The Intersection of AI, Trust, and Consumer Experience in Financial Services

Tarun Dadoo: I can bring all this data, put it in a box, and Gen AI will generate and spit out things. But somebody still has to moderate these experiences and the data governance. Otherwise, we will end up scaring away a lot of customers. If you don't have the proper governance in place, I think that is the main thing first you need to do is build that framework before you decide and go outside and start marketing using those data.

Kailey Raymond: Hello and welcome to Good Data, Better Marketing. I'm your host, Kailey Raymond. There's a critical balance between privacy and personalization in the financial services industry. Companies like Discover are navigating a tightrope of strict data governance measures influenced by laws like GDPR, new technologies with the advent of composable technologies like CDPs, emerging consumer behaviors like the demand for hyper personalization, all of which is making it more challenging to create secure yet meaningful customer experiences.

Kailey Raymond: However, those that embrace the change and adapt to these evolving trends and advancements are better able to foster trust and loyalty among consumers. Discovered Tarun Dadoo and I discussed the delicate balance between privacy and personalization. The implementation of composable, CDPs, and the complex interplay between good data and consumer trust. 

Kailey Raymond: Today I'm joined by Tarun Dadoo, VP of Products and Delivery at Discover Financial Services. Tarun is a seasoned investment sales and marketing professional with over a decade of experience in consumer banking across both emerging and mature markets. Prior to joining Discover in 2011 as the Director of Marketing Strategy, Digital Innovation, and Product Development, he served at Citibank for six years in various roles.

Kailey Raymond: Tarun, welcome to the show. Thank you. 

Tarun Dadoo: Thank you. I'm excited. 

Kailey Raymond: I am excited to learn from you today, but I wanted to hear from you first. I know I just gave you a, you know, brief introduction. You've been in financial services, um, in various roles throughout your career, but tell me in your own words about your career journey.

Tarun Dadoo: Yeah. I mean, I grew up in India right out of college. Only thing on my mind was to get my first job and I didn't know where. And the first offer which came through was from Citibank. I joined into their operations team, then eventually moved on to the marketing side. I spent around six, seven years at Citi.

Tarun Dadoo: We did various roles, got completely burned out, decided to come and do my master's in the United States. Landed here, right out of college here, I did my master's, uh, in economics and finance, and then I applied with HSBC and Discover. Discover offered me something in the marketing area. Since then, my journey started with Discover, I mean, it's a fascinating company, a lot of good people, a lot of good work, a lot of innovation, and it gives you a lot of room to grow.

Kailey Raymond: That's great. It's always good to like what you do, so I'm excited to hear from somebody that's passionate about it. Tell me a little bit about how your role intersects with the consumer experience and journey that you're building. Thanks for any of your consumers at Discover. 

Tarun Dadoo: Sure. I am part of the card acquisition marketing team.

Tarun Dadoo: So I head their product side. So all of the customer card acquisition website experience falls under my organization. So we manage all of discover.com, prospect side, new to customer, new to bank, customer experience. So we have, my team is, major goal is to manage the content, website experience, all of the new product development and technology.

Kailey Raymond: That is a big, big role and something that I'm sure that you're kind of very tuned into are a lot of the trends that are impacting your industry today. And something that I wanted to kick off with because it's timely that's happening in your industry around open banking is this new CFPB ruling. It's just announced the final rule around section 1033.

Kailey Raymond: I wanted you to, first of all, for the listeners of the show that might be a, not be as intimately familiar with what that ruling says, what's actually kind of embedded there. First of all, what is that? And then second of all, why is it such a critical update to how financial institutions are really thinking about consumer experiences?

Tarun Dadoo: Yeah, so consumer experiences are evolving very fast. I think it started somewhere in Europe, where the data under the GCPRA got democratized a little bit more than what it is in the U. S.. U. S. is making an attempt to go in that direction. You own your data and it's a consent based permission to the retailers or the consumers of the data.

Tarun Dadoo: So what essentially it says is Open Banking gives us the permission to the lenders or the financial institutions to go look into your financial health through your Open Banking solutions. So which means it lets you log into your various financial services, bank accounts, assets accounts, and different places to make an informed assessment.

Tarun Dadoo: of what we want to offer to you. So this is the 1033 ruling came around the data governance of how you extracting the data when somebody is giving you permission or consent. So it started in a little bit of an unorganized way. But the governance and the ruling just came out, and I think the implementation time is up to 2027.

Tarun Dadoo: It is essentially the battle of between screen scraping and getting the data in a more organized way through a permission base. It is one of the biggest trends, which you're going to see probably in next couple of years, is that space of data open banking is going to open and is going to solve a lot of consumer problems.

Tarun Dadoo: And the example I generally give is we use it as a solution for. Looking into providing a lending to the certain types of customer who might not be eligible just based on your traditional bureau or your tax course. We give them an additional option, how to give them a chance to participate in the financial world.

Tarun Dadoo: But the most exciting example I saw is, I went with my nephew, he was getting out of college, getting to trying to rent an apartment. And the department association said, why don't you just log into your bank account, we'll send you a link, log into your bank account. We want to verify you and see your, you know, financial health and, you know, make sure you have enough to cover your rent and, you know, you're just not declaring something on the application, but we want to ensure you have a job, money's coming on time.

Tarun Dadoo: And he was able to get the apartment in exactly five minutes. He just logged in and connected the account. Now, only thing what scares some people is giving access to your bank account. So when I did first time, I was very hesitant. I said, okay, I'm going on third party website. Somebody is telling me to log into my bank account.

Tarun Dadoo: That's my only place where my money is. What if somebody skims off all of this? So I think that is education, that's what we have to build around it to make people comfortable into the solutions. 

Kailey Raymond: No kidding. Yeah, that's a really scary experience perhaps for the first time is giving some business that you may not be super familiar with or not trust necessarily and logging into your bank account.

Kailey Raymond: I'm wondering also just from a pure like just interest standpoint, they're looking at cash flow trends versus credit history. Is that one of the things that's kind of like, okay.

Tarun Dadoo: Yeah, I mean, so you see the number of people who are migrating into the U. S., plus all the students who are graduating out of the grad school.

Tarun Dadoo: All of them have no credit, but that doesn't essentially mean they are not creditworthy. Only thing is the lenders have a hard time assessing your ability to pay, and the best way to look at it is some of your cash flow. How have you managed your cash flows, whether your incomes are regular, whether your payments are going regularly back?

Tarun Dadoo: All of that, plus there is a lot of information sometimes which are delivered through paper. You go and ask for a mortgage, they ask you hundreds of documents. What they're essentially saying is log into this open banking platform to different places. We'll extract that information and instead of you giving us all those papers, we can all do it online digitally.

Tarun Dadoo: So two things have to happen. People will have to get more digitally savvy, how to use these tools. And secondly. People will have to get more comfortable, which means the onus is on the companies to provide that kind of security. And trust, that it is a trusted place and it is a one time expedience.

Tarun Dadoo: Somebody is not holding your bank account forever and continues to peek into it, uh, for the rest of the future. 

Kailey Raymond: It's super interesting because, you know, really in a lot of ways, what it seems like, you know, this could do is increase consumer choice and therefore perhaps increase competition between financial institutions to make sure that they're doing right by their consumers.

Kailey Raymond: And so it's giving power. to consumers, which, of course, makes sure that you're putting a lot of onus back on financial institutions to be able to drive a lot of trust. And that's where this great customer experience comes back in, is making sure that you are the ones that kind of can provide that really, really interesting trend happening right now.

Kailey Raymond: I wanted to see if there were any other ones. that were on the top of your mind. Anything related to any industry trends, macro trends, you wanted to mention that are impacting customer experiences today? 

Tarun Dadoo: Lots of them. I mean, so other than just the open banking, what we're seeing is, and it's, these all are part of the same ecosystem is personalization.

Tarun Dadoo: Hyper personalization has become kind of table space for most of the companies, whether you're in financial services or you're not in the financial services. AI based, uh, chatbots. Omnichannel has been long pending, you know, it's been discussed, but to deliver that kind of an experience, the tooling which is required is still your CDPs and all of those things are still challenging.

Tarun Dadoo: It's an idea which has been toiled with for so long, but it is still, it has not been able to be completely delivered as it was thought. Loyalty programs. I mean, that's becoming the biggest trend in the market. No matter what industry you belong to. Loyalty. Programs have become, again, a very important factor, how you drive your engagement with your consumers in the future.

Tarun Dadoo: With the millennials, the trends are changing. The brand loyalty is not as sticky as it used to be. Till the time you continue to deliver strong brand loyalty, Loyalty programs, till the time you contribute your best customer experience, they are loyal to the brand. But they don't hesitate to switch. Back in the day, my parents were a different school of thought.

Tarun Dadoo: They were not ready to switch. So there was a big switching cost associated with switching a brand or switching a service. Today, the first experiences have been seamless to switch. And secondly, there is a Less of, you know, attachment to the brand till, till the time the brand is not delivering to it. And I think the last piece is, of course, privacy.

Tarun Dadoo: Privacy is a big concern as well as a trend. Accessibility to your information is the number one requirement from consumers. 

Kailey Raymond: You're right. A lot of these things are completely related together. And ultimately what they're really speaking to is building that trust with your customer. How can you make sure that you're protecting their information?

Kailey Raymond: How can you make sure you're using that information? the right data that is consented to, that you can personalize experiences with, to make sure that you are building loyalists that aren't going to switch over to your competitors. I'm wondering, how does Discover balance those two things that are really difficult to balance together, which are privacy and personalization in a regulated industry?

Tarun Dadoo: Yes. So you exactly said it the right way. I mean, the financial services is one of the most highly regulated industry. We are very constrained by how we can use our data and how much we can use our data. So we are taking a little bit of a precautionary approach when it intersects with the privacy of the customer.

Tarun Dadoo: Data, which we acquired directly from the consumers, we do have all the permissions. and consents in place. So there's a lot of data governance around before we decide to use that data anything. Data which we are acquiring through third parties are the places where we do have a little bit of a very precautionary or cautionary approach, uh, of not using the data till the time the data is not mapped to the last hint or touch point of the data.

Tarun Dadoo: Email is a classic example. You give consent on one website for something what you were trying to do in that moment in Somebody popped a screen in front of you, you say, oh, blah, blah, blah, you know, there is 10 lines written to it. You read the first two lines. If you give me the consent, you're good and I'll send you the promotion.

Tarun Dadoo: You click, but what you ended up clicking is giving consent to 20 other parties or third parties. And then that's when you start seeing your email mailbox start bombarding, as you know, fast forwarders, and I don't think so. We believe in that principle. We wanna make sure the data acquired is through a proper customer consent for the purpose, because the tracing back of the data and the traceability is becoming more and more important, which means.

Tarun Dadoo: We've heard the names like first party, third party. What is a hot trend right now? Ike Delian Financial Services is fourth party. And first time somebody told me fourth party, I said, what do you mean? Like, what is fourth party? 

Kailey Raymond: You're blowing my, I haven't heard it yet. Please tell me what it is. 

Tarun Dadoo: So, so that's what I was saying.

Tarun Dadoo: Okay. I said, there is first party. I understand. First party is what somebody comes to my website. There's third party. I'm connected to the vendors. What is fourth party? They're saying fourth party is the party which is third party has acquired, had a relationship with and acquiring things. So things are going from first, third, to fourth, fifth, and tenth.

Tarun Dadoo: So that's what the data lineage, the companies are expected, or at least financial services, they're expected to map it down to. It is just not acceptable that third party said, okay, I'm good. We are, you're good. We have taken the consent. That's not enough. So I'm very fascinated, again, as the way data is shaping up.

Tarun Dadoo: Data is, again, it is non negotiable for a marketer. If somebody is not using data for making these marketing strategy informed decisions, you're going to be losing money in market today. But at the same time, data is also becoming very challenging. How to organize your data and how to use your data. 

Kailey Raymond: So interesting.

Kailey Raymond: I hadn't heard of fourth party and now my brain is going in a million directions and I'm gonna have to do a lot of research later. So thank you for bringing that to my attention. You mentioned this very briefly related to trends. You said, you know, Gen AI and really what we're talking about with privacy and personalization, I feel like AI kind of just amplifies this and kind of puts it on steroids and really make sure that you're looking at your data governance and your strategies with hopefully a magnifying glass to make sure that you are complying to everything.

Kailey Raymond: AI has been around for a really long time, right? So there's probably some no brainer applications of AI that financial institutions are or should be using, and then there's probably ones that you're a little bit more cautious about, rightfully so, but I wanted That's a g Get your opinion on some of those practical examples of AI being embedded within discoverer's customer experience that are obviously keeping that consumer privacy in mind.

Kailey Raymond: Any, any things that come to mind, those practical examples? 

Tarun Dadoo: Yeah, no, we do. But one, on a little bit lighter note, somebody just recently told me about GNI. You know, they're saying marketers are under so much pressure with Genii, Genii has become that hammer and they're just looking for a nail. So I think the approach should not be that I have this hammer and now I have to find a nail.

Tarun Dadoo: Versus it's other ways I need to find nail first and see if I need this hammer for it. 

Tarun Dadoo: So, participating in GNI is not a compulsion. I think it's a prudent decision wherever it's required. So at Discover, again, with financial services constrained, we have been very, very cautious about where things are and how to use them.

Tarun Dadoo: First use case, which I, we've GNI is mostly in our operations, where, you know, we have customer service interactions. That's where we build a lot of efficiencies so the consumers don't have to wait. They can get self service themselves. They can get answers to what they're looking for without waiting for someone to personally come and explain them and, you know, wait on the call.

Tarun Dadoo: So, so that has been a very successful use case. Coming on the marketing side, I think Gen AI has been able to deliver a lot of value on the cost side. What marketers or the organization are still struggling to use Gen AI on the revenue side. So on the revenue generation side, the moment you get in, which is more on the marketing areas and brand marketing and the use of AI is what we are looking at is how to personalize your creative and content.

Tarun Dadoo: We have not gotten into the offer side of the world because again, What's behind AI is still big data and big data has to be organized and cleaned and governed and has to be brought in one place before we can start giving you a personalized offers. And that puts us at risk of discrimination, UDAP, and all of those risks.

Tarun Dadoo: So we've been extremely cautious. What we have started using as light use cases is how to personalize your experience. So when you come to our website, we try to see, have you visited us before? What have you been trying to look based on your behavior? Some of the indicators we get from various third party data and first party data.

Tarun Dadoo: We try to deliver you a very personalized experience. That is our first attempt. It is something which we are testing in production, but I won't say it has been successfully complete success story and we've been, you know, we've been killing it and nailing it. I think there is a lot of learning here. So we are learning to crawl first before we started walking and running on this one.

Tarun Dadoo: So there is a lot of word of caution and privacy included with the Gen AI, especially in the revenue side of the business. 

Kailey Raymond: Any learnings that you'd be willing to share about some of those initial tests related to personalization on the web or in other places? 

Tarun Dadoo: Most recent example of what I can give you is we are kind of those student leaders in the student card market.

Tarun Dadoo: And what was the biggest revelation as part of this whole GenEye implementation is we figured out that it's 50 percent of the parents are making the decision for the incoming students in college that they decide their card. It's not the student. They are, they don't have financial literacy in place at that time.

Tarun Dadoo: And we uncovered a lot of this through the AI process that there is needs to be a parent section, which is causing earlier, we were trying to deliver a student experience to a parent. And parent questions are very different from a student questions in their head, right? So the content and all of that. We want to jazz it up for students and millennials.

Tarun Dadoo: We were, we were trying to jazz up things, a lot of things, but it looked like it was failing. And I said, okay, that is something we are missing part. So we dug deep into the data and what we figured out is, and by joining some of the third party data, we figured out is it looks like somebody's dad is trying to apply for this card for their behalf.

Tarun Dadoo: It's not actually the students. So that was a game changer that we were able to generate a lot more. ROI by uncovering this kind of use case. But at the end of the day, we didn't make any distinction in offers. That is still our biggest guardrails. That till the time now, we are not 100 percent sure about data, data governance. We will not personalize the offers. 

Kailey Raymond: Interesting. This concept of household, I think, applies to a lot of industries, and I hadn't necessarily really considered, you know, the kind of financial ones, but it makes, obviously, total sense for somebody. My first credit card was under my parents names, too, so that way I can help build credit.

Kailey Raymond: Like, of course, it's, it's an absolute no brainer. And you could have mentioned this, I feel like there's a balance between what we're talking about with it feeling like, you know, me, and this is something that makes sense. Your example of, you know, a dad versus, you know, a kid kind of applying, you might have different creative, different content that you're showing them.

Kailey Raymond: You want to create that highly personalized experience, but there's also the darker side of personalization, which some might say is like a little bit creepy. It's creepy. So, so how do you think about that? Balancing the two and making sure that you're holding that right line between being personal and relevant and not being creepy.

Tarun Dadoo: Uh, I think that's a fair and valid concern today. And again, I am just not a marketed, I'm a consumer myself, right? So when I go to different places and I see. Somebody's showing me something which I just spoke yesterday over the phone. How is it possible that I'm getting a very relevant content around it?

Tarun Dadoo: That's creepy to me. What is less creepy is again, when you try to personalize the data based on customer permission based data, that seems a little less creepy to the consumers. What happens is when you try to combine third party or so called fourth party in your first party world. Marry those two together and try to create a personalized experience.

Tarun Dadoo: So suddenly, let's go back to your household. Household information, we don't have it on the first party side. We, we have to acquire this from a third party. If third party is data is quality is not good. So data is all data is not equal. Some data is equal, some data is not good, some data is bad. When you try to get the data information at the household level, And you start showing things at the household level, people start to get worried that I never asked for any of this.

Tarun Dadoo: And how do people know that I'm ready to travel? Like the most common example used in the industry is the travel. The moment you start traveling or decide to travel, you start searching. You go to various websites. You start going to different vacation places and then you start giving consents. And the moment you give that consent, the data comes back to a third party world and a marketer picks up the data from third party and says, Hey, listen, I know you're ready to go to Mexico.

Tarun Dadoo: Let me show you something, which is it. And then you start thinking, wow, like how do they know I'm going to Mexico? That's not okay. I never said you should know I'm going to Mexico. So I'm saying how you bring your data. That's where I'm just saying that data governance is very important. It is not generative AI.

Tarun Dadoo: I can bring all this data, put it in a box, and Gen AI will generate and spit out things. But somebody still has to moderate these experiences and the data governance. Otherwise, we will end up scaring away a lot of customers. I don't know if the example again, which goes back in the day in 2015, it was a famous big Google example.

Tarun Dadoo: People were labeled based on Gen AI. They're profiling and some of the human beings were labeled as color and races were labeled as animals, not as human beings because they were trying to use generative AI. So it all comes back to, I think the good data governance. These will lead to good marketing outcomes.

Tarun Dadoo: If you don't have the proper governance in place, I think that is the main thing first you need to do is build that framework before you decide and go outside and start marketing using those data. 

Kailey Raymond: Let's double click into that. So, you know, I've heard you use the term guardrails, we've obviously been talking about governance a little bit today.

Kailey Raymond: If you wouldn't mind sharing, like, what are some of those guardrails that you need to be really mindful of regarding your data, in particular, this regulated industry? Are there any rules or principles that Discover abides by? Tell me more. 

Tarun Dadoo: Yeah, so interesting. So data, again, there are so many variables in the data.

Tarun Dadoo: When we try to build some of the Gen AI or AI models, we have to pre-select the variables which can go into the data. And those variables go through a full data governance model. So, you have to submit your variables, then those variables are run through different places to figure out that this is not going to create any kind of discrimination for any segment of power.

Tarun Dadoo: So, for example, if I use a very high effluent data, If I start marketing that data, then it might just exclude people who are not so perfect with credit, not so perfect with their financial situation. So we don't want to create discrimination using the data. Everybody should get an equal chance. So, that's where we, what we do is first before we set up our AI, Gen AI models, we go collect all our data, look at all the variables, then the variables go through their own process of, you know, rigor.

Tarun Dadoo: And end of the day, you end up selecting X number of variables, which we run all the combination. If I run, for example, if I take 20 variables, I run all those 20 variables in different methods to see is the outcome changing or creating any kind of biasness. If there is any kind of biasness coming out of these variables being coming together, which variable is creating that biasness, we have to exclude that variable out of the market.

Tarun Dadoo: And that is the centerpiece of setting up your marketing for good data. If people are not familiarized or they're not familiar with how to use this, I would just caution to read that whole piece together first, understand and build a structure before going on. Otherwise you're going to get penalized. I can tell you right now.

Tarun Dadoo: There is a lot of sensitivity and a lot of zero tolerance. around all these things. 

Kailey Raymond: I'm glad that there's zero tolerance around all these things because there's plenty of industries that aren't regulated that are using data in very creepy ways right now and we all feel it as consumers every day and frankly it doesn't feel good.

Kailey Raymond: You know, you've used this term a couple of times now already, which obviously I am thrilled by, but I wanted to hear a little bit more from you. You've mentioned that there's good data, there's bad data, so I'm wondering how you might define the term good data. And if you want to, how do you actually end up achieving that as a company?

Tarun Dadoo: The way I look at good data is how you've collected the data. So Is the data, which you can build the data lineage on a little bit and track the data down that I've collected this data. When somebody clicked here, this was a click, which was a permission based click, which customer gave, and I collected this data and I know where was the source of the data, versus I go into these journal databases which are collected widely across.

Tarun Dadoo: One good example would be. We have data access to the utilities people use today, right? So I know some of you can go out in the market and buy your data for people who pay their bills with the people's gas or they pay with the comment. But people move around, people have households. When these companies, third party companies, collect the data, they created a journal database.

Tarun Dadoo: They created this journal database for a very general marketing, not a very hyper personalized one. When the hyper personalization is used on a journal database, then it creates a database. A lot of weird experiences and poor experiences which drive people away from the company. So that is one of the places where again we have to see good data and bad data.

Tarun Dadoo: The other part of it is how the data is organized. Even a good data badly organized in your warehouse, in your data hubs, can lead to a bad outcome because it's big data. So you're dealing with big data, it's just not four fields or four lines which you're dealing with. You're dealing with thousands and thousands of variants, which humanly is not possible to scan through the eyes.

Tarun Dadoo: And when the data is not organized properly, and if your models are not built correctly, then the outcomes of those are going to be, and these are in our real life example at Discover. I mean, we have millions of people coming to our website. If we don't have any governance around what we're showing to the customer, then you might end up showing.

Tarun Dadoo: A versus B, which is totally non relevant to you, but also you end up showing something which is offensive to the customer. If I show them what is not relevant to them. If I'm not showing you something relevant and you don't like it, there is a way you can give us a feedback and that's how our feedback loop system works.

Tarun Dadoo: We go back and look into that method and say, did the method go wrong or is the data bad? So there is a whole ecosystem which has to be built and that's where some of these Martech tools also come in. Like, you know, you don't have to have a full flown CDP into your system. I think you need a composable CDP where you take a portion, you run your rule based engines, you make sure everything is hygiene.

Tarun Dadoo: And then once you have reached that hygiene level, then you go out in the market. And start testing. Testing is our biggest principle, at least in current acquisition and Discover. We test, test, test till the time we don't reach our company. We don't go, okay, let's go. Back in the day, the traditional marketing was done on two methods.

Tarun Dadoo: One was your gut feeling, assumptions, and some marketing research data combined together. I'm ready. I mean, I'll drop hundreds of emails. I will drop hundreds of direct mail. Something will stink. Otherwise, I don't care. 

Kailey Raymond: There are so many nuggets in here that I want to follow up on. The first is, I'm wondering, and I think a lot of folks will find this interesting, because I think it's a term that has been on the rise for the past, you know, three or more years, is this concept of a composable CDP.

Kailey Raymond: I'm wondering, especially for an enterprise company like Discover, what are the benefits of, you know, having this CDP? Flexible composable architecture that you're building around your customer data with a composable CDP. What, why is it so important? 

Tarun Dadoo: Uh, it's a great question. So, when I started the journey on CDP exploration, again, it was a very hot and sexy term in the market, so to say, CDP, CDP, everybody was talking about CDPs.

Tarun Dadoo: When I looked at the CDP, the amount of requirement to set up entire CDP for an organization was almost like a giant task. And when, when, when we met most of these CDP players, I said, okay, show me your most successful use cases. And I could hear actually, you know, in reality, a full CDP implemented, there were very few selected because most of them left the journey halfway because the amount of requirements to bring all the omni channel data and every single data point.

Tarun Dadoo: So the requirements were very high. They understood that market is not accepting this kind of situation. We don't have enough resources. It's very expensive. They created this composable CDP. They say we'll give you the bells and whistles of CDP, but you don't have to digest everything in one go. You can take a portion of your use case, use the CDP.

Tarun Dadoo: So that's what we are experimenting right now is a composable CDP. Our challenge is we have data from first party, third party, and privacy and everything other places. Our challenge is to bring all of this data and run a rule based engine. So to bring that rule based engine, a lot of these composable CDP give you up portion of the CDP, which can connect you to the ESPs or it can connect you to your, or mail partners, or you can connect to your Martech tool. So they bring all of this composable part, easy to work, easy to bring your use case versus first organize the entire enterprise data for the CDP to run. So I find it very exciting.

Tarun Dadoo: I think that's what we are experimenting with right now. It will solve a lot of our current challenges. 

Kailey Raymond: It is really this concept that you want to make sure that, of course, you're able to have these really robust, rich customer profiles that you can take action on, absolutely blending together data from a lot of different sources.

Kailey Raymond: And at the same time, being flexible and agile enough to keep up with the industry and leverage best in class tools that, frankly, marketers are going to need to and want to use. You know, you've got to have the best of both worlds here, for sure. I'm going to pivot to some of my last questions, Tarun, which is I'm wondering if you have any companies that you look to that you think are doing it right in terms of building great consumer experiences?

Tarun Dadoo: I learn constantly by looking outside. And we look not just within financial services, we look across the board. So Amazon is a classic example. When I started as a digital marketer in 2015, I saw what the way people interact with websites Amazon was one of the top examples. The user experience, checkout experience, everything.

Tarun Dadoo: Amazon back then till today, they have figured this out, right? I mean, I think they have a great experience. But the best thing some of the fintechs and startups have done, they've taken a consumer small problem. So we deal with the whole ecosystem of financial services. But what some of these fintechs have done is they've taken a small problem of the customer, gone there, spent hyper personalization and user experience in a way, which is fascinating.

Tarun Dadoo: The recent ones are, if you look at go to credit card mounts and two rows of the world, you look at Chime, their experiences are phenomenal, but they're, one, they're risk regulated because they're in the fintech space. Secondly, I think they are hyper focused on one problem. This is where consumer behavior and, you know, some of these trends have to be understood.

Tarun Dadoo: I think consumer behavior or has not been given enough weight as part of the user experience as well as the customer experience. Both UX and CX has to be attached. We have recently hired a behavioral company who builds all the experiences with and they have added tremendous value. of getting the user experience right.

Tarun Dadoo: Because earlier user experience was pretty much I have a hypothesis, I build something, put it in front of the customer through usabilities, and then bring it back in production for testing. Now we have added an additional layer of behavioral science.

Kailey Raymond: Beautiful. I love that you're doing kind of that extra audience work and making sure that you're putting those insights to work. One final question. If you had any recommendations for somebody that's looking to uplevel their consumer experience, what would it be? 

Tarun Dadoo: I think it is not a, I don't think I have a single answer for it.I mean, it's a, it's a combination of things in my view. Again, I think somebody will have to start. It's almost like a customer journey. Thank you. And to get to the right customer experience, you have to start with the customer. And your whole customer journey mapping, you have to start. That's where the data will come.

Tarun Dadoo: That's where your behavioral will come. That's where your mark tech tools will come in. When you're able to combine all these three tools, I think you are able to generate a very strong customer experience, which is sticky and more loyal than versus something which you do it in the moment. You might be able to get the click from the customer, but I'm not sure if the customer is going to come back.

Kailey Raymond: This is great. Tons of insights today. Tarun, thank you so much for being here and sharing tons of information, in particular around privacy, personalization, and the impacts on, you know, this regulated industry that you're in, in financial services. Thanks so much for being here today. 

Tarun Dadoo: Thank you. Thank you for inviting me. And this was very, very well organized and very interactive. Thank you so much.