Latest / The Prompt / Ep. 587 | Beyond monolithic martech: how composable B2B marketing unlocks real AI impact

Transcript

Ep. 587 | Beyond monolithic martech: how composable B2B marketing unlocks real AI impact · The Prompt

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This is on base your one stop shop for solving your most
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pressing B to B go to market challenges.
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Each week, host Chris Moody and Paul Gibson talk to sales and
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marketing leaders to get you in depth insights and creative
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strategies to set your revenue teams up for success.
0:18
Everyone, welcome back to the On Base podcast.
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I'm your host, Chris Moody, and we're going to jump in today and
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talk about something that we all deal with, and we know this
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problem well. Most B2B marketing stacks are
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connected but not often coordinated.
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And we're going to jump in and discuss composable B2B marketing
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and why orchestration, not just more tools, never just more
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tools, hopefully is what separates high performing go to
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market teams from the rest. And we have an incredible guest
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to carry us through this conversation.
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Joining us today is Dan Rosenberg, founder and CEO of
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Octane 11 and one of the clearest thinkers on how modern
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B2B teams design flexible multi channel strategies that actually
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scale. Dan, thanks for your time today.
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It's great to have you I'm. Glad to be here.
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Awesome. One of the best headlines I've
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ever written when I was an analyst was technology alone
1:11
will not solve your problems, right?
1:13
Like it was kind of the notion of what we're going to hit on
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today. So I know we'll tap into that.
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And you've spent a great career across adtech, martech, data and
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now AI. We were talking about that
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earlier, some of your moves. But from your perspective, what
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feels fundamentally different about the moment we're in right
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now in B to B marketing versus 5 or 10 years ago?
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It's an awesome time to be in marketing right now.
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I mean, AI is, is finally really here in a real way and there's
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so many amazing tools and techniques.
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So it's, it's really fun. But I would say that it does
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feel a little bit like incremental right now.
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It's kind of like when you build like a campfire, you've got a
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big pile of wood and you've got like little fires you're
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lighting around the side to kind of catch it all on fire.
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And you've got like all these point solution tools that you
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use in marketing that are like like those little fires, Like
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everything's getting AI enabled content creation or video
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snippets or voice overs or strategy and all that.
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And it's like some of those fires are starting to catch on,
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but it's not like a whole on blaze yet.
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That's kind of what it feels like now that things are
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starting to catch on. Like we're using AI for our own,
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you know, our own marketing and our clients are definitely using
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it. But I think where we're headed
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is it's going to become the whole thing.
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I mean, I think the AI tools, when you think about the AI
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tools that you're using, like when do they start to get
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connected where you've got like you all your marketing data and
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it's connected to that one-on-one creative and across
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all your channels and performance tracking
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optimization, like all of that, definitely like human in the
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loop for strategy and curation and like the gut check of like,
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is this a good idea or not? But all that busy work is, you
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know, I think it's going to be amazing to see all that get
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really automated and that's when it's going to be really fun.
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That's going to be the big like bonfire.
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And that's kind of where we're headed.
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And actually like that's what we're building, not a 11.
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Like we built that data layer that connects all the different
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multi channel B2B marketing tools and lets our clients like
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really start using AI for analytics and decision making
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across everything they're doing. And they can do it now and it's,
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it's amazing. And it's like it's only getting
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better. And it's like all super
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exciting. So I think it's a great time.
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Yeah, I totally agree. I, I, I think the fact that what
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we do at work bleeds into how we live our lives and our personal
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lives and the task we did. That part is very exciting for
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me. I mean, even yesterday my 14
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year old made the baseball team and they send the schedule out.
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And look, a year ago, two years ago, right, I would have had to
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go through, pull up Google Calendar, type all of those and
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they didn't have an easily accessible link that you could
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just import or whatever. Hey, I can just take a
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screenshot. I don't even have to send the
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URL. I took a screenshot, put it in
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Gemini. I think I tried ChatGPT first
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and it didn't like working with Google.
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To your point about things working together, put it in
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Gemini, it automatically loaded it all on my Google Calendar.
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So I'm like, oh, cool, That just saved me what, 10 minutes?
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I mean, it's only 10 minutes, but every single day we're
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working that way. So that part's very exciting for
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me. And you know, one thing that I
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think we've seen a ton in marketing, we love our acronyms.
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So you love to name things. You have to come up with new
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terms and they come and go like the tides.
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But there's been a lot of conversation.
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I see LinkedIn post about this probably every other week about
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ABM is dead or ABM doesn't work. I'd love to know what you think
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people are actually reacting to when they say that and what's
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being misunderstood. I love the term ABM and I agree,
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it always kinds of bugs me that like people are arguing about
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like, what does it mean? Is this, is this a good idea?
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But like to me like all B to B marketing is account based
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marketing. I mean, if you're in B to B,
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you're selling to businesses and you're not marketing to
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businesses, then what are you doing?
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So it's like, I think maybe what people are reacting to is like
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sometimes you can get like stuck in A like a mode where you're
5:31
just like over targeting. Like maybe you're just trying to
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target accounts that you think are in market because like
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they've got, you know, some kind of intense scores or things like
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that, or you think that's going to be the most efficient, Like
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you're going to target or serve content to them, they're going
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to engage with it and that's going to show great ROI.
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But that's a little bit oversteering.
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Like that means that you're ignoring like the 90% of your
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potential market that isn't in market today, but like you need
5:59
to create the brand awareness so that you're filling that upper
6:03
funnel and or even like connecting with users that
6:07
aren't like the direct buyer so that when people are asking them
6:11
their opinion, they're like, Oh yeah, I know that company.
6:13
Like that's kind of that like Interplay, like is ABM, you
6:17
know, if you define it narrowly, like, yeah, maybe that's over
6:20
targeted, that's not good. But like marking the businesses
6:23
like that's a good idea. You know, if you're in B to B, I
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mean, just like one kind of maybe funny example, like we had
6:29
a client that was uploading a target account list into a Meta.
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So you've got like, here's my customers, I can load that.
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I can target those folks on Meta.
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They wanted to get more scale. So they turn on look alike
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modeling. But in Meta look alike modeling
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is like demographics. So like maybe there are people
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in the original market who are like, you know, 30 something
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women living in cities or something.
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And like, so now they're just targeting all these people who
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demographically look the same, but they don't care about like
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that server security system that the client was selling.
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So like that's kind of like the example of like why like you got
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to start with the business like B2B buyers and people who care
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about what you're selling. I mean, so that's just a kind of
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a counterexample that proves like both got to do account
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based market. Like you got to start start with
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that. So anyway, like off the soapbox,
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but like that's kind of my view on it.
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No, I agree. I mean, even if people don't use
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the term account based marketing, it's still going to
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be there, right? It's it's in everything we're
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going to do with AI and layering additional context and
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personalization. So yeah, I don't think it's ever
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going away and it's always been there.
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That's the other irony of the whole thing before we caught it,
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that that's how the best sellers always sold.
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They knew their top accounts, they got to know them really
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well. That's what they did.
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So you know, I'd love to hear across your wide range of
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experience and working with lots of incredible clients.
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When you look at the teams who are succeeding with Account base
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today, what is the biggest mindset shift that they've made
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compared to some of the earlier approaches?
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I think there's just like a that kind of age-old formula.
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It's like start with your ICP or your ICP is like multiple like
8:14
ideal customer profiles. Start with that, develop a
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message that resonates with those buyers and then reach them
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wherever they're at. I mean, that's the X of the ABX.
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It's like across channels or across platforms.
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But then make sure to track it all.
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I think a lot of times that gets left out because I think a lot
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of marketers have been just thinking about like high level
8:37
metrics like clicks, which, you know, isn't revenue or they're
8:41
like going very, very low and saying like the last mile, like
8:44
click in a buy, which like hardly ever happens in B to B.
8:48
So you need to really instrument your channel so that you're
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getting signal like at all those different, you know, steps
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across all the different channels, like bringing that
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into a place and testing and learning.
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And then what's even better is when you can take those signals
9:01
and then hand them off to your sales team too.
9:03
So you're not just using the data for improving your
9:06
marketing, but you're getting like, you know, more lead data
9:09
to to your salespeople because, you know, let's face it, mean
9:12
people are not filling out forms and asking to, you know, get an
9:16
outreach from salesperson. Like you got to know who's who's
9:19
in in market. So that's really working.
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I mean, there's one example that I really love, but just like I
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think a great Casey on this Jean English, she's the CMO of core
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weave now, but before that she was the CMO of Juniper Networks
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and they did this awesome campaign with Christina
9:36
Hendricks. You know, she's the red haired
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actress from for Mad Men. And they had this edgy, like
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totally on brand creative, but then they sliced it and diced it
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into like every channel possible.
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I mean, they had like TV and billboards and YouTube and
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Facebook and LinkedIn and CTV and events and e-mail like
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everything, but they tracked it all, everything they could back
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to account level reach and engagement and pipeline.
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And like that is like a, you know, a big scale version of how
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to do that. And not every market has a
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budget to have like an award-winning actor, but that's
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the framework. So like the companies that we
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talked to that are doing great, they just have that framework.
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ICP, great hero, creative Multiplex, the creative
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research, our customer measure and learn and AI is just going
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to make that even easier and better.
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So that's going to be super cool.
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I got the Olympics on behind me, so I got to, I got to turn that
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off. Yeah.
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The lights. The lights flickering.
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No, that's fine. Yeah, lots of good stuff to
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watch right now with the Olympics.
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And I'm a huge fan of Mad Men. I always love the campaigns
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where people turn once not small.
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I was going to say one small thing, but it is the old days of
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let's take our pillar piece of content and atomize it and be
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everywhere but when it's very orchestrated.
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And this fits perfectly with a term I mentioned in the lead in
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I do not want to steal your Thunder and offer my definition,
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but let's talk about composable B to B marketing.
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When you say that, what is the simplest way to explain it to
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everyone listening who may not know that?
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I mean, composable beating market simply just means
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building your marketing stack from the best in class modular
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components rather than relying on like one single, like all in
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one platform. And so it's kind of like like
11:26
Lego blocks as opposed to like a monolith.
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And you, you know, one day writes and talks about a lot
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Scott Brinker over at Chief Martak, I mean, talks about like
11:36
the Stacky awards every year in the spring, they have companies
11:39
that say like, here's like a cool design of like the map of
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like all the tools that we're using in our, in our marketing
11:46
stack. And it kind of celebrates the
11:49
fact that companies are using lots of different tools.
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I mean, I once counted all the entries into the Stacky Awards
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and it was like 35 different tools in use.
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And that's pretty common where companies are using all that.
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So knowing that, that's what really what composability means,
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like being able to use like whatever tools you want and plug
12:07
them in. And that's been hard
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traditionally, but like it's getting better and easier with
12:12
some of the interconnectivity across the tools and that that
12:15
makes it pretty. Exciting.
12:17
Absolutely. Yeah.
12:17
We've won a Stacky award in the past, and it was such a cool
12:21
visual that Creative had just to show how everything works
12:26
together. Because as far As for the trees,
12:28
right when you're in it, you use what you use.
12:31
You don't see how everything's hooking together and powering
12:34
what's happening here and here. And I've certainly lived the
12:38
monolith experience. I was acquired into a company,
12:42
one of the first marketing clouds, and it was the bet that
12:46
people want to buy everything from one person.
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And you know, I just don't think a lot of folks work that way.
12:53
But let's let's let you unpack that.
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So what is the problem that composability actually solves
13:00
that a traditional B to B martech stack may not be able to
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address? The thing that we all love being
13:07
all of us who have been at this for a long time is this how much
13:10
markings is constantly changing, but there's always something
13:13
new. And that's like that's the
13:15
actually by definition, it's always going to be that way
13:18
because marketing is about getting attention.
13:21
And so you just have to be breaking through the clutter all
13:24
the time. And that means that you have to
13:26
be always trying something new, but like it's always going to be
13:30
changing and new formats and, and all that.
13:33
So like you just, you have to be flexible and you have to have
13:36
like a set up a platform that's going to help you to test and
13:39
learn. I mean, like a year ago, who is
13:44
thinking about LLM search optimization?
13:47
And now it's like a tool that, you know, there's lots of tools
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that help with that and everyone's testing them.
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And like even six months ago, who was you doing ABM on Reddit?
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And now everyone's talking about ABM on Reddit.
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It's like a super high demand. So you need to have your stack
14:04
set up so that you can plug in these different tools and
14:07
constantly be testing and learning.
14:09
I love that. And I mean, most B2B teams are
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using tools from different categories, right?
14:16
And we see that in the stack your words and Scott Brinker's
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award, they're way too many tools now.
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But if an enterprise is using a tool like Demand Base or one of
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our competitors or LinkedIn e-mail events content, what do
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you think separates a stack that's connected versus one
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that's really composable? Yeah, well, I mean, it might
14:38
sound subtle, but I think the difference is if you're
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connected, like you can kind of Daisy chain data from one
14:44
platform to another, but you still need to like go into each
14:48
platform to see what's happening.
14:50
When you're talking about something that's composable,
14:52
Like you really got more of a unified account model where like
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you can analyze everything, you can plug in tools and data and
15:00
you can analyze everything together, activity and outcomes,
15:04
no matter what tools you're using.
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And that's, I mean, that's the approach that we take at RT 11.
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Like we work with all the tools you mentioned and our job is to
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be the glue across that composable stack.
15:16
And we have clients that love demand base and but they use
15:19
other tools too. They use Octane 11 to see the
15:22
activity from demand base alongside the other things that
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they're doing. I mean, that's actually why we
15:28
started Octane 11. When I was at Media Mass and I
15:32
was overseeing marketing there, we were huge demand base
15:35
customers. We love Demand Base, even though
15:37
Media math was a the DSP where there's a media buying platform.
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We also loved man base, but we were also using like a dozen
15:43
other tools. And what we really needed was a
15:46
way to connect the dots across everything in an easy way.
15:49
And that was became the idea for Octane 11.
15:51
But something that's pretty interesting in the kind of the
15:54
AI context is that the way this is all getting connected is
15:58
through the MCP protocol. And that's the, that's the model
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context protocol that the AI tools use.
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And that's how the AI tools talk to each other.
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So like at Octane 11, for example, we synthesize the B2B
16:11
data and then we make it available through an MCP.
16:15
And we have an analytics agent that uses that MCP that you can
16:20
interact with to get insights and get recommendations.
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And then you can also use it to push data to other platforms
16:27
that have an MCP like receivers, like an API, like that's the
16:31
like the AI version. So you can use the data from
16:34
1911 and use it with whatever LOM you want or any other AI
16:38
enabled tool. And that's where things get
16:41
really interesting. And that's like, that's like
16:44
where that the composability becomes super interesting, but
16:47
you really have data flowing from different tools to get the
16:50
best value from, from each of the tools in your stack.
16:53
I love that. I think that's such an exciting
16:56
space to be in too, for all of us in marketing where we don't
17:00
have to go to let's say 6, but it's really more like 40
17:04
different places to do different things and hope they're all
17:08
talking together. If we've got the tech side
17:11
buttoned up. Let's jump to the human side.
17:13
So we know as humans, sometimes we make mistakes, some more than
17:18
others. I will not insert a domestic
17:21
joke there about. Stay in your lane.
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Probably hear me. So I'm not going to do that.
17:28
Where do you think teams most commonly breakdown when they try
17:32
to orchestrate across all the channels, all the data measuring
17:37
everything, who owns what? What do you think is the human
17:41
element that's most common to break?
17:43
Well, what I've seen for myself as ACMO and then also with
17:47
companies that we work with is that sometimes when you start to
17:50
talk about ABM and this kind of like this concept of going like
17:54
across channels, sometimes it gets a little over engineered.
17:58
And so you really you don't need to go big on day one.
18:02
Like you can start simple. I mean, just like nail that ICP
18:06
and those target accounts, get that creative story, execute
18:10
over as many channels as your team and your budget can handle.
18:13
It doesn't, you don't need to do 20 channels, but like start with
18:16
a few test and learn, you know, add more as you go, but like
18:21
make sure you're really connecting like that ICP, the
18:24
creative, the channels, the measurement, the analysis and
18:28
this you can kind of learn and improve.
18:30
And I guess like some teams do get caught up by ownership or
18:34
like team silos and you definitely have to be careful of
18:36
that. But like if you start small and
18:39
you kind of prove the point with a couple of channels, like what
18:43
you, you'll be able to do is go to other team and say, hey, like
18:46
we should get our social data in here too.
18:48
Like there's a, there's a benefit to like the data you can
18:51
get and show how, because I use social as an example, because a
18:55
lot of times it lives off in a silo, but like show how the
18:59
social engagement, like where it fits in the customer journey,
19:02
like it plays a huge role and it should be visualized and
19:06
measured in that way. And that's another like, you
19:08
know, the composability helps you to plug in those tools that
19:12
you're using, you know, across those different silos.
19:16
Yeah, I, I love that social actually rolls up to me.
19:19
So bonus point to you for that because I didn't tell you that
19:22
when we were talking. But as we have all these
19:25
signals, I'm, I'm thinking about how we separate the important
19:30
signals from the noise and what matters the most.
19:33
How do you think about that with the teams you're working with?
19:36
It's the same thing like on the execution side, it's the same
19:39
thing with like the measurement and the analytics.
19:41
Like you just start simple. I mean, engagement tied to
19:45
accounts, accounts are tied to pipeline and revenue.
19:48
Like with that alone, like you can get a great picture of
19:52
what's working like what, which channels are engaging the
19:56
clients that are turning into pipeline and turning into
19:59
revenue. And something that's really cool
20:01
again on the AI is that it's like the AI is like is great at
20:05
interpreting that. So in the past, I mean maybe
20:09
even like now for most companies, like they're looking
20:12
at tons of data. And they're trying to make sense
20:15
of it. And that's can be really hard.
20:17
But if you're plugged into data across your channels with the
20:21
outcomes from CRM data for revenue and pipeline, and you
20:26
can plug that into a smart LLM that has a context, It'll give
20:31
you like a great point of view on what's working, how things
20:36
are working relative to each other, which you should do more
20:40
of or things that need attention.
20:42
So it's, it's getting pretty smart.
20:44
And I think it is, it's going to just really step into the shoes
20:47
of a lot of the traditional attribution tools.
20:50
I mean, there were a lot of attribution tools over the years
20:53
that were just like super complex that needed that like a
20:56
like a data scientist, like a lot of advisory hours to like
21:00
set up an instrument and like tweak it and get it quite right.
21:04
And you know, even when it got right that people disagreed with
21:08
like the assumptions. But I don't really think you'd
21:10
need that anymore. I think if you've got your data
21:13
organized and integrated with the tool like opt in 11 or
21:16
something else like the AI can like it's amazing at
21:19
interpreting it and give you like real insights that you can
21:22
share with the CMO or the TFO or the CRO or CEO at the board.
21:27
And that's it's really only getting better.
21:29
Yeah, I think we're all excited for that.
21:31
Attribution has been the bane of many marketers existence for a
21:36
very long time, trying to fight those fights and win those
21:39
battles. And what you said resonated with
21:42
me too, because it wasn't that long ago when I was an analyst
21:46
and my most popular research piece was double funnel.
21:49
And it was literally from that pain point of trying to
21:53
understand what was working and what was not in a very large
21:57
high growth organization. And everything was a drop down.
22:01
So they had a very sophisticated BI tool and it was like, OK,
22:05
let's see how events perform. Boop boop, boop, here's how
22:08
events perform. OK, let's see how website
22:11
performs boop boop boop website. And you know, I was sitting
22:15
there as an analyst going, but how have you ever put them side
22:18
by side to see throughout the entire funnel how it performs?
22:21
Because you're being told your conversion rate for this is bad,
22:24
but compared to what? And then that was, oh, dummy,
22:28
you know, you need to put everything side by side.
22:30
So the fact that now we can look at an infinite number of data
22:35
sources and have those inferences in the comparison, I
22:37
mean, that's very exciting to me as a marketer and hopefully
22:40
everyone's geeking out about. Yeah, it's a super fun time.
22:43
And think about this like not just your for sure, you want to
22:47
be able to compare your marketing tools side by side.
22:50
Like I mean, you, you could should have visibility on that.
22:52
But like, hey, there was a product launched that that
22:54
quarter or there was like some kind of global events that like
23:01
push down sales, like the AI will be able to ingest all that
23:06
kind of context. So like getting your data in and
23:09
the global context is going to be incredible.
23:12
I was laughing because the detective work we've done in our
23:15
past lives as marketers to figure out why, why did it spike
23:19
in October of last year? What was in October?
23:21
Oh, the brand launch, that's what.
23:24
Yeah. Or, you know, actually in Google
23:26
Analytics, someone annotating different things that happened.
23:29
That used to be how we would watch that You'd have to put a
23:32
little label in and say here's what we changed.
23:34
So that's really cool. One question I have for you
23:37
before we jump into the the lightning round, some of the
23:40
quick headers that we like to ask.
23:43
We've talked a lot about accounts and the individuals at
23:46
those accounts. Your meta example is really good
23:48
too. Like we can't conflate the two.
23:50
We have to be smart with starting with the account moving
23:53
down as we think about buying groups.
23:55
So connecting the important folks at an account and trying
24:00
to orchestrate things with them together.
24:02
How does composable marketing fundamentally change how we
24:06
engage buying groups? Well, I mean, I think buying
24:09
groups are great. I mean, B to B purses are most
24:12
often made by a group. So you have to be top of mind
24:15
for all the different influencers in the group.
24:18
And that's what Yon Schwartz and Mimi Turner, I don't know if you
24:21
read any of their stuff at LinkedIn, B to B Institute, they
24:24
call it buyability, where the brand recognition of your
24:29
product when it comes to the buying committee is critical to
24:33
getting everyone over the finish line to make the buy because it
24:37
greatly reduces the risk. So I, I think a lot of companies
24:42
get overly focused on like precise targeting.
24:45
Like this is the buying group of like, these are the five people.
24:48
We just got to interact with them.
24:50
But I don't think you need to obsess about that because in
24:53
reality, for most B to B products, like you need to be
24:56
known by a lot more people from the finance department, like the
25:00
procurement team, the CEO teams that you may not think are part
25:04
of the decision are going to be part of the decision.
25:06
So, you know, the more your brain is known across the
25:09
organization, the better. And that just means like loosen
25:11
the targeting. I'd say that's our
25:13
recommendation. So it's, you know, across
25:15
departments. And if you're in a very big
25:17
company, you can narrow down by, you know, the right departments
25:20
or the right geography that you know, you're, you're focused on.
25:23
But for smaller companies that you're selling into, like just
25:26
target the whole company because you kind of need everyone to be,
25:29
you know, on board. So but anyway, that's, that's
25:32
more about, you know, buying groups on composability.
25:35
I mean, it's just, it's just about being able to use whatever
25:37
tools or media is going to help you reach those target audience
25:41
and target companies and whatever departments, whatever
25:43
you define to be the buying group and the influencers.
25:46
So you can kind of breakthrough the noise and then measure it.
25:50
Cool, cool. So we like to ask some
25:52
consistent questions and I am really excited for your answers
25:56
on this because with composable marketing and a lot of the
25:59
things you're doing, you probably have used an infinite
26:02
number of tools. So the first question is, what
26:05
are your favorite tools or technology that you'd recommend
26:08
to our audience? Well, we had a lot of clients
26:11
who love demand base, of course, but some of the things that also
26:15
are constructing a lot of success with maybe a little bit
26:17
news like CTD on LinkedIn. Companies are loving that
26:21
companies are loving Adm on Reddit.
26:23
That one is like come out of nowhere.
26:26
So like we are seeing like the larger platforms, like seeing
26:30
some, you know, new stuff and innovation.
26:32
But for like the AI tools, there's just so much, I mean,
26:36
it's coming in so fast and furious.
26:37
Like my Instagram, like every other post is an ad and they're
26:43
for really cool tools. And most of them are like AI
26:46
marketing tools. Like, you know, if I'm, you
26:48
know, as soon as you download more, you're going to see ads
26:50
for a bunch of others. I just was trying out arc ads
26:53
for like AI voice overs. Maybe you'll see some ads that
26:56
we're running the using tools like that or cap cut we use for
26:59
our video editing. We're starting to do a lot of
27:02
video for our own marketing. So I think the innovation is
27:05
amazing. It's going to get great when the
27:07
tools get connected though. These are all, remember these
27:09
are all still like point solutions in a lot of ways that
27:12
are off on their own silos. Like imagine when they start
27:16
talking to each other through the MCP protocol.
27:19
It's going to be super cool. I expect out Team 11 to be part
27:21
of that. But that's where things are
27:23
going to get really fun and that's that's not too far out.
27:25
Yeah, we have some cool stuff we're working on that will plug
27:28
right into what you're doing already, which is nice.
27:31
But it is frustrating when you hit a stumbling block when
27:34
you're using any AI chat interface and then you're like,
27:38
oh, you have to go here and do these three things and then go
27:41
here and do these three things. Eventually that's going to be
27:44
staggered along like dumbbells. Yeah.
27:47
Well, what are your favorite information sources?
27:50
So we call this Goodreads, but it could be book, blog,
27:52
newsletter, podcast. You just talked about viability.
27:55
I'm curious, what are some of the things that inspire you or
27:59
keep you grounded that you recommend to folks?
28:02
In our category in our industry, like I, I'd listen to market
28:05
texture a ton. That's with our area, Paparo and
28:08
Eric Franchi. There's always, there's going
28:11
through all the news and AD tech and martech and AI and just
28:15
what's happening. So that, that one I love as AB2B
28:18
marketer or CMOI love listening to open market.
28:21
That's also Eric Franchi, but also Joe Zappa.
28:24
And that's more of like a practitioner's guide to B to B,
28:27
which I love always walking out of those with some really good
28:31
ideas. But in our business, I'm always
28:34
listening to like saster to in like 20 minute BC for just kind
28:40
of, you know, broader SAS tech industry.
28:43
I love those. Those are always inspiring.
28:45
What about people? So exact same question, but
28:47
people? You've mentioned a couple, so
28:49
it's fine if you want to shout them out again, but who are a
28:51
few of the people who inspire you the most?
28:55
Well, I love, I mentioned Jan and Mimi from LinkedIn B2B
28:59
Institute. Those guys are always great.
29:01
It's always kind of provocative what they're putting out there.
29:04
They could be great folks to have on.
29:05
Putney Clues is a great suit. She's the CMO at Bambura.
29:08
She's been great doing really good things.
29:10
It's like Acmo, then you came from Amex Incision, but now
29:13
inside of like a more tech company, which is really
29:16
interesting. Paul Connecting is a is a repeat
29:19
CMO. He's the CMO of out brain, which
29:22
is a publicly traded company and beeswax before that.
29:25
So like some great kind of long term perspective on like how to
29:28
breakthrough, particularly for marketing martech companies.
29:31
So I always enjoy talking with those folks.
29:35
Awesome. And then the last question.
29:37
This is the most important one, though.
29:39
We saved the hardest one for last.
29:41
For the folks who want to pick your brain or may want to talk
29:44
to you about how you could help them with composable marketing,
29:47
how can they get in touch with you after this episode?
29:50
Well, if you're an enterprise marketer or you're at an agency,
29:53
and particularly if like advertising is a big part of
29:56
your marketing plan, definitely just reach out to me on
29:59
LinkedIn. I mean, I'm on there every day.
30:01
And just hit me up. I'd love to show you a demo,
30:04
show you how this composable stack works in practice.
30:08
And some of the like amazing things you can do, like once you
30:11
get your data integrated in a line across all these channels
30:14
and then you plug that into an AI analytics tool, like it'll
30:18
blow your mind. Awesome.
30:19
Well, thanks so much for your time today.
30:21
This is really helpful. I know I'm taking notes here,
30:25
have some of my screen too with AI actually, but lots for me to
30:29
do to continue to ramp up on this.
30:31
So thank you so much, Dan. Yeah, Thank you.
30:33
That was fun. Thanks for joining us for On
30:36
Base. If you enjoyed this episode,
30:38
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