In this edition of the Digital CxO Leaderships Insights series, Mike Vizard talks to Folloze CEO, Etai Beck, about how generative artificial intelligence (AI) platforms such as ChatGPT will transform digital marketing.
Mike Vizard: Hello, and welcome to the latest edition of the Digital CxO Leadership Insights series. I’m your host, Mike Vizard. Today I’m with Etai Beck, the co-founder and CEO at Folloze, and we’re talking about B2B marketing and ChatGPT, which everybody and his brother seems to be talking about these days. Etai, welcome the show.
Etai Beck: Thank you very much for having me.
Mike Vizard: You guys have a platform that helps people manage B2B marketing, and you integrated that with ChatGPT. I’m sure you’ve got other AI technologies in mind. But how do you see AI being used in the context of marketing? And how will all this play out?
Etai Beck: Yeah, thank you, maybe I can give you a little bit of background about what Falloze is. And it would lead itself very easily into AI. In general Folloze is the first and only no-code experience platform for B2B marketers, built on the idea that B2B buyers today are completely digital or digital first. So you have to find ways on how to surround them with digital content and experience, prior any product or any sales motions. And therefore you need to find ways to provide for them the most personalized, relevant and specific experience in content on the digital channels. And that’s what we built, the platform is serving, empowering global deployments for companies like ServiceNow, Cisco MetLife, T, mobile, all of this, Oracle, Adobe, Salesforce and so on. Kind of that’s who we are, in general. And what we actually bring to the table is what marketers expect, today from B2B marketing to be is to have three major factors be able to be incredibly agile and run with the pace of the world, of the business world, optimize their engagement of their prospects and customers and then get the best insights from all that interaction so they can take the next best action. When you bring AI to that three kind of elements of that flywheel. AI allows you to be far more agile, because it helps you to save a lot of time and energy and cost. It allows you to personalize in a way that is optimizing the engagement and it allows you to get the best insights possible. That’s kind of how we see AI. It’s not replacing marketers, it’s not replacing salespeople, but rather, it’s assisting them and getting them to the next level.
Mike Vizard: So what will people specifically use ChatGPT for? I’m gonna be researching with that to find things on the web that are relevant? Or what role does that specifically play?
Etai Beck: The way that we built ChatGPT into our AI module is to be able to kind of classify all the micro universe of every one of our customers, the micro universe of their digital content, and be able to classify that in a way that allows marketers to find the most fit – relevant market content for every situation. Second, is to recommend content automatically to their prospects and customers as they visit any digital asset and have a digital interaction. And the last one is to build out of that a combination of engagement and the classification of a very strong picture of an insight of what are the actual topics of interest by every person and every account. The role of chargeability here is that classification, and the rest of it is algorithms that we put on top.
Mike Vizard: How do you know that the content that you’re using is trustworthy? Because we’ve seen some interesting reports involving multiple personalities with ChatGPT? So how did you work that out?
Etai Beck: Yeah, that’s a major, of course, top-of-mind kind of a topic of interest – the way we’re seeing, for now, ChatGPT, is as an engineer to classify content that was produced by marketers, not to write for them. Content that, over time, can help them to write content. But right now, what we’re doing is we take the content they produced, and they verified and they’re comfortable with, and help them to classify it and recommend it into the right places. And therefore, it’s a very strong combination of automation and the factor in a way that doesn’t risk any kind of a confidence level and doesn’t destruct it. The way that ChatGPT is being discussed in the broader kind of a context is, ChatGPT is classifying the universe of content, and there you can get into all kinds of unpredictable situations; it doesn’t happen the way that we use it.
Mike Vizard: So you’ve narrowed the scope somewhat? How does the engine that you created use that content to personalize a message? How does it know what to give to a particular person based on their interests? Or how do you know you’re getting the right content to the right person at the right time?
Etai Beck: Yeah, so that part is not so challenging. That’s part is our own algorithms. What we look into is a number of different factors. First, we take data, a profile data of the people that are interacting with the digital experiences and content; this could be account demographics, this could be stage of relationship or deal, this could be a past behavior, it could be a contact role and contact other attributes. And we cross correlate between that and similar interests by people like that, and we use in the classification what we’ve done with chargeability to surface the relevant content based on the cross correlation of that.
Mike Vizard: The real time capability of all of that – how do I kind of make sure that I’m not moving faster than I can process, if I haven’t had somebody to kind of look at something? You know, as one wise guy once said to me, “It’s one thing to be wrong. It’s another thing to be wrong at scale.” So are there guardrails? Or how do I kind of make sure that I don’t make a huge mistake versus a small mistake?
Etai Beck: So the classification of content is done at the point where marketers introduce content into our platform. And there’s no, there’s no rush, right? But what happens there is they don’t need to kind of a classify thousands of assets on their own. But every time they close, they introduce a new piece of content, we run the algorithm to classify, they can inspect, they can verify, you know, what these tags want to add these tags we want to remove so that that one is is really under control if if they want so when actual visitors from their prospects or customers come in. At that point, the content is classified and proven. The data that is powering the real time recommendation is data that is proven; that data is either the customer’s data from their CRM and marketing automation, or for any one of their kind of CDP systems, that data they prove, in what is often the fashion, that what happens in real time is a high confidence, kind of a correlation. In some cases, for instance, what could be, for instance, an area where real time may be questionable sometimes, is that did you identify the right person, right? Someone landed on a webpage or an event? Is that the right person? And we use a whole set of different sources of data in order to validate that there is a person; we can even apply a confidence score that allows us to either kick in the recommendation or not. And marketers can actually tune that. You know what some people would say, we want only a confidence score three and above to allow personalization. Otherwise, we keeping it more concrete, generic. So we have all the different levers in order to make sure that what people see at the end of the day is the most relevant one. And we’re not taking any more than minimum, false positives.
Mike Vizard: We’ve been talking about personalization for a long time. And yet marketing up until now at least, has been a fairly blunt instrument. And so we get caught up in a lot of spam conversations and filters and people don’t read their email messages. Are we getting to the point now, with a little help from AI, that we can have more meaningful, targeted conversations so people don’t view what they’re being fed as spam as much as it is just, you know, some helpful interaction?
Etai Beck: Definitely. And then the other thing that is very interesting is that if you if you look at B2B marketing over the past few years, what became a kind of a front and center is the whole practice of canvas marketing. And it’s actually expanded to account based experience and account based strategy connecting together all the different notions between marketing and sales. And that is the practice. So and sometimes, you know, the combination of art and science to really match specific messaging and content to specific account situations – we would apply from allow you to do it on a one-to-one basis, or one to a one too many. But one of the key things that we believe are, and we’ve seen very, very clearly, is the whole notion of agility, right? It used to be that marking organizations would run a very centralized operation, where they expect everything to be done fully automatically from one place. And when you work with companies which are larger, and they have a broad portfolio, and they can work in, you know, 25 to 30 different countries in different languages and cultures, what we believe in is, is the empowerment of every marketer and sales person on the ground, to take those concepts that we discussed earlier and match it to the specific audience. So, think about that marketer in Denmark that is working in a healthcare environment in a healthcare vertical, or the other marketer in Singapore that is working with a financial services environment; we believe in allowing them to create the messaging content and marketing and sales motions that are relevant to those, and then they add personalization with AI on top of that, so that very scalable notion allows that kind of very deep degree of personalization. And we see the results. And we have a lot of customers that report back on, you know, four or five times better results and outcomes from what they used to do in, you know, with broad marketing emotions.
Mike Vizard: So where do you think we’ll be in a year or even two with AI? Because machines keep getting smarter. So what should we expect?
Etai Beck: You know, we can only expect this to be done more, and over time, trusted more. I know there’s a lot of doomsday predictions in the market, whether the machines are going to take over, I don’t think they’re going to take over, I believe that machines are going to allow us to be better in what we do and all of us to be much better in what we do. And we’re going to see over time, smarter and smarter and more accurate motions. And yes, there’s going to be some point in time when we can trust more some content creation also by algorithms in a way that we feel comfortable with. So eventually, it’s going to happen, you know, if you look today at new electric cars. With AI based navigation, it’s almost there, but it’s not really there. You can really get your hands completely off the wheel and go to sleep. Some people sometimes will do that. But that’s not yet the safe way to do it. But take it 10 years out, probably we’ll be able to get to that point. Same thing goes here. Give it a decade and we will be in a very, very interesting situation where AI can actually do very smart things that we don’t even predict today.
Mike Vizard: All right, folks, I think you get the message. Everybody who’s in marketing is gonna get a little AI buddy to help them do their job, and we’ll see how it goes from there. Etai, thanks for being on the show.
Etai Beck: Thank you very much. Thank you for having me.
Mike Vizard: And thank you all for watching the latest episode of the Digital CxO Leadership Insights series. You can find this episode and others on the digitalcxo.com website. And once again, thanks for spending time with us.