Michael Hartmann: 0:24

This is an episode of OpsCast brought to you by MarketingOpscom, powered by all those mo-pros out there. I'm your host, Michael Hartman, flying solo today, but joining me today is my guest, Dean de la Pena from Resonate, a company at the forefront of predictive consumer intelligence. Dean is the VP of Identity, Data Strategy and SaaS and brings a wealth of experience in helping marketers go beyond surface-level targeting to create meaningful, scalable, personalized experiences. So, Dean, welcome to the show.

Dean de la Peña: 0:51

Thank you, happy to be here.

Michael Hartmann: 0:53

Yeah, let's do this. So we're going to start at the beginning, really, because I think the heart of what we're going to be talking about is personalization and what that really means in the context of AI, your world with AI. But when we think about this, how do you define personalization from a marketing context? And maybe what's the difference that you see that, between what people aspire to do and what we actually see in practice these days?

Dean de la Peña: 1:20

That's a great question. I think of personalization as a really fulsome one-on-one conversation, getting to know the person that you're trying to message to, right? So you know, I think about it a little bit as like the holy grail of marketing. It's basically like what, if we were able to have a one-on-one conversation with everyone that we were trying to connect with, everyone that we're trying to engage, right? And if you think about having a one-on-one conversation with every adult in the US and you took an hour for that discussion, you'd learn a ton and it would take you about five times the length of recorded human history, right, right, we don't have that kind of time.

Dean de la Peña: 2:01

So, you know, I think, for really good reason, that's a daunting prospect and because it's daunting, people have a tendency to fall back on what they know, right? So you know, I think the difference between what you know, ultimately we're aspiring to from a personalization context, and what we see in practice, I think people tend to fall back on. Hey, give me a sense for what the demographics are, who you know, what are some of the age and gender characteristics of the person that I'm trying to chat with, some of the deterministic data, and I'll call it a day right and I think what we, you know, that's something that you can get your hands on easily, it's something you can get your head around, but it's not really answering that question of who are you, how can I engage with you?

Michael Hartmann: 2:44

And, at the end of the day, to me at least, personalization is really about adapting what we communicate and how we communicate to the specific person we're trying to talk to. Yeah, with as much context as we understand. I was just kind of smiling for those who are not watching that Cause I was. I was thinking, like most people probably think of personalization.

Michael Hartmann: 3:01

Victory is, uh, you know, inserting first name into your email, your message, right? No, but I think what's really interesting that just struck me in what you were described and you said it from the beginning is it's because I think a lot of people me included, when I think of personalization, probably think of a single communication, right, and you talked about it as in terms of a conversation, as opposed to that. So, which is interesting, because that's like that actually, I think to me like mentally changes how I would think about it. Right, there's, if it's a one time thing, like it feels like, there's like almost feels even more daunting right to use your word because you have to get it right in that one moment, whereas if it's a, if you think of it as one of many chances to try to understand that person, you could like maybe give yourself a little bit of leeway to like don't make assumptions about what you know and you can change how you talk to somebody you know and try to build more understanding.

Dean de la Peña: 4:04

Build more understanding and build a relationship right. Yeah, it's like, if I think about my relationship with brands and I'm a tough cookie it's hard to get me to click into a digital advertisement. It happens, and where I find many of the marketers that are engaging me are most successful is when they really are connecting with me. They know generally what I care about and they're building a message right, and I think historically we've seen that, you know, not from a digital perspective, and and and. Over time you'll see linear tv campaigns, right, and, and. Those campaigns will evolve over time and and. Once they have the message firmly established and they've got the catchphrase in your head and you know people are excited about that, they'll build on that, like I think about the um, uh, many years ago. There's, you know, the bud light commercial about that. They'll build on that, like I think about the um, uh, many years ago. There's, you know, the Bud Light commercial, um, and I'm not affiliated with Bud Light in any way, right, but just I'm thinking about this as an example.

Michael Hartmann: 4:55

So funny Cause I was thinking about a Bud Light series that I just just popped up popped up recently in my one of my social feeds.

Dean de la Peña: 5:02

Yeah, I mean, it's like I remember the. I remember here we go, you know, and if I think about that message, the message of action, and you know, enjoying when yourself and like having a lot of fun, and I remember that once they really established that you know they were starting to transition that into more of like hey, we have a dog and the dog's name is we go, and it's like here we go, and the dog would bring you a beer and everybody's having a lot of fun, and it's that kind of consistent message. If you can do that understanding who the person is you're trying to talk to, you know you're actually building that much more one-to-one relationship and that engagement over time, which is how you delight your consumers, how you, you know, really change how they perceive you and your brand and engage with you over time you and your brand and engage with you over time.

Michael Hartmann: 5:49

Well, and that's, I mean, to me, like this taps into human nature, right, that's how I think we build actual human connection anyway, right, it takes time and it takes some consistent effort to build that, because what you're trying to build is trust, right, and that's a tough thing to do. So I'm curious. My guess is anybody listening to this, any marketer, any marketing ops person, is going to go like, yeah, that sounds right or at least in the right track. Why do you think we've all kind of collectively missed the mark or come below where we think we should be for trying to do personalization?

Dean de la Peña: 6:29

Great question. I think there's two parts to my answer to it. The first is more of a historical view and recognizing that technology is a really important part of it and I think, historically, marketers have been limited in their ability to think about and answer the right questions that create the underpinning for that really strong relationship. Right, because, like, we're basically trying to ask the question and answer are you, you are a specific consumer, michael like, are you in the market for my product? Do we share similar values? Can I engage you on those values? Do you want me I engage you on those values? Do you want me to engage you on those values? Like, is that something that you actually do? Want this messaging and what's the right message for you specifically? Right, and that's been really hard for a long time.

Dean de la Peña: 7:21

You know we've traditionally relied again on data that I'll talk a little bit later about asking the right question and we're kind of asking the wrong question if we're just looking at age and income and I think we've fallen back on some of those characteristics and historically you'd find the regions geographically or you'd find broad segments of consumers that generally met the kind of the vibe right or the set of characteristics that you were trying to engage with. Like you had a strategy. You knew who your consumer kind of was. So let me find a group where a lot of those people probably live, and then I'll go and I'll scattershot, I'll peanut butter my marketing to that group. I love it. Peanut butter, my marketing, peanut peanut butter marketing. Um, and you know, and the idea, and that the idea and that works right. You hope you capture as much attention and interest as you can, but that really falls afoul of the old John Wanamaker quote. I know 50% of my marketing goals work.

Dean de la Peña: 8:22

Trouble is I don't know which half right, right, yeah, and so it's just an inefficient approach. You're not really engaging, and if you don't know the specific individual, you know you're lucky. If you are, you're lucky, not intentional, if you are creating that kind of one-on-one relationship, and I think you know that's the technology side of it. Now, technology has come a long way. Analytics has come a long way, right, and the predictive AI people's ability to create really intelligent machine learning models and predictive AI that's become a reality. Now, right, no-transcript? We're going to have a lot more success.

Michael Hartmann: 9:34

So I mean, do you think that's what differentiates how you approach this Like? If so, like could you like? What do you mean by asking the wrong questions versus the right questions?

Dean de la Peña: 9:43

Yeah, that's fantastic. So there's a really good quote that I think about a lot from a guy named John Tukey. He's a statistician since past, but he wrote a book, I think the Future of Data Analytics back in the 60s, and so this is back in the 60s, right? This is way before you know modern. To the wrong question, which can always be made precise, right? So instead of saying, look, I want to, you know, find the general age group group, like, I know that you know, the people who are engaging on my product are typically 25 to 35 year old female on the West coast.

Dean de la Peña: 10:34

Whatever, that is Right, that's not really the right question.

Dean de la Peña: 10:36

The right question is are you specifically going to engage on my message and be excited about the opportunity to purchase my product, have a conversation with me, to build a relationship with my brand, right? So you know, we tackle that head on using Ray, the predictive AI that we've built over a decade and, you know, more than $100 million at this point of investment in that AI, and we use that AI along with consented consumer online behavior and that lets us really have that one-on-one conversation at scale, right? So the question you asked, like what is the right question In my mind, is really deeply understanding people's intent, their motivations, their values. What makes you tick and what differentiates us is our ability to line that up with their behavior and use AI to scale that so that we have a really good sense for, hey, based on how you act and again, based on consented data right, privacy, protected, careful about that Based on how you're acting, we can make an assessment of what you care about and we've seen really strong results in connecting that.

Michael Hartmann: 11:50

Ultimately, Okay, so I'm a, so I think I'm following the. The pushback maybe not pushback, but I think what I'm hearing, though, is a little bit different than asking the right question. I guess it's what a question are we trying to answer? As opposed to asking the right question to the consumer, right, that's what? But the other part is what I heard you describing what we're looking for. You essentially said we look at behaviors rather than what people tell us. Is that kind of part of it too.

Dean de la Peña: 12:21

A bit of both. We look at behavior to understand, based on what several and I'll talk a little bit about, kind of how our secret sauce works and how we do this, but we ask people what they care about. We talk to the consumer and we also understand how many of them behave and can connect that behavior which we have for everyone, to really understand the intents and motivations of the individuals that we haven't spoken to directly, Right, and so you know to to maybe one way for me to analogize and clarify what I had highlighted about you know, asking the right question, understanding the consumer in a different way than I think we have historically. Yeah, you know, if I think about um, let's say that I shift. I shift from more of a marketing perspective to a sales perspective and I want to sell you, Michael, Like I'm a clothing retailer, a fashion retailer, and I want to talk to you, Michael, specifically about you know, whether I can get you excited about my product. I'm going to have a conversation with you, right and, as we're having today, right, I get to ask you questions about what you care about, understand generally, how you feel, take a look at what you're wearing right, which is going to tell me a lot about.

Dean de la Peña: 13:39

You know your fashion, what you care about. I might, as an example, see you walk out of the gym and if you walk out of the gym, even if you're wearing street clothes, I bet you make a pretty solid guess that you were just wearing athletic gear, that you care about athletic clothing or athleisure clothing. Right, and that's really powerful. The traditional approach would be to look at you from afar down the street I don't know anything about you, I don't know your name and to just get a sense of what you look like, right. How old do I think you are? You know, what's your gender, what zip?

Michael Hartmann: 14:14

code are you?

Dean de la Peña: 14:15

in? What zip code are you in? Like I mean, I see you down the street, right, so I know you're in the general area, but I'd much rather talk to you, learn about you see, how you react to questions that I'm asking, and that's just so much more powerful in how we can engage and connect with right. That connection with the consumer, then, more of that distant view of some of the facts that don't matter as much. You know, when we think about what people care about and how they purchase.

Michael Hartmann: 14:43

I mean, the reason I asked you the question is because I think so. Parts one, I think one I started my career in marketing and in database marketing, so even back then, right, the volume of data that was available sort of stunned me, and it's only increased. Um, but the the bigger thing to me is that I'm I get a little skeptical about the when we ask questions of consumers to get their input, because of two things. One, sometimes people just flat out lie, right, I mean, I think that's the case. We've probably all done it to some degree, just to get past the gate. Or, probably more prevalent is we answer things the way we think that we should, or what we believe we do it, but our behavior actually does something different.

Michael Hartmann: 15:29

The example I go to is if you ask people about how much they care about their online privacy, virtually everyone's going to say, absolutely, I don't want my stuff shared, blah, blah, blah, blah, blah. But then nobody actually reads. You know, end user license agreements for all these online apps that are consuming all this data and generating all these insights about you, right? And so, like, that's why like the trade? Because they're they're consciously or not they're, they're assessing the trade-off of like I'm willing to give up that. What I care about, right, it's not that they don't care about the privacy piece, but on the other hand, right, there's a lot of benefits and convenience that comes with letting that, letting go of that to some degree, so that I can have one click purchase or one click subscribe or whatever. So that's why I was asking the question about are we asking questions of people? Are we looking at behavior or some combination of both?

Dean de la Peña: 16:22

No, I think you raise great points Right and I also don't think you're wrong. You know what people do as opposed to what they say they do or are going to do can sometimes be different. But you know our observation and this is borne out in the results that we get with our clients and their ability to really move the needle on better marketing, more efficient marketing, more effective marketing, higher return on your ad spend right Is that, by and large, you know people are answering questions in good faith, like they're trying to do their best.

Michael Hartmann: 16:51

I actually do think that's true too, yeah, and I see that in when we've had this is more of a B2B context, but you know gated forms for accessing content, for example, and you have optional questions, like. I'm always stunned at how much people still fill that out, and they fill it out in a way that is actually mostly truthful, yeah mostly truthful, and I think you know the other piece of it too is.

Dean de la Peña: 17:13

that's where I get back to why I like that Tukey quote so much right, Better to ask the right question and get the approximate answer than the wrong question precisely. I think there's some noise in that right and with really good predictive AI, with good modeling and analytical techniques, you can sort through that noise and get a really useful value driving answer. That might be a little bit imperfect, right, like we're not necessarily going to get that question right every single time, but again, I would so much rather know if I give you a nudge and I connect with you with my messaging, you're going to buy my product and I know that correctly 80% of the time. I'd way way rather know that than know with a hundred percent certainty that you're male.

Michael Hartmann: 18:02

Right, yeah, no, so I guess that's a good this is. That's a good clarification. I'm glad we kind of wrestled through that so you guys do mostly B2C work right.

Dean de la Peña: 18:14

So we are typically working with marketing agencies and brands, so a little bit more B2B2C.

Michael Hartmann: 18:20

Okay, okay, okay, but ultimately you're helping consumers.

Dean de la Peña: 18:26

We're helping marketers connect with the consumer. That's right. Yeah, we're helping marketers connect with the consumer, that's right.

Michael Hartmann: 18:30

Yeah, yeah, okay. So I just want to make that clarification because I mean, it's not that I don't think it applies to B2B, because I do think many B2B marketers should be thinking more like B2C marketers, particularly when it comes to targeting, messaging, the whole bit, but that's a whole separate topic of its own. But I'm just curious. So, um, okay, I bought into this idea like asking better questions, even if the answers maybe are not as precise. Um is better at better to inform your targeting and messaging. And what? Are you hitting the right people at the right time? It's like what are some of those inputs and signals that help you and your clients identify the people that you know will are better fits for whatever their product or service they're selling?

Dean de la Peña: 19:21

Yeah, absolutely. I mean. So you know, the the most important input again is for a subset of individuals, right, like we're not, we're not, we're not asking 250 million people I just talked about how that would take us, you know, just untenably long to do. But we do ask these questions of consumers, right, what? What are, what are your motivations? You know, are you in the market to buy a variety of specific products? How do you feel about certain issues? Right, more about who you are. We get to that level of depth and then you know, we're also, like, I think, traditionally right, if you're doing that kind of survey and you think, from a market research perspective, you take that and you build out panel insights.

Michael Hartmann: 20:02

Yeah.

Dean de la Peña: 20:03

Doesn't get you that far right, like that's part and parcel of the old challenges with personalization, where, ok, now I've got my panel insights, that helps me guide my creative a little bit. But what I really care about is finding that person and connecting with them and who they are, and that's where that falls short.

Michael Hartmann: 20:19

It kind of gets you to the ability to do a persona, which is an amalgamation of something that tries to get it.

Dean de la Peña: 20:26

Exactly, and so what we're able to do then is with the AI and with you know again, the consented online behavior, like we're not talking, you know we're talking like big data at this point right, billions of signals that help us understand, you know, the behavior across the consumer base in the US adult consumer base, us and then using Ray to connect those dots.

Dean de la Peña: 20:50

And again, like the way I kind of think about that from a human perspective is again being able to assess a lot about you know a friend of yours, or if you meet someone new but you have the opportunity to sit down across the dinner table from them, you'll learn a lot about them, right. You'll learn about kind of who they are in a much better way than just some of the basic deterministic facts. And if you think about what predictive AI is doing, it's making those connections between behavior and underlying intent, motivation, preferences at scale. It sees so much more than we do with our hundreds or thousands of acquaintances and it just is able to develop. Basically, you can think of it as a lot of practice, right, of just being able to kind of link those things.

Michael Hartmann: 21:38

Yeah, it's interesting. So you, you know we can't have a conversation feels like these days without talking about AI. I think when you and I talked before, you talked about something to me combines two things that I haven't seen together a whole lot, although I'm bullish on it. I guess, as you called it, predictive AI, right. So I'm familiar with the idea of predictive analytics, which is hard on its own, and then it sounds like predictive AI is combining that with kind of AI to is combining that with kind of AI to either assist in that or generate different kind of insights based on some sort of an analyst. Talk to me about what that means. Like, what is predictive AI and how are you using that?

Dean de la Peña: 23:12

I'm really glad you asked that question because I think that is. I think it's getting lost in the zeitgeist right now. So I think of predictive AI and generative AI as two sides, two parts of the same whole right. And generative AI is what's buzzy right now. We think of chat, gpt, claude Grok right, all of these different, you know, primarily chat based interfaces where you can ask a question and get back a very fulsome answer, not always exactly correct, but certainly it it.

Dean de la Peña: 23:48

It really helps speed up traditional research, putting ideas together, language Right, and you know that's that's obviously come a tremendously long way. But that generative AI part of the world is. I see that as a tremendous workflow enhancer. It's an efficiency enhancer. It helps to pick up tasks that we used to have to do manually.

Dean de la Peña: 24:16

I used to have to write an email manually. I used to have to write an email manually. I used to have to, you know, put together my thoughts on X, y and Z, or do proofreading manually, right, and you know coding used to have to be done Like you had to get that out of your fingers on the keyboard, right? It didn't. You didn't have quad to help. You know, do 80% of the heavy lifting for you and that's incredibly valuable.

Dean de la Peña: 24:42

But what it doesn't do is it doesn't do what the deep learning, neural net modeling and the you know like the extreme gradient boosting nonlinear modeling that allows you to take these massive data sets and make sense of them and translate that into predictions of who these individual consumers are with a tremendous degree of accuracy. That lets us connect with them where they are. And so, you know, increasingly from a software perspective and not just from our ability to assess kind of who consumers are, but for our ability to help our clients get really efficient, good use out of that information, to connect that directly to the DSP or social media and the digital targeting that you know our clients are able to do. Generative AI has been enormously helpful at sitting on this this Ray asset that we have in predictive modeling to help our clients really, you know, make that happen efficiently, directly, automatically.

Michael Hartmann: 25:36

Yeah, I mean to me when I said I was I've been bullish about that as a potential thing is because I've directly, automatically yeah, I mean to me what I said I've been bullish about that as a potential thing Because when I was in database marketing at a big telecom company but we actually had what today would be called data scientists but they were doing predictive analytics, modeling for different kinds of things like churn, likelihood to buy, etc. Etc. But the way I think about it, as I understood the process right, there would have to be some sort of prediction. They had, like almost like scientific method. They have a hypothesis. You're going to go through a bunch of data, they're going to do some modeling, see if their hypothesis was true and then turn that around into a predictive model. See if their hypothesis was true and then turn that around into a predictive model. The piece that like, the piece that I feel like this AI stuff could do, is not totally eliminate the need for the hypothesis part, but like because it's like they could comb through these large, large volumes of data and look for pattern, identify patterns that we may not otherwise, you know, be able to do without. You know, with, you know, manual efforts, limits on technology and so on, and so to me, like that's, like I'm excited about that as a possibility, I I still think, I still stand by, like I still think you need humans in the middle of it, at least for the near future, because it may.

Michael Hartmann: 27:00

In fact, we had a guest on you know one, one guest on recently who talked about like if you put, if you were to put some of these AI models in for, say, best customers, it's going to tell you like people who returned stuff right, are are great to target, and it's like, well, no, they return stuff. It's not really not great. So, anyway, so that's that's what I'm bullish about that, but I don't know what else to what else to do there. I think, I think I'm curious about that. So you also mentioned to me that you, you, you have a large scale consumer study. You've kind of hinted at that. Yeah, how, like? How is that? How do you tie that together with the predictive AI? And I think you called it Ray, that is, ray, the predictive AI modeling engine.

Dean de la Peña: 28:02

Yes, yeah, so the the survey that we run, so it's the US Consumer Study, it's ours, it's proprietary right and that's what helps us really get deep on understanding of individual consumers. There are a lot of, and really the power of Ray is our ability to connect the dots between this deep understanding of some consumers, broad spectrum behavior and demographics, and an ability to say, all right, for everyone who we haven't asked, or for everyone who we haven't talked to, or for everyone we don't have data on, sort of that dependent variable, that outcome that we're trying to understand, can we actually predict that outcome for everyone else? Right? So that's the key and you know, the consumer study is essentially how we, one of the ways, in many ways the deepest way that we can create some of that truth, that ground truth, data at scale right, where we actually say look like, let's ask you, right, if we don't know. You know what motivates you if we don't know that.

Dean de la Peña: 29:05

You know you are really uncertain about the economy and how it's unfolding or you are totally excited about the direction that you know the economy is taking right now and you feel very confident and sure in your spending habits. You're we don't know that you are about to have significant family milestones and that's going to change your how you interact with the world writ large, including how you purchase and what you care about. We ask right, and again, it's that ability to be able to that gives us a lot of control over the depth of question and the depth of insight that we can create. And again, of course, right and you know, looming in all of this conversation is privacy and the ethics and regulation around making sure that you know we're doing right by the consumer, that we're connecting with them when they want to be connected with and not otherwise. That survey, obviously people choose to take that. They choose to provide us that benefit of understanding and that's an important part of the overall process as well.

Michael Hartmann: 30:09

Gotcha Makes sense, all right. So all this is making sense to me, no-transcript.

Dean de la Peña: 30:38

Yeah, absolutely so. I'll give you one example.

Michael Hartmann: 30:40

You know, obviously sanitized to protect the innocent here, but um, it's Bud Light, isn't it?

Dean de la Peña: 30:43

Bud Light? Yeah, exactly. No, it's not. Um, I will, I will say I'll, I'll give you the negative. This is not. This is not Bud Light. Um, but uh, you know we have worked with um one client in specific where you know they are using the benefit of our one-to-one understanding of the consumer as they are engaging on customer acquisition right. They're trying to recruit a specific type of consumer, like they know, they know where they're strongest, they know where they're weakest and they know who they need to be having a conversation with, right.

Michael Hartmann: 31:16

And so I just how do? They know that. I'm curious Like is it because they haven't analyzed their customer base and know what that looks like, both in terms of like profile, demographic type stuff, as well as other characteristics, maybe behavior-based things like that?

Dean de la Peña: 31:33

Yeah, I'd say you know in in three broad spectrum ways, right? The first is you know they understand the trends in the market in general. So just from a very umbrella strategic perspective, let's say, as an example, you're in the food and bev industry and this client actually is in the food and beverage industry and you know that Ozempic, wegovie, some of these, you know these are increasingly impacting people's relationship with food, how they spend, how much they spend. You know how it changes their habits and their behaviors. Right, understanding that and building that in, there's the second piece of it, which is kind of one layer deeper, which is more of a study of how the demographics around their industry are changing and what they care about. And the third piece is the layer deeper than that, which they're actually using our understanding of the consumer to develop a much more targeted, much clearer analysis of who is still in the market and who's not. So you know, it's not just our ability to connect the consumer. The most important part is our ability to connect the consumer and the brand, but there's also the element of helping the brand actually understand the nuances of that consumer and who is best to. You know, have that conversation with right, but then in enabling them to execute their digital marketing to the right group of people in a much more focused, thoughtful way and to develop messaging that makes sense and is again just more laser focused. It's more engaging, right? Um, they've seen 38% increase in their engagement metrics as a result, right, relative to their incumbent approach, without the benefit of our understanding of the consumer, and, you know, when you think about that, I mean that's a, that's a big number. But it also makes sense because it's the difference between somebody you know, talking at you, right, you don't care what they have to say, it's not relevant to your interests to somebody who, like, really hits you between the eyes with oh my God, I actually really, I really do care about that.

Dean de la Peña: 33:48

I was just thinking about, you know, and so I'll give you an example of my personal life. Um, I am a pretty avid newly a pretty avid cyclist. I live in the city of Chicago and I was walking down the street back to my house one day, two Octobers ago, and there's a bike store that was closing down, and as I am walking past the bike store, as I'm walking up to the storefront on my way home, I was thinking to myself it's a beautiful day. This walk is taking too long. I would love a bike. I really should think about buying one.

Dean de la Peña: 34:26

And I turn my head to the left and I see we're going out of business. All of our frames 45% off. You know, get them while they last. Now, that's purely serendipitous, right? That is luck, right? They obviously, you know they were on hard times and they needed to, you know, shift their business model and so they were selling their bikes at a discount. But that was a great example of right message, right time. And I'm now the proud owner of a weirdly bright blue Bianchi bicycle. And you know what? It's an awesome bike. It's also one of the last few frames that they had in the shop, right, because it was so compelling to me in that moment. That was what I was looking for, I'd had the thought and it just connected the dots.

Dean de la Peña: 35:12

And that's the power of really knowing in near real time what your consumers are thinking. Hey, you know if some of the consumers out there are concerned about impending tariffs, right, and you know they buy a lot of French wine, or they buy products from their home country or a country that is well known for Japanese ceramics. Whatever it might be. I think a lot of people probably purchased ahead of tariffs. Actually, I saw an article in the journal recently about Swiss watches. Swiss watches are not cheap to start with, and if you're adding a tariff to that they're going to get more expensive, and so you actually saw in the economic data an uptick in people purchasing at that moment, and knowing who is and isn't aware of those dynamics, who is and isn't in the market for that, it starts to become pretty easy to see how you can drive 35, 38, 40, 45% increases in row as an engagement by finding that individual right when they're ready to make the purchase.

Michael Hartmann: 37:22

Yeah, makes sense. Two questions are totally unrelated, so let's go with one first. So one, okay. So the idea here, it sounds like, is trying to replicate that sort of serendipitous real life experience to an online digital experience. Can you go a little deeper on how that works?

Dean de la Peña: 37:50

Sure, I mean, it boils down to being able and again given the consent associated with it being able to identify what makes a consumer tick when they are in the process of the you know digital bid, right? So it's like when you're seeing the banner ads on you know your, your edition of the wall street journal or wherever it is that you're online or you're getting advertisements on TikTok or social media, making that connection at that moment and realizing that that's what you care about. And so it's about making this understanding of who the consumer is, what they care about in that moment, how they work, and connecting the dots, kind of at that specific moment where they are ready to essentially consume that or related content. Um, and doing that through the you know the DSP, ssp and the digital marketing process.

Michael Hartmann: 38:48

Gotcha. I mean, are you and is it tailoring messaging to to some degree, or is there sort of like we've got a, maybe not three, messages, but we've got 3000 messages, right, and it's a little more focused?

Dean de la Peña: 39:01

Yeah, I think it's a. It's a question of tailoring messages and it's tailoring timing.

Michael Hartmann: 39:05

Yeah.

Dean de la Peña: 39:05

Okay, and so you know one of the things that we had talked about I think when we talked last Michael was around hey, segmentation versus one-on-one marketing, and I kind of see it as tool for the job right.

Dean de la Peña: 39:16

Segmentation is still really valuable and I think building your segments off of a really deep understanding of individual consumers and building that up into groupings that help you, you know, kind of get a sense for the gestalt um helps you create the creative. It helps you strategize, it helps you maximize your reach. It breaks out the, it breaks out the broader spectrum strategic consumer group you care about into chunks that are manageable to the human brain. Right To your point. Humans are, and will continue to be part of this process. Really important for us to understand how we each you know, how other humans view the world, what's going to land to build that creative process. Like I personally believe, even as a technologist and someone who's been in AI for 15 years, I really believe that humans stay a critical part of that and you know our ability to help them kind of make those connections faster is really the kind of core of the game.

Michael Hartmann: 40:12

Yeah, all right. So my second question is really so this is consumer focused. I'm trying to think of how this would potentially be analogous in a B2B world, and so one of the things in fact, we just talked about this in a recent podcast something like the anatomy of a deal, right. So looking at, yeah, here's a deal we won last quarter. Right, here are all the touch points across sales, marketing, whatever right, including digital ones, and that can be like, I think, your point. That's why I was asking the question about how did that client you talked about understand what a good customer looked like? Right, I think that's the analogous there, and then kind of going from there.

Michael Hartmann: 40:57

Typically, b2b buying doesn't happen by an individual right. Very often it's a group right. So could could something like what you're describing also be adapted to look at it from that standpoint, or is it? Is it really dependent on this um, like ongoing survey etc. That you're doing where you're gathering additional input from people, or do you do you think that individual consumer stuff could apply in the b2b world as well?

Michael Hartmann: 41:27

yes, to the mic drop there, yeah, yeah exactly so, um, I I'm going to.

Dean de la Peña: 41:37

I believe the answer to you know the sort of overarching question of is this valuable in different contexts B2C, b2b the answer to that question is yes. I'm going to reframe it just a little bit by abstracting notion of hey, is it like the consumer survey that helps us create some of this data at scale, or is it, you know, these other pieces? It's more about the principles at play and the technologies of being able to use and it takes a lot, it's hard to develop these modeling technologies, these neural net, you know, nonlinear models, the analytical techniques required to take data set A right, these predictable characteristics of are we likely to win the deal with XYZ business, or who is expected to be a really good business that we want to be working with and we want to, you know, prospect and try to attract from a marketing perspective and the data points that make that so. And so you know, I guess, the questions that I would ask from a B2B perspective and you know I've lived that world in the past more from a sales perspective than a marketing perspective but how do we talk to other businesses and how do we, you know, kind of connect those dots and show the value that we can provide.

Dean de la Peña: 43:00

What makes a good client? You know it's like it boils down to. You know the extent to which their strategy aligns with the product that you're providing. You know, do they? Are you a nice to have versus a need to have for them? And you know what, in general, has been their perspective.

Dean de la Peña: 43:15

Like you know, are they a company that is renowned for finding the best technology and deploying it? Are they a company that is much more careful with their investments and very tight knit? Are they a company that likes to build things themselves? Right? These are all the key data points that I would use in my own head as a human to decide whether that's a good opportunity. And those are the kind of data points that you'd want to be able to collect, broadly speaking, for some of these businesses to help you, as a machine learning expert, build the AI to make those determinations. And so, from that perspective and from our perspective, right, where we are generally most helpful is in this really complex, like we focused on this really complex problem of people, and so you know, to your point, right, the survey is a part of that there's no intrinsic reason why you can't start to collect that kind of information for businesses and apply the same general approach that makes sense, yeah, and that's kind of what I assume for businesses and apply the same general approach.

Michael Hartmann: 44:17

Does that make sense? Okay, yeah, and that's kind of what I assumed. I just was like just because I know a large portion of our audience is primarily B2B and I think it's good for them to hear about some of these things that go on in the B2C world, because the scale is significantly higher, right, just so that it's interesting to me, all right. So maybe one last thing before we wrap up. I mean, you've touched on this a little bit. You brought up the point about privacy and compliance and that kind of stuff. You know clearly, right, this kind of volume of data, there's potential risks and concerns about privacy. Like, how do you handle that? How do you balance that right, between, like, the goals to help your clients achieve what they need to, while also being respectful of the people whose information you've you've got responsibility for?

Dean de la Peña: 45:09

I love that question and in part because I'm a bit of a privacy nut, right. So you know I'm the guy that rejects all cookies all the time, uses the Apple, the Apple iPhone, you know, private relay, proxy, right. Like you know, I operate, you know very much in that, and so I come from the perspective that I really want others to respect my own choices. From that perspective and that's really what it starts with is being respectful, ethical and privacy first, right. So that's step one. You toe that line and in fact, actually we even go further than that because, as we think about the kind of data sizes that you're talking about and being careful with and good stewards of that data, we rely on technology that includes vector embeddings as an example, which basically takes a data set that, even if it's massive, actually, especially if it's massive would otherwise be human readable, and turns that into something that is condensed, actually easier for a machine to use, easier for a model to understand and completely unintelligible to the human. It's gobbledygook, right.

Dean de la Peña: 46:21

So it really starts with, you know, focusing on consented data, right, using data that consumers allow for the use to connect them, because, you know, to your point, right, consumers actually want the value. Where I do give up my privacy rights is Google Maps is a great example. I turn on the GPS and I let them know everywhere that I go and track that in history, because it's extraordinarily useful and as we are helping brands connect with consumers that want that connection, that want that message. We want to make sure that we're doing that. But that starts with making sure that the data that we use is consented Our survey, of course, is double consented and, where there are sensitivities on a state-by-state basis, right where, hey, we're not allowed to use certain data for certain purposes for any reason, making sure that we always have the appropriate constraints and guardrails there to protect ourselves and our clients.

Michael Hartmann: 47:18

That's great. No, I mean, it sounds to me like, really like it's a guiding principle, right?

Dean de la Peña: 47:22

That would be the term for you as an organization, and so that's great you know, michael, actually, on that note, before we close out on that, that topic, right, I think the elephant in the room is that makes it, that makes the um makes it harder, right, because people want privacy, um, it's harder to actually make that connection, it's harder to sort through the data and that's a. That's a real differentiator for us is our ability to still drive the kind of results that you know we're seeing with our clients and to get the, the clarity not always right, right like 80 confidence that we're getting the right answer, answering the right question, but that our ability to do that well and accurately and precisely, I think, really sets us apart in a market where that problem, that problem is increasingly difficult to manage.

Michael Hartmann: 48:09

Yeah, that makes sense. All right, so we do need to probably wrap up here, but just before we move on, is there anything that we like, like you wanted? Like anyone listening or watching this walks away from this like one key point that we may not have covered, that you want to make sure they heard, or we covered everything?

Dean de la Peña: 48:26

I think we've covered about everything. I mean, um, I think, just the the advent of of, you know, data science and how it's connecting to the human experience and helping us, you know, kind of have that more fulsome conversation, that fulsome human conversation, right, whereas really propping up how we as people talk to each other and engage in the right ways at the right times. That's what I'm about and I think that's really it's really cool that we have the opportunity, as resonate, to support that, that focus and that I have the opportunity to talk to you about it today.

Michael Hartmann: 49:03

So fantastic, all right. Well, so let's move. If people want to learn more cause I'm sure we didn't actually cover everything, but like, if they want to learn more or connect with you or hear more about what you're doing, what's the best way for them to do that?

Dean de la Peña: 49:17

You connect with you or hear more about what you're doing? What's the best way for them to do that? You can always find me on LinkedIn. Shoot me an email.

Michael Hartmann: 49:20

Happy to chat. All right, perfect, that sounds great. Well, dean, again thank you. This has been a fun conversation. It's kind of taken me back to my roots and database marketing and consumer stuff, so it's always fun to go and think about that, thanks. Thanks also to our long time and first time guests and listeners, or listeners and supporters. We always appreciate that. If you have suggestions for topics or guests or want to be a guest, you can always reach out to mike, naomi or me and we would be happy to get started on that until next time. Bye, everybody, you.