Have you ever wondered why, despite having access to advanced AI tools, your marketing strategies still don’t hit the mark? Could it be that you’re focusing on the wrong data and missing the emotional connections that truly drive consumer behavior?
Today we’re exploring the intersection of AI, emotional intelligence, and marketing with Joshua Goldberg, EVP of Strategy at Zenapse. We’ll dive into how Large Emotion Models (LEM) are revolutionizing consumer engagement and delivering impressive marketing results.
About Josh Goldberg
Josh brings over 25+ years of leadership roles in strategy, marketing, and digital delivery. He leads Zenapse business development and channel partnerships. Josh specializes in strategy, business acceleration, digital media, and marketing. He has delivered plans for rapid business improvements and insights to many companies including: Vanguard, Capgemini, Applied Materials, Fisher Price, J.D. Power, Reuters, Viacom, and Wunderman Thompson.
Resources
Zenapse: https://www.zenapse.com https://www.zenapse.com
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Transcript
Greg Kihlstrom (00:00)
Have you ever wondered why despite having access to advanced AI tools, your marketing strategies still don’t hit the mark? Could it be that you’re focusing on the wrong data and missing the emotional connections that truly drive consumer behavior? Today, we’re exploring the intersection of AI, emotional intelligence, and marketing with Joshua Goldberg, EVP of Strategy at ZennApps. We’re going to dive into how large emotion models are revolutionizing consumer engagement and delivering impressive marketing results. Joshua, welcome to the show.
Josh Goldberg (01:27)
Hey Greg, nice to see ya.
Greg Kihlstrom (01:29)
Yeah, looking forward to talking about this with you. Definitely ⁓ a good topic here with all the, you know, all the discussion. We talk about AI in every episode, but there’s always another angle to pursue and another way to look at it. Before we dive in though, why don’t we start with you giving a little background on yourself and your role at ZenApps.
Josh Goldberg (01:50)
Thanks a lot, Greg. You know, I gravitate towards businesses that are creative, have a high rate of change, and really at their core are about connecting with people. And we talked about the MTV experience before the podcast. I think when it really started to click for me was when I was part of a small team that was building one of the first pioneer interactive agencies, Organic. And that’s where I was actually able to meet many of the XenApps team members.
It was at Organic that we really were building these experiences for e-commerce, for financial services, entertainment, and really about like shortening the distance between brands and consumers. And it was also this incredible window into what keeps a marketer up late at night. And that is really, how do I deliver an experience? How do I use technology so that it works for me? And also, how do I engage consumers so that they convert? So if we sort of fast forward,
past marketing and strategy work for media companies and publishers and consultants and land on XenApps, which is where we are today. It really is great because we’re in this new territory that you talked about, which is about AI, business and emotional intelligence. And what’s exciting about it is one, just being able to connect with a really seasoned team at XenApps. These are people who led big marketing and development teams within the Fortune 100.
We work with the bleeding edge in AI. So we’re part of the Comcast Lyft Labs AI Accelerator. And we’re also very close with the Google Cloud and Google Gemini teams. And most of all, our team has built a platform for really amazing brands and marketers to deliver experiences that leverage AI and emotional intelligence and deliver results.
Greg Kihlstrom (03:41)
Great, great. Well, yeah, let’s let’s dive in here. And, know, as I mentioned, AI comes up in every conversation, I think, lately. But, you know, so we’ve certainly talked a lot about large language models and, know, and, you know, agentic AI and stuff like that. But, you know, here we’re here going to talk about large emotion models. And, you know, I’d love to hear first, you know, how do you define a large emotion model and, you know, how does it compare to something like a large language model?
Josh Goldberg (04:09)
Yeah, so Greg, you know, LLMs train on billions of words. They predict the next sequence of words and they’re used for these amazing utilities like content generation and language translation, customer service. And again, they’re great utilities, but for marketers, they’re really looking for a different type of value. So we built a large emotion model, which trains on emotions, sentiments, beliefs, and activities.
And it’s all really at the service of really understanding what matters to a consumer. Because when you understand what matters, then you can deliver an experience and then you’re more likely to see huge lift in conversion. On our side, the ZenApp side, we’ve built the first large emotion model. Over the past 24 months, our model has interacted with over 200 million consumers. It’s logged over 6 billion interactions.
And essentially what it allows a brand to do is it gives it an opportunity to interact with the consumer. One they may not know much about and to predict what is the right message, content, offer, copy, and image that has the highest likelihood of converting them. We do this at scale. We do it dynamically and in real time for some of the world’s largest brands. And the results are really stunning. We’ve seen lists in conversion anywhere between 40 to 400 % using this LEM.
Greg Kihlstrom (05:33)
Wow. So can you talk a little bit more about, how how does it how does a large emotion model predict and respond? mean, definitely to your point, it’s nice to generate content and all that stuff. But yeah, when you’re when you’re tasked with driving conversions and building loyalty and all of those things like this is this this seems really, really relevant. But, you know, can you talk a little bit more about, you know, how how it works and how it predicts and responds? Yeah.
Josh Goldberg (06:03)
Let me start first off, I think if it’s helpful to just start with like, what’s the challenge for marketers today? We’ve experienced these challenges. I’m pretty sure you have as well. So as you know, the tools that are available to a marketer today are either demographic or behavior. Demographic is you’re this old, you live here, here’s a picture of palm trees and behavioral is you bought shoes so you must need socks.
But when we speak to marketers, really the barometer for success is conversion. And unfortunately, conversion rates are hovering around 2 % in e-commerce, maybe higher for financial services and healthcare. Think about that for a second if you flip it on its head. That means 100 consumers raised their hand, the brand had an opportunity to engage them, and 98 of them walked away.
Yeah, so what the platform, what we believe and what the platform has actually proven is people don’t make decisions based on behavior and demographics. A Harvard study actually shows that 95 % of decision-making is emotional. If you read a book like Thinking Fast and Slow, it’s the same takeaway. When you understand what matters to a person, you can deliver an experience and that experience can deliver an outcome. That’s what marketing is experience plus results. So then let me talk a little bit about how we deliver those predictions. And our LEM captures as invention, emotion, belief, sentiment, and activities. Activities are the things you do, travel, video games, gardening. Sentiment is your attitudes towards them. Do you like cooking? Do you hate it? Is it an obligation? And then with emotions and beliefs, we look at 85 different emotions and beliefs.
Greg Kihlstrom (07:25)
Yeah.
Josh Goldberg (07:53)
Nothing controversial. We’re not looking at politics or religion. Instead, we’re looking at things like what’s your attitude towards money? Is it a spending tool or a savings tool? Knowledge. Do you trust experts or do you learn by doing? Family. Do you put them first or do you value your personal time? Those are sort of the key areas that we’re looking at. We also train the AI on specific goals that will move a user through the funnel.
a form submit, a lead start, setting up an account, calling an advisor. Let me give you a real world example of those predictions in action. A consumer will interact with a web or a mobile experience. The model detects what are the emotions and beliefs that are built into that person. And with a number of different marketing variations, which variation actually has the highest likelihood of converting that end user.
The variations can vary from calls to action to button color to headlines to offers. And they’re very powerful for delivering these predictions.
Greg Kihlstrom (09:02)
Yeah, so yeah, so to that end, you know, I want to talk a little bit more. I mean, you mentioned up to 400 percent, you know, conversion increases and stuff like that. So I want to I want to talk a little bit more about that and, you know, just how marketing ROI can be improved with the large emotion model. So, you know, not only increasing conversion rates, but cutting acquisition costs, you know, all of those things that make the marketers happy and then and
those that they report to even happier. I’m sure. Can you talk about, know, how I know you’ve touched on this a little bit, but you know, how does how does the LEM contribute to these these outcomes?
Josh Goldberg (09:43)
Yeah, I mean, the results are really amazing. And that’s also because we’re working with really amazing brands who are very interested in AI and emotional intelligence and also really interested in delivering better predictions so they can deliver a better experience. We work with one of the top pet insurers in the U.S. When we started working with them, new policies were under 2%. Let’s say it’s about 1.7, 1.8%.
The platform allowed us to redesign the funnel. Over the course of 10 months, we were able to raise conversion rates from 1.8 % to almost 9%. I think actually over 9%. That’s like a 4X. At the same time, we were able to drop the CAC by about 75%. And for a big organization that we’re working with, they’re not looking to just reduce their cost of acquisition. This is really allows them to put sort of more resources towards more marketing. Yeah. Another example, and this is maybe ⁓ quite interesting. We work with one of the top fast fashion brands and they have a very low price point. So you can imagine like dropping a fleece from $15 to $14 isn’t going to move the needle. What we discovered through the platform was there was ⁓ a sub segment that was really interested in the environment and they had strong social beliefs about making a difference. When we changed the messaging to made with sustainable materials, conversion rates lifted 20%. So I think what’s also really interesting is how emotional intelligence actually works across diverse industries.
Greg Kihlstrom (11:32)
So along with all of the the benefits of using AI, there’s also, you know, I guess for all the hype that it gets, it also feels like there’s some wasted opportunities. Right. So can you talk a little bit about, you know, despite increased AI adoption in many ways, you know, not not just in one specific, but in many ways, you know, many marketing opportunities are still going wasted.
Josh Goldberg (12:00)
Yeah, I think we’re seeing the same thing too. And we’re marketers and so we get it. know, marketers today ⁓ face two big pressures. One is they’re being asked to perform like general contractors. So in addition to their core duties, they have to be experts in IT, cybersecurity, compliance and so on. They’re also under a lot of pressure to deliver value quarter to quarter. They need to show a business case immediately.
Our solution, as I mentioned, is built by marketers for marketers. So some of the things that are built into the ZenApps platform that are attractive, not only to marketers, but also to the chief digital officer and the IT team. One, it’s immediate. So when someone signs up for the platform, they get immediate access to our graph of 6 billion interactions. That means that personalization can begin immediately.
It’s not six or 12 months down the road. Secondly, it’s low code, no code. It’s two lines of JavaScript that run in the Tag Manager. It takes less than four hours to deploy. It’s really amazing. It sits on the tech stack. Another important part is there’s no PII. We do not capture name or address. It runs on the client side, but there is nothing that can identify an individual directly.
It’s also goal based, so we talked about this before. A lot of programs or platforms are about clicks. We care about goals and metrics. Did someone complete a form? Did they create an account? Did they select an annual plan? Did they select a multi-day pass for a theme park? Also, I can tell you what’s very interesting is the ROI is delivered within weeks, not months or years. We’ve just launched a pilot now with a media company. And within two weeks, we’re already seeing an increased ROI. So it’s really significant.
Greg Kihlstrom (14:02)
Yeah, yeah. So I want to talk about another factor here, which is, you know, we’ve added the emotional component to AI and, you know, there’s certainly generative AI in there. ⁓ As far as content creation, there’s the emotional component. Now let’s talk about the real time component as well. And so, you know, when when all of these things are kind of added together.
How can marketers use these, you know, an AI driven solution to provide real time insights that can enhance marketing effectiveness?
Josh Goldberg (14:36)
Yeah, awesome question. I think at the root of this is about like testing and also listening. And I’ll give a real world example. I mentioned that we work with fashion brands and I’ll talk about the fast fashion brand that we work with. Just as a test, we wanted to ask consumers after the purchase process, how they were feeling. And believe it or not, something like 20 % of consumers responded.
And when we asked what they were feeling, a lot of them told us they were overwhelmed. We would never have discovered this, but just by asking and asking around emotional intelligence, we got incredible insight. So what did that mean for the experience going forward? Well, it meant for that segment that felt overwhelmed, having too many choices or being pressured, it meant turning down the volume on messaging like limited time only or by now. And instead, a lot of the messages were like, just for you, or selected for you. And in fact, once we did that, and updated that experience, again, we saw this incredible lift in conversion. So when we think about like real time, it’s about sort of in real time listening, and then being able to adapt quickly. And the results are really stunning.
Greg Kihlstrom (15:58)
do you see this evolving over time? I you know, it’s it’s feels like in all ways, I think with with AI, and ⁓ we’re kind of in early days, you know, how do you see AI and this emotional intelligence connection continuing to evolve? And you know, where do you think? Where do think we’re going to be in the sort of the next phase of this evolution?
Josh Goldberg (16:20)
Yeah, I think it’s really exciting to be honest. I think with this large emotion model and the combination of emotional intelligence and AI, it will give brands and marketers an incredible opportunity to build relationships and shorten the distance between them and consumers. Right now I can say from the ZenApps perspective, we’re really following an omni-channel strategy. So, you know, the platform serves web, mobile, CTV, but you can imagine the emotion that’s built into so many other touch points, emerging touch points, smart homes, the screens inside a self-driving car, wearables, video games. And so for brands, I think what that means is there’s a huge opportunity to connect with them on an emotional level, to be able to drive transactions and outcomes. And then importantly,
All the data from those different sources can then be fed into the model and help those brands to deliver even greater engagement and experiences going forward.
Greg Kihlstrom (17:28)
Yeah, yeah, I love it. Well, thanks so much for joining today. One last question for you before we wrap up here. I like to ask this to everybody. What do do to stay agile in your role and how do you find a way to do it consistently?
Josh Goldberg (17:42)
I love this question by the way, Greg. First off, I always carry a book with me and my wife is a middle school librarian. So her motto is get caught reading. You never know when you’re going to get in, get into a great idea. I’m actually reading this book by Chris Voss called never split the difference. You might’ve he’s a. Yeah. Yeah. So I picked it up because my 13 year old is, in debate club and she keeps winning arguments.
Greg Kihlstrom (17:44)
Great.
Josh Goldberg (18:12)
But actually, you know, what’s amazing about the book is it, if you want to understand the power of emotional intelligence and how people make decisions and how to get results, this is absolutely the book to get. So I think just getting that information from different sources and always having a book handy is a big deal. And then we also talked about this before the podcast, I think maybe just to keep my mind young and flexible. I’m a blues musician and A big part of what we do is improvise and even songs that I’ve been playing for decades, I’m always thinking about how can I improve my technique? How can I find a new song within the song? How do I listen better to my bandmates? And that’s great practice for the business world as well.
