00:22:40 · Henry Innis
[00:22:40] S0: of experiments. How did you think about that in like Of course. I was always quite adamant that marketing should be planned on outcome, not input. So I just fundamentally believe that coming up through agencies. I thought that what, what was missing from the ecosystem in general, what was missing from, you know, how marketing budgets are allocated. Marketing budgets fundamentally, we all talk about it as media mix and market mix and, you know, what channels are we optimizing for? I've got a different word for it, capital allocation. Right? What we're trying to do is allocate capital to our most efficient bets for our best payoffs. And that's fundamentally what the job of a marketer is. No one frames it that way, but that is what marketing ultimately is. And I remember distinctly a conversation with Tim Doyle who basically laid it out that way to me, and I was like, oh, that's a really good way to explain it. And so ultimately in Mutinex, what, what I wanted to build was a capital allocation system. I knew the techniques that people were using to do it. I felt that a large model approach would kick an analyst's ass any day of the week. And so going down that approach of starting to build, how do we build a large scale model that's built in house, it's built by us, that's built to reflect and understand the dynamics of marketing rather than try to model a specific business was very, very important to getting right first. I have to say that I think we... Know, ChatGPT and Co did the world a favor by making it an easier concept to sell that, like, you should license a model rather than build your own. It kind of permeated that into the world's consciousness a bit. So that was helpful from an education perspective, but we just relentlessly work towards the user problem. Just like if if you think about what these problems are, enterprises spend millions of dollars to get one deck a year, one PowerPoint deck. Marketers who are optimizing spend constantly, optimizing capital constantly, they want insights live, real time. They want easy ingestion to it. They want all of these things done in a way that feels natural to them and sits within their workflow. You know, if you have a tool, you genuinely start to move them towards that and you unlock the capability of them. Right?
00:24:58 · Henry Innis, Sachin
You unlock a marketer to go from being okay, like I understand the data and I've got intuition, but I can't bring those two things together. Whereas I have a capital allocation system where I can plan out my kind of different scenarios. I can deploy my capital quickly. I can forecast. I can review tactical decisions. I can do all of these things and I can do it in one system rather than looking at 10. Yeah. And that's a very powerful thing. So I think by starting to work towards that, really, becomes a crux of how do we execute that well rather than changing the problem. So I think when I'm doing experimentation and stuff like that, I'm experimenting not on what the problem is, I'm experimenting on what the best execution to solve the problem was. And I think that's a big distinction that with that fundamental, like, [00:25:47] S1: almost belief that wasn't analytical necessarily, like in the micro that it's like, you've seen this problem, you know, the world should have this, you know, market should operate like... Correct. And then you experiment in the micro to solve that problem.
00:25:47 · Sachin, Henry Innis
[00:25:47] S1: almost belief that wasn't analytical necessarily, like in the micro that it's like, you've seen this problem, you know, the world should have this, you know, market should operate like... Correct. And then you experiment in the micro to solve that problem. [00:25:59] S0: Correct. I, and I think too many people think it's like either you're all in on lean startup or you're all in on the jobs paradigm. Yeah. I think it's actually a bit more nuanced than that. I think most great founders are very, very strong at understanding where the thing needs to be and what the problem they're solving is. And then they're very, very good at building teams that can iterate to execute against that quickly and basically generate feedback quickly to go, are we solving this in a really good way or not? There are some people who are just product savants, right? Who just have an intuitive sense of the customer that they're dealing with. You know, I wouldn't put myself in that category, but I've generally... Because I speak to customers so much, I've got a pretty good sense of it. And I
00:25:59 · Henry Innis, Sachin
[00:25:59] S0: Correct. I, and I think too many people think it's like either you're all in on lean startup or you're all in on the jobs paradigm. Yeah. I think it's actually a bit more nuanced than that. I think most great founders are very, very strong at understanding where the thing needs to be and what the problem they're solving is. And then they're very, very good at building teams that can iterate to execute against that quickly and basically generate feedback quickly to go, are we solving this in a really good way or not? There are some people who are just product savants, right? Who just have an intuitive sense of the customer that they're dealing with. You know, I wouldn't put myself in that category, but I've generally... Because I speak to customers so much, I've got a pretty good sense of it. And I [00:26:40] S1: think that's very important. Henry, when I first met you, something I came away thinking is that there's a lot of arrogance in the tech world because I think when you're young and in the tech world, you think that there's only smart people that exist inside the tech world, and you're kind of this outsider that just got up to speed so quickly. You're running one of fastest growing businesses in Australia. Curious to hear your take on this. Do you think like tech people have like an inflated sense of their own intelligence and self importance, there's actually just, you know, intelligent people evenly distributed across most industries?
00:27:11 · Henry Innis
[00:27:11] S0: I think tech people have a different orientation to risk indecisiveness, which is the trait that allows them to move faster. I'm not sure intelligence necessarily lets you move faster. I think an appetite for risk and an appetite and a decisiveness is one unlocks speed and generate speed in organizations. So, you know, I always think that a more important kind of way to look at why a big, what's a big corporation has unlimited resources. Their primary cost is cost of alignment, cost to align the 20 people who need to make the decisions. And that's why they can't execute. A startup, it's the flip side. There's very little cost of alignment, but there's very high constraint on resources. So I think that they're just different orientations to understand. So the skill set that you build to get things done in a large corporation, which is, you know, generating high alignment around decisions is probably not the same skill set that applies well in a startup, which is like executing well and not necessarily bothering to align people. So I just think they're fundamentally quite different and you get different environments to teach you different things. For me, you know, I think getting up to speed in this space and stuff like that, I think, you know, and to go to the tech arrogance point, I do think there is a bubble filter that that does exist. I'll give a really good example of this. Early on in the stage of Mutinex, you know, kind of just pre series a and stuff like that when we're looking to raise a bit of money, a lot of VCs were very, very keen on a, making instructions for us to portfolio companies and b, judging us on whether or not those portfolio companies bought. Now that was problematic for two reasons. One, d to c companies and things like that for me are a tiny part of my market segment and probably not that relevant of a one given how much they rely on multi touch attribution and stuff like that and other dodgy attribution stacks that kind of matters to them, but they're not statistically sound. There's a high cost of education without high cost of contract... Without a high payoff in contract. Second thing is they didn't necessarily have money to spend, which is a big, big challenge for us. Like we're an enterprise first business, and that was a really, really important aspect of it.
00:29:23 · Henry Innis
And I think the third element for for me was like a lot of marketing managers and marketing directors, because I've noticed that VC introductions don't always go really well, even though they're really well intentioned, really well set up by the VC. My gut feel is that the marketing director, who is probably two levels below the founder and stuff like that, probably doesn't want a VC accountability thing coming in, so probably slow walks it a bit in 90% of scenarios. Because it's a scary thing. Right? Hey, the VC's got relationship to this analytics company, which is going to be able to tell us exactly what the marketing budget is gonna be doing. Shit. Is the VC gonna have access to that? So I I I wondered whether or not it was like the bare best thing, and I didn't realize that really recently that that might be a problem. And so I've kind of tried to try to think through it a little bit more intelligently how we use those connections, things like that. But it's just an example of me of like where there's probably an over indexing to to to like why we weren't winning startups. And for me, startups who could buy our product are like 5% of the market if that. Yeah. So I don't really worry about whether I'm winning in startups. I worry about whether or not I'm winning in tier one brands. And and I'm not sure that was necessarily appreciated for what it was until we got