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Well, hello and welcome to the e -commerce podcast with me, your host, Matt Edminson.

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Now this is a show.

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All about delivering e -commerce.

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Well, at least trying to help you do that.

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That's what we're here for.

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That's what we're trying to do.

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So do Stay do with us as we talk about all things e -commerce with today's amazing guest Jason wood from specific specific I could Jason you're gonna have to say your name because obviously I I think I've just gone and found one of those words that I just can't say You know, those are random words.

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We're going to be chatting about all things, e -com, but before we do, why not go?

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Check out the e -commerce podcast website if you haven't done so already e -commerce podcast .net Make sure you sign up to the newsletter And we will send you all the notes, all the links, everything from our conversation today or come to your inbox automatically and for free which is amazing.

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Genoa else is amazing today's show sponsor.

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Oh, yes now today's show sponsor is of course the wonderful e -commerce cohort This is our monthly membership group which you can join pretty cheap like 14 bucks a month but you get all kinds of amazing things by being a member.

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including expert workshops delivered every month plus you get to watch the live recording of this podcast yes so whenever I do podcast Just recordings you get to come join in live and ask the guests all kinds of questions.

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So try it out.

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Come check it out ecommerce cohort .com.

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Now, Love in the music, by the way.

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Let's just, yeah, here we go.

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Let's meet Jason, the digital marketing maestro who doesn't just think out Side the box.

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Oh no, he vaporizes it as the trailblazing CEO of the spes -a -sip specificity.

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I don't know why I'm struggling with this word, Jason.

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Is anybody outstuggled with your company name or is it just me?

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You're out of hands.

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You're absolutely for over a year that still stumble over here.

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It's been so good.

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It has made me feel so much better.

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Now Jason is reimagining the marketing game with your dropping tech from things like pickpocket which I want to talk to you Actually, about.

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because I'm really intrigued by this.

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From leading startups to a winning awards, he's the guy who's turning heads and rewriting the rulebook.

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Oh yes Jason, welcome to the show, man.

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And looking forward to this one, how are we doing, sir?

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I'm doing well, man.

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It takes a lot for having me to dab and looking forward to this, man.

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That's great to have you on and we were talking before we hit the the...

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record button there that behind you is the Kansas City Chiefs and you are obviously a Kansas the city chief's fan, which I didn't say before we hit the record button so am I, ironically.

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Oh really, I didn't know that!

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Yeah, when I lived in the States, I lived in North Carolina and they didn't have the Carolina Panthers at the time.

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So your nearest team was...

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what was then called the Washington Redskins.

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Which were, you know, I kind of enjoyed watching them play.

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When the panthers started I've been to the stadium, I've got the shirt and all that sort of stuff, but for some reason it was the chiefs and so they've been to London to play They the played the Jaguars and I took my kids, my two boys, my daughter didn't want to come actually but I took the two boys down to Wembley and watch we were the chief's play here in the UK so I'm a big chief fan.

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Nice.

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I love it.

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Love it.

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Love it.

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Yeah, yeah, absolutely.

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It's always interesting, isn't it?

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American football, we call it, Yorfsle does call it football, we call it American football because Obviously football here has very different meanings, but we call it American football and I just love the game.

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I don't know what it is about that, it.

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um, you know, I wasn't brought up on it anyway, shape or form, but I just got hooked onto it, man, and it was, it was just interesting.

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Well, it's a combination of just like this, this or type sport where it's rough and humble and it hard and yet there's so much strategy and chest to it that it makes for a great game.

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We love it here in the States.

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I mean obviously.

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A big deal here in the US.

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Yeah, massive, massive deal.

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So if you ever get chance to watch the game, do go and watch the game.

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If you haven't seen one already.

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They do they do like three or four games a season now here in the UK and I think they're expanding the amounts different countries from what you stand.

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Yeah, they are.

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It's kind of weird being a lifelong football fan, you wake up in the morning on a Sunday and get your coffee and get the pregame on it.

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We got a game that's live here in an hour.

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4 at 9 30 in the morning.

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You asked time.

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Well, I will be on football at 9 30 in the morning.

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Yeah.

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Get out of my way in England.

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That's why, yeah, the Brits.

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Subscribe again.

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Thank you.

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Well, it just really doesn't feed well into that demographic that likes to consume a lot of alcohol.

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All right, that's good.

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9 30, the morning they're pounding their, you know, they're drinking choice.

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Yeah, which was interesting.

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Javrums during the Yeah, game.

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yeah, absolutely no doubt no doubt Since I didn't even think about that.

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Yeah, that's true.

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It's um No, it's a sport that I thoroughly enjoy and you know one of the other things that amuse me Jason you won't know this but in our system here where we do all a our sort of podcast management for and to better expression.

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Saddath who is the shows producer you did a call with Saddath.

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before we jump onto the call to see how sad I know what's going on you've met her you've chatted to her which is great and sad I've usually writes me quite detailed deeply.

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notes about the guess and what kind of questions to ask and all that sort of stuff.

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And so, Saddha, if I wanted to read this out, she because she's funny what she writes about guess sometimes and so in the notes What was it, uh, said I've said here?

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Matt, Jason knows a lot in capital letters.

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letters, right?

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A lot is in capital letters.

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Feel free to take the conversation in any which direction and I'm sure the audience It's will all clean.

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So whatever you and set I've talked about she came away very impressive.

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Nice, nice, well it's kind of works.

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I think it takes a lot.

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Let me tell you to get that out of the set up.

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So take it, that's for sure.

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So, spess Siv us and specificity specific I'm doing only really sorry specificity and What's your company do?

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How did it get started?

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Let's just jump there and understand a bit about you.

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Yeah, so, you know, express We the point.

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kind of have some core beliefs that really drive everything we do, right?

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So we understand technology changes, add tech technology changes, emerging and what's actually more what's not that all changes the core of what really drives the specificity is an understanding that the more understanding and control market could just have over whom it is they're actually targeting the more successful they can be across everything they do in marketing.

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So It kind of runs, you know, counterintuitive to a lot of the mainstream thinking because we've all gotten so I'm going to say a dick.

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to add tech and social media where we don't have any marketers anymore.

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You know that these marketers are in their early 30s and younger.

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They don't remember the days is of doing data modeling.

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They don't remember the days of really having to root through, you know, personas and convert those into addressable data points and all of that because they grown up in marketing where it's just his platform and you check these boxes and what we've seen as I think an industry is just a fundamental Undeniable understanding that those data points just don't mean what they say they mean all the time and they're growing increasingly diluted somewhat attention.

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And the goal of big tech and tech is always to, you know, grow your spend towards a mass CPM model and not so much much.

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about micro defining the high conversion audiences that we so covet as digital marketers.

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Just define what you mean for those that might not know Jason.

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When you say a CPM model just explain what that is.

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What were you talking about Google?

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Whether you're talking about the meta -swee, whether you're talking about, you know, LinkedIn.

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and programmatic, OTTs, connected TV, DSP, anything that you're talking about, display networks, they all have one thing on common and that is their profit or their revenue.

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I should say is directly correlated to a CPM model cost per thousand impressions so they make their money and derive their them profit by a greater audience size, not necessarily a greater conversion.

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So as marketers, I think that gets lost.

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So, on this all the time, we're always looking for this compressed CPM model as a means of keeping our marketing costs out.

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And I think what we don't understand is that with the iOS, some data and everything is taking place.

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These targeting tilites just don't mean what they mean.

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So what they used to mean, I should say.

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And so that's a loose concoction.

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problem.

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So when you have big, when you have a platform to make money, I'll vote you.

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And as marketers, our ROI is directly correlated to our cost per acquisition.

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Yeah, that means better to find audiences we have more successful we are marketers and branders just want to counter into it to their model yeah yeah it's It becomes in a lot of ways, Jason, if I can put it this way.

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There's sort of The silver bullet the sort of the holy grail isn't it is like how do I target like How do I find my target audience audience?

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and actually hit that target audience rather than just blasting you know ads and necessarily out to the wider universe because it has become More more.

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trickier has become more complicated.

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How do I do that?

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How do I do that?

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Well, I think has become a big question that everyone seems to be asking about now.

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Excuse me, Matt.

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For us, it's just a fundamental understanding of what everybody at the table's goals are.

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And when you understand that, navigating those those goals.

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platforms become so I think a lot more clear on how to do that.

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You know I'm not here to say that oh you know I'm big tech and big social.

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So an ad tech they're all you're trying to just you know screw us over and they're not looking partnered with all of them We need them.

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There's no doubt and upon their targeting or their like audience billbounds or any of that.

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And your eggs are all in the basket of their data.

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I'm actually troubled moving forward as a marketer.

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And that understanding, I don't think is really debatable.

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Matt, I think it's been fairered it out.

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I mean, it started with Cambridge, and and I'm not going to be able to do that.

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Matt had a back then which was just Facebook and really popping the hood and seeing what kind of data they have.

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And compare that.

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to what they make available to marketers and what's their motive.

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Their motive is again, their motive is getting broadening the audience mass oppression because that's how they make money.

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I get why they do that.

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It's a common point of us as marketers and technologists to understand how to navigate that and how to use it.

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In my R -Perview, as I said, tools that are both in emerging tech, but also we're driving some of this stuff back from 15 years data ago.

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modeling and things like that that are really powerful.

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We just don't trust their platforms to go in and Define the audience on those targeting platforms with any of them.

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I'll be have for clients.

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We know we'll do a lot better if we just use the data model.

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the data world and build these audiences outside of ad tech and then convert them into publishable audiences into ad tech.

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There are.

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There we know our spend is relegated to this set of device IDs.

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You're not asking Facebook to make decisions.

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We're not asking Instagram to make decisions.

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We're not asking asking the OTT or any of those programmatic or DSP to make any decisions for us on where to next take that ad in terms of what it seems.

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makes his the best strategy because naturally their business model is part of that.

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That's really interesting.

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You say your whole company then was all about creating the the audiences outside of the ad tech platforms is like how do I do that how do we how do we create those audiences yeah it is He's you rooted in a very healthy acknowledgement that we need them and an even healthier acknowledgement that if we're all being honest.

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We can't trust them.

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I mean, I think if we've all learned anything the last seven or eight years and Digital marketing is that you just cannot Hope believe blinders on and set it forget it with campaigns because you cannot trust big tech to have your best interests in mind.

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They're gonna have their own.

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Yeah, it's powerful.

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for powerful so how do you go about creating these audiences and i'm curious if i for example were any commerce podcast where you talk about e -commerce And I'm just gonna pull out a random thing off my desk.

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I say random.

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There's only three or four things on my desk in front of me And so if you've listened to this show, you'll be going, man, that's not random.

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You always pull this out So I've got I've got to hear myself a little as you can see that they're a little Lego Indiana James right in the horse.

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I don't sell these online, it's just a fun thing to have on my desk.

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But I've got, let's say I do sell online, them online.

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right?

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I'm studying at my e -commerce business.

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How do I go about then, be finding or creating these target audiences rather than just going to say meta and saying fine for me everybody that likes the Lego page you know what sort of things do think I need to about it.

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Well, like a Lego page doesn't make a high conversion audience because first of all, you know, adults and kids alike, you know, play with Lego's, our generation.

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We came up for this.

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And Indiana Jones specifically is going to suppress out a lot of your audience and are in mind craft.

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and all of this and really that's where you really get into it.

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Matt is contextual data layering.

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It's not enough to understand somebody likes the Legos to then sell them back A to particular you.

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piece of leg up right you've got Indiana Jones well there's a demographic appeal you know you had a recent launching last couple years on a remake or I don't know if there's another narration I can see yet.

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So is there an audience play there with the ability to identify people that don't just like Lego so one Lego fans, people who spend money on Lego's, people who collect Lego's, two people that genre -specific like Indiana Jones, and like like that that raiders the loss arc and all of that at three people that are actively buying labels not just that have them in a collection but so there's all these contextual layers and then you have to always put in there intent.

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What's their intent?

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Are they buying labels with frequency?

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Because there's decalmers.

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It's not enough to...

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to hit an audience of likes to product or that you know is going to be amenable to it.

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You've got to identify people that are actively buying it because what you're to serve ads to everybody that likes Legos, you've got to then make decisions within that larger Lego audience.

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Who is it that is likely to buy This the particular like a piece and so for that you need contextual data layering.

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Contextual data layering.

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Which is a great phrase.

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by the way, I don't come across that phrase that often.

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Contextual data layering.

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So I'm assuming Jason rightly or wrongly that this is where your tech can help people because again I'm thinking about you know the young guy or the young girl or the young couple or starting their sort of side hustle business selling products online and they've not got the budget say that I've got you know because I've got an established e -con business.

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with a big ads budget.

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What sort of things do they need to think about with this contextual data layering that's going to work?

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For them just starting out well, you know getting into contextual data layering is not necessarily a startup type of strategy.

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There are certain learnings that have to be understood before you start applying real data model.

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into your marketing that has started up.

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She doesn't know yet.

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I mean, we all consider our in our offices, home offices, or at our, you know, our conference room.

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And as marketers kind to of do do what we think is a high likely conversion audience, but as you know, having a big e -commerce guy the are, that is almost always illuminated to be slightly smooth.

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Who's actually buying I've never got it right yet to be honest with you.

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Yeah.

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Yeah.

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No, I mean yeah, I don't think it about me right I out have a gate, how can you?

201
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Because that stuff, dubbing, this, there's trends and all this stuff.

202
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So I would say to marketers this, in order to understand really what's actually questionable in your business, you have to be able to leverage analytics, right?

203
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And there's all these tools that are free.

204
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You don't have that money, but what you have to also understand is that when you're testing offers, you're testing creatives, what audience.

205
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against is not being presented to.

206
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So if you're in a medic campaign and you're just niv.

207
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Facebook ads and you're doing an A, B test.

208
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on some creative or an offer and you go, wow, this one's really popping.

209
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The big question we always have is with all of the slots built into that data, with all of You you.

210
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ronious slacks that are either diluted or just not present anymore.

211
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Who who who liked it of that audience?

212
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Was it was it I can be take Wamburgini?

213
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So much of their traffic or what digital marketers take credit for, except a teen -year -old boy is going to their website to get a picture for the background of the Like that's a significant audience segment for them.

214
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Is that where you put your retargeting efforts?

215
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Is that where you put your brand's strategy?

216
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No, so how do you define you know the the result of a task if you don't know the audience well And I know who actually liked it was that the 1820 year old You know kids that love the ad and they just love it because they're active on social media and they're more likely to see it and that's Engage or is that high conversion say?

217
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is that who liked it?

218
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And so being able to understand that takes some, just to understand it is you look at your analytics, I think.

219
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Yeah, and checking out that dates.

220
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And it's interesting because One of the things I hear a lot on the show is, you know, when it comes to data, obviously you've got to test this, that test that headline against again.

221
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this headline.

222
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Test that image against that image, that copy against this copy, split test AB test.

223
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I've not heard many people jacen and come on the show and say yeah but what audience are you showing that to?

224
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You know everyone sort of focuses on the things which are kind of say things which which is seen because, you know, headline is easily seen, isn't it?

225
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Whereas the audience is not necessarily that straightforward.

226
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Yeah, well, I mean, it's...

227
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It's so obvious and errant parent and yet it runs so counterintuitive to an understanding we have to have a digital marketer to say that we start digital doing marketing campaigns from the ad serving audience piece forward because we just assume that when we tell Facebook for example that we want to target this audience gasping the ads are going.

228
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Well, we're over here screaming from the sidelines as specificity as, but it's not.

229
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It's really really not I was at the digital marketing world forum based I think in the UK there I'm they they do shows all the over the world world, the world, the world they want to Miami.

230
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And so we're talking to these folks about, about, you know, all of these things.

231
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And what really comes to understand as a marketers cross those data selects are just buttoned up so what we did just as a little case study going into this is I went into face Facebook or my team going to Facebook and say listen listen narrowly my narrowly defined an audience.

232
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So let's go by job title Which as you know not everybody puts their job title, but we just want to serve ad to people with these five or 10 or 12 job titles in these cities.

233
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And let's see, let's look at the engagement metrics and let's just show how obvious We say they don't match up.

234
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So we target five or six cities and marketing job titles.

235
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We had people a thousand miles away, nowhere near at marketing.

236
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marketing advertising or even business replying and commenting on our post.

237
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We're waiting there.

238
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We told Facebook and gave them money and said, you just want to go After after people that have marketing made into marketing director chief marketing officer job titles, how does this gentleman in Tucson Arizona when our campaign is supposed to to be?

239
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be targeted on the East Coast.

240
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This guy was one particular guy.

241
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We tired Vietnam, that variant of veterans.

242
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causes went with this profile nowhere near marketing nowhere near marketing and yet he's commenting on our posts because he didn't understand why got the ad Yeah, we don't either.

243
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So if you think that your ads, if you start your campaign, which is that trust, and well, we know that if we set this up and And matter Google or any of these big tech platforms that's who it's going to you're already losing 30 40 50 % your ads And it's just leaking out the front door, but the big problem matters is it makes your analytics diluted.

244
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It really dilutes the action ability.

245
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of the analytic insight you get from campaigns when the audience is so or so also sloppy.

246
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I mean how can you take action?

247
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action on activity and engagement when half of your audience are 30 % of your audience, depending on the market you're in, it isn't even the right audience.

248
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But man, I really like the the ad because it's orange and they like orange and consumers take action on orange.

249
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So they're clicking the ad.

250
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But this gentleman in Arizona wasn't going to hire us.

251
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as you're marketing, but you're not even close.

252
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Nor did they have just the interest category of ad -tack or marketing or more tech.

253
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So I, for us, you've got to take a step back and start with that piece, the audience.

254
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Who do you want to to see?

255
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serve the ad to and how do you make sure that's where you serve your ad.

256
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So what we're doing is building these audiences outside of ad tag with legally compliant F typically and F. source data where we're modeling for contextual data layers and illuminating that illuminate amenability hobby.

257
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The economic wherewithal just all of these things intergerman to a high -permversion audience.

258
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But then we're converting them into nothing more We're than going to list and device IDs that we publish to add deck and we publish it across the board.

259
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So we have commoditized for our clients these ads.

260
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I take platforms because you know, frankly, I don't know about you, but I don't think any of my clients give a rip if that person saw it on metas, one of metas platforms like Instagram or or Facebook where they thought I'm gonna display add on the 10 speed website they frequent.

261
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I don't think they care.

262
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They want the conversion and they want the right audience.

263
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and if you're accomplishing that, then really you shouldn't care what channel they're seeing it on.

264
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So publishing it to all of them, and then simply allowing that to play out, that's going to feed your on the channel and device much better.

265
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So if I'm understanding this right, Jason, the way that you control the audio.

266
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is you are telling Facebook the idea of the person you're in effect saying to me or whoever these are the people you to need reach as opposed to and that's based on your own research, your own data sources as opposed to saying to meta Find me all these mocked indirects and they just happened to leak stuff out.

267
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We're not giving Matt a list of criteria we would like for them to see.

268
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Present.

269
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and to serve an ad because we know they're not going to pay attention to it.

270
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And even with that, when they are, if you think about this, really just a mechanics of it, with iOS, I said, I have a really killing abstract data here domestically the US over 95 % of consumers have opted out of it.

271
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That is all their second third party data it's gone.

272
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So now they can't do do that with contextual data layers because they were just API -ing them and using you know permissions and things really nefariously get at it.

273
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So consumers said no they We're got but here in the US and as you know we're way behind you guys in terms of data privacy for consumers we're way behind But you know, one of the things that we all have to understand is to be a really hyper target marketer.

274
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Here's one piece of data you never need.

275
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Personally identifiable.

276
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more information.

277
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I don't need any of that.

278
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I don't need your name.

279
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I don't need your data birth.

280
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I don't need any kind of government ID here in the States.

281
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It's so scary.

282
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I don't need any of of that.

283
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I just need to know that this set of devices belongs to a human being that's in the market for this or is showing behavior that they're going to buy something that they're my client.

284
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and a cell or that they're into a certain, whatever the case is.

285
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We just need to know that those devices are in the purview of somebody.

286
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Somebody that's going to take action on a product, can insert the ad about that product and give them that option.

287
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We don't sell data.

288
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We don't make the zero revenue comes There's in.

289
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a specificity for selling data.

290
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Zero.

291
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We don't sell any data.

292
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So you day, I'm, I'm, this is fascinating.

293
00:24:31,848 --> 00:24:39,851
And a lot of ways because you have just said or at least what I've just heard let me preface my this correctly Okay.

294
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That you don't need the name, you don't need the email address, all the things that we've been told as a mob says we need.

295
00:24:46,531 --> 00:24:49,150
You just need it, I think you said a device ID.

296
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So you've got that information and your giving Facebook that information to market to those people or you just buy pass in Facebook entirely.

297
00:25:03,943 --> 00:25:16,006
Well now we look we You know, Facebook's a great place to serve ads, especially for the core demographics spending the most money, you know, it's, it's full of age, you know, 30 to to 54, whatever that age group is to pick on a product category.

298
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And they're there.

299
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I mean, it's, it's, it's, it's undeniable that there's still certain and segments that trust Matt at least Facebook specifically to convert.

300
00:25:25,351 --> 00:25:26,430
So no, we want Facebook.

301
00:25:26,911 --> 00:25:29,191
We just don't, we just when they say, hey, we'll go ahead and for talk to you.

302
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you.

303
00:25:29,604 --> 00:25:31,763
We say no thanks to target these people for us.

304
00:25:32,144 --> 00:25:42,447
And again, at Anderson's Temple, to you know, calculation, what we're really doing as We're a just saying to big tech world everybody that their targeting selects are diluted and they know it.

305
00:25:42,687 --> 00:25:46,326
The messaging they're putting out Facebook just sent an email out Last like.

306
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week, I'm sure you got it.

307
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Terry agency in the world.

308
00:25:49,365 --> 00:25:51,525
Hey, we've got this new AI tool.

309
00:25:51,985 --> 00:25:54,025
And you know, I hope you broaden your audience.

310
00:25:54,185 --> 00:25:54,405
Yeah.

311
00:25:54,525 --> 00:25:55,545
And I don't put anybody.

312
00:25:55,453 --> 00:26:01,693
Either cares about ROI that's going G if I could just broaden my audience I'd be more successful.

313
00:26:01,693 --> 00:26:16,331
Now we're looking at narrowly defined audiences we're looking to understand consumer segments be to be segments and how they're taking action and what what what what works with a segment a versus segment be even under an umbrella of a high conversion audience.

314
00:26:16,450 --> 00:26:17,390
I want to be a little smarter.

315
00:26:17,272 --> 00:26:18,772
then just more people.

316
00:26:19,312 --> 00:26:20,271
Yeah more people.

317
00:26:20,552 --> 00:26:21,411
Yeah yeah yeah.

318
00:26:21,412 --> 00:26:21,911
Yeah it's more people.

319
00:26:21,912 --> 00:26:23,491
More people just never really works.

320
00:26:23,612 --> 00:26:24,312
Does it?

321
00:26:25,532 --> 00:26:32,722
So Someone's listening to the show, you know, there are reasonably sized e -commerce business, turnover a couple of million.

322
00:26:33,717 --> 00:26:40,957
What's, and they've maybe done traditional meta advertising and Google advertising.

323
00:26:41,497 --> 00:26:42,017
What?

324
00:26:41,895 --> 00:26:45,415
That's the sort of the advice for that group of people.

325
00:26:45,575 --> 00:26:47,635
What are some of the sort of takeaways that they can take?

326
00:26:47,835 --> 00:26:50,135
I mean, yes, you're mentioning, you know, check out the make audience.

327
00:26:50,407 --> 00:26:51,547
sure it's going to the right thing.

328
00:26:53,187 --> 00:26:55,967
Look at the analytics, but what sort of thing should I be looking for?

329
00:26:56,307 --> 00:26:58,126
What are some of the next steps?

330
00:26:57,992 --> 00:27:11,292
So I should take well, but before I keep for for people not doing business with specificity not ready to do business specificity and I'll tell you right now technology are to is really focused on serving ads here domestically in the US.

331
00:27:11,653 --> 00:27:11,813
We're not.

332
00:27:12,033 --> 00:27:14,392
We can do ads like through two -blown the .com.

333
00:27:14,440 --> 00:27:20,760
UK and Europe and other countries, but we're relegated again to some flattening of the data.

334
00:27:21,340 --> 00:27:30,080
Not not Because because the data privacy balls are different and we don't have all the the often data that we have here domestically, but the first thing I can tell Mark.

335
00:27:32,066 --> 00:27:38,145
Or if they're not going to come down our road, it's a source, a much smarter data API.

336
00:27:38,083 --> 00:27:40,023
software for analytics.

337
00:27:41,103 --> 00:27:50,134
GA4 is great for a marketer that doesn't have a budget and GA4 is great if you can afford the very expensive version that really pops the hood.

338
00:27:50,754 --> 00:28:00,105
But for the free version, I mean Google inherently is going to show you or illuminate It results more clearly than take place in their ecosystem.

339
00:28:00,945 --> 00:28:06,325
So they just have to select, they say, you know, it's basically just direct traffic.

340
00:28:06,740 --> 00:28:07,960
And what is that?

341
00:28:08,120 --> 00:28:10,059
That's everything you're doing with your digital handspin.

342
00:28:10,560 --> 00:28:13,279
That is that's that's just flight as programmatic connected.

343
00:28:13,400 --> 00:28:14,280
That's all these things.

344
00:28:14,480 --> 00:28:16,040
They don't yet make a living on.

345
00:28:15,866 --> 00:28:19,305
And so it's just lump it into this box that you can't parse it out.

346
00:28:19,586 --> 00:28:28,294
So there's a lot of tools out there for analytics to at least arrive I'm at going to better resolve in terms of your segments channels to know where that put through which coming from.

347
00:28:28,715 --> 00:28:41,820
The other thing is everywhere you have the opportunity to deliver Either through big tech or even outside of big tech through direct campaigns where you really understand your audience, watch those analytics and always layer.

348
00:28:41,747 --> 00:28:50,646
And then, John, suppose everything you're doing a big tech, you'll see these widening of data points that really speak to what's going on in in your life.

349
00:28:50,697 --> 00:28:51,716
your social campaign.

350
00:28:51,857 --> 00:28:58,277
There are ways to manipulate those selects and Facebook, for example, to make your campaigns.

351
00:28:58,198 --> 00:28:59,057
It's performed better.

352
00:28:59,158 --> 00:29:01,818
There's a cottage industry to do that.

353
00:29:01,938 --> 00:29:04,638
You know, here in the US, we have Gary V. We better check media.

354
00:29:04,958 --> 00:29:13,999
And he's talking about just what's been called If to you put out a video and it performs well and you want to keep boasting it, keep moving it.

355
00:29:13,862 --> 00:29:41,416
and drive more revenue out of it than the end of this video since we found that if you put a meme first and then a video and then I'm like wait no Like I'm like the 1990s cheap codes on Nintendo's right forward forward back back to BBA bunch like that's great for Gary Vee who's got the inside I'm trying to track it better but all of us out here we're not friends with the management team that better we don't get the cheek goes ahead and talk so by the time he's sharing it They're done.

356
00:29:41,897 --> 00:29:42,236
There they have.

357
00:29:42,297 --> 00:29:48,996
There are you've been used by the big agencies that have these inside tracks and took for me to understand your audience.

358
00:29:49,676 --> 00:29:56,455
and it takes time to dig through your following profiles and really understand what they look like.

359
00:29:56,708 --> 00:30:02,447
I think that understanding until you're ready to really harness smarter data modeling is at least a start.

360
00:30:03,168 --> 00:30:04,407
Yeah, and I very good.

361
00:30:04,288 --> 00:30:06,148
It's very good insight.

362
00:30:07,567 --> 00:30:11,627
So, what software would you recommend other than GA4?

363
00:30:12,168 --> 00:30:15,028
You mentioned, you know, it's OK, but there are better ones out there.

364
00:30:15,032 --> 00:30:15,388
So What's the problem?

365
00:30:15,372 --> 00:30:25,269
the platforms coming to your mind well there's a ton of them mom and you know to be really frank with you We intentionally remain agnostic I'll stick on all of these issues.

366
00:30:25,269 --> 00:30:27,068
We don't advocate for one versus another.

367
00:30:27,389 --> 00:30:29,968
We advocate for clients that were big believers in it.

368
00:30:30,049 --> 00:30:40,531
And if you really prank if you if you understand How these software's work, they all have like not some of them at multiple, but they all have like a particular thing they're really good at.

369
00:30:40,352 --> 00:30:42,952
a little better than the others and they kind of cut their teeth on that.

370
00:30:43,332 --> 00:30:48,732
So you want to try to partner with a firm that's really specialized in e -colors or in B2B.

371
00:30:48,567 --> 00:30:57,846
or in branding or even vertical market high -end e -commerce versus you know you're more mass volume, $5 product.

372
00:30:57,687 --> 00:31:00,267
like needs 20 million impression campaigns.

373
00:31:00,847 --> 00:31:06,546
So I would say to your homework, we are going to put up on our website later this week a list of some of these software.

374
00:31:06,354 --> 00:31:13,253
Where's the reviews on the average clients over the last six to 12 months, but you know, AI has really changed so much.

375
00:31:13,254 --> 00:31:15,114
Yeah, I'm in terms of what you use and them.

376
00:31:15,535 --> 00:31:16,614
watch not anymore.

377
00:31:16,875 --> 00:31:21,794
It's really rock the boat and I think there's a lot of misunderstanding of AI right now.

378
00:31:22,695 --> 00:31:23,974
Yeah, there is, isn't it?

379
00:31:24,055 --> 00:31:24,515
I need that.

380
00:31:24,393 --> 00:31:33,693
I love how everybody is throwing the word AI onto everything like it's you know I can buy this now because it's you know Indiana like Indiana Jones AI.

381
00:31:35,389 --> 00:31:38,468
If I put AI on it, it makes it magical.

382
00:31:38,649 --> 00:31:40,629
It's going to do something you never anticipated.

383
00:31:41,169 --> 00:31:42,569
Where do you see...

384
00:31:43,488 --> 00:31:51,089
As we're on the topic of AI, where do you see AI going in relation to the type of thing that you're talking about in relation because to?

385
00:31:51,204 --> 00:31:54,903
Facebook have command said, you know, we've now got AI this going to help you target better.

386
00:31:57,444 --> 00:32:04,630
Is that I have mixed feelings about whether The Facebook ever tells me the truth or not but um they go.

387
00:32:06,490 --> 00:32:14,986
It's one of those isn't it but where do you see over the next few years This that whole industry going because of AI some of the things that maybe we should watch out for.

388
00:32:15,747 --> 00:32:30,286
Well I think what people have to understand about AI is that let's take I think these analytics software that are touting and that some of them already do a 9 -10 phase revenue leveraging AI for your analytics and how to You know, right?

389
00:32:30,426 --> 00:32:31,406
It's more conclusions.

390
00:32:31,706 --> 00:32:39,826
They all start with the assumption that the data you're getting out of Facebook and Instagram and threads and TikTok and Twitter.

391
00:32:39,659 --> 00:32:52,303
for X now and LinkedIn and through your programmatic and DSP and all of those and they're assuming that this data is good and from there we're We're going going to to use AI to draw conclusions, but here's a thing.

392
00:32:54,184 --> 00:32:55,683
There's a case studies of this.

393
00:32:55,964 --> 00:33:00,603
If you feed AI, I dumb information is gonna get you dumb conclusions.

394
00:33:01,843 --> 00:33:03,682
Yeah, it'll just work quickly.

395
00:33:03,683 --> 00:33:04,543
Yeah, that's true.

396
00:33:05,543 --> 00:33:08,003
Go with J. Go with J. All right, it's the absolutely.

397
00:33:08,523 --> 00:33:08,543
Yeah.

398
00:33:08,863 --> 00:33:12,483
I have cut my teeth on emerging tech and digital marketing for 20 years.

399
00:33:12,823 --> 00:33:16,600
And it's hilarious to me and that I'm Sure, sure you've got some shared experience here.

400
00:33:17,140 --> 00:33:22,420
Our industry gets grass vinaigular way before usability.

401
00:33:22,367 --> 00:33:24,987
and then everybody flocks to do it like it's a real thing.

402
00:33:25,687 --> 00:33:27,727
So you got, yeah, so you got this analytic tool.

403
00:33:27,727 --> 00:33:29,307
That's great, but your data's still bad.

404
00:33:29,687 --> 00:33:33,928
So what it's going to show you is all the people that aren't relevant They're liking your ad.

405
00:33:34,028 --> 00:33:52,993
Yeah, let's go to more of those but they don't know that's the 17 year olds looking for the iPhone background picture or the Android picture for their For their phone from labor geeky that guy doesn't know the difference it doesn't have that understanding even if you feed it The company's like meh, I'll never pop the hood like your AI tool for your campaigns.

406
00:33:53,374 --> 00:33:55,813
Yeah, on their into their into their ecosystem.

407
00:33:56,054 --> 00:33:58,074
So it's always going to be a hit hard and hope.

408
00:33:57,941 --> 00:34:00,861
and really trust it meta and we don't.

409
00:34:01,041 --> 00:34:03,540
So I just don't call you a single very large company.

410
00:34:03,641 --> 00:34:05,620
Now you're six weeks with a very large company.

411
00:34:05,941 --> 00:34:06,440
So I'm the house.

412
00:34:06,286 --> 00:34:10,606
We really think about partnering with this company because audience ideas really are challenging.

413
00:34:10,846 --> 00:34:12,406
They've got this trade optimization tool.

414
00:34:12,686 --> 00:34:14,785
My great, so you know your audiences are deluded.

415
00:34:14,926 --> 00:34:16,006
You know you're wasting a lot of I ads.

416
00:34:15,968 --> 00:34:27,231
say and you're gonna feed AI all of that data to help you arrive at all of the conclusions based on data you know is bad that doesn't sound like it That is kind of like a great strategy to me.

417
00:34:27,471 --> 00:34:28,830
I've said on the sidelines today.

418
00:34:28,831 --> 00:34:53,034
I for 18 months just watching the market just do what it does with everything new And I'll be frank and I'm just acquired an AI programming company with there is a play with AI real life there's a play that we're making I think there's real danger in the overconfidence people have in their eye and there's a real challenge with the bastardization of communication channels that they are.

419
00:34:53,594 --> 00:35:04,099
That frequency of that per - And since cost model gets flattened something like email, I mean, GI, that's what I'm hoping for is more emails, right?

420
00:35:04,387 --> 00:35:13,487
I think we've got an AI email tool because it unfortunately works and you've got to go where the market goes and it's automated and you know conversions are cheap.

421
00:35:13,330 --> 00:35:13,610
keep.

422
00:35:14,130 --> 00:35:23,169
However, long term, we're all going to end up in a cloud for corporate communication because email is going to get just crushed as a communication channel by AIG.

423
00:35:22,932 --> 00:35:26,132
I mean, you can see a ramp up.

424
00:35:26,192 --> 00:35:28,311
The cost for instance is so low to send email.

425
00:35:28,652 --> 00:35:30,732
Who's not going to pay email right now?

426
00:35:30,832 --> 00:35:31,751
Who's not going to But do it?

427
00:35:31,805 --> 00:35:34,525
yeah, it's a really interesting one isn't it?

428
00:35:34,585 --> 00:35:35,524
How you're right?

429
00:35:36,265 --> 00:35:49,621
I'm a spend I don't even know how on long the start of every day just delete delete delete and you you don't even look at them now because you go with somebody that's not even from a person this is a iran this and you can tell want the world.

430
00:35:49,634 --> 00:35:50,714
to straight off the bat to be fair.

431
00:35:52,114 --> 00:35:53,913
But you're right, I don't need more email.

432
00:35:54,074 --> 00:35:57,453
But my email seems to be, I don't actually have any more emails.

433
00:35:57,284 --> 00:36:18,445
I was getting this year as opposed to last year, I suppose I'd be a really interesting step to know, but yeah fascinating, so but I like this, you know, I It's such a sensible thing what you said AI is not going to solve your problem if you're still giving it crap data and so and use a chat gbt4 to to produce a programming that will automate to me.

434
00:36:18,745 --> 00:36:23,425
Malone is not the same thing as real machine learning when it comes to identifying high conversion quality.

435
00:36:23,623 --> 00:36:31,522
audience that takes a whole different type of programming and a whole different type of programmer and and that's just not to play chat.

436
00:36:32,313 --> 00:36:42,764
GPT4 and just go ahead and say well I'd like to I would like to figure out how to make my house you know energy efficient for five dollars a month and I have a seven thousand square foot house And it'll spin out how to do it.

437
00:36:42,885 --> 00:36:44,165
It's ridiculous and crazy.

438
00:36:44,365 --> 00:36:47,904
And if you understand that that's what AI is going to deliver with bad data.

439
00:36:48,459 --> 00:36:56,878
that it didn't, that I guess it's okay, but it is, it is not doing right now, doing nothing, but really assessing bad data inputs and how to refine Yes, those.

440
00:36:57,367 --> 00:37:13,668
and I guess if you've got the if you've at one end you've got the data as in the client data You figure out who the right target audience is or you've got that information and then you can connect that to the consumers or your customers.

441
00:37:13,967 --> 00:37:17,228
you know, e -com system where they can analyze what they bought and when.

442
00:37:18,448 --> 00:37:21,768
Then I would imagine that I could give you some very interesting information.

443
00:37:22,508 --> 00:37:27,227
Well, I mean, you know, man, I don't want to run over it, but here's a great, uh, by case study.

444
00:37:27,067 --> 00:37:31,986
on the difference between my big texts or getting on what we're doing.

445
00:37:32,547 --> 00:37:33,547
And this is going to commercial.

446
00:37:33,827 --> 00:37:34,967
I'm talking about approach.

447
00:37:34,705 --> 00:37:41,284
So you take an industry like the window industry, window replacement industry here in the Tampa, Sarasota market.

448
00:37:41,845 --> 00:37:50,485
So if you're a window company, your goal with your depending on where you're at the market are we have a client that sells like 50 ,000 dollar plus window jobs.

449
00:37:50,726 --> 00:37:51,005
Oh well.

450
00:37:51,166 --> 00:38:00,973
So naturally they're just hard So to the audience is a consumer audience is you want to suppress out for example if you don't own a home we don't want more content nobody's buying windows.

451
00:38:00,846 --> 00:38:01,806
for the rental property.

452
00:38:02,146 --> 00:38:04,006
Nobody's buying high end windows for the rental property.

453
00:38:04,566 --> 00:38:06,266
And then there's all this value of housework.

454
00:38:06,506 --> 00:38:09,525
When you really get smart with data and you start with all the data.

455
00:38:09,376 --> 00:38:11,795
select that you can then use for analytics.

456
00:38:12,096 --> 00:38:19,390
You arrive at a conclusion that your highest conversion audience in this market forms this client and somebody that That's asks 26 % home equity or more.

457
00:38:19,771 --> 00:38:25,251
That's the one coronary across all segments that illuminates the highest conversion rate and the most cost.

458
00:38:25,057 --> 00:38:36,045
acquisition, you'll never find that select that understanding anywhere in meta, anywhere in any big tech or big app Tech platform, it dates, not even there, they're not even trying.

459
00:38:36,506 --> 00:38:43,030
Because if they know if you do that, all of a sudden your audience went from a million, like, Take the whole consumer 3 million people.

460
00:38:43,371 --> 00:38:45,331
Now we're home owners, now we're a million five.

461
00:38:45,511 --> 00:38:46,890
Now we're homeowners of a certain value.

462
00:38:46,991 --> 00:38:48,111
Now we're 500 ,000.

463
00:38:48,331 --> 00:38:49,051
Now we're homeowners.

464
00:38:48,885 --> 00:38:50,544
There's a certain value, a certain equity.

465
00:38:50,885 --> 00:38:57,004
Now we're down to 115 ,000 people or 140 ,000 people on an annualized basis to focus our ads That's on.

466
00:38:57,013 --> 00:38:57,412
bad dog.

467
00:38:57,613 --> 00:38:58,352
But the conversion.

468
00:38:58,473 --> 00:39:06,283
So the ads that comes way down, the frequency goes up, the cadence gets better because the analytic understanding this is the the audience.

469
00:39:06,664 --> 00:39:06,824
Yes.

470
00:39:07,204 --> 00:39:13,103
And I buy so their behaviors are really informative and informative campaign back in real time.

471
00:39:13,583 --> 00:39:16,337
And so because that's how action Well those analytics we can't.

472
00:39:17,357 --> 00:39:30,238
Yeah, super powerful and you look at that and you go well that makes an awful lot of sense You know, instead of spending money out in advertising to a million people, I'm just going to advertise to 50 ,000 people over here.

473
00:39:30,149 --> 00:39:35,909
Who I know are the exact people I need to advertise to, so I'm saving myself 950 grams worth of advertising.

474
00:39:36,229 --> 00:39:42,990
Plus, my conversion rate is going to be, I imagine and significantly higher and the buy is going to be significantly higher.

475
00:39:43,151 --> 00:39:45,910
So then I'm getting a bigger return on investment and then the management director.

476
00:39:45,748 --> 00:39:47,707
I'm just happy and everyone's happy on that one.

477
00:39:48,328 --> 00:39:50,507
It's like the holy grail of marketing.

478
00:39:51,488 --> 00:40:03,084
And tell me about Well, whilst we're talking about this Jason tell me about peak pocket because I was on the peak pocket website because obviously I would you know inside of something me these notes.

479
00:40:03,244 --> 00:40:06,064
I'm like, pickpocket is just one of really cool name.

480
00:40:07,544 --> 00:40:09,963
And I sort of wonder what that's about.

481
00:40:10,084 --> 00:40:10,804
And then I went on to the website.

482
00:40:11,669 --> 00:40:19,910
I'm like, what you have done, or which I assume I've read in the data is US based only, but what you have done I I think is thought was, really good.

483
00:40:20,668 --> 00:40:27,507
if I've understood this right, Jason, I thought it was quite magical, almost witchy.

484
00:40:27,217 --> 00:40:32,097
which craft like, but just explain what it is for the listener.

485
00:40:32,997 --> 00:40:36,217
Yeah, so pickpock is the self -serve platform.

486
00:40:36,517 --> 00:40:44,328
So it's really hard We're dipping our toe into the water of competing with frankly big tech and doing it with better data.

487
00:40:44,968 --> 00:40:48,247
So right now, PIGPocket is relegated to location based only.

488
00:40:48,408 --> 00:40:48,988
It's in beta.

489
00:40:48,799 --> 00:41:03,867
beta testing right now, we're fusing AI and doing as we speak right now it's relegated to location base so wherein you've got like like geofencing and some of these technologies it's a half a mile big circle or a mile and a half big circle.

490
00:41:04,408 --> 00:41:12,278
Pickpocket is API data sense that arriving and audiences that are location based relegated to circles as small as three feet by three feet.

491
00:41:12,739 --> 00:41:25,296
So you can go ahead and you can put the addresses you want to compete with or the two -on -a -polyty So if you're in a retail space, there's about 15 vertical markets where location just matters.

492
00:41:25,121 --> 00:41:25,940
That was quite a bit.

493
00:41:26,161 --> 00:41:26,300
Yeah.

494
00:41:26,721 --> 00:41:33,761
As an illuminate of a high conversion audience, especially in frequencies, verticals where people, you know, go to a bar they can do silver frequency.

495
00:41:34,381 --> 00:41:38,865
So PickpockerLogs you go and set up those locations in your market.

496
00:41:39,085 --> 00:41:40,405
So here's seven of my competitors.

497
00:41:40,645 --> 00:41:43,385
I'd like to tell them about our Friday night food special.

498
00:41:43,225 --> 00:41:51,584
or whatever drink specials or any it's big, it's scalable and you put them in and then it calls the data and you upload your own ad, you spit it out.

499
00:41:52,512 --> 00:41:56,892
disseminate your own spin model for frequency and link to campaign.

500
00:41:57,113 --> 00:41:58,552
You get to set it up same way you do matter.

501
00:41:58,913 --> 00:42:00,453
The only we promise you is we're not I'm going to.

502
00:42:00,426 --> 00:42:02,786
just going to make a bunch of wild assumptions and grow your spend.

503
00:42:03,306 --> 00:42:07,566
You tell us you want to send 500 bucks for the month on these locations.

504
00:42:07,966 --> 00:42:09,306
One thing we guarantee you.

505
00:42:09,503 --> 00:42:20,580
You will not serve an ad to anybody that did not visit one of those locations in the time period you're running your campaign that we are in team and so it's It's our first move into that market.

506
00:42:20,881 --> 00:42:25,500
We're going to bring in criteria based where you're going to be able to set criteria with contextual data layers.

507
00:42:25,300 --> 00:42:30,359
and then go after it and then it publishes the ads literally everywhere.

508
00:42:30,820 --> 00:42:37,297
It's through an attack platform that then does the the ad placement through device ID only to everywhere.

509
00:42:37,598 --> 00:42:41,717
So it's social, it's programmatic, it's DSP, it's all of that.

510
00:42:43,588 --> 00:42:52,107
And when I saw this, I thought, if I end a restaurant, for example, this struck me as particularly genius.

511
00:42:51,940 --> 00:42:54,780
It's because I could do very high -per -localised marketing.

512
00:42:55,340 --> 00:42:55,600
Yeah.

513
00:42:57,299 --> 00:43:00,979
And using your system and I can go right, I'm just going to go here and here here.

514
00:43:01,116 --> 00:43:09,910
and it could be anything like you say a restaurant a gym tennis club it doesn't it if it's a hyper localized business you could use this system to people target in your area.

515
00:43:10,930 --> 00:43:18,350
And then I thought actually could I as an e -commerce business use this for example on the go back to my Lego Indiana Jones.

516
00:43:19,570 --> 00:43:22,751
Let's to assume in Colorado somewhere.

517
00:43:23,331 --> 00:43:32,773
There is a Lego Indiana Jones conference going on at That's a big exhibition centre and there's 50 ,000 people going to that exhibition.

518
00:43:33,674 --> 00:43:38,269
Could I use your system To to target that exhibition for that period of time.

519
00:43:39,110 --> 00:43:39,950
Yeah, absolutely.

520
00:43:40,250 --> 00:43:43,849
And you can start with last year's attendees and market to them ahead of.

521
00:43:43,690 --> 00:43:44,730
of this year's conference.

522
00:43:45,590 --> 00:44:02,721
So that's a major play with polygon technology correlated device ID is there's a time component to it that allows you have reduced to be a beast space a lot for conferences where you've got like you know you've got companies that go to conferences you know literally It's one of their primary modes of lead generation.

523
00:44:03,301 --> 00:44:15,726
And so we start with last year's attendees, we'll pull all the device IDs that were there last year and that's time period, suppress our competitors, suppress our custodial staff or you know all the staff that they've been going to putting on the conference.

524
00:44:16,433 --> 00:44:25,913
And then from there we arrive at a really robust list of attendees and then you start to market to them going into the conference you pull real time data during the conference.

525
00:44:25,662 --> 00:44:27,301
Conference to add that layer in.

526
00:44:27,922 --> 00:44:34,122
And then, and this is a really important, it's supposed conference follow up because so many transactions take place through e -commerce.

527
00:44:33,915 --> 00:44:42,795
on your Lego model on Monday or Tuesday or in February when it's Matt's birthday and we know he likes Indiana Jones and we know he likes Lego.

528
00:44:43,471 --> 00:44:49,470
And so that's the that's the opportunity there is it does so much more than just Surveyes and so much more than transactional.

529
00:44:49,551 --> 00:44:58,047
It's real audience identification and it's a real target audience the inside the that you can market to in perpetuity to drive conversions and a product like like Lego.

530
00:44:58,907 --> 00:44:59,707
That's wild.

531
00:45:00,327 --> 00:45:22,092
I'm just thinking you know like I Could could follow Coldplay around the United States, for example, and sell Coldplay merch online, and just have all the people that have gone the conference just, you know, We're doing exactly that not with cold play but we're doing that with the band right now on behalf of one of our clients that sells a cannabis product That's a bad down a little bit.

532
00:45:24,972 --> 00:45:26,472
That's a bad down a little bit.

533
00:45:26,472 --> 00:45:27,251
That's a dull with You us.

534
00:45:27,429 --> 00:45:38,488
know controversial spaces because we're not selling the the cannabis cyber saw on the CBD side But that's what we're doing is that they never really You're good following with a band that kind of buys a spokesperson for them.

535
00:45:38,848 --> 00:45:41,868
And we just grab those audiences all over the world, but not all the world.

536
00:45:42,048 --> 00:45:44,228
Keep the location based in Europe, but all over the US.

537
00:45:44,178 --> 00:45:46,977
We pull these audience to go to these concerts.

538
00:45:47,658 --> 00:45:48,697
That's fantastic.

539
00:45:49,098 --> 00:45:49,538
Fantastic.

540
00:45:50,278 --> 00:45:52,758
Jason, listen, I've really enjoyed the conversation, man.

541
00:45:52,831 --> 00:45:56,371
It's given me some whole new ideas, especially for our US market.

542
00:45:56,731 --> 00:45:59,010
So I'm going to be talking to the team tomorrow.

543
00:46:01,491 --> 00:46:01,850
Fascinating.

544
00:46:01,911 --> 00:46:10,911
If people want to find out more about you, about the company whose name I call and pronounce, about pickpocket, which is in name I can pronounce, what's the best way to do it?

545
00:46:11,834 --> 00:46:14,254
I'm going to specificityink .com.

546
00:46:14,714 --> 00:46:16,053
That's the easiest way.

547
00:46:16,834 --> 00:46:19,874
That's best a little bit difficult to spell, so you can go to Jason A. Wood.

548
00:46:19,763 --> 00:46:21,503
dot com as well.

549
00:46:22,023 --> 00:46:25,143
And you can just click on the specificity icon there.

550
00:46:25,643 --> 00:46:26,962
But kick that on social order.

551
00:46:27,043 --> 00:46:30,382
My name is Jason A Wood or specificity or pickpock.

552
00:46:30,112 --> 00:46:33,512
pocket for that matter and then you can find it wherever you are.

553
00:46:33,512 --> 00:46:34,012
Fantastic.

554
00:46:34,472 --> 00:46:34,771
Fantastic.

555
00:46:35,052 --> 00:46:38,452
We will of course link to Jason and Spesson.

556
00:46:38,159 --> 00:46:41,339
This is specificity in the show nights.

557
00:46:41,819 --> 00:46:42,939
I just...

558
00:46:42,939 --> 00:46:43,539
I love it.

559
00:46:43,799 --> 00:46:46,898
Abs, I've never in my life had a word which I can't pronounce.

560
00:46:46,778 --> 00:46:48,677
I don't know what it is about this one.

561
00:46:48,678 --> 00:46:50,097
We practice him for weeks now.

562
00:46:50,178 --> 00:46:51,358
Can I tell you real quick?

563
00:46:51,538 --> 00:46:52,918
I want you to know the specificity.

564
00:46:53,338 --> 00:46:54,358
Yeah, yeah, go for it.

565
00:46:55,167 --> 00:46:57,847
So like I said, I've had other agencies.

566
00:46:58,107 --> 00:47:02,686
I've been in this core of audience ID side of digital marketing my entire career.

567
00:47:02,807 --> 00:47:04,266
I've just been a believer in it.

568
00:47:04,267 --> 00:47:09,552
So when I But was except a what I would talk to prospects about what we do, I would use this phrase all the time.

569
00:47:09,772 --> 00:47:13,612
You can target audiences with absolute specificity.

570
00:47:13,952 --> 00:47:19,739
And so my team started Part to of teasing me are clients that have been with us for years and years started teasing me for using that word all the time.

571
00:47:20,019 --> 00:47:22,659
So when I decided to take our company public, I said, you know what?

572
00:47:22,509 --> 00:47:24,069
I'm calling it specialist.

573
00:47:27,489 --> 00:47:28,889
And why not?

574
00:47:29,429 --> 00:47:32,089
And I'm grateful for the staff that like may me.

575
00:47:32,123 --> 00:47:32,563
component.

576
00:47:33,943 --> 00:47:41,063
Take Your Signals to SPTY by a way on the on the rtcq gosta from haven't you found it taking your company published?

577
00:47:40,854 --> 00:47:49,253
because I mean that's not as I mean I've served on one public board before and in the UK the legislation is horrendous for that that.

578
00:47:49,304 --> 00:47:58,204
but um but yeah I have you found that going public as a as a company you know it's a lot I mean capital Markets more are really tough.

579
00:47:58,344 --> 00:47:59,244
They're a snake pit.

580
00:47:59,484 --> 00:48:14,154
I mean, I'll just be one of the guys out here because we don't really realize so much on capital markets We go after individual investors because we We're won't we trying to build more of a team of investors than just people looking at cash in cash in cash out and all that make these equity place but capital market.

581
00:48:13,927 --> 00:48:19,847
Or snake bit everybody's gonna promise you the world everybody's gonna do this to do that We had a guy come to the table.

582
00:48:19,847 --> 00:48:20,306
Yeah, man.

583
00:48:20,507 --> 00:48:26,179
We're all in it to Bill I've got three other funds and then you I'm know a cap of markets and stuff right now and the age of bulls out.

584
00:48:26,420 --> 00:48:28,400
I guess it's just so uh, species.

585
00:48:28,760 --> 00:48:40,295
Every eye hard guy in the world will tell you we can get right at You the know that retail investor likes to microcaps face and likes martycken on it really how are you doing that since we don't have after i can date anymore.

586
00:48:40,735 --> 00:48:41,795
Yeah tell me how you doing that.

587
00:48:41,656 --> 00:48:44,376
I can do it, but you can't do it.

588
00:48:44,556 --> 00:48:45,776
It's tough.

589
00:48:45,976 --> 00:48:47,956
It's the regulations are on us.

590
00:48:50,588 --> 00:48:58,247
But you know it gives you access to capital markets and if you want to make a way and if you want to fund heads with big tech you better be able to build a workshop.

591
00:48:58,067 --> 00:49:01,186
just to do it and that's why we took her company public.

592
00:49:01,347 --> 00:49:04,647
We've got it for proprietary advantage right now with marketplace.

593
00:49:04,947 --> 00:49:05,607
That's a big boy.

594
00:49:06,207 --> 00:49:07,047
Yeah, nice fat Thank place.

595
00:49:07,108 --> 00:49:08,587
you for playing, but check it out.

596
00:49:09,008 --> 00:49:12,748
And we will of course, like I say, link to all this information in the show notes.

597
00:49:13,188 --> 00:49:14,928
All you can find it all on the website.

598
00:49:14,818 --> 00:49:17,058
e -commerce podcast .net.

599
00:49:17,558 --> 00:49:21,538
Listen Jason thank you so much for joining me man thoroughly enjoy the conversation.

600
00:49:22,478 --> 00:49:23,857
It's been great always a to nice day.

601
00:49:23,851 --> 00:49:25,691
connect with a fellow chief's fan as well.

602
00:49:26,051 --> 00:49:28,771
So yeah, absolutely, absolutely.

603
00:49:29,571 --> 00:49:31,590
Brilliant, thank you, thank you, thank you.

604
00:49:31,633 --> 00:49:32,033
Thank you.

605
00:49:32,233 --> 00:49:33,052
Thanks for having me, Matt.

606
00:49:33,313 --> 00:49:34,553
No, I didn't.

607
00:49:34,553 --> 00:49:35,732
Great, great, great, great.

608
00:49:35,893 --> 00:49:38,853
And also a big shout out to the shot, the show sponsor.

609
00:49:39,033 --> 00:49:39,973
I've just lost my ability.

610
00:49:39,801 --> 00:49:44,540
So, please talk about anything that e -commerce co -hort, check out e -commerce co -hort .com.

611
00:49:44,641 --> 00:49:52,288
If you fancy joining that membership grip and if you're an e -commerce I should probably should check it out because it is a little awesome pot of gold to be a member of.

612
00:49:52,389 --> 00:49:52,849
Yes it is.

613
00:49:53,229 --> 00:49:58,008
Now be sure to follow the e -commerce podcast wherever you get your podcast from because we've got some more great.

614
00:49:57,912 --> 00:50:01,751
conversations lined up and I don't want you to miss any of them.

615
00:50:02,192 --> 00:50:16,741
And before I wrap up today's episode, let me take a moment to invite you or maybe somebody you know to be a part The of the show, if you're an e -commerce entrepreneur or an expert and would like to share your insights with our audience, we would love to hear from you.

616
00:50:16,602 --> 00:50:26,014
Well, like I say, if you know someone who would make a great guest, send them our way, just head over to the website ecommercepodcast .net I've lost it.

617
00:50:26,314 --> 00:50:29,213
e -commercepodcast .net and get in touch.

618
00:50:29,774 --> 00:50:32,193
And in case no one has told you yet.

619
00:50:32,051 --> 00:50:34,631
Today, let me be the first person to tell you.

620
00:50:34,791 --> 00:50:35,750
You are awesome.

621
00:50:36,070 --> 00:50:36,451
Yes, you are.

622
00:50:36,571 --> 00:50:37,230
Created awesome.

623
00:50:37,751 --> 00:50:38,491
It's just a burden.

624
00:50:38,771 --> 00:50:39,531
You have to bear.

625
00:50:39,711 --> 00:50:43,383
Jason, since got a bear it, I've got a bear it, you've got a bear it as well.

626
00:50:43,723 --> 00:50:47,402
Now the e -commerce podcast is produced by Aurean Media.

627
00:50:48,101 --> 00:50:52,300
You can find our entire archive of episodes on your favorite podcast app.

628
00:50:52,741 --> 00:50:55,381
The team that makes this show possible is the wonderful.

629
00:50:55,214 --> 00:50:58,594
before Sad After Bain Honours, we've talked about Antannu Herpselec.

630
00:50:58,654 --> 00:51:06,671
Our theme song was written by Josh Edmondsson and as I mentioned if you'd like to be the transcript or note, set over to the website e -commercepodcast .net.

631
00:51:06,892 --> 00:51:13,252
Where coincidentally, you can also sign up for the newsletter and get all of this good stuff direct here in box, totally for free.

632
00:51:13,282 --> 00:51:13,522
free.

633
00:51:14,282 --> 00:51:16,401
That's it from me, that's it from Jason.

634
00:51:16,602 --> 00:51:17,962
Thank you so much for joining us.

635
00:51:18,322 --> 00:51:20,642
Have a fantastic week wherever you are in the world.

636
00:51:21,142 --> 00:51:21,862
I'll see you next time.

637
00:51:22,302 --> 00:51:22,761
Bye for now.

638
00:51:24,600 --> 00:51:29,540
If all went by will you buy tomorrow's original version?

639
00:51:29,540 --> 00:51:32,780
whooshing Who's MUSIC that?

640
00:51:32,780 --> 00:51:33,039
Oh what?

641
00:51:51,023 --> 00:51:55,251
MUSIC you