Experts of Experience - #40 Leveraging Predictive Analytics and AI for Hyper-Personalization

Episode Date: July 24, 2024

On this episode, Benjamin Baer, the Vice President of Product Marketing at FICO, takes us through FICO's journey from disparate technologies to developing a robust AI decision-making platform. He explains how FICO adapts its product strategy to address the rapidly changing tech industry, the intricacies of predictive and prescriptive analytics, and the future of hyper-personalization in customer experiences.Key Takeaways:The evolution of FICO’s technology, the integration of predictive analytics, business rules engines, and optimization technologies to create a seamless solution for businesses.How prescriptive analytics helps businesses make informed decisions based on data, predicting outcomes, and optimizing responses.FICO's role as a B2B2C company, helping clients improve their customer experience using advanced analytics.The importance of building authentic, non-transactional relationships with customers to enhance loyalty and long-term engagement.Understanding the current challenges and opportunities in integrating generative AI into customer-facing solutions while ensuring regulatory compliance.Real-world applications of in-stream analytics for real-time customer engagement in various industries.The vision of a fly-by-wire enterprise, where business operations are optimized and automated through advanced analytics and decisioning technologies.The significance of integrating AI as a feature within broader business solutions, rather than as standalone products.–How can you bring all your disconnected, enterprise data into Salesforce to deliver a 360-degree view of your customer? The answer is Data Cloud. With more than 200 implementations completed globally, the leading Salesforce experts from Professional Services can help you realize value quickly with Data Cloud. To learn more, visit salesforce.com/products/data to learn more. Mission.org is a media studio producing content alongside world-class clients. Learn more at mission.org.

There are a lot of companies that do predictive analytics. There are some companies that do rules and business rules and decision rules, and there are far fewer companies that do optimization. FICO does all three of those. And we don't view those as silos. So at the end of the day, being able to predict something is fine, but if you can't map it to actually the way in which you do business, it doesn't really help anybody.

In a lot of ways, the way that hyper-personalization at least is being used today by a lot of companies out there, it's transactional. And this is something that I think I bristle at a little bit. And I think FICO views the world just a little bit differently. The relationship to be a true relationship has to be more than transactional. It has to be more than me trying to sell you something. And I think that is the future. Hello, everyone, and welcome to Experts of Experience. I'm your host, Lauren Wood. Today, we are speaking with Benjamin Baer, the Vice President of Product Marketing at FICO,

which you are likely familiar with because of their widely used credit scoring system by 90% of US lenders, but there's also so much more. So we're going to get into all of it today. So as I was preparing for this episode, I couldn't help but think technology is advancing rapidly, and especially in your world of mitigating financial fraud and helping some of the world's largest companies to really keep track of customer data, how is FICO adapting their product strategy to really address this rapidly changing tech industry and landscape overall? Yeah. So it's been a really interesting journey.

I started at FICO in 2013 after a career in mostly IT infrastructure, working for companies like Sun Microsystems and SGI and Jumper Networks. And when I joined Figo, it was a struggle to figure out this company had so many disparate technologies, predictive analytics, data ingestion capabilities, business rules engines, optimization technologies, and we'd started investing in application development. And we went through this migration or this evolution from 2013 through the end of last decade to kind of put those products together in some semblance of order and develop really a cloud offering, which is today a platform. We call it the FICO platform and it's an AI decisioning platform. And so we have this methodology for ingesting data, predicting the likelihood of somebody doing something,

of something happening next, building business rules to respond to those predictions, optimizing the outcome. And at the end of the day, we kind of call that prescriptive analytics. So descriptive analytics talks about what happened, predictive analytics talks about what that's likely to mean in the future. And prescriptive analytics for our customers are, tell me what to do about what the data is telling me. And then also build around that an agile application development framework to allow companies to quickly build applications to deliver that prescription, if you will, to deliver that outcome of those decisions seamlessly to wherever the customer is. So tell us a little bit, just to give our audience a really clear understanding, because like I had said in the intro, a lot of people know FICO

because of your credit score system, but really you're a B2B company. And I'd love to understand a little bit of who are your customers and what are some of the problems that they're really looking to solve with your solutions? So we have technologies that address almost every industry that you can imagine. We have customers in every space, supply chain, government, healthcare, et cetera. But our real sweet spot, I think, is financial services and insurance. And if you think about the decision-making process there, it's extraordinarily complicated. And to think about a loan, a credit application, as an example, a financial institution could get hundreds or thousands of these applications every day. And if they were reliant on a human being to approve the application process, you can imagine very few people would get credit.

So we've been helping companies like that build business process, document their business process in what we call rules. And rules very simply are if-then statements. So it's like software programming. You determine if a FICO score is this high, then move it to the next stage. If they own their own home, move it to the next stage. And there's a whole series of very complex business rules that follow things like credit cards or underwriting an insurance application or doing a claim or detecting and treating fraud. So there's a whole bunch of use cases within financial services and insurance that we can apply these technologies to. They have a whole bunch of additional benefits, such as you can ensure consistency in the way that you treat those applications or treat customers for fraud. But in addition to that, it allows these companies

to remain regulatory compliant. So the other industry characteristic that we address is the fact that all of these industries tend to have a lot of regulatory oversight, a lot of compliance issues, a lot of ongoing and changing regulatory issues and laws. And this allows them not only to maintain their compliance with these laws in the rules, but also print out audit reports so they can prove and they accept a loan or deny a loan why they did it and to make sure that they are applying that process consistently and within the law. I've always wondered how when I apply for a credit card, automagically, it will say

you're approved. And I'm like, how did you go through all that data so quickly to know that, yes, I can. I check all these boxes and I can have that credit card. And so it sounds like you're the magic behind the screen. So this technology really applies in a myriad of ways. And again, as I said, we have customers in the widest array of industries. But even in the credit card or banking space, most people don't realize almost every single credit card fraud or transaction is detected for fraud. Basically, it's the opposite of a prediction. You look for anomalies. You look for things that people aren't likely to do, but then are automatically treated through a solution that we call FICO Falcon.

And it's used, I think it's two thirds or three quarters of the global credit card transactions every day run through this solution that not only detects what's potentially fraud, but then determines how to treat it. And whether it's frozen and somebody from the call center calls you, or you get a text message on your phone that says, did you do this? That's all FICO technology throughout that process. Wow. And so I know that FICO has been, I would assume at least, using AI and machine learning technology to process these massive, massive amounts of data. But this technology is also changing very quickly now. I'd love to hear your thoughts on what is really being opened up for FICO in terms of what's possible now that AI and machine learning technology is advancing at the rate that it

is. So according to our CAO, he has a very distinct opinion on this subject. And at the end of the day, if you think about neural networks and you think about the black box that happens in the back end in terms of predictive analytics, AI has been in use for 15, 20 years now. Part of the challenge in AI has always been explaining why did it do what it did? And that's where you end up with a lot of issues, particularly when you're trying to prove regulatory compliance and audit. So in today's world of generative AI, we're still looking at ways to use generative AI safely within the solution. And we're looking at things like chatbots and other ways to help on the authoring side

figure out how to implement that. But in terms of the customer facing or consumer facing end, we're a little more reticent because of some of the outstanding issues there. With that said, though, these technologies increasingly are helping companies automate all of their decisions, automate all of the ways in which they deal with the consumer. And in some ways, we call ourselves instead of a B2B, but we do sell the business. We're a B2B2C company. All of our customers, our clients are dealing with a customer challenge and a customer experience challenge.

And in a lot of ways, we can help them not only build models and build solutions that treat the customer consistently, but also deepen and enrich the entire B2C relationship. And I think that's really fascinating. That was actually my next question. It's a perfect segue into how is FICO really supporting their B2B customers in improving the customer experience of their customers? If you could give us some examples or tell us a little bit more about that, I'd love to hear. Sure. And we've been using the term, and a lot of people have been using the term hyper-personalization. And I think it's a little bit overused in that it's more of a characteristic of what we are going to come

to expect in a broader context in the future. But I think that hyper-personalization is just the beginning. You're thinking about how can I create a segment of one? And so for people who are in marketing or people who are in advertising understand segmentation, men, women want to be treated differently. That's at the highest level. And then you can get into working class or professional people or people who love to watch NASCAR or people who are attorneys. There are so many different ways to segment the population. Now, in its most fundamental, there's this idea of a one-to-one segmentation. And that is that I'm going to understand you, the individual, and I'm going to treat you as an individual. And in a lot

of ways, the way that hyper-personalization at least is being used today by a lot of companies out there, it's transactional. And this is something that I think I bristle at a little bit. And I think FICO views the world just a little bit differently. The relationship to be a true relationship has to be more than transactional. It has to be more than me trying to sell you something. And I think that is the future. If you want to truly transcend and differentiate what you do as a business, prove to me that you know and understand and want to build a relationship with me that isn't simply built on me buying something from you. The transactional relationship is an easy one, but it's one that isn't very sticky and isn't very lasting.

And I think that's the direction we're going here, is how can I build a system? And you can think about the way that generative AI is used today. How can I build a system that seemingly knows me, understands me, communicates with me on an unbiased and non-transactional level so that when I'm ready to buy something, I'm ready to engage with you, it feels more natural and it feels more truly relationship-building. I love where you took that because it's something we talk about a lot on this show is how can you actually create authentic personalization? And it is something that the consumer wants and craves and expects today. I was speaking to a guest on the show last weekend

from a company called Movable Inc. who helped Spotify to create the Spotify year in review, right? The Spotify wrapped, right? Hyper-personalized communication. And I think that I actually, I think about the Spotify wrapped a lot because a lot of companies have taken bits of that. Like, here's how you've used our platform. Here's what the value that you found. I think we can take that another level and really showing them like, Hey, here's value we know that or here's something we know you will find value in. How can we help you to really leverage something that we have that maybe you didn't know about or something that we know you probably are having an issue with? And we're just going to proactively jump in and support you. I think that's where technology is going.

And that is where the consumer's expectations are today. The companies like Spotify are absolutely raising the bar there. But then think of this from a financial services perspective. We don't deal with our banks. As a matter of fact, millennials and post-millennials don't want to deal with their banks. To them, it is entirely transactional. I have my money in a savings account. I go to an ATM. I get it when I need it. Or now I have a credit card on my phone. I don't never have to deal with my bank.

And so for a company like Spotify, I think it's very easy. And I've opted into Spotify and I get value from it on a day-to-day basis. But what do you do if you're a much more traditional mainstream organization like a financial services firm or an insurance company, I mean, people don't want to deal with them. And so how do you build a relationship, an ongoing relationship such that you can not only enrich the consumer, but also create a relationship that's sticky and can be maintained over the course of a lifetime. It's a big problem. It is. And I actually have a different opinion that I do want to have a relationship with my bank. I just hate relating to them because it's a difficult experience. And there's so much information that my bank has that

I actually want to know about. So I use a tool called Copilot to process all of my transactions so that I can track my day. Like I can track and see where's my spending been, what have I been spending on? How can I adjust my spending to fit my goals better? There's companies like Mint or I think there's another one called You Need a Budget. There's a lot of these companies that are using bank data to help consumers actually see the information they want. And I've always wondered, why are banks not helping us do this? Because it just seems like such low-hanging fruit. So it's really interesting. I can't remember the name of the credit card, but there's a system, maybe you know what it is. There's a credit card that you can sign up for your kids,

and you can manage their chores and manage their allowance. And then they can use the credit card themselves. I can't remember what it's called, but it's brilliant. And as soon as I saw that, I was like, how come Visa didn't figure this out 10 years ago? This is so easy, low hanging fruit. The fact of the matter is there are two tiers of financial institutions and you relate some of these spending apps that use your banking data to help you understand where and how you're spending your money. These are new, agile, the word that's used is fintechs. They can be a lot more agile, and they can be a lot more automated and use a lot more intelligence in the backend than the large large established, overly burdened financial institutions

that we normally think about. And I think that a lot of those traditional banks, they're the ones that are threatened now by these fintechs coming in and creating a fluidity and a liquidity in the way that people can move across financial institutions. I come from a world where the idea of moving all of my credit cards or moving my savings accounts or moving my checking accounts or moving my home mortgage from one bank to the other is so painful and so challenging that the idea that I would go to a fintech is like a no brainer. It will never happen. Whereas if you're younger and into a lot more agility and financial kind of fluidity,

it's very easy to change your banks. And it's very easy to do that. But in a lot of ways, the apps that you just described are all about disaggregating your bank from your financial data, right? It allows you to, regardless of where your spending is happening, to see it in a central location that it's independent of those banks. So Benjamin, I wanted to circle back to the concept of personalization, because when I think about personalization, I also think about privacy. And there's this fine balance between us wanting companies to be able to speak to our specific unique needs. And also, it's a little bit creepy if we know that someone else has all of our information and data. And I'm curious to know how FICO is really approaching that, especially, I mean, I hear so much about increases in financial fraud and things like this happening as technology advances. And so, yeah, give us the spiel. What's happening in the realm of privacy here?

Well, so I'm not a privacy expert, but I can tell you from FICO's perspective, we take it very, very seriously and we have the highest standards. And obviously, any issue with our privacy and data security would reflect very negatively on our customers. So we look to that at the highest levels in the organization. But I think it's also very important to point out that FICO is not a data broker. We don't own any data. We don't maintain any data outside of our own corporate data. We help our customers securely access the best data and the most predictive data. But most of it is on their own premises and under their own lock and key and adherent to their own privacy and security guidelines, regulations, and oversight.

This is also one of the things that I think we like to make clear, even with regards to FICO score. The FICO score is an analytic that is run against other people's data. It is not, we don't own the data, control the data, or see the data itself. But at the end of the day, we look to the financial institutions themselves. We look to the data brokers themselves to have the highest levels of data security, data privacy, and follow the letter of the law. We take that all very seriously. But to some extent, we're beholden to them to follow the best practice.

Makes complete sense. And I can imagine that a lot of these banks have, I mean, they're the ones who are really responsible for how that data gets used at the end of the day. Yes. And by the way, just as an aside, and again, as I pointed out in my intro, I'm not a specialist or an expert in the FICO score. But in a lot of ways, I relate in a general level to the story that if you think about when the company was founded in the late 50s by a couple of mathematician, PhD mathematicians from Stanford, Earl Isaac and Bill Fair, they went to find the data. And the place they were drawn to was financial institutions and banks who had gathered

a lot of data on their individual customers. Obviously, in normal business practice, banks would collect a lot of that data. So it was very natural for them. But if you think about part of the challenge that all financial institutions have in making loans, in making credit decisions, is they don't see what the other banks do. So if you go to Bank A and you get a loan and you use your house as collateral, how is Bank B going to know that? You could go to Bank B and say, hey, I want to use my house as collateral for another loan. And that's kind of the genesis of the FICO score, the opportunity to anonymize that data and create kind of an understanding or a level set of risk for each of us. And what we represent in terms of risk in each of those banks' portfolios is really at the genesis of the credit score.

And if nothing else, it made credit much easier to get and much more accessible to more people. When you're using Salesforce to tackle your company's most important goals, failure is simply not an option. That's why their most highly skilled advisors, Salesforce CTOs, are available to help you succeed with expert guidance and implementation support at every step of the way. Learn more about Salesforce CTOs at sfdc.co slash professional services. And I really appreciate that. Personally, I'm like, if I am ever feeling like I want to go and check on my score, if I'm thinking about a mortgage or whatever, there's been moments in my life I've always really appreciated how simple FICO has made it for me to access that

information. And speaking of simplicity, since you are a product marketer, I'm sure that is something that you think about often in terms of how can you make sure that your customers are able to understand what it is that you're doing and have a frictionless, perhaps, experience. How do you approach that at FICO in making sure that your B2B clients and perhaps even your customers' customers are able to really see and understand all that FICO has to offer? It's a little bit easier on the B2B side, only insofar as the businesses usually identify the fact that they have a problem. They have a challenge. We call them problem statements or use cases. And it's one of the reasons that we're so heavily focused on credit lifecycle because it just represents a huge pain

point as well as in insurance and underwriting and in claims. Those are kind of the sweet spot. And as I mentioned to you at the beginning, the methodology that we deploy is, I think, very differentiated from a competitive perspective. There are a lot of companies that do predictive analytics and just predictive analytics kind of software and solutions. And there are far fewer companies that do optimization. I think there are only three companies in the world that have an optimization solver. So the mathematics that go into figuring out how to optimize process or optimize a schedule or optimize delivery or whatever. So at the end of the day, I think there are really only one or two companies, one of which is FICO, that does all three of those. And we don't view those as silos. So at the end of the day, being able to predict something is fine. But if you can't map it to actually the way in which you do business, it doesn't really

help anybody. It's like saying, okay, you sold X number of widgets in Japan last year. Okay, what does that mean? What is that? How is it going to help me in business process? And then to be able to map the business process. So if somebody does something and you can determine there are five things that I can do because of that, how do I optimize the best response? So one of the examples I often use is somebody buys a big screen TV. All right. I can use the

data as a retailer to say, if somebody buys a big screen TV, All right. I can use the data as a retailer to say, if somebody buys a big screen TV, they're likely in the next three months to buy a surround sound system. Okay. There's my prediction. Doesn't really help me in real time. But if in real time, I can say, he just bought a big screen TV. He's a really good customer of ours. We have all bunch of Sony and Vizio and other Samsung high-end surround sound systems in inventory. And I know that Sony is going to replace theirs in the next three months. So we need to move the inventory. Wouldn't it be great if I was to make an offer of a surround sound system to that customer in real time at the retail kiosk. And then knowing that they're a best customer, knowing that they like to spend a lot of money, knowing that they're a really high-end audiophile,

I can optimize which one I make an offer of and optimize what the discount's going to be. And so that's the prescription. And then I build an application that connects to my retail kiosk so that I can deliver that in real time to the customer when they're buying the big screen TV. And that's kind of the way that we view what we've built in FICO platform. Injust the data, make a prediction, determine the best action, and then deliver that action consistently wherever the customer is. So you're advising which actions to take. Like in this example, you would say, at the point of sale suggests that they

purchase this. Yes. It's the same with a credit application, right? Or detecting fraud in a credit card. I don't want to tell a financial institution, hey, it's likely that credit card transaction was fraudulent. No, I want to treat that all the way through, get verification, freeze the transaction, cancel the credit card, whatever it is, depending on where the transaction happened, how big it was, how important the customer is. So all of that's articulated all the way to the end. And in a credit application, 80% of the approvals or the denials can happen in business process.

The other 20% will be reviewed by a case manager, go through a workflow, get approved by the boss, whatever. And so I can mitigate that. I can speed the time to action. It sounds like there's so many different use cases for your product. It really runs the gamut in terms of where it can be applied and how businesses can use it. How do you help your customers really understand the potential of this platform? Yes. So the potential is a different and even more interesting thing. There's so much you can do, particularly when companies start articulating their decision logic

or their business rules. You can start doing things like digital tweeting. I can take a sandbox snapshot of my business rules and say, what if I change my risk tolerances? What if I use a different set of data? What if we change our rules to streamline the process and then run those in a sandbox? So you can simulate what would happen. Once you start simulating and you add more rules around your business process, you can start doing some really interesting things around managing business outcomes. And so we're looking, at the end of the day, if you were talking about the hyper-personalization vision, how do we make this happen? We believe at some point in the future, not today, but we're building towards it,

there's this concept that's been called fly-by-wire enterprise. And I didn't make that up. It came from a series of HBR articles in the 90s. It's just taken that long, I think, and it's still going to take a while to get there. But the idea is, are you familiar with the idea of fly-by-wire? Okay. So fly-by-wire was originally done in airplanes. And back in the 70s and 80s, prior to the 70s and 80s, airplanes were manual controls, like most automobiles, right? If you pulled back on the yoke, you were pulling back on a wire that was connected to the ailerons and you were physically moving the ailerons.

And the aviation industry figured, you know, it doesn't make any sense to build an airplane that way. We can add sensors to the steering yoke. And the sensors detect when you're pulling back on it. And it runs an electric, you know, electric wire. And it sends an electric current to a motor in the wings that makes the ailerons move. And so the idea of fly-by-wire is that you're literally flying by electrical current. You're no longer flying by physically moving components in the plane. And some companies, I think Tesla just announced that they've

really putting a fly-by-wire idea into a car now. And so, they're in newest cars. When you turn the steering wheel, you're not physically turning the wheels of the car. You're turning the switches and sending electrical currents to turn the wheels of the car, you're turning the switches and sending electrical currents to turn the wheels of the car. And so the idea here is that if you can get to a point where you can simulate and model the way in which you run your business, I should be able to create a fly by wire enterprise, meaning here's how I want to treat my customers. And there's a knob for that. Here's the kind of risk that we have tolerance for. Here are all the things, the knobs and switches for running my company. I should be able to set those and then press a button. And that's the way the company is

run. And so we're still a long ways from that. But the idea or concept, when you think about hyper-personalization, that only works because I've set up a series of rules and set up a series of predictive analytics around the data you're creating in your life. And I can react and respond to that. There's no reason that an entire business can't be operated that way. And so when you're working with your clients, you're simulating saying, okay, here's what you're telling me. Here's what it could look like. And then you kind of play in a sandbox until you get it to the place that they want to be in, then you roll it out. So FICO platform has that capability in it. It's an inherent part of the system. It's something that we've spent a lot of time and energy and innovation to build up. It's got a lot of funny

names, what-if scenario analysis, A-B testing, but it's not A-B testing in the traditional advertising sense. You can run it against existing customer data and run two marketing campaigns against each other and see which one outperforms. That's traditional A-B testing. But this idea is I've gathered all the data on how customers reacted and responded. I can then run the A-B test in a sandbox to determine which generates the best outcome for my business. And you can set the parameters for the outcome.

Is it share of wallet? Is it customer loyalty? Is it revenue or margin growth? Whatever those parameters are. And I can set it and test it on test data, real-world data that's already been run and already been captured before I implement it. So it's actually a version of real-world AD testing that happens in a sandbox. That's amazing. So in the case of the TV and the surround sound system, you could say, what happens if we were to suggest the surround sound system at this point or at this

point? Yep. Or if I had changed from instead of offering Abysio, I'd offer Sonnen. Would I get better uptake? Or if I'd offered my best customers a 40% discount on the bundle at the time of acquisition or 10%, it wouldn't have made any difference, but I would have lost money in the deal. There's all sorts of ways to view that. And yeah, the idea here is that I'd be able to Because when we ask customers, which one would you like better? Like, it's not always true, right? And so I am always a proponent of asking your customers for feedback. But then we also know that customers don't always know what they want, right? It's an inherent problem of product management. So I used to do product management years and years ago, and I was in the computer industry. So I'm going to use a laptop as an example, right?

Or a server as an example. But it was that question of, did you want two Ethernet ports or four Ethernet ports? Did you want redundant cabling? Is $2,000 too expensive or can you spend more? And at the end of the day, you knew what the answer was going to be. I want all four Ethernet ports. I want redundant cabling and I want to spend $500. At the end of the day, you got to do that trade-off. Customers and people who buy stuff aren't often very forthwith in terms of understanding those trade-offs.

And it's always a challenge. So being able to do that based on what the data is telling you rather than what the consumer is telling you, I think it's very empowering and much more useful and valuable. That's great. Oh my God, I want to play in the sandbox.

It sounds so much fun. What kind of insights do you get from your customers? What are you hearing from them in terms of what they need, what they're thinking about? And then how are you responding to those customer needs? So we talk to customers very, very regularly. I talk to them a little less as a marketer.

We spend a lot more time doing things like success stories. What metrics did you achieve? But I know our product management team is talking to customers every day. And as a matter of fact, when I talk about the FICO platform and the idea that we've built a platform, built this agile application development framework around it is entirely based on customer feedback. So I can relate to you back in 2013, 2014. We have a product. It's a standalone non-platform product called Blaze Advisor. It's a standalone business rules engine. So people who just want to do business rules. And we started to talk to customers, particularly in Asia, and discovered that they were bundling, our reseller partners were bundling Blaze Advisor with

third-party agile application development tools from companies like OutSystems and Mendix and Pega. These are companies who create this really cool framework for orchestrating an application rather than software programming the application. And we looked at that and said, why are they doing that? They're doing that because they want the rules and then they want to apply those rules consistently in an application. And that application could be a mobile app, could be a web app, could be an app for retail kiosks, could be at a call center, but they want to implement the rules consistently everywhere. And it was that kind of feedback that led us specifically to integrate agile application development frameworks within the FICO platform, just as an example of where and how we really evolved these products to represent customer voice. Generative AI is another one. We haven't formally announced anything yet, but we're looking to figure out how to integrate chatbots into things like documentation, make it easier for people to find the answers, to develop these apps, to troubleshoot rules, to develop these applications in a much speedier fashion and a much higher quality

fashion. So that's low-hanging fruit. Yeah, completely. I mean, the world of chatbots and how they can help you, as long as they're good. As long as you can explain why they did what they did. Completely. Well, it sounds like you've been really innovating in this space and taking many different customer needs and pulling them into one holistic platform, which I'm always a fan of because who wants to use a million different tools to get one answer? It's always better if it's all connected. I think that openness is a core component here because we know we're not going to be the best at everything. We can be really, really good or the best in some things.

But in the same way as we're not a data vendor, right, we need to maintain openness and connect to any data set anywhere, anytime, in batch or real time, structured or unstructured. We want our customers to have access to the tools they feel most comfortable with in this kind of paradigm. We feel that that's a really core component to any platform. We think we can truly innovate in a lot of different areas, such as things like the FICO score or things like our rules engine or optimization. But at the end of the day, they're going to have their own view on BI tools or data visualization or ETL or et cetera.

So that's a core feature. Yeah. It's that customization too. You want to enable people to customize while also providing them with all the answers if they want to get them from you. You mentioned in customer experience, another area that FICO plays in, but we recognize that we're not the most advanced or necessarily the industry leader, and that's the customer experience itself. So how do I design a UI? How do I design a mobile app? How do I design

or integrate best practice in terms of CSS or HTML? There are so many companies really at the cutting edge there in terms of the way in which you communicate. So we want to develop the best prescriptive analytic. We want to create the most consistent user experience. But the way in which customers engage with those apps or engage on the platform, we leave that to other companies to kind of innovate. That's great. I'd love to shift gears for a moment just towards your team and know if there's any tools or tactics that you really rely on to help your team to consistently innovate for your customers. I can relate to you one tool, and I'm sure that Microsoft would be really happy for me bringing this up, but I've become, and I admittedly was not three or four years ago, but going through COVID, I've become a huge fan of Teams.

Used a lot of Zoom and the rest, and I still love those tools. But I found that Teams as a really good integration point, much like Slack, I don't want to take away from Slack, but being able to provide a single place to not only collaborate, collaborate on documentation, but also collaborate in terms of instant messaging, texting, video conferencing, all of those tools all in one place. Just being able to do that from anywhere at any time, being able to connect with people, particularly as we're increasingly virtual. We've never gone back after COVID. I don't think we ever will. So having tools that integrate all of that into one place are really critical for

a marketeer to have access to and use. Awesome. Going back to that full integration, having one place where you can do everything that you need to. And of course, I'm sure if you had wanted to use a different tool for documents or something, you could, but just the fact that it's an option is something that I think is ever more appreciated as we become so bombarded with so many different tools. I know for myself, when I'm working with any of my clients, I'm like, how do we find the all-in-one solution? And we can adjust later if needed, but it's nice to just have like one ecosystem that we work in. I don't work for Microsoft. I don't have any stake in the

game, but I've also found that certain products like Teams allow you to do things like integrate different file storage repositories, integrate other instant messaging capabilities, integrate from different websites. It's just that flexibility. But to have it all in one place, I think really helps. There are just increasingly so many tools that you can turn to, and it's a little bit overwhelming. It is crazy. I mean, just in the last couple of years with AI, the number of new companies and tools that I've been exposed to is like, it is truly overwhelming. And as excited as I am about all of the innovation, I think we're very much in a place where we're going to go through this boom of a million different options. And then I expect the dust will probably settle and there'll be some clear players that kind of win. Yeah. Again, not to go off on a tangent, but I think what's most interesting is the Apple announcement from two weeks ago. And again, I'm not on any stake in the game. I don't want to become a show for Apple, although I am using their products. I think what they announced with, what did they call it? The Apple intelligence, something like that.

Something like that. Instead of artificial intelligence. They've shown, and at least in terms of the coverage, AI, generative AI is a feature. It's not a product. And I think that was the aha moment. I mean, we'll have to see how it rolls out with their products. But if we were to take a step back and think generative AI and AI capability is a feature of an operating system or a feature of a larger product rather than a product itself, it changes the way in which you think about a lot of these products that we've seen roll out, right? And I think Adobe also did this in a good way. Their Adobe

Creative Suite integrated AI as a feature in their product, rather than just say, hey, we have an AI platform, or we have an AI widget, or something like that. But I think that that's the direction we're going. I think you're absolutely right to think that a lot of these products don't have a long shelf life. They're going to prove themselves and then become a fundamental part of something bigger. I know I speak to a lot of CEOs who are like, okay, we need to get on the AI train. What does that look like? What tools do we need to be using? And the first thing I say is go to the vendors that you're already working with and see what AI solutions they've come up with. Because a lot of these big players like Salesforce,

for example, have really invested in AI and you don't necessarily need to change your CRM to get AI. And also we don't need to necessarily check an AI box. It's more of a, like you said, it's a mindset of how is AI now helping us to do things that we've been doing. And I'm not to say I'm really excited about some of the new AI platforms that are coming out, but it's not really like AI or not AI, like everything's going to be AI. It's just a matter of which AI is solving your specific problem. I do think that there's a huge, huge potential in the realm of CRM and how we can be more

easily creating those personalized experiences, both for our organizations and for our customers. Oh, what's interesting is, as I've described, and you've heard me describe this B2B2C relationship and hyper-personalization and kind of the way in which we view that one-to-one segmentation happening at some point in the future, mission critical for all of these organizations. Our CEO loves to talk about FICO platform as next-gen CRM. And I hesitate because we're not a CRM. But his thinking is CRM is a repository of a tremendous amount of very valuable data. And that data can be, as you said, embraced and extended or super powered or supercharged using FICO platform. So we view CRM as kind of the linchpin or the foot in the door, if you will, to a lot of these technologies just being super

advanced. So how can we extend what companies are already doing with CRM to give them even more fine grain control or even more personal one-to-one relationships and predict next best action or predict what consumers are going to want or need going forward. So it's a really interesting space that we're always looking to learn a little more about. Do you have any customers who are using their FICO data with their CRM? So all of them. All of them have CRM systems and all are leveraging CRM in some way, shape, or form. Some are more advanced than others. So we have some companies, we have an offering that's an in-stream analytics solution that's

bolted onto FICO platform. And so we have some customers that are doing true sense and respond. So they're actually in-stream detecting when customers are in the retail environment or walk into a bank or engage with their ATM and generating real-time offers based on the analytics in real-time based on that sense of respond. And those are all CRM data-driven. So they ingest or have the repository of CRM data, detect the customers using the ATM, or we just walked into the retail bank and make some predictions in real time about why they're there or how to resolve any issues in real time. So we have customers that are doing that.

We've had some beta that have never gone live with some retail customers, shopping customers that integrated our technology and their existing CRM database or the loyalty database with real-time digital pricing on store shelves. So depending on who the customer is, what time of day it is, what inventory looks like, they can change in real-time the price of the product that the customer is looking at in real time. None of this has gone live. None of this has gone full-fledged. But there are retailers out there who are looking at, how do I optimize the customer's experience in real time in the store? Wow. That is wild. Great. I mean, I'm excited to see where this takes us. Talk about personalization.

But keep in mind, that's really no different than Amazon right now. So Amazon does that. They just do it for you on your website. So they know who you are. They know what you're looking at. They know what their inventory is. And they make some decisions in real time about how to price it or how to bundle it or how to discount it. It just looks like normal Amazon. Yeah, completely. I haven't figured out how to hack the system yet, but I would like to. I always get the discounts. No. Let me know if you figure it out. Yeah, right. Well, Benjamin, I have two last questions for you that we ask all of our guests.

The first is, I would love to hear about a recent experience that you had with a brand that left you impressed. What was your experience and why was it amazing? It's my hairdresser. And I was thinking about this the other day. She's gone on vacation and I can't get my haircut. My wife was like, well, just go to a barber or go to Supercuts, you know, go wherever. You've got a pretty standard haircut.

It's not like you need anything special. And I relate the idea that my experience in getting my haircut is far more relationship-based than just simply going to a supercuts or a barber. This is a woman who I've known for 20 years. She cuts my hair and we have long conversations about the kid. She knows who my kids are. She knows who my wife is. She knows what I'm interested in. She knows that I've gone on a trip. We have long engaged conversations that aren't transactional to come back to the very beginning of this conversation. And it makes it a much more valuable experience that I'm willing to pay more for. And I'm willing to not go to a traditional barber or somebody down the street. And I'm willing to look a little shaggy on a

podcast simply because that's a relationship that transcends a transaction. And so if you think about the challenge that all of these financial institutions or all of these companies have, it's how do I create a relationship for life? And that doesn't mean selling me something all the time. It does mean you know who I am, you know what values I have, you know that we have a shared sense of value. And that is a challenge that companies increasingly have to face. thinking about how can we in our unique businesses create that personal relationship, even if there isn't a one-to-one person-to-person conversation happening, but we can all, you know, I think you've mentioned Apple. So I'll just use that as an example. It's kind of the quintessential brand that I think people think of where it's like, they just like, they get me. I, you know, even if you walk into the store,

you do get to speak to someone, but the way that they speak to you makes it feel like relatable and familiar. And there's just something about how they've thought about the online and the retail experience and the product experience that creates something that almost feels personal. I think there's still ways to go. So there's another element to that that's also very important to point out. And it's very clear in the Apple experience. They know who they are. They know what they are. And more and just as importantly, they know who they're not. And so we talk about that retail experience because we like the products and we connect to the culture. There are a lot of people who don't. And Apple's like, that's perfectly fine. You like an Android phone? Go buy an Android phone, right? This is

not the store for you. And we're not going to change who we are to suit or address the entire market. And I think that's just as critical and just as important to understand. Yeah. And I think that really comes, as you're saying that I'm having a light bulb moment of like, that's what that personal experience, it's part of what that personal experience relies on because you are that very clear delineation between who we are and who we are not that allows you to sign up or leave. It also helps us get through the day, right? If I try to be everything to everyone, I'm going to be nothing to no one. You're not going to win every deal. You're not going to make everyone happy. At the end of the day, you have to be kind of Zen about who you are, what you are, what you stand for, and be fine with the success that generates in and of itself. Amazing. Well, one last question for you, Benjamin.

What is one piece of advice that every customer experience leader should hear? So I think I touched on it a little bit by saying know who you are and know what you are and be faithful to work a little harder to gain trust, to communicate your value and communicate your culture and communicate your differentiation. So, you know, it goes back and forth. You know who you are and know that won't work everywhere. I think it's that simple, but as simple as it sounds, it's extremely complicated and difficult for people to figure out. Because it means saying no to potential customers and no one wants to do that. But the reality is, is that if you know who you are and you know who you're not, and you focus on being who you are, you'll attract a stronger relationship.

Well, you'll attract customers that are more fitting to your product and develop a stronger relationship with them. So I think that's really great advice. Yeah. And I'm not sure if this is consistent with your podcast, but I'm going to mention somebody else who talks about this a lot. Great. That's a guy named Simon Sinek. And he's talked about the why. Understand why you are doing what you're doing. Why are you doing it? And it's that core central, he draws concentric circles, but it's the center of the circle. And so few companies do that. So few brands stop to think, what's important? What do we represent? What is our value? And I think that if you know that and can communicate

that, I think that'll truly differentiate who you are and what you are. Completely. I'm so glad you mentioned that. It's a great, if anyone wants to go and check out Simon Sinek's TED Talk, even just for a taste of what is being talked about, it's like one of the most watched TED Talks ever. So if you haven't seen it, go and take a look. But Benjamin, thank you so much for coming on the show. Thank you for having me. It's been a good time.

Yeah, this has been such a great conversation. We covered a lot of ground and really appreciate you coming on. I hope you have a wonderful day. Thank you very much. And thanks for having me. You are a business leader with vision. You've seen the future as an AI enterprise, thriving with Salesforce's agent force,

and it is bright. Getting there? Eh, it's a little fuzzier. Don't worry. Salesforce CTOs are here to work with you side by side and turn your agent force vision into a reality. We're talking expert guidance and implementation support from the best of the best.

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