banking experiences through our digital tools. You have to have data to do that. That both drives customer experience benefits, but also quite a bit of efficiency in the organization. So we’re going to leverage our data assets to really go against those critical business priorities that we have, which are a combination of innovation and new, with just that streamlining and getting better at what I’ll call kind of the everyday transactional things we do. 

Michael Krigsman: You mentioned this earlier about the underlying body of data that then can be used in different ways. And so it sounds like you are developing a variety of different use cases. Some of those may relate to innovation. Some may relate specifically I don’t know– to personalization. Some may relate to improving the efficiency of operations, or making it easier for your consumers. So you’re looking at these use cases, then looking at your data, and then deciding how do we use that data to feed and support these various use cases. Is that a correct understanding? 

Beth Johnson: Yes, though, the one nuance I think that I would add to how we think about it is, we also want to have this platform of data capability that can then sort of– we’re not going to build twice, right? So we’re not building use case by use case by use case as we think about our data and analytics capability. We’re going to build in a way that’s going to enable multiple use cases with the same foundational capabilities, if that makes sense. So you have to kind of look at it both directions, be very use case-driven, but also build scale, scalability in your platform, so that you can then get the next use case done much faster and much more efficiently. 

Michael Krigsman: So then it’s not just the data. It’s the technology infrastructure, the entire body of the technology infrastructure, both of which need to be very flexible and very scalable. Because at the end of the day, you don’t know what use case you may need a year from now. 

Beth Johnson: Totally agree. We talk a lot about scalability. And a big piece of that is the technology that underpins all of our data and analytics ecosystem. For example, we have to have channel integration. So I have to be able to pipe that insight into our branch network, and maybe that’s through Salesforce, or into an origination system. 

There are very specific systems that we use in banking for things– like, I used home equity before as an example– the origination system to originate that loan. Or I have to pipe it into our mobile app, so I can provide something directly to the customer. So that piping is then scalable across all the use cases in that channel based on the foundations, not just the data, but the analytics that sits on top of it. 

Michael Krigsman: Very interesting. Beth, as we finish up, what advice do you have for folks on how to use data to drive a better customer experience? 

Beth Johnson: I think the most important thing and the advice I have for people that are on this journey is, making sure you understand all the different components that it takes to really transform your organization into a data and analytics-driven organization, and make sure you’re equally investing in all the roles and the capabilities. I think sometimes, trying to go too much towards technology, sometimes, we tend to go too specific around data, and then it’s not actually helpful in the decisions we’re trying to make. And sometimes, we have leaders that don’t understand how to use the data to really drive innovation, or a better customer experience. So to me, it’s making sure you’re thinking through all the different components, bringing the right people together, doing it holistically, which is the power that unlocks the capability, and the ability to scale and deliver for the customer over time. 

Michael Krigsman: I’m glad that you also wove in some of the kinds of pitfalls, or obstacles that tend to come up quite a bit as well. Beth, where is all this going, the role and the use of data and customer experience? 

Beth Johnson: I don’t think that use of data and customer experience is going anywhere anytime soon. If anything, I think it’s accelerating. I think as we see the pace of change get faster, and faster, and faster, we’re going to continue to have to use data as a foundation of innovation. And it’s going to be critically important that we continue to innovate to meet the needs of our customers. And so I think you’re just going to continue to see us be able to use data and analytics foundations to better deliver new opportunities, new insights, streamline business processes, just make it easier for our customers day in and day out. 

Michael Krigsman: Beth Johnson, Chief Experience Officer of Citizens Financial Group. Thank you so much for taking the time to talk with us. It’s been a fascinating conversation. 

Beth Johnson: Thank you, Michael. Thanks for taking the time and having me.