Latest / Connect To Market / Don't Forget the Human on the Other Side of the Glass: David Stark - Episode # 69

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Don't Forget the Human on the Other Side of the Glass: David Stark - Episode # 69 · Connect To Market

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when you wrap yourself around the cloak of data, it becomes a warm,
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fuzzy kind of blanket and, uh, you should base your decisions from it.
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But you should also remember that you have a gut and intuition.
0:16
Welcome to Connect to Market.
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I'm Casey Cheshire.
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Join the conversation with the marketing leaders driving the
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fastest growing B2B brands.
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We're sponsored by Ringmaster, building B2B podcasts and communities
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to reconnect you with your audience
0:32
cool.
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We're doing this thing.
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Let's do it.
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Let's do it right.
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We're about to get started on a really cool conversation.
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I'm excited to introduce my guest today.
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awesome.
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He is a seasoned marketing leader, thought leader, a marketing thought
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leader, all the like, all of the above.
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Circle that bullet on the test.
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He is all the above.
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He's also in the CTM community.
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You've probably bumped into him on breakout sessions,
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he was also a former radio host, so if he sounds better and more articulate
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than I do on this pod, you'll know why.
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More experience.
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But he is leading programs, and they are generating mentions.
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He is showing up in magic quadrants, and if that has been something
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you've been dying to do, this is the guy to learn it from.
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CMO of Openstream.ai, David Stark.
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Welcome to the show, sir.
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Thank you very much, Casey, for that introduction.
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I'm gonna have to, um, really work hard to live up to the
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expectations that you set here.
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To ask our first question, I need to enlist the help this
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giant blue foam finger right here
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Well, it's,
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you
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he's n- he's number one.
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what is the number one thing that marketers need to do in
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order to connect to their market?
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Yeah.
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It's gonna sound so crazy and basic, but we have to remember as marketers,
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and particularly in this day and age.
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You know, how's that sounding?
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Old right away.
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In this day and age.
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You know, back in my day, we didn't know.
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Right?
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You have to remember that there's a human being on the
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other side of the glass, right?
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And we as marketers get wrapped around the axle easily in, in, in like a
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heartbeat of like, oh, it's our buyer, it's our persona, it's this, it's that.
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Yeah, that's all true, but at the end of the day, there's a living, breathing human
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being on the other side of the glass.
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And if you really start to think about what you do for a living, you're trying
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to connect with that person, right?
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And, uh, the good news is, uh, we're all human beings, so you can very
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easily empathize with that person, or you should be able to try to
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empathize with the person on the other side of the glass and try to
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figure out what is their pain, right?
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And, and I don't think it matters if you're in the B2B space, where I've
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spent most of my universe in, or if you're in the B2C space or someplace in
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between, in the B2B2B2C, whatever world that you wanna come up with, right?
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All those things exist.
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You know, somebody out there is going, "It's my world. Thank you for the
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shout-out." Um, but the reality is there's somebody trying to solve a problem, right?
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Um, and so yeah, that's my number one thing, Casey, is remember there's a human
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being on the other side of the glass
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Why do you suppose we forget about that?
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Why do you-- H- how, how did we get away from that?
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Was it 'cause we stopped drinking bourbon with them in like "Mad Men" days?
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Or like, what how did we lose the humanity side?
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I think that's potentially part of it.
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I, I, I don't think I can completely wash that away.
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Uh, and there is some romance to being able to go out and hang out
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with people and then, uh, you know, commiserating with them and kind of
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reading the non-verbal cues that they're giving off and seeing how they're
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networking and how they're ebbing and, ebbing and flowing kind of thing.
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Um, but how did we get away from it?
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I, I think it's te- you know, some of it is MarTech, right?
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MarTech has been an up-and-coming thing, digital transformations,
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you know, operationalizing your business, et cetera, et cetera.
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Data.
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Uh, we are, uh, you know, crazy with data, right?
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So it's pretty easy to crawl into your marketer's, uh, foxhole and, uh, just
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stare at the data, and then you get into this situation where you're, um,
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dealing with, uh, executives or team members, colleagues, other partners
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in crime in sales or wherever, and you're just trying to justify your
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existence and the validity of your great idea because you're showing the data.
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Now, again, I'm not gonna say data's a bad thing.
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I'm, I'm a huge fan.
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But when you wrap yourself around the cloak of data, it becomes a warm,
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fuzzy kind of blanket and, uh, you should base your decisions from it.
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But you should also remember that you have a gut and intuition.
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Um, and I, I think with AI, uh, which we can also get into if
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you, if you so choose, Casey,
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Oh, yeah
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and, and, and with the, uh, with A- AI now being more of a prevalent capability in
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everyone's toolkit, um, the challenge is remembering the humanity that's out there.
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So you have to actually talk to people.
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One, one thing I always tell, uh, young marketers, uh, um, is, you know,
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carry a bag at some point in time.
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In other words, be a salesperson, right?
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If you have a chance in your career, uh, to change gears and
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be on a quota, it will change your perspective on a lot of things.
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Um, and you will really find out what it takes to, uh, establish a rapport
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and a relationship with somebody.
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Absolutely.
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As someone who has-- Part of carrying a bag is that you carry the pressure
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of that bag, which is you gotta go out there, sell a deal, and bring it home,
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and if you don't, you get paid less than the person cleaning the office, right?
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So,
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Yeah.
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You know, it's like you-- or less than everybody, you know,
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less than the barista downstairs.
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You're gonna get paid nothing if you can't bring it home.
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So there's some pressure, especially if you got families and stuff.
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So yeah, it's almost like this empathy.
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You get that empathy that you want for a customer, but you get that for sales who
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is like your other customer, you know?
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Yeah, exactly.
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I mean, you are s- you're constantly selling a- as a marketer.
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You're constantly selling yourself.
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You're selling your concepts.
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Uh, I don't mean selling yourself like I sold my soul to the,
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you know, corporate devil.
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Maybe you did.
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I don't know.
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But some of us m- have, I mean.
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But the, um, the reality is you are constantly selling.
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You're listening more importantly.
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And, and that's probably part of what we've-- what some people have lost in the
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trans- in, in the, uh, evolution of the marketing career paths and the different
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specializations that exist is, um, you forget to just stop, look, and listen.
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Um, and that's true for what product or service it is that
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you're trying to get out there, and again, remembering the person on
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the other glass is saying things.
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Listen to them.
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Um, it's also true for, um, you know, your career trajectory and,
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uh, any, uh, internal politics that you may be, uh, encountering and
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bureaucracy and things like that.
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Um, it's in working with those other, uh, colleagues to tell them
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that you're right, but not overtly telling it, like shoving it in their
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face like, "I'm right, you're wrong.
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Look how smart I am.
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I'm a, I'm a big, shiny marketer, and you're not." What you're not doing
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many-- in many cases, and certainly I was very guilty of this early in my
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career, and perhaps some of my colleagues today would say the same thing, but
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I'd like to think I've learned over the years, is that you have to know
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when to turn on your ears and really listen to what they're trying to convey.
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So like circling back around the human being side of it, do you have
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any experiences that you recall, any, any stories of, of where
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did connect that human side and it just led to results that, you
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know, no survey, anonymous.digital type thing would've done?
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yeah, there's probably a couple of examples.
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I'll, I'll go a little bit into my way back machine just
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'cause it's a more fun example.
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Um, you know, years ago when I was with a company called IBM, there was a, um…
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We, we were working with business partners during the height of the dot-com boom.
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And for those of you maybe a little, uh, younger with less gray hair on, on
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the roof kind of thing, um, that was really when Google was born, right?
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And a number of different companies were, were born and, and so forth.
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So there was a lot of excitement and money and new capabilities, and
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everyone was trying to figure out, do you say www dot something anymore, or
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do I have to say HT- We-- There was a lot of learning, let's just say.
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Yeah
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and, uh, we were working with the business partner community
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and trying to get people excited.
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So we were partnering with a particular business partner and trying to figure
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out, how do we get people to, uh, engage with both of our businesses
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and generate opportunities, right?
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This is classic marketing stuff.
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Like, I need to generate leads for my sales teams.
9:15
Yeah
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so what we did was a, a face-to-face event, um, where we built it up as a
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teaser, as I will tease it out to you now.
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So, uh, so we physically sent mail to people, uh, as a way to break through
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the noise of email at, at the time, um, which is also something I would
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recommend people, people reconsider.
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Like, how do you break through the noise?
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Well, surprise them with something shiny in the mail.
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Um,
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Yeah
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so we first sent them a, uh, a mysterious invitation from IBM and this company.
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Then a week later, we sent them a, uh, a key, like a, a blank car key.
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And then a couple of weeks later, we sent them a die-cast metal,
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uh, vehicle, a race car, right?
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And that included the final invitation, which is, we'd like you to come join us
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at this, uh, uh, Richard Petty Driving School on, for a, for a racetrack, right?
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Now, because it was IBM and this partner was also pretty well-to-do, we were
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able to afford something like this.
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But the, uh, the point is, we were trying to introduce something that was unique
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Hmm
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and, and interesting to these people that might engage with them at a different
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level than other organizations had.
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So
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Right
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we, brought all these, uh, prospects out to this racetrack where they were
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promised that they would get to drive race cars at speed for, like, the day.
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But part of the, you know, the hook was you have to show up, you
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have to go through the, not only the training for the vehicle, and
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we drive people around the track.
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And I'm, I'm sitting there as, as a young man at the time, watching
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these executives, these very crusty old guys s-start, start to transform
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into little boys again, right?
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Everybody's getting so, so excited about the potential to drive one
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of these crazy cars that most people had only seen on TV, right?
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And, uh, so then we brought them into our presentation room, and we walked them
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through the entire, uh, presentation, the communication, and shared with
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them what we were trying to do.
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Then everybody got a chance to drive, uh, the vehicles, and every one of those guys
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and gals came out of those vehicles with a smile on their face from ear to ear.
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Hmm
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And y- And, and so just that level of human connection, taking them out of the
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day-to-day grind of their business and the pressures they were under, reminding
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them that we're all in this kind of together and we can have fun, uh- And
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that you can trust us to have fun with you while delivering the business value
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that we promised you we would deliver to you, uh, ultimately generated something
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like, uh, $10 million worth of leads or something crazy like that at the time.
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And, and I really only think that that was possible because we lifted
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people up out of their world.
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We asked them to spend an entire day with us doing something really fun.
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I mean, 90% of that day was having fun and bonding with each other and,
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you know, schmoozing and all that.
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And, uh, you know, very little of it was the business portion, but they all
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knew that they were there at our…
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A- as a guest because, you know, we were hoping to make some money with them.
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And, uh, again, we did generate opportunities and,
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uh, leads and it was great.
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It was just a lot of fun.
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It's funny how sometimes the, the best sources and the best channels
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can be the most fun because they're-- it's that human connection fun.
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Mm-hmm.
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know, just, and it… You know what's funny?
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And it also, the value of it continues on afterward, because I'm sure you
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brought back so many, you know, intentionally or not, just customer
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stories and the voice of the customer.
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You just sort of took that mantle on yourself
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Those are, those are memories that you've, uh, unique moments in time that
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you've established with these folks.
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You can establish a rapport and a relationship.
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Uh, anytime in the future, I, I know that when, you know, the salespeople
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would follow up with the, the prospects and be like, "Hey, remember
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we drove those cars together?"
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It wasn't like, "Oh, hey, remember when you gave me your business card at the
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trade show? And I'm just following up because you stopped by my booth." Right?
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It's totally different.
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And I, and I think we run into that trap as well.
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Again, remembering there's a human on the other side of the glass.
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Like, uh, companies will execute, uh, webinars and things like that, right?
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Right
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the webinars sometimes are really, really dry.
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Like, I regularly attend competitor and non-competitor webinars just
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so I can see what people are doing that's kind of cool and interesting.
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Yep
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people get very geeked out about what they're talking about, what excites them.
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Like, the companies are like, "My product is great and you should totally
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listen to my awesome presentation on why my product is great."
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Is that really something that you think is gonna be unique and engaging
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to those prospects as they're getting solicited mercilessly by 100 other
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webinar opportunities just probably for that week or for that month?
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Yeah
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have to work hard to break out of the noise.
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Um, some of that comes to the panelists or the webinar presentors, right?
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Uh, uh, is that a word now?
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It is a word now.
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I'm gonna make it a word.
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It is now.
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Hey, this podcast is nothing but truth, so help us God, right?
14:29
So like
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Well, I did not know that.
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Let me write that down.
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Uh, that's excellent.
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Um, s- so you have to remember that you have to make it
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interesting and entertaining.
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Um, so if you're gonna present really dry, boring stuff like this, you're
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not gonna get any of that enthusiasm.
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That might, might really be possible.
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Um, if you're not excited about your product or service, how are you gonna
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emotionally engage with somebody on the other side of the glass, right?
14:58
Yeah
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a- and people forget, again, you also have to provide a
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certain amount of entertainment value in everything that you do
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Well, you know, that kind of leads me to my next question, which is the famous
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question, the famous framework question.
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If you had to build a connect-to-market strategy from scratch, have no budget for
15:19
ads, what would be your top three moves in order to get in front of and build trust
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with your ideal buyers, your ideal humans
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I think the first recommendation I'd have for myself in that situation would
15:32
be to step back and, and to listen.
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Um, part of that listening is listening internally to your new
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colleagues, your new partners in crime.
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Like, what are you encountering?
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What's worked for you?
15:42
What hasn't worked?
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Like, one of the, uh, the golden rules is typically don't break it, right?
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In the beginning, don't break it.
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You don't know… You might be really smart and really great, but
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the reality is you don't know what the frick you're talking about in
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the beginning in that business.
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As, as, as well-studied as you may be on the topic, on the company, the
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relationships you may have with the people that brought you in, all those
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things, the reality is you just don't know until you're sitting in the seat.
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Um, so listen internally as you are turning your listening microphone onto
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the audience that you believe that this company, this team, this product,
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this service is trying to address.
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Yeah
16:18
do you know about them?
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What are they actually doing?
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Um, you know, what are they saying when you're not there telling
16:24
them what to understand at, you know, 3:00 in the morning?
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So listen to your colleagues, your partners in crime internally.
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Listen to the customers and the prospects and that ICP, um, your, your ideal
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target market, and figure out what it is that they're encountering in the world.
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Um, there's a few ways to interpret that.
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Uh, one is what they're encountering in terms of the problems that
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they're trying to solve for.
16:49
The other is the perception of you as a valid solution or not versus the
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reality of they might not even be able to spell your company name, right?
16:59
Um, and that will immediately give you some actions, some, some information
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to work with, which is, "Oh my gosh, they don't know how to spell my name.
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Oh my gosh, I have a lousy reputation," or, "I have a great reputation."
17:13
Uh, companies are-- We, we have our own… Internally I've listened,
17:17
and they say, "Well, these are our named competitors," but the reality
17:21
is our customers and prospects are shopping three other organizations
17:24
that we don't regularly target.
17:27
You know?
17:27
It's one of those moments when you're new that you're allowed to hold a mirror
17:31
up to the business and be like, "Here's what you really look like." Right?
17:37
Um, and what are we gonna do about it?
17:39
Now, depending on your role and your level, sometimes, you know,
17:41
you have to be a little judicious in how you share that truth.
17:45
Um, but the reality is you will know it and will inform what you need to do next.
17:50
So, um, regardless of your level of budget, in this scenario,
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you said you have no ad budget.
17:57
You have to figure out how to get out there.
17:59
So you could conduct some primary market research.
18:03
"Hey, sales guy, give me your top ten or top twenty or whatever customers that you
18:07
might feel comfortable sharing with me."
18:09
A lot of the sales guys won't do that.
18:12
Um, but you can ask, um, you know, "I'd like to find out why people work with
18:16
us. What do they like? What don't they like about us?" That's all free, right?
18:20
That's just you spending time on the phone or over a Zoom call or whatever,
18:25
uh, conducting some due diligence.
18:26
And, you know, you might need to get some clearance about what you can and can't
18:29
ask, but the reality is you can still hear a lot just by listening, giving them
18:33
Yeah
18:34
one or do-- one or two good questions to prompt people to start talking.
18:38
Um, fifteen minutes, you might even have to-- maybe you lay in a Dunkin'
18:43
Donuts coffee coupon or whatever, uh, but something just to get them talking.
18:47
Um, it'd also be ideal if you could talk to people that chose to no longer
18:51
work with you for some reason, or they no longer buy your product, right?
18:54
You'll learn just as much from them, and they might even be more vocal.
18:58
These are things that you can listen to.
19:00
Um, if you're working with analyst teams, um, spend some time talking with
19:04
them, introducing yourself, making, making your rounds, and hearing what
19:09
they have to say about you, right?
19:11
That you don't know or that other people haven't heard from before.
19:15
Uh, if you're working with a press team, it's a good opportunity
19:17
to engage them, or if you have a press person on staff, even better.
19:21
Or if you are a press person, uh, conduct some, uh, analysis, uh, of the, the
19:26
sentiment that's being shared, the kinds of articles that are being written about
19:29
you, what people are actually saying.
19:32
Social media, another rich repository of information, assuming your business is
19:36
wired for sound social media analytics.
19:39
There's a lot of great information that you can gather from the different, uh,
19:42
social platforms that are out there.
19:44
Um, so you can spend your time gathering information.
19:49
Uh, synthesizing it, trying to prioritize it in some way, shape, or form.
19:54
Um, I think all this is, is, is free.
19:57
That's without you pushing anything net new out there.
20:00
Um, the other-- the probably the third thing I, I'd mention
20:03
only because it's, um, just was make-- it would make sense to do.
20:07
You-- I am going to assume you have a website as a company.
20:11
Um, look at the data there, right?
20:13
What are people actually doing?
20:14
What are your top pages?
20:16
Uh, you know, not only volume and velocity of, of visits and so
20:19
forth, but what are-- what kinds of content are people engaging with?
20:22
What are they not engaging with?
20:24
Um, how healthy is the patient, right?
20:27
And, uh, you might have a really sick patient that nobody's bothered
20:30
to take a look at for a while.
20:32
Uh, you might have a patient that has a ton of potential, but no one has,
20:37
uh, started to tweak the, the knobs and, and, and wheels to optimize
20:42
conversions and, uh, just basically to give that content a, a refresh.
20:48
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21:18
Curious because, like, we have this AI thing swooping in and just taking the
21:24
world by storm, I love just thinking about the, gray area in the middle where
21:29
they, they, they converge and collide a
21:32
little bit.
21:32
And, um, and we've talked a lot about the human side.
21:36
Where do you think AI is making marketing better, and then where
21:40
do you see it making it worse?
21:41
I think it depends on the day.
21:43
Um, but I would say generally speaking, as a particularly powerful collaborator
21:49
for marketers, um, if you've been in a resource-strapped business or a startup,
21:56
um, kind of thing, AI can be a great way to get some sanity checks on things.
22:00
Um, so, and actually I'll, I'll build off the examples that we
22:03
just said, where we're just, we're really gathering a lot of data.
22:05
If you net down what I was sharing, you, you can gather a lot of
22:08
data listening and otherwise.
22:10
Um, AI is a great place to kind of throw it into a blender, right?
22:14
And say, "Hey, AI tool," and again, pick your favorite flavor
22:17
of AI ice cream, I don't care.
22:19
Uh, and say, "I'd like to sh- uh, tie together my, my CRM data outputs with
22:25
these fields, with the social media listening, uh, outputs that I've seen
22:30
with, uh, analyst sentiment, uh, PR records and da, da, da, da, da, and give
22:35
me so- and here's the definition of my ICP, and I want you, AI platform, to
22:40
give me a synthesized list of prioritized actions that you recommend based on best
22:45
practices over the next 30, 60, 90 days."
22:48
Now,
22:49
Yeah
22:51
long enough or have been a business person long enough, 'cause I, I actually,
22:54
I, I believe that marketers aren't marketers, we're businesspeople, right?
22:58
Uh, and I also firmly believe that everybody in an organization works for
23:01
marketing, whether they admit it or not.
23:03
Uh, right?
23:04
Because in theory, we're setting the strategy, the tone, the direction.
23:08
We're feeding the machine what it needs to survive and live, and we're
23:12
also that parent that will tell them, "You've been bad," or, "You've been
23:15
doing really good," before, right?
23:17
Salespeople's, uh, different teams like sales are, are mechanisms.
23:22
They're catalysts to help you to achieve your goals as a marketer,
23:24
not the other way around.
23:26
Yeah
23:27
how's that for a bias?
23:29
So AI, though, not to digress too, too much.
23:32
No,
23:33
AI is a g- so in that scenario, you can use AI to give you some recommended steps.
23:37
You can have AI, uh, help you to understand the 30, 60, 90-day
23:42
plan, uh, to format it into a way that other people will consume.
23:46
But what I was trying to get at before, before I lose the, the thought, as
23:49
I'm known to digress, um, is If you've been a business person long enough, you
23:55
can also smell when it's wrong, right?
23:59
AI gave me these generic three steps or these generic 10 steps.
24:03
Or when I look at it even with my data, it may be-- you may
24:06
initially feel it's believable, but when you really start looking at
24:09
the data points it's aggregated, you're like, "Smells wrong, AI.
24:13
You made up some stuff," right?
24:15
Or, "This is never gonna work within the confines of my organization." So it's a
24:21
great way to organize your thoughts and to come up with some hypotheses or to
24:24
bounce your own hypotheses against it, to aggregate multiple data sources that
24:28
were never meant to talk to each other.
24:30
Uh, it's great at those kinds of things.
24:33
And you can tell if the outcomes you're kinda looking for, maybe not the answers,
24:37
but the format in which you'd like to see the outcome, is generated so that
24:41
you can consume it as a business person, and ultimately, if you're collaborating
24:45
with others in your business, to potentially collaborate with them.
24:49
Um, so I think AI is, is good for that sort of thing.
24:51
Um, AI is a good, uh, sanity check for, uh, information.
24:58
Um, again, I, I've found it really powerful at things like, uh, research.
25:02
So we're talking about ICP.
25:03
Maybe you're showing up at a business that doesn't have an ICP defined,
25:07
right, uh, at all, at least not from a marketer's perspective.
25:11
Uh, that may- they haven't been sophisticated enough, maybe they
25:13
haven't been big enough, maybe the talent that was there never bothered.
25:17
Maybe nobody cared before.
25:18
Maybe nobody ever will care.
25:20
But you might care showing up.
25:22
So how do you develop that ICP?
25:24
Well, you just give it the information.
25:26
"Here's, here's my sketch," right?
25:28
Uh, "Here's my ICP.
25:29
I want it for, you know, companies in North America that meet this profile,
25:33
that are of this size and girth, that have these kinds of titles in it, uh,
25:37
on a Tuesday, and, um, you know, tell me what these folk-- how many of these
25:41
companies are there?" So then I can develop my, uh, total addressable market,
25:45
my serviceable market, my, my TAM, SAM, and SOM, right, from that information.
25:51
And you're starting to get some really refined data immediately from your
25:57
hypotheses, because you need to have some actionable intelligence in order
26:02
to be able to inform the plans that you need to birth in order to help
26:06
your business to achieve its goals.
26:08
Um, you can take that TAM, SAM, SOM and then r-wrap it up against your CRM export.
26:14
Uh, a lot of these platforms now, like, uh, HubSpot, for example,
26:17
has native connectors into Claude.
26:19
You can say, "Hey, Claude, go s- now go sniff my, uh, my HubSpot instance
26:25
for all the companies that match this.
26:28
Hey, Claude, go sniff that and then tell me about all the different sales
26:31
discussions that are tak- how many sales discussions are taking place recently.
26:35
You're not only understanding how many companies you have already in your
26:37
database or identifying a gap that you have in your database, but then
26:41
you can find out are your sales teams actively engaged or not with these, uh,
26:46
people that meet this profile, right?
26:48
So you can learn a lot in a very short period of time with an AI
26:53
system as a catalyst to help you to get from point A to point B.
26:56
Whereas in the past, and this is only going back five years
27:00
now from a marketer's lens,
27:01
Sure, sure,
27:02
years ago, you would have to wait weeks for that information to come together
27:06
if you were lucky, or you'd have to spend tens of thousands of dollars for a
27:09
third party to go do that work for you.
27:11
Now you can do it for 20 bucks a month, right?
27:15
Uh, the risk of using a public, uh, system, uh, one of the, uh, tech titans
27:22
like, you know, again, Anthropics, uh, OpenAIs or whomevers, is of
27:26
course you have to be careful with the data that you give it because
27:29
it's your data and your data becomes their data kind of thing, right?
27:34
Um, so do be careful that you don't violate any secret double secret policies
27:37
or give away information that you wouldn't want otherwise shared, even if these
27:40
companies say that the data is anonymized, uh, in some way, shape, or form.
27:46
So, uh, hopefully that is informative.
27:50
It is, and it really has me thinking my next question, which is like, who are you?
27:55
How do you know these things?
27:57
Can you take me back in time to, like, little you days?
28:01
Little you, David growing up.
28:04
Do you know he's gonna be a marketing leader, doing all these things, teaching
28:08
us the way on a podcast years later.
28:12
Yeah.
28:12
It like?
28:13
Um, you know, I, I was kind of boring, uh, in the grand scheme of things.
28:18
I, I think one of the more interesting things that I ever did as, as a
28:21
young person that helps me today is I learned how to play chess early on.
28:25
Um, chess is a great, uh, teacher for helping you to understand the
28:30
permutations of a decision, right?
28:33
Or what are the-- what are the nine potential outcomes of
28:36
moving my pawn to the next space.
28:39
And you can apply that to business all the time, right?
28:43
And so it helps you to, to think clearly, um, even if I can't speak clearly.
28:49
Um, I think just being inquisitive in general and, and, uh, toying with things.
28:54
I was always kind of creative.
28:56
Um, you know, never did really well in school, at least, uh, not
29:00
before I got to college, because everyone was telling me what to do,
29:03
and it wasn't what I wanted to do.
29:05
Yep
29:07
a bit rebellious in that regard.
29:09
I think going into school was great college because there I was able
29:14
to, uh… They had a program at the college that I went to, um, where
29:18
you could make up your own major.
29:20
Uh, so th-then I decided to combine marketing and advertising into a, into
29:26
a dual-- It was a dual degree, but I was able to combine those disciplines
29:29
and skip over a lot of the basic classes just to get to, like, the good stuff.
29:33
And I initially, when I got out of school, thought for sure I was
29:37
going into the advertising world.
29:39
Um, but when I graduated, there was a recession taking place.
29:43
Um, so it was really hard to get a, a gig, and at the time, I was living
29:46
in, uh, just outside of Manhattan.
29:49
And, um, you know, that was the days before LinkedIn and, and emails.
29:53
And so you were literally like, you'd have to create a resume version.
29:57
You'd have to physically print it off or type it out or print it on your, uh, dot
30:02
matrix printer, mail it out, and pray that somebody would open your letter.
30:07
Or you'd go, uh, almost literally door to door and bring your resumes into New York
30:13
City for me at that time and kind of go to different businesses and prospect them.
30:17
Um- It turned out that advertising wasn't gonna be, uh, very fruitful for
30:23
me i- at that time in terms of income.
30:25
I finally got, like, a job offer.
30:27
I was like, "Yay, thank you, job offer." Um, but it was paying so little
30:31
I couldn't have afforded to commute from where I lived, uh, into New York
30:34
City, and my, uh, my parents were not gonna supplement my income that much.
30:39
Right
30:40
went to a corporate job, uh, working for a, uh, a trade publication.
30:46
Uh, and that was my first real reality check as, as a marketer, uh, especially
30:51
coming out of coll- coming out of college, uh, you think that you're
30:54
a king or queen of the world, right?
30:56
Yes, I know everything.
30:58
And then they're like, "Here, go make some photocopies, man." What?
31:02
Me?
31:02
Do, do you know who you hired?
31:04
Do you know who, who I am?
31:06
And like, and like, "We do. Go make photocopies." Uh, so, uh, but
31:11
then you start to, to learn things.
31:13
At the time, I was one of the guys at the bleeding edge of designing stuff, so I was
31:17
using, uh, gosh, CorelDRAW at the time.
31:20
Bef- this is before, like, Adobe Illustrator.
31:22
school,
31:23
man
31:23
that was old school.
31:24
But I was even older school.
31:25
Like, my part, part-time jobs growing up, summer jobs were, uh, cutting
31:31
Rubylith to do color separation for an old school, uh, newspaper.
31:36
It is
31:37
I would literally, uh, set type manually.
31:40
We'd photographically, photographically create all the copy for an article, and
31:44
we'd paste it with, uh, a wax onto a board and paste it down there one by one.
31:50
We'd hand design ads with tape.
31:52
Like, you go into pick your favorite application, and you say, "Oh, I need a
31:55
two-point border." Well, there was a time where you had to do that with an X-Acto
31:59
knife and sticky stuff and create that two-point border ar-around what you had.
32:04
Um, so all those little ste- And I was also a, uh, photojournalist,
32:08
uh, for that publication.
32:09
Oh, sounds very il-illustrious now looking back.
32:12
But it's, uh, you know, I was able to go out and shoot things in the community
32:16
and get my work published, so I was always trying to apply some creativity.
32:20
And when I got into the business world, in that first gig, I would start to-- I
32:24
was finally able to start applying some of that in a more realistic fashion.
32:28
And I'd always been exposed to technology Uh, my dad was a, a pretty, uh,
32:34
high muckety-muck in, in a business,
32:36
Hmm
32:36
and, uh, he always brought-- Like, he brought home the first compact
32:39
computer that I'd ever seen.
32:41
It was literally the size of a suitcase with a small green screen glowing
32:44
in the middle of it kind of thing.
32:46
And, uh, so I was fortunate that I always got exposed to technology.
32:51
And I decided after my first gig for work of this forest corporation, I
32:55
said, "I wanna be involved in technology somehow." Uh, so, um, I made some moves,
33:03
but before I went there, I went to work for a conference center company
33:07
where I was carrying a bag, right?
33:10
And I was-- So I was, I was on commission.
33:12
I was trying to drive people to book training sessions and
33:14
whatnot at our conference centers.
33:17
Um, I was doing research.
33:19
Uh, we called that mapping a business, so I'd have to understand every in and
33:22
out of a business to understand who the names were in the business unit that were
33:26
actually making these decisions while understanding the environmental concerns
33:30
affecting this business and whether or not they'd be in a moment in time where
33:32
they'd need conference center space.
33:35
And then I designed for that organization a, uh, a database because they
33:39
were doing everything literally on business cards and folders and stuff.
33:42
So-- And this was the early '90s, so it really wasn't-- everything
33:45
really wasn't taking hold then.
33:48
And then I went to go work for a software company, and, um, things
33:51
just started building from there.
33:53
And then I was fortunate enough to get into, uh, IBM a few years later
33:57
and spent almost 20 years there
33:59
Wow, 20 years at IBM.
34:02
IBM also was a great preparation, not only for, like, the business discipline,
34:06
the acumen, and the… A kid from me coming from a, you know, not an, a
34:10
non-Ivy League school, getting to work there was a world-class education for me.
34:13
I appreciated it.
34:15
Uh, but it taught me how to collaborate with others, uh,
34:18
how to think outside the box.
34:20
And you get smarter if you work with smarter people.
34:24
Like, it's, it's a lot more fun to learn on the job than it is to, uh,
34:29
be the one teaching, I would say.
34:32
Mm-hmm.
34:33
And when you get to work with people that did go to Ivy League schools and
34:36
people that did hold PhDs and so forth regularly, I mean, some of that mojo
34:40
would rub off on you after a while.
34:43
Um, so it was very good.
34:44
But, uh, the advice I'd probably give myself, uh, then, uh, versus the ad-
34:50
versus where I am now would, might be, one is to be even more bold, not with how I
34:57
carried my- myself, but in the adventures that I might be willing to take.
35:02
Um, so, you know.
35:04
And that's both for personal life probably and, and professional, right?
35:08
You know, you can, you can afford to take more risks at
35:10
different stages of your life.
35:11
You should take them.
35:13
Take them as agg- as aggressively as you possibly can.
35:16
And everybody does the best that they can at that time.
35:19
Uh, but I think, uh, having a little bit more faith in myself and my abilities
35:24
at that time in my life probably would've served me well, and taking
35:28
just a few, just a few more risks.
35:29
I took risks, but I probably could've been more aggressive about it
35:33
Yeah.
35:34
think if you told that advice to your younger self, you would listen
35:38
to yourself and take more risks?
35:41
Um, it would depend on when I caught me.
35:43
Uh, right?
35:44
So, so if you were, uh, kinda Marty McFly in, uh, Back to the Future and with, with,
35:49
with Doc and zoomed back and I pulled up to myself and be like, "Hey, don't go
35:53
in there," uh, I don't, I, I don't know if I would've been smart enough early in
36:01
my career to listen to older me, right?
36:05
'Cause I would've asked myself, uh, I would've asked my older
36:10
self, "Where did you come from? And you look terrible." You know?
36:16
Like, like, "Where did you come from?
36:18
What did you get to do?
36:19
What did you achieve?" Because, uh, another, um, thing that I experienced
36:24
that was important for me also in guiding myself, you know, irrespective
36:28
of the possibilities of time travel, was, uh, very early in my 20s I said
36:34
to myself, "Here's how much money I wanna be making by the time I'm 30,
36:38
and here's the, the title that I want."
36:40
And every step of my career, once I decided I wanted to go into the
36:44
technology space, was kind of a, a meandering journey along the way.
36:50
You know, what can I pick up?
36:51
What can I learn?
36:53
Uh, how do I take the next logical step in the general direction of this, right?
36:57
And, uh, that, that served me well.
36:59
At least it gave me some sort of a, a focus and objective, and I, and I beat
37:04
my objective, uh, uh, a l- a couple years before I was 30, which was nice.
37:09
Which was nice
37:10
Boom.
37:12
Just goals and goals and goals.
37:13
And so love to… know, what, what are you up to at OpenStream?
37:17
Like, shout out to the OpenStream team.
37:21
Should we keep our eye on it?
37:22
What's, what's
37:23
Yeah, always keep your eye on OpenStream.
37:25
Thank you very much for, for that.
37:27
You know, OpenStream is a terrific, uh, a terrific place.
37:31
Um, I've been at-- I've had the good fortune of working
37:34
with super smart people, right?
37:36
Uh, again, PhDs and rocket scientists are running around inventing, uh,
37:41
you know, the next things that are possible or hypothesizing about the
37:45
next things that are possible in AI.
37:48
Uh, you know, when I first started working, I certainly couldn't say or
37:51
understand what the heck, you know, neuro-symbolic AI meant, uh, or, you
37:55
know, the importance of multimodality or, uh, you know, how conversational
38:00
AI can be applied and, and a whole host of other capabilities and tools.
38:04
You know, when generative AI started to hit the streets, uh, LLMs and,
38:08
and so forth, very few of us really understood that, and I credit all of my
38:13
knowledge to, uh, to the great team here.
38:16
Um, you know, we combine… Today, what we're doing is we're combining multi-agent
38:21
systems with neuro-symbolic verification.
38:24
Uh, so we help to deliver trustworthy, operationally ready AI outcomes
38:30
that experts and customers can ultimately feel comfortable that
38:33
are v-verifiable, explainable, um, actionable information pieces.
38:41
Um, another way to think about what we're, what we're evolving to become.
38:45
So when we were Magic Quadrant, we were Magic Quadrant for conversational AI.
38:50
We were the sole visionaries in the Magic Quadrant for, for, uh, conversational
38:54
AI for two consecutive years, right?
38:57
Uh, so that was really exciting.
38:58
So that's always gonna be a part of how OpenStream thinks and operates and,
39:03
uh, serves well for us, uh, s-serves us well architecturally, especially
39:07
when we talk about collaboration.
39:09
But where we're starting to head now is into this, uh trust layer kind of thing
39:15
for, for an enterprise without giving away too much of the secret sauce there.
39:19
But, um, you know, we work with, uh, foundation models.
39:23
We use neuro-symbolic capabilities.
39:25
Uh, we work with any model, not just founda- frontier models, but
39:28
we, uh, we wrap everything up with a bow, so basically you can really
39:32
trust the outcomes of, of a decision.
39:34
So a lot of AI is, um, what they call, uh, probabilistic, right?
39:40
Which is these are generative AI, AI systems, LLMs, which basically means
39:45
they're guessing what you want to hear.
39:47
They're guessing what the right answer probably is based on a number of
39:50
inputs, but they're guesses, right?
39:51
They don't really know what's right or wrong.
39:53
So how do you ensure that what your AI system internally creates
39:58
for you is actually something that you can trust, right?
40:02
We just talked about a few examples of that throughout my own career and,
40:05
and how you need to scrutinize the information that you give, uh, an AI
40:09
platform and that it gives to you.
40:12
So we use a symbolic, uh, reasoning to ground everything
40:16
that comes out of the system.
40:17
So said i- in a more, uh, straightforward fashion, you have an
40:23
AI system that generates a report.
40:25
Maybe it's a 10-page report.
40:27
That's a lot of pages, right?
40:29
Where is that engine getting all of that information from?
40:32
How much of that is made up?
40:34
If you're in a business that makes multimillion-dollar decisions daily
40:38
or hourly, um, either autonomously or semi-autonomously with a human
40:43
in the loop, without a human in the loop, all those things,
40:46
Mm-hmm.
40:46
uh, you sure as heck better be sure that the information in that report is
40:50
correct, not just factually correct, but correct according to your business
40:54
rules, your processes, your procedures, the things your business might have
40:59
been doing for 20 years, right?
41:00
How do you encapsulate that inside the body of a of an AI thing and have that
41:08
be a repeatable process or repeatable scalable answer over and over and over
41:13
again because, um, you know, if you get that ans- if one link in the chain is
41:18
broken, in the, the truth chain, right?
41:21
Uh, th- it, it just, it's like the old game of, uh, telephone tag, right?
41:27
Where,
41:27
Yeah
41:28
you know, "Hey, uh, what's your favorite ice cream?" "Vanilla." And by the
41:32
time it comes out the other end after 10 other people, it's strawberry.
41:36
Well, I don't-- It's not strawberry, it was vanilla, right?
41:40
The same kind of thing can start to happen in, in, in, uh, in AI.
41:43
So we f- we, we focus a lot of our time, uh, nowadays on helping to ensure
41:48
that the systems we built have this ground truth and that everything is
41:53
verifiable and accurate and so forth, and that you can collaborate with
41:57
it, uh, from a conversational end.
41:59
So a little bit more of a ramble probably than is appropriate, but,
42:03
um, hopefully that makes some sense.
42:05
So should you watch the space?
42:06
You should watch the space.
42:07
We've been a, we're, we've been a bleeding edge company for, for a while.
42:12
Um, we're constantly innovating.
42:15
Uh, our website is about to go through another change, uh, so that
42:18
we can tell that story, that current narrative even more so, and, um,
42:23
we're really excited about the future
42:26
Man, I, I am too, and I think you're wise that you're, you're
42:31
grounding systems in, in truth.
42:33
You know?
42:33
Like it-- You need to build it on a solid foundation so that the, the really
42:39
tough, challenging answers are easy to do if, or are more l- likely to be
42:44
true if one plus one does equal two.
42:47
Yeah.
42:47
I mean, go figure, right?
42:48
Why, why would the math actually math out like that?
42:51
That's crazy, you know?
42:53
Uh, but it's so important that a business, uh, really consider
43:00
whether or not the thing that they're collaborating with is trustworthy.
43:03
Do they understand that on the other side of the glass, the AI does not operate
43:09
like a human being at all, and that most of these systems, uh, the publicly
43:13
available engines are, uh, designed to please you with a pleasing answer?
43:18
Um, and if you've ever had an argument with an AI lately, um, you know,
43:22
you'll see something that smells wrong.
43:24
You'll be like, "That's wrong." It'll be like, "Oh, you're right, Casey.
43:26
I'm so sorry.
43:28
We're not supposed to do that." Right?
43:31
Right
43:32
and, uh, yeah, I wish I knew that like 30 minutes ago, man.
43:35
Uh, well, you know, you, you know, 30 minutes ago I gave you a plausible answer.
43:39
I was conducting research on a company the other day, and I said-- And I knew
43:42
what the answer was, but I wanted to see what the system would come back.
43:44
And I said, you know, "Who's the CEO at this place?" And it came
43:47
back with an answer of a CEO that's been out of the chair for 24 months.
43:51
Jeez
43:53
this was, uh, this was through, uh, Google Gemini.
43:55
Pretty, pretty reasonable, reasonably funded, uh, enterprise, uh, I think.
44:02
And, uh, it was fricking wrong, right?
44:04
But if I didn't know it was wrong, I might have believed it
44:07
because it sounded plausible.
44:09
And so you have to be sure that you scrutinize the outcomes of AI.
44:12
And as a marketer these days, it's really important.
44:15
What you're gonna start to lose over time as a marketer is access to the old guys
44:20
oh, for
44:21
the people that have been there and done that, uh, who can tell you
44:24
right away if that smells wrong.
44:26
Yeah.
44:27
Right?
44:28
I mean, you just get a spreadsheet in front of them, and they'll spend
44:30
some time, and they'll be like, "Oh yeah, that number's wrong.
44:33
That calculation's wrong.
44:34
How did you come up with that calculation?
44:36
Why is that there?
44:37
Where did you get that information from in the first place?"
44:39
Yeah
44:40
are things that you get through a, a conversation with somebody
44:43
who knows what they're doing.
44:44
You are gonna have to get to take on that skill and assume AI is that
44:48
collaborator, but AI only has the experience that you've taught it.
44:51
It only has the instructions and guidance that you've given it.
44:54
Right
44:54
it only has whatever its, uh, uh, i-its, uh, father and, and mother
44:59
in, in AI land have given it, right?
45:02
But you are responsible for your decisions and the outcome.
45:05
So don't get lazy, right?
45:08
You're, you're going-- You can move faster, and you can make more mistakes
45:11
quickly, which I'm a huge believer of.
45:12
Fail forward.
45:14
But at the end of the day, don't, don't get so comfortable with AI in the driver's
45:18
seat that you trust your life over to it.
45:19
It's, it's not ready for that
45:22
No.
45:23
No, it's not, not ready.
45:24
Man, I don't know if you've noticed, we've had our own Back to the Future time warp.
45:29
Like, wow, we have zapped through time so fast.
45:32
I feel like we all have to automatically book another time, and
45:36
we should just, we just, just spend an hour talking about AI and bots.
45:39
You know?
45:40
We did the human side today,
45:42
Let's do it
45:43
you know, let's like, let's totally do it.
45:45
So where can people go if they want to connect with you?
45:48
Uh, they can go to, uh, first they can go to openstream.ai.
45:52
Uh, that would be a great place to start if they want to learn more about our, our
45:55
company and our products and services, and how we might be able to help you.
45:57
They can definitely reach out to me on, on LinkedIn.
45:59
Uh, it's, uh, The David A. Stark, if I remember my trailing,
46:04
uh, identity on LinkedIn
46:07
All right.
46:08
Well, thank you.
46:10
Thank you, David.
46:11
And, uh, yeah, all the t- all the tech and the crazy in the worlds,
46:15
but, uh, appreciate you being on and, uh, see you all next time