AI Spices Up Consumer Connection, Marketing

have him join me this morning. Thanks for doing this, Benny.

that was a real eye opener. You know. I got back and I was working out an investment firmat in San Diego, and I came back and said, oh my gosh, the world actually doesn't revolve just around numbers, revolves around people making decisions. And that just became a passion. I was trying for the last twenty five years or so figuring out how we humans make decisions. And the more

I got into it, the more fascinating it was. And you know, I went through a financial career and then into emerging technologies and I say, look, I need to really figure that out, you know, I it's it's it's just fascinating how you go into through a financial career and you work and you know, I was a market standing then at City during the financial crisis, and with negotiating on the mortgage site with homeowners without knowing anything

around human decision making, just felt, you know, that something is missing, and so I was on a you know, on a mission to figure that out. And that's how we started knob Labs to really understand human decision making processes.

actually an on on the other side. And so you can modify and and change the asset and take the homeowners who are you know, process and into waste management something which is good for the bank and something is good for the homeowner. And so I went to my boss very early on and say, okay, that's great, but now I have to negotiate, to find a way to negotiate, you know in quotation marks negotiate, but through through analytics and outreaches with millions of homeowners. How do I do that?

Where do I find the chief psychology officer within city who can guide me how to do that? Then guess what, there wasn't any There isn't the chief psychology officers of the city. So you have investment banks and you have consumer banks, which by definition work with individual consumers, and there's no psychological understanding how that engagement should work. And

it's just mind boding, correct. And so it was very clear that there is a world out there which goes beyond the hard data, which is on touch to some extent, but probably more important than the hard data. And so how did we figure it out? And by the way, I think the team at City at that time Citimot did a great job. We kept about a million and a half American homes of families in the home. So whatever we did, we did. You know, it worked and it was a great outcome. But still something was missing,

and and that's where I am now. Well, look, think about the US economy. Two third of the US economy is a consumer dreaming about the consumer. Yeah, how consumers make decisions? You had bloomberg, open up a blooming terminal. Yeah, every piece of information out there, take data and you know, revenues and learning scrolls and and anything. Where's the cognitive the behavioral signals on your screen? If two third of the economy is dreaming of the consumer, where is that piece on your terminal?

and or a restaurant. You know, who's going into the restaurant, who's who's going to McDonald's with a Starbucks, and what's driving them really or on the consumer side, you know, why would somebody you know buy a Peloton bike or not buy a Peloton bike? And and really understanding the

decision making process and so the customers. So the financial companies obviously are a great customers, but also the corporations are because they have to reach out to their clients and emotionally engage with them in a way that they can drive performance. And so let me step back, if you can give me a couple of minutes, just explain why that's actually relevant. So you know, if you go back even to Sigmund Freud who said, look, we have a rational mind, that we have a subconscious mind, and

the subconscious mind makes a lot of decisions. It was never really identified how much at that time. But what became interesting is a few things which came out of it. One is, yes, there is a subconscious mind. Second, the subconscious mind makes actually the majority of decisions. We assumans are not as rational as we think we are. You know, we're not making rational decisions. And you see that in finance correctly. We started off with you know, efficient marketing particies.

Everyone is rational, but now we understand the cognitive biases and all that stuff. All of a sudden, Oh my gosh, there are actually inefficiencies in the market that are driven by cognitive bvices. Oh we're not as rational. We're not rational machines. So we saw that there, and but we have validation, you know, down the Economan and Donostoreski in

the seventies did their whole analysis down. Economan got then a Nobel Price in two thousand and two around you know, prospect theory, how we are not as rational, and then you have the So we know that the rational mind, well, while it's important, it doesn't make that many decisions. Really the subconscious mind, which makes the majority the rational mind, is more controlled process correct and so sometimes it breaks down. If you in wage for example, it may wage break down,

But otherwise it really is a controlled process. But the subconscious mind makes most of the decisions. So that's great, Well, how does it make those decisions? Are they similar to the decision a rational mind would make, Right, the answer is yes, Then all I would say there is around the rational mind and the factual decision making process still hold. If the rational mind, however, makes the subconscious might make the decision in a different way than, we're in trouble. Well,

it turns out we are in trouble. The selfconscious mind doesn't make decisions the same way the rational mind makes it. And here's why. Well, Donny Conneman found out and I'm as swear to everyone else that they are cognitive biases. Correct, So those cognitive vices obviously are different. So we know that they make the dish decisions they're differently. Well, that's great.

So maybe we just asked the rational mind what decisions were made, so we can still use the rational mind to figure out how people make decisions, even if the decisions were done differently than the rational mind would do. Well, that doesn't work either. Again, we're intro why there's a guy that in the name of Benjamin Libbert and scientists or in the eighties that the subconscious mind makes a decision a fraction of a second before the rational mind

actually recognizes the decision was made. Wow, So here we have a problem. We know that most of the decisions are made by the selbconscious mind. We know that decisions the subconscious mind makes are different than the rational mind. And now we find out that the rational mind doesn't even know when the subconscious mind makes a decision. Therefore it can't explain it. So now we're will in trouble. Correct, how did you mentioned? How do we figure out therefore,

how people make decisions. I can't ask you, Mike, why did you do something? Because you probably acted on it before you even figured out that you're acting on it. And so surveys are great, I can ask you, but they are probably wrong some of the time, maybe not all of the time, but many many times. Then we can go into that and why that's relevant to AI and why it has to do with a lot of things which happening today with AI and how oscination and so on. But this is an important understanding as a

starting point. We're not rational. The majority of decisions are everyone non rational, and rational mind doesn't know what the heck is going on. In.

by Connoment is back there too. So it's definitely a very cool and interesting subject, you know, And it's something that comes up, you know, I see an advertising I've read about advertising that sometimes you need you need to get in front of the customer I think eleven times or something on average before like you enter the consideration set. And so different companies that we work with talk about the different ways that they're trying to reach out out

to customers. It's just just really interesting to me.

into any languages and no translation. Then we map that through our proprietor psychological framework into an intense score and an action personas what we found with Target, and the question was Target has been on a downward trend and

actually was hit obviously with its Pride merchandise. When they came out of that, there was a whole controversy around that, and the stock really took a dive and as been settling somewhere and the question is, you know, what's actually happening in terms of the consumer's emotional actitude towards target.

And so what we did is our team they analyzed social media and discussion forms around target, conversations free frond conversation, extracted those emotions and as I mentioned, the intent score, and what we saw is that a couple of things. It's not the first time target is getting into a order. I mean, that's part of who they are, and that's

perfectly fine. If you look at the intent score, you see spikes up and down, and the intent is really how emotionally engaging the consumer is visa v target and how emotionally engaging they are in to go and shop, and the motivation score we see ups and downs, and you know, we see we saw quite a bit of a some kind of an action around obviously the controversy. When you look at and I think that's an interesting component.

We always look at what is their base line emotions, what are the typical emotions they evoke in the consumer, and how has that been disrupted by the private merchandise. And while that's then disrupted, is it coming back to a symbol or emotional profile and an emotional attitude of the consumer, or is there a structural shift which would

impact consumer behavior. That was really the question. And I'll tell you how that works for Target, and then I'll explain that how that actually works with Pepsi I'm sorry, with bud Light, not Pepsi, bud Light, which went through a similar event in April. So when you look at Target, you clearly see that there was a there was a certain profile, emotional profile which was somewhat reflective of the consumers, you know, emotional attitude and responses towards Target, which was

disrupted when they came out with the merchandise. What we have seen just recently over the last couple of weeks is that there has been a reversal back to that emotional baseline. Not yet there, but we see a relaxation and a return to that which from a I'm not going to say anything about the start, but what it means is that emotionally, it seems at least that we're settling back to the status quo it was before the event. And leave that up to you to figure out what

that actually means in terms of human behavior. But that's an important component. Why is an important component again, because emotions strive decisions, and if the emotional profile. A certain profile, complex profile leads to certain action tendencies, and they're coming back now to a similar baseline they were before. They're not there yet, but they seem to go back. It will tell you something here about consumer behavior going forward.

This is not what's happening with but Light yet. It's interesting but Light that has a completely different profile and had a different profile before, you know, the April first event where the transgender influence of Dylan more Money came out and had that video, And what we saw is a complete disruption of that as well of that profile

and no reversal yet. And what's interesting in addition, what we also measure is not just the consumers response emotional response to an event or a company or a brand or marketing. We also measure the response from the company itself, from the CEO, what they put out. And what we found in the case of bod Light is a complete disconnect between the feeling of the customer after the event after April first and the CEO's positioning. So think about it.

I have a problem, I call you. You are my call center, correct, I have a problem with you with a product, and I'm really angry and you just tell me everything is homepy door, and all is fine. I will feel as a customer, you're not you're not listening. You don't hear me, you don't hear you hear my word, my words, but you don't hear me emotionally. You do not connect with me emotionally, and therefore you don't solve the problem I'm in. And that's exactly what's happening with

but Light. They actually put something out which reflected their emotional profile pre event, pre April first, without taking into account and appreciating that that's not where their customer is right now, and so we haven't seen that reversal yet there whereas in the case of Target we start seeing a reversal.

give you what you expect. It's really it shows you the tone of the conversations, how people talk, not what they feel and how they're going to act. And you know, the example I always give is, you know, you go to a restaurant and you sit down, you get dinner. Five minutes later, the waiter comes and ask is everything okay? And what do you say? Yeah, yeah, it's all fine, and you give a positive sentiment and even the food came late and doesn't look appealing, you'll never go back

to the restaurant. Just gave a positive center. And that's why sentiment does really work in clients contours and say, hey, centim is always positive, except in the reare cases when it's not. It's usually positive, and we don't know what the drivers are. So what we do is it really have to go to the emotional level. And more importantly, you have to understand how emotions combine into complex emotions which lead to action. So people always think, oh, they

have good emotions bad emotions. There is joy and hope and trust which is good, and anger, fear and and you know, and contempt of sadness is bad. But that's not the way the human psyche works. We have always all the emotions right, there's no bad and good, it's it's a combination. So, for example, fear can be very good for marketing. You know, too much fear is bad, it freezes you. But a little bit of fear creates

fear of missing out leads to call to action. So the combination is important, and so we always look at the combination. That's where our unique psychological framework comes in. And we're able to do that because we're really complaining deep machine learning with behavior psychology. So we have software engineers and data scientists. We also have a chief psychology officer as part of the core team. So we built a psychology into the technology.

will not do anything. Correct. If you're in front of with your friends, in front of a TV watching your favorite whatever, your sports team win the finals, you're so happy you're going to sit there and not get up and do anything. Why would you? You're already happy, You're already in a balanced stage. You achieved it. It's we call it an aspirational goal. You're already there for me to have you move, I need to get you out of that happy stage and create a reason to move

away from that unhappy stage to a happy stage. So to get to that how do you do that? Well, we take them through an emotional journey. You create some anger at the competitors, or at the lack of a product, or at the lack of quality of a product, whatever it is. Create some fear, some contempt. Then you come in with with a surprise and amusement, some trust that you have the solution. Think about every marketing campaign as a movie. That's what I tell my clients. Think about

a movie. So let's say you like I guess if you like going to the movies. Let's say you sit down and everything is happy, joyful and hopeful. What happens it's boring, You fall asleep. You need a villain to create some action, some tension, some fear. Then the hero comes in, there's surprise, is amusement, there's some trust, the the the you know, there's a again, I mean, the villain comes to and there's a battle going on. It's

an emotional journey. That's what captures us. Every marketing campaign needs that. If you're stale and you just put out hope and joy, you're going to fail because it's not creates doesn't create a call to action. And we measure that and we tell you what you need to create to create a call to action, and that's what turns out to be predictive. And that's what we have been providing you for the last five years or so. Yeah.

at least in the mind of McDonald's. And so what we did is we looked at the last several months of social media conversation so acted emotions and created that we intend score, Motivation Score, And what we found was fascinating. We found that breakfast has a high motivation. Consumers highly motivated, two awards breakfast at McDonald's and very stable, so they can really consistently going there and buying, you know, getting breakfast at McDonald's.

up and down, it was mainly negative. People were clearly moving away. And when we looked at it, it was you know, it wasn't the marketing, it was the product. And the suggestion we had and you wrote that down in twenty eighteen perfectly in the first quarter is that if that's the biggest driver, they're gonna miss or run the risk of missing revenues. And so fast forward quarter and you know, mcnolla comes out announcwer innings, the miss revenues.

They say, the miss revenues because of the Big Mac. And by the end of the year they we did the product and then six came back. So that was a fascinating study.

But can you maybe give us an update on what's going on with plant based meat and the consumer and what could it mean for the recent introduction of cell cultured meat.

was started to fade. And I think that's something which is a learning for every company out there, including self, you know, cell based, cell grown meat and any product, is that you have to understand what is emotionally engaging, what's not. What are the key emotional drivers of your customers towards your product. And what we found is that we know today we knew then that plant bait meat, you know, was built to have the flavor and the

texture of meat, but it's actually quite unhealthy. Maybe good for the environment, but it's unhealthy. But when you come out with a plant based meat and that concept, the first thing is, oh, it's vegan. Vegan is healthy. So merely in the conversation, we saw that it is a dissonance, emotional dissonance between what the product stands for and what

it actually delivers. And we pointed that out and said, look, I understand it is an internal conflict because the product was built differently than what it's what it looks like. So maybe not calling it plant based meat and doing calling it slightly different so it doesn't have the connotation with the vegan of vegetarian community might actually help here. And that started to hurt. And I think this is a great example of why you need to understand your consumer.

And you know, I mentioned to you that maybe outside of the of your your vertical and your interests your industry. You know, another example of a company which completely missed understanding its clients was Peloton. You know, we talked quite a bit about that. So we had a private equity company come to us in early twenty twenty one asking us about the analysis of Peloton, and Peloton did phenomenally well.

They went to become publican now a year and a half before in the late two thousand nineteen, and then twenty twenty, obviously with COVID and the pandemic, everyone stayed home. Revenues went just you know, went, you know, accelerated, and the stock just was on the tear. In early twenty twenty one, they announced it going to open up a second manufacturing plan because the demand was too big. So the question was what happens in twenty twenty one when

the vaccine comes out. COVID vaccine was just coming out late twenty twenty, and yeah, the expectation was that the world will open up again, and so what happens to you know, home equipment, home sports equipment. So we didn't talk to Peloton. We only talked to our client at Private Equity, and we went to the website Peloton's website better understand what is the strategy. And as soon as you looked at the website, it became very obvious what

their strategy is. And the strategy is that to compete against the gyms. They viewed that the gyms would be their biggest competitor. People will go out, the world opens up, people go back to the gym, and so it's all about competing against gym's membership. So everything was around price. Only forty nine dollars a months were less expensive than membership. Overusing. It was around price. It was very honest and by

the way, this makes perfect sense. If you ask people, and you ask the rational mind, would you think about price and Peloton, everyone will tell you it's expensive. It's expensive like Lululemon. For years people said Lulu Lemon is expensive. But here's the issue. When we looked at the emotional profile of conversations around Peloton and specifically around price and how expensive it is in early twenty twenty one, we saw that people clearly talked about it, but nobody emotionally cared.

And that's the key point. It took us exactly three minutes to figure it out. People emotionally do not care about price when they Buipeloton or don't like Peloton. What they do care about is online classes, is instructors, it's the social status. And if you focus on the reasons which are unimportant to your clients, you will miss out on actually what's important to them, and therefore you're going

to lose revenue. So twenty twenty one, we going back to our clients said hey, I think their risks missing revenues big time. And six months later they announce they're going to miss a billion dollars in revenues. And then another six months the CEO was gone and now they look at their company. It's all about online classes and instructors. And that's the same with plant based meats. You have to understand what are the key emotional drivers of your customers, otherwise you miss.

later we came out with the Job Index. There was a lot about the jobs and the silent designation and people understanding what's happening, and it was important for us to measure the public emotional attitude so we can actually

do something about it. I think understanding not just companies, but the society at large, the public at large, better understanding what their emotional policies around key policy issues is incredibly important because we have a tool which can provide that as a social good, so we can actually again politicians, public figures, the media, if they use the tool, they can address the issues which are important to us as

citizens and emotionally engaged. So we actually and emotionally engage in an emotionally intelligent way without technology, so it provides a better outcome.

It's the hot topic of the day. I think it's it's driving tech company valuations here in the first half, so I figured we'd hit on it. In regards to chat GBT, what are some of the opportunities for large language models.

world and professionally, personally really to a different level. And this awareness is incredible and it opens up a lot of opportunities, both of the good side. And obviously there are some risks, but there's no revolution without risks, and nothing gets solved before it's actually here. So now we're here and now we have to face it in terms of opportunities. I mean the opportunities I think short term

are somewhat known. The longer term I think are significant, very significant, because all those large language models are improving agguessively improving not just within the large organization but also within you know, open source developer communities, and so there's there's a lot happening there are There are really two ways to think about this. Let's call it generitive AI. One is depending on the large language model is exactly

what it sounds. It's trying to use training from textual conversations, you know, WI just be pre trained on a very very large data set to become you know, conversational and provide answers like a human being would. Now it's all still heavily statistical. It's like us putting something into the Google search bar, which we have been used for years, where when you start typing, it shows you what else you could mean. It's predicting what it thinks you have

in mind. Large language models or genitive AI is based on large language model. Is really that it's trying to predict not the next word or phrase, but in the sentences and narratives and paragraphs, but it's still a prediction model. It's based on what it thinks, and that's why it's also lascinating. It's making up stuff, which right away is

very similar to the brain. We make up stuff because again the subconscious mind makes decisions, the rational mind tries to make find a reason and narrative, so it makes it up all the time, and we can go into that. But this is fascinating. So that's using generaltve AI to have an interaction with a machine to get answers in a much easier way than it was we were able to be able to. This is a second part of general DEVEAI, which is or AI usage not on a

large language model, but actually on structured data. And that's where also a lot of the usage comes where instead of having a terminal where you look at the data, maybe if a search find you should ask the question, hey,

who is my best salesperson? Or tell me about you know, McDonald's, or targets behavior customer behavior around around the event which was you know a few months ago, and it just spits us the answers and gives you the results in a nice chart format without you actually doing the research. So there's a lot happening depending how you train the models and how you use it, and that will clearly create a lot of efficiencies, effectiveness what we call also

cognitive load reduction. It uses our need to use the rational mind to find the results because it's there. But it will require us to change our definitions of what it means to be a stock picker or you know, a writer or an artist or whatever it is, and so does so it comes with a change, but it has all everything has come with a change. Correct when we started with having computers people who are open arms,

what happens to maths? Now people don't have to learn math, well, they don't have to learn that math, but they have to learn a different kind of logic, and so it takes you to a different level and it enhances clearly the human The capability is productivity and I believe longer term also you know, satisfaction. But it comes with risks, and I think the biggest risk here is not just

how it impacts us as humans in our worlds. They you know, personal as well as the professional in the professional settings, but also the risk in terms of privacy, in terms of security, the risk in terms of ethical behavior and the responsible behavior and all those things have not been addressed yet to full extent as it should, and it's not expected to because as long as the technology isn't out there, nobody feels the need to come

up with policies and guidelines. But now it is, so we really have to put our act together and come up with it otherwise we're the need to a free

for all. And we see a lot of the bad usage of the capabilities like we see today already in terms of cyber security issues and incidents and deep fake issues correct where somebody can pretend I could pretend on Mike Hayleen and talk about a company to buy and short and it's not you, and I'm just making it up, and that has obviously illegal implications, and that's a risk, and that's a risk which todays technology can still somewhat figure out. So we have AI fighting AI to figure

it out. But I think that capability is slowly going away as AI is improving, So we need to find better ways to protect ourselves.

to be some sort of regulation on it. But yeah, it's interesting and it's really interesting to see what happens to the job market job market right with all of the improvements in AI and automation, and you know, what does that mean for workers moving forward?

The first we actual manchat ChiPT came out from educators from teachers was oh my gosh, we're going to have to you know, prohibit the use otherwise we can figure out if the student actually learned it or vote it, or whether it was done by one of the large language models. I think that's the wrong attitude. I think the attitude is this is here. I mean, it's going to happen. Let's figure out how we can leverage that and make sure that our students are even more creative

than they used to be. And so we have to just yes, it's effort. We don't like effort. We don't like to change our status quo, which is by the way, emotional as well. But no, we don't want to change the status quo. And so we're looking to, you know, suppress new opportunities, not understanding that the opportunities are here and they actually have a positive can have a positive

impact if we actually think it so. And so it's a challenge for all of us, everyone, every profession, every vertical to understand what does it mean the fact that we now have a capability which is out there, people are aware, which are being used day in, day out, and how does that What does that mean to society? What does it mean for us? That doesn't mean for me?

So we're just you know, we're aggressively building out our capabilities with every new capability, new functionality which is being which is out there to provide more value to our clients.