Pod Insights The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch 20Growth: Why Product-Market Fit is Not Enough, Revenue Does Not Create Usage, Metrics Must Be Before Strategy, Why it is Always Better to Concentrate than Diversify Marketing Channels and Secrets from Hubspot's Growth Engine with Brian Balfour @ Reforge About this episode Brian Balfour is the Founder and CEO of Reforge. Previously, he was the VP of Growth @ HubSpot. Prior to HubSpot, he was an EIR @ Trinity Ventures and founder of Boundless Learning and Viximo. He advises companies including Blue Bottle Coffee, Gametime, Lumoid, GrabCAD, and Help Scout on growth and customer acquisition. In Today's Episode with Brian Balfour We Discuss: 1. Entry into Growth and Lessons from Hubspot: How did Brian make his entry into the world of growth? What does Brian know now about growth that he wishes he had known when he started in growth? What are 1-2 of his single biggest takeaways from his time at Hubspot that impacted his mindset? 2. The Foundations: What is growth? What is it not? What does Brian mean when he says "all growth can be boiled down to 4 things"? When is the right time to bring in your first growth person? Should the first growth person be senior or junior? Should the growth team be standalone or sit within an existing function? 3. The Importance of Product Channel Fit: What is product channel fit? How should founders approach it? How do you know when you have it? What are the single biggest mistakes founders make with regards to PCF? 4. Next Comes Channel Model Fit: What is channel model fit? How should founders approach it? What are clear indicators that you have or do not have channel model fit? What are the biggest mistakes founders make with CMF? 5. Finally, Model Market Fit: What is model market fit? How should founders approach it? What are clear indicators that you have or do not have model market fit? What are the biggest mistakes founders make with MMF? 6. Brian Balfour: AMA: Why is product market fit not enough? What does Brian mean when he says "revenue does not create usage"? What are the biggest dangers of mixing customers and users? What do Hubspot do better than anyone else to know when an existing product/strategy is dying? Is it always better to diversify marketing channels?
Transcript 11,030 words · 5 speakers
Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.
0:00 Speaker 00 Revenue does not create usage. To understand what your metrics should be, you have to understand the qualitative underpinnings. You have to have something called product channel fit. Then you need to understand channel model fit. Focus your firepower on fueling that thing as fast as possible.
0:18 Harry Stebbings? This is 20 Growth with me, Harry Stebbings. Now, 20 Growth is the monthly show where we sit down with the best growth leaders in the world to discuss their tips, tactics, and strategies to starting and scaling growth teams. Today, we're joined by an OG of the growth world, Brian Balfour. Now, Brian is the founder and CEO of Reforge. Previously, he was the VP of Growth at HubSpot. And prior to HubSpot, he was in EIR at Trinity Ventures and founder of Boundless Learning and Viximo. He also advises companies today, including Blue Bottle Coffee, Game Time, GrabCAD, and others on growth and customer acquisition. But before we dive into the show today, listen to this.
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2:29 Speaker 00 You have now arrived at your destination.
2:32 Harry Stebbings? Brian, this is such a joy to do. I mean, I feel like I've interviewed like everyone from Reforged. And so I've been waiting for this show in anticipation. So thank you so much for joining me today.
2:42 Speaker 00 Thanks for having me. I'll do my best to live up to all the rest of the folks you've interviewed, but we'll see how this goes.
2:48 Harry Stebbings? Listen, I had nothing but wonderful things. I want to start though with a little bit of an entry point, which is how did you first make your first foray into the world of growth as a starting point?
2:58 Speaker 00 I made my way into growth where I would say like 70% of like the growth OGs made into growth, which was the early Facebook platform, social gaming days. If you look at like some of the top people in growth, there's like a lineage, almost like a coaching lineage, like all the way back to the social gaming days. And so I had started this company shortly after school called Viximo. And we were in the social gaming space for a while and then it kind of transitioned to mobile gaming. And that was like the perfect Petri dish to create growth people. What the Facebook platform did was that it opened up a ton of viral channels as well as like paid acquisition channels.
3:41 Speaker 00 The games were very driven by like product driven levers, like virality. It was a highly quantitative game. You were playing this high like arbitrage game. And games are so focused on the psychological aspect of users to a degree that other software products aren't. And when you combine all of those things together, that's really kind of what growth turned into, which was understanding how your product grows, which is different than how your business and company grows. And we can talk a little bit about that later. Combining it with the quantitative elements of growth as well as with the psychological elements of. Growth. Those three things combined, especially in a high pressure, high competitive environment,
4:25 Speaker 00 is what really formed, I think, the like initial injection into the growth scene. And so as a founder of that company, you know, there was like nobody who really knew what to do and how to do it. And so a big part of a founder's job is just like, go solve the problems that you don't have other people for and figure it out. And that's how I got into it and I just, I loved it. I actually loved the game of trying to find an opportunity that other people weren't seeing and figuring out how to exploit that. And so I just loved it and I got into it. Been there ever since.
5:00 Harry Stebbings? I mean, it sounds like you should be a VC as well, but it is fascinating to see actually how many came from those early Facebook gaming days. So totally get you there. I do want to ask, I think so much is gained in hindsight and with years of experience. If you could go back to your first day prior to your first role in growth and tell yourself one piece of advice, cool yourself up that night before, what would you tell yourself, knowing all that you know now?
5:23 Speaker 00 Probably two things. One is like, there's not an infinite world of growth options. It's fairly well-defined and constrained. And it's not like there's an endless list of ways to grow. There's actually a fairly set menu of things and you can innovate within that menu, but it's actually pretty rare that a new dish gets added on to the menu. Knowing those sets of things helps really start to hone in on what your realistic opportunities are and not. And then the second piece of that is conviction and patience. When you look at a lot of the highest-flying growth strategies, right?
6:04 Speaker 00 What is underneath them is what we call every forge growth loops, where other people call flywheels, but they're basically systems that work like compound interest, right? There are things that feed itself and grow over time. And the really hard part about those systems is just like compound interest. It looks like tiddlywinks at the beginning and it doesn't look like much. And so what that does is it puts a lot of pressure and I see a lot of founders doing this of like, oh, this isn't working, so I gotta move to this next thing. And this isn't working, this isn't moving, next thing. When actually, the right strategy is to have conviction in one of those bets and invest your way through it. Because compound interest, right, it pays off later. The hockey stick happens later, right?
6:44 Speaker 00 And so you have to look for early signals of like the fire starting and have conviction that as long as you keep adding like kindling and fuel to the fire, this little campfire is going to turn into some kind of raging thing that you can't even control.
7:00 Harry Stebbings? You mentioned that the compound interest and having conviction in a strategy or a channel. Yes, and I think content's a great example of that. It's about consistency and keeping going and keeping going. And it's a game of who can survive the longest. Sometimes things just don't work. How do you determine when something just isn't working and won't work versus consistency? Just keep going.
7:23 Speaker 00 I think the mistake that most people look at and the reason they kill things too early is that they're looking at the output and not the inputs and seeing like how those things are improving. And so in the content game on SEO, the things that you're actually wanting to start to look at is like, well, is my domain authority increasing? Is my rate of like new pages starting to increase over time? And these are like the types of signals that as they grow, they feed each other and things like start to compound. But this is also kind of gets to probably the biggest mistake I see across all of growth, which is that before anything, whether we want to talk about metrics or this question or all of that kind of stuff,
8:07 Speaker 00 you have to have a hypothesis about how your product grows, which is captured in what we call is like a growth model. And this is very different than a business model. A business model or a financial model is saying, when I put a dollar in, how do I get more than a dollar out? And what a growth model says is, when I put a user in, how do I? I get more than one user out. And the levers between those two points, A and B, are actually very different than a financial model. If I'm looking at a product like, I don't know what it's called. Loom is one I was an early investor and advisor in, right? Money does not help that company grow that much. The things that are helping that product grow are its organic viral and content loops, right?
8:52 Speaker 00 I record a Loom video and then I send it to somebody. And then that person kind of picks up the product and they start using it. Understanding what that system is, what that loop is, I can then start to identify, well, where are my biggest constraints in that system right now? And how might I start to unleash these constraints? So an example in Loom's case is like, hey, I could onboard somebody onto a use case where I'm recording a video and sending it to one person, like a one-on-one communication. But I could also educate the user on a use case like company communications, like I use it at Reforg, right? And that's a one-to-many use case that has a lot more virality built into it.
9:34 Speaker 00 And so I can start to influence like these steps of the system by understanding what the system is and where the constraint in the system is. The constraint also tells you who should you hire and when should you hire that person, as well as what metrics to track along the way. But getting back to your original question, how do I know something is not working? It's not about the output. It's about understanding the system and whether or not you're able to continue improving those levers in that system and putting it on a trajectory that if I keep moving those numbers, if I keep improving those inputs, at some point, this system goes from me having to add a ton of manual energy into it to it's starting to act like compound interest and it like evolving itself.
10:20 Speaker 00 And so playing that out ends up being the fundamental key, part of the equation to understand like when to kill something or not.
10:27 Harry Stebbings? Brian, can I ask you, I think, I mean, I'm an early stage investor. I work with many, many, especially kind of PLG SaaS companies, very similar to Loom in terms of kind of go to market and business model. And I think all the founders would say they understand the machine and the system, but they don't know what the constraint is. What do you advise founders who don't know what the constraint is?
10:47 Speaker 00 I would first go back, which is I actually think a lot of people don't understand what the machine is. And the reason is, is if you ask them to draw you a picture that answers, how does the product grow? They'll either struggle to draw that picture, or it'll look like such a jumbled mess that you, as the recipient, can't really understand it. That's actually signaling that not only have they kind of boiled it down, they understand it, but they're not able to communicate it in a way that the rest of the team understands. And then the rest of the team doesn't understand it. That's where you run into these problems like, oh, we're gonna, you know, come up with these 10 different tactics, try them all, hope one of them works, because they don't really understand how things like actually like map to the equation. But understanding the constraint ends up coming down to
11:32 Speaker 00 the quantitative part of this, right? The exercise I just mentioned is more of the qualitative part is like, hey, can I draw a bunch of boxes and arrows that say, as a new user enters the system, they walk through these four steps. And if they complete these four steps, another new user comes out of it. Right? That's kind of what that picture looks like. The quantitative is now taking that picture and saying, okay, this is the metric that maps to this step. This is the metric that maps to this step. This is the metric that maps to step C, right? And then saying, okay, where are we performing on these metrics right now? And then you need to go through the exercise of, okay, well, if I move this part of the system from A to B, what happens to the output?
12:15 Speaker 00 And how does that differ between if I move, you know, metric B from A to B? And what that starts to tell you is like, well, the system is more or less sensitive to one or the other. And then you need to layer on, how easy is it to move these levers as part of the system? Depending on what the loop is, there are tactics that you can use to actually like pressure test this. The easiest one that you can pressure test are anything to do with paid acquisition and paid loops. Because what you can do is you can run what you call spike tests. Where you basically take something that's like at a low volume and in a 24 or 48 hour period, you basically ramp up the volume as much as you can to understand where the
12:57 Speaker 00 system breaks, right? Like what starts to perform less, right? So if I'm spending a hundred dollars a day on a paid acquisition loop, for example, it might look like it's performing pretty well. And then I ramp it up to 200, 300, 400, 5,000, 10,000, right? And at some point, the performance breaks and the performance will break in, you know, your performance of your creative, in the performance of your sign up rate, something down funnel. And so you can like really understand like where is the piece that that's kind of breaking the most. That's easy to do in some types of systems. It's much harder to do in other types of systems like content loop that organically take a much longer time. If we're plotting it on the curve, the base of the curve before the inflection
13:42 Speaker 00 point looks much, much longer, right? Because there's just like less levers that you can dial manually as part of that. But understanding the constraint, once again, comes down going from your qualitative system to mapping it quantitatively, starting to understand the sensitivities of all these levers and then essentially trying to understand things that you can try to understand how hard it is to essentially move these levers. And the combination of that starts to give you the indication of this is where the constraint is at in the system and this is like where we need to focus. My last point on this is that the constraints actually tend to follow patterns depending on the type of product you're at. So very commonly with the product we were talking about, Loom, which is like
14:24 Speaker 00 a horizontal product, the constraint is activation. And the reason the constraint is activation is that the biggest strength of horizontal products is also its biggest weakness is that it can be used for many, many different things, right? When a user is onboarding into the product, it's actually really hard to get them and understand what is the ideal use case to activate them on. Like, what is the thing that is most relevant to them? But if you do activate on them and it's somewhat viral, like Loom, the fact that it can be used by so many people has such a spread rate that that's kind of like the easy part of the system. It's very different than a vertical product, which is very targeted at a single persona or a single market or a single use case.
15:08 Speaker 00 I actually know very specifically what I'm activating them onto. And so if I get them over that hurdle to like signing up or buying that product, it tends to be easier to activate that person, right? So it follows patterns based on the dynamics of the system and the types of products that you're at. And so these things end up being fairly predictable when you've seen enough of the game play out, enough time across enough companies.
15:35 Harry Stebbings? You mentioned sensitivity of levers there. I have a contrarian thought on growth hires and timing, that everyone says you should hire growth after product market fit. And I say you should hire it before because you need to throw enough people at the machine to know if you have product market fit. You need enough data to understand if some segment of people liked it. And a growth hire can help you get that data to understand. Do you agree with me or do you agree with everyone else that growth is a post-product market fit hire?
16:07 Speaker 00 I agree with you that you have to have enough volume coming into the system to really understand what these levers are in the product and what you can play with, right? And sometimes pre-product market fit, you need to hire a dedicated person that's just focused on bringing volume into the system. Sometimes you actually don't. So to give you an example, like if I was to start an amplitude competitor, a new analytics product, right? That thing's not viral at all, right? Like, you're buying that thing for tens of thousands of dollars as a whole, like setup costs, like all that kind of stuff. There's probably a team that's really focused on building that product and building that engineering. And that growth model is going to be very marketing driven versus product driven.
16:50 Speaker 00 And as a result, you need a totally different skill set of person required to focus on bringing volume into the system so that you can understand if what you're building is on the right track or not, right? Use a counter example, which is like, if you're working on like a new consumer social product as an example, or even something like Loom, where the system, the machine and the loops are actually very product driven, that person actually looks very close to the early product and engineering team that you're hiring. And those things are driven so much by virality that if you're not getting the viral loops
17:31 Speaker 00 working, well, then hiring a different type of growth person, a marketing or some other thing, it doesn't fucking matter. You're dead in the water anyways, right? So I think the answer to this comes down to what do you actually mean by a growth person? Like, what type of profile does it mean? What is the machine and the type of machine that you are building? And then three, like, you can start to match, well, do I need a person dedicated to that pre or post journey, right? Loom is the example where I would probably wait till post-product market fit to start to carve out like a dedicated product growth team, dedicated marketers, right? Those, those types of things. Whereas the Amplitude competitor is one where it's like, hey, I need somebody dedicated
18:16 Speaker 00 on this from day one to drive some volume to understand whether or not what the hell we're building is even close to on the mark.
18:22 Harry Stebbings? It's a shit question, isn't it? I mean, what a bad question. What awful interviewing. I totally agree with you. It's like totally company dependent and it sets you up for a very challenging answer. My question to you is, you said about post PMF there for Loom. You said before in some of your work that product market fit isn't enough. What does that mean? Because founders chase this product market fit. Like, what should it be and how could it be changed?
18:49 Speaker 00 Product market fit is not enough to build a venture scale business, meaning like 100 million plus in revenue within some reasonable time period. And so I think there's like a few, few pieces of this. One is that I think one of the mistakes is people think about product market fit as a binary thing and it actually lives on a spectrum. There's two vectors of product market fit. There's how strong of a fit I have and with how big of a market, right? And there's some kind of efficient frontier on that graph of like you cross over and it's like it's strong enough with a big enough market where I'm the venture viable path. But there are companies that certainly live with very strong product market fit, but with a small market that just aren't venture viable.
19:31 Speaker 00 And there are actually, I've seen companies that have a very large market, but weak product market fit. Those are also not venture viable, but in neither of those cases, they are viable businesses in the grand scheme of things. There's this little tiny world that we live in around venture is not part of it. So that's the first part of it. The second part of it is that you have to have something called product channel fit. And so the mentality before was like, ah, I get product market fit and then I'm going to like bolt on a bunch of distribution that'll play off. But that is not true. We cannot mold channels to products. We have to mold the product to the channel. And what I mean by that is Google, Facebook, Apple, whoever owns all these huge distribution
20:14 Speaker 00 platforms, they do not give an F about your product. They are the ones determining the rules of the game. And so your product has to play to those rules, right? That has to mold to those rules, right? And so if you just build your product in isolation of this concept, what you end up with is like a total mismatch. And this gets back to understanding your growth system. So if your growth system is going to be very content driven, like a Pinterest or HubSpot was very content driven with like their SEO, like all that kind of stuff. You basically have to mold your product to fit with that channel. You have to be writing the content that's going to rank or your users have to be generating the content that's going to rank, like all of those types of things.
20:57 Speaker 00 You have to instrument your product in order to adapt to that channel. The second part of it is like, once you have product channel fit, then you need to understand channel model fit, right? Which is essentially saying all channels don't fit your monetization model, right? So you can't use viral loops for a product that you're charging $10,000 upfront for. It just doesn't work. It's weird to share that type of product with somebody, but even if I do, the conversion rate on that is like so low that That system, that loop, it like never actually really gets spinning. And so what you see is that there's channels like virality and UGC content and paid acquisition that work with lower friction, lower priced products.
21:40 Speaker 00 And there are channels, like different variations of sales and other things that work with higher priced products. And so you have to match your pricing to the channel to not only match the friction, but also match the economics, right? Because if I'm using a bunch of sales, for example, right? Like, I have to make sure I get my money back on the cost of that human touch. So that that piece has to work too.
22:02 Harry Stebbings? Well, when we say about pricing, channel fit there and aligning the two, would an example be like a luxury brand having a core channel in first-class British Airways or Delta? High price point, high luxury, good. Is that what we're doing, Mark? Because like, does that mean enterprise products should not do YouTube and Twitter? And do you know what I mean? I'm just trying to understand what that kind of means then for the high-priced products.
22:26 Speaker 00 You know, in your example, an enterprise product, should they not do YouTube and stuff? It's more about what the purpose of YouTube and stuff is driving for that company. Yes, it might be driving awareness and these other pieces, but that alone is not going to drive customers for an enterprise product. And even if you were doing it, if you looked at the overall mix of like at scale of what's driving customers, it's going to be a pretty, likely a pretty small fraction. And so it kind of gets to, in an enterprise product, you have to make your sales machine work. And if you can't make your sales machine work, everything else that you're doing is just pure noise. And so you got to get the core machine working.
23:08 Speaker 00 And then you can add these other things that help accelerate it, as an example. But where, you know, the focus piece of it is, I can do a bunch of these things, but it's actually pulling attention away in the early days from actually understanding and getting that core machine working. It's very different than, I think, a company where, like, what you're seeing is, if we think about a product that, like Riverside is actually probably a good example of this, that the product that we're on right now. I am naturally creating videos, so I should probably be asking the question, well, where are all of the different places that people are consuming video? YouTube is one of them. And so then the question becomes, well, how do I make it really, really easy for my users to essentially post video to YouTube, potentially with my branding on it?
23:53 Speaker 00 Maybe they can pay to take the branding off of it. That all of a sudden starts to look like a really interesting growth system because I bring in a user, they're going to record a bunch of videos. If I make it really easy to distribute to YouTube and there's some exposure to my brand on it, that's probably going to bring in more customers. That starts to look a lot more interesting.
24:11 Harry Stebbings? Two things that actually come from Kip Bodnar at HubSpot related to channel. He's said on the show before that one channel working really well will get you to 50 million in ARR. Two channels working really well will get you to 100 million in ARR. First question, what do you advise founders in terms of channel selection? How to know which channel to choose?
24:33 Speaker 00 So I agree with Kip. Once you figure out that core, that thing that's working, it's almost always in a venture scale company, the better thing to do is to focus your firepower, your limited attention, your limited capital, your limited talent on fueling that thing as fast as possible, which is very counter to a lot of the common advice, which is like, oh, you don't want to be too reliant on one thing. You want to diversify, like all of that kind of stuff. That is a bad investor's point of view. Like, yes, that might work for money management. It does not work for growing a business because it ignores all of the complexity
25:15 Speaker 00 that comes with diversification of products or channels or any of these types of things. It's like, if you find something that's working, you better focus that firepower. But the second piece of that is that you then need to anticipate when that one thing might start running out of fuel. So you're not caught with your pants down in trying to find that second thing that Kip is talking about too late because that creates this stall out effect and is really hard to get yourself going from a stall out effect.
25:44 Harry Stebbings? If we just dive on that, do you think it's obvious when channels are starting to deteriorate in effectiveness and growth?
25:51 Speaker 00 This is, I would actually say, even harder than understanding your constraint in the system. Essentially, what you're trying to do is predict a point of saturation of what you're doing. It's hard on multiple dimensions. One is that I think the tendency is to actually think something is going to saturate much more quickly than it actually does. And that's because if you look at the really high-growth companies, you know, taking HubSpot as example, along their way on content, their path to really establishing that content loop, they hit ceilings along the way, right? And it wasn't like they stopped at that first ceiling and been like, oh, throw the hands up, like, we're done.
26:31 Speaker 00 Like, every step of the way, there was some new idea, some innovation that unlocked another pool, right? And so going beyond, digging beyond that, is really, really hard work because you're basically trying things that others aren't trying. And that's actually just very hard for both people and a company to do. So I actually think predicting saturation is one of the hardest things for companies to do. HubSpot, I would say, is actually, one of the biggest things I learned there is they are probably one of the best in the game at this, both from a growth and product strategy perspective.
27:13 Speaker 00 If you take into account, they have not missed a earnings since they went public, which was like eight years ago. They have never missed an earnings. A perfect record, as far as I know. And that was one of the biggest things I learned. I joined 18 months before the IPO, and we were already talking about a five-year exercise of saying, like, where do we want to be five years? And how do we work our way backwards to what we should be doing today? And where that got us was, hey, our single marketing product and our single marketing and sales motion is not going to get us to our five-year goal, which was maintaining 50% year-over-year growth for five years. And what that led to What do you do is say, oh, we need to like kick off a multi-product strategy.
27:58 Speaker 00 And actually, finding the second product is probably going to take us a year or two to do. So we better start that. We better start that now. And actually, the second product might not even get us there. So we're going to need a third product. So not only do we need to plant those seeds, but we need to come up with a system to start to find new products that we can expand into. And so a lot of it comes down to looking into the future, playing out your growth today. And saying, okay, well, if I want to maintain some sort of growth, what does that mean a year for two years from now? And then you got to start going through the exercise of working your way backwards of like, what has to be true for that to occur in our system? What starts to feel like really unrealistic around those things?
28:42 Speaker 00 What does feel realistic? That's just a really hard exercise, I think, to go through, especially because you don't do it that often. And so it's like one of these like low frequency, low rep things. And there's just not that many people in the world that has a ton of reps at these things.
28:56 Harry Stebbings? If we get to that critical inflection moment of predicting saturation in a channel, what do we do then? Do we go, right, we're predicting saturation and we're going to divert a little bit of resources and really try and carve out? A content strategy, a SEO strategy, a you name the channel. Or do you say, hey, we've got one channel that's saturating. Let's split the resources between four and see which one springs with hope. Which one is the right approach?
29:24 Speaker 00 Biggest mistakes of this are, one, not starting early enough. Two, underestimating the amount of time that it takes to get a new channel or new product going. And three, over resourcing it. And then four, essentially, this is an area where I would actually take a couple bets, but not like 10 bets, right? So the way that we did this at HubSpot, when I came in there, my mission with a couple others was help establish a second product category for the company. And a second channel, go from the sales and marketing motion we had to more of a product led motion. We had Those two missions to figure out. I did not come up with this. This really came from Dharmesh and Halligan, the two founders, which was the philosophy behind it was, okay, we are going to start with multiple bets.
30:09 Speaker 00 We are going to treat each one of these bets like a new venture investment. We are going to seed fund this. And so they like made us come and they would pitch for our seed funding for the idea, which was basically one year of funding for a small team, like a four or five person team. And then at the end of that year, and then Halligan, JD, who was the COO, like they would act like our board essentially. And we'd have to go do like board meetings internally to them every like month or couple of months. And then at the end of the year, we'd have to come pitch for our Series A. And so like the next year would be like equivalent to like a Series A funding for a slightly larger team and then so on and so forth. And then at some point, the bet gets big enough where it's like, now we have to integrate it into the core machine.
30:52 Speaker 00 That's typically around the Series B phase, I would probably say, like internally. And then things got integrated into the machine. But as part of that, they initially funded a few bets for the first couple of years. And sometimes they would work, sometimes they wouldn't, and they wouldn't pass to their Series A funding. And it was kind of that natural evolution. But part of that, I think, is companies, I think probably the biggest one that kills these things is they over resource them. They over resource these things. The more people you have, it's like the slower these things go, the more voices that you have in the room, the slower that you iterate and change, like all of these types of things. You want to find a couple of people, like a couple of generalists, separate them off, protect them a little bit from the rest of the company.
31:36 Speaker 00 Essentially let them loose with the right guardrails and checkpoints. So with a couple of people. And look, we made this mistake at Reforged with one of our new product bets. And last year I had to kill it, fully reset it, handpick a team of three people and go forward with it. It's one of those painful mistakes that especially with people who have something already going, they're like, oh, I've got resources. So let me just leverage that. And they fail to remember all of the lessons learned from the early stages, which is just like sometimes more people, more money does not help you find things faster. It's about going through the natural stages with their natural constraints to find things along the way.
32:15 Harry Stebbings? What do you do if this channel is working, but it's not driving back to the core? And what I mean by that is like, I was with a company this morning, an enterprise company, and they've actually got a really impressive short form video execution, and they've done amazingly well on TikTok and YouTube Shorts, but there's no obvious correlation to customer signups or to revenue. And so it's like, yeah, a ton of people are watching your videos, but what? I didn't really know how to advise them.
32:40 Speaker 00 Yeah.
32:40 Harry Stebbings? What do you advise when there's like a channel that's working in terms of attention, but not obvious value derived back to business?
32:48 Speaker 00 Yeah, it's adapt or kill. So we went through this at HubSpot. You know, the first product we built, it's now called, referred to as the Sales Hub. But at the time, it was essentially a bottoms up tool for sales folks that let them track their emails and contract opens and stuff. And at the time, that thing was magical. We got to 100,000 weekly active users or something, and then we looked at the user base and there was a huge mismatch between a lot of the types of users that were showing up in that product and the target market that was driving the core strategy of the business. The core strategy of the business and the marketing product was really around mid-market companies, companies that were between 20 and 2,000 employees. And we had high conviction on that.
33:31 Speaker 00 But when we looked at the user base of this, we were like, oh shit, these two channels, these two growth mechanisms, yeah, we're getting some of that mid-market, but there's a huge amount of these like very small business owners of one or two-person shops or like other pieces that were using this tool. And there was a huge disconnect between those two things. And so we had to go through this exercise of adapting. Okay, we've got some of these components working, some of these aren't. What if we held the market constant, like the mid-market piece? What would we do to these other pieces around our product and our channel and our pricing to make the rest of this work? And so what we did is we adapted some of the product that we were doing.
34:13 Speaker 00 We redid our roadmap around some features for like the, the sales leader and the sales admin targeted more the mid-market. But then we had to change our channel. So we killed a lot of the paid acquisition. We kept a decent amount of the viral loops, but we added in more of a content motion. We layered in content and a little bit of inside sales. And then we had to change the pricing to match with that. So we raised prices in a couple of areas. I think like minimum seat limits, all those types of things. And then the system started to work for that core market, which was the mid-market. So I think in your case, there's this whole exercise of like, oh, there's this really cool thing.
34:54 Speaker 00 Do we have bets that like can adapt it, can mold it to what we're trying to sell and what our product is? Let's take a couple of bets at that. But otherwise, honestly, with limited time, limited resources, you gotta kill it. Because what you're doing is you're stealing time and attention away from finding that core machine that does contribute. You're focused on the icing, not the cake and you need to eat the cake first.
35:19 Harry Stebbings? Speaking though, like knowing what works and seeing the success in a channel, the decision around whether it's successful or not is largely made by the metrics that you see and how you interpret them. You've said before that people often get metrics wrong. What do you think are the biggest ways that you see founders and growth teams really misunderstand or get metrics wrong?
35:39 Speaker 00 Well, the first and foremost is metrics before strategy. Your metrics are there to help answer the question, is your strategy working? They are not there to determine your strategy. You have to have a reasonable hypothesis of what your strategy is first. Like what is your core growth loop, like all of these things? And then you can say, well, what are the metrics that we would use to measure that strategy? And what would success look like? So that's number one. Number two is they basically go quant before qual. So to understand what your metrics should be, you have to understand the qualitative underpinnings.
36:15 Speaker 00 A great example of this is retention. Like, setting retention metrics, for example, is 80 to 90% understanding the qualitative definitions of what is the problem that you are solving? What is the natural frequency that that problem occurs in your target market's life? And then you can start to match the metric to it. Like, should we be tracking this on a weekly active user basis? Or a monthly active user basis? Active, what does active mean? Well, what is the behavior in the product that indicates we are solving the problem for this user? But those things are underpinned by your qualitative definition
36:56 Speaker 00 in understanding of like your user, of the problem, of the natural frequency. Whereas I think most companies are like, we're just gonna track it on like a weekly active or a monthly active or like quarterly buyer case, like all that kind of stuff. And I'm like, well, okay, what is the problem? Does your user actually incur that problem that often in their lives, right? But that ends up being the dynamic there first. I would say the third, especially among SaaS companies, is they focus on revenue metrics before usage metrics. So almost everything is defined on like ARR, MRR, my revenue retention, all of those types of things. But what people miss with that is that usage is what creates revenue. Revenue does not create usage.
37:39 Speaker 00 You have to understand the usage of your product first. Like, those are the things you should be focusing on, not necessarily the revenue metrics. This is a classic like sub example of outputs before inputs as part of that. And then I would say finally is like, a lot of people mix customers versus users, right? So there are dynamics in some SaaS products that are very different. Like HubSpot, we had a customer, but we had multiple users on that customer's account. And to understand how to move, grow the business and how to grow the product. It actually wasn't about a usage metric at the customer level. It was about a usage metric at the user level. All right.
38:20 Speaker 00 This was very clear with something like the free CRM, which we built is like, we originally tracked weekly active teams. But it's like, okay, well, the way to influence a team is actually to find one of the users in that team and how we can influence their usage of the product. And oh, by the way, there's two very different types of users. There's the admin of the CRM and there's the end user of the CRM. And the way to move their usage is fundamentally different as well. And so just by focusing at the dollar or the customer level, you actually don't get deep enough into the things that you need to understand to actually grow the business. You're two levels higher, too high in altitude.
39:00 Harry Stebbings? Speaking of actually growing the business, over the last few months, AI has been the hottest thing. And I'm just fascinated for you at the center of the world of growth. How do you think AI changes the way that growth teams operate and the world of growth?
39:16 Speaker 00 This is an interesting one because I think it changes a lot and not a lot at the same time. I think the surface level tactics and systems will definitely change a lot. A lot of these analyses that seven years ago were sort of leading edge, things like finding what your habit and aha moment are, for example, which comes down to some form of a regression analysis, like those types of things. All those things are going to get automated, super, super simple.
39:43 Harry Stebbings? Sorry, can I just interrupt you? How is finding your aha moment automated? Is it not highly nuanced and contextual, dependent on the millions of infinite options of what a product could be?
39:54 Speaker 00 I think like today, it's already kind of automatically done inside tools like Amplitude and others. But I think there's another layer of that where the friction to do them doesn't require the same skill set that it required you eight years ago. But this kind of gets to the dichotomy that I was talking about. The things that don't change, that I don't think AI is going to really help you with that much is understanding like all of these qualitative underpinnings of your product, of your use case, of your problem, of your natural frequency. And then the psychological levers you can tap into to move a user's behavior. AI is going to have a really hard time in doing that thinking.
40:37 Speaker 00 But in addition to that, growth boils down to four things, which is You find an arbitrage opportunity, you use that to spark some type of compounding system, some type of growth loop, you optimize the crap out of that system and then you repeat that, but don't wait too late, right? Like you try to anticipate the saturation, right? Like those things do not change, right? Like all of growth will still come down to those things. I think it's just a lot of the surface layer tactics and other components of how we do those things actually like will change. Maybe we get a fundamentally new distribution channel out of this wave of AI technology. If so, that is like a frickin'
41:21 Speaker 00 field day for growth people because what a lot of people are focused on right now is like, oh, AI is going to take away traffic from Google. It's going to reduce my marketing surface areas because people are just going to be interacting with a chatbot versus a website. And I'm like, yes, that's true. But at the same time, it's going to also inject all sorts of new chaos into the system. And chaos is actually good for growth people because within that chaos lives these arbitrage opportunities, these new things that nobody else has figured out. And those sparks are what give new companies and new things life and hope.
41:57 Harry Stebbings? When you think about, and I think lessons are learned from often mistakes, what is the biggest growth decision you've made that went wrong, Brian? And how did it change your mindset?
42:08 Speaker 00 So my fundamental view is like, the only way to figure things out is to like create. You can do some thinking upfront, but then you got to get into like the making, the creation of these things. And you learn through that creation of like what's right and wrong. And then you go back to like the start of the process and think a little bit. I get really frustrated with folks who think they can think their way to all the solutions. And I'm like, that's impossible. We just need to get into the making of things, right? And so as a result, I think a lot of people look back at your question that you asked and are like, well, what is something that I thought long and hard about, but I was wrong? And as a result, it like had a huge cost. I just try to view things as like, it's just being wrong is like a next step. I will answer your question directly. Okay. So my biggest
42:51 Speaker 00 Mistake at HubSpot was I was in love with like the virality and other things that we had going with the early product. But there was a disconnect with the core target market of the core business. I was pushing for like that virality. I kept going down that path and I created a lot of resistance. What I didn't see at the time was, yes, even though I had those things working, the fact that there was a disconnect with the core target market meant that down the road, we would not be able to leverage all of the assets that we had already built up on the core business. All of the core knowledge around our content motion, our sales motion, our knowledge of the mid-market, like all of those types of things. And so what that did is it probably left that product in a state that disconnect with the core business for a little too long.
43:35 Speaker 00 Luckily, I actually got vetoed over this and we maneuvered the product and the business to a different direction. At the time, I disagreed with it, but now in hindsight, I'm like, ah, I was the dumb one. I was stupid. And so like, that was a really bad decision. I think in the context of Reforge, I think we've probably made two mistakes. One was a few years ago, we transitioned from a transactional to a subscription model, a membership model. That had huge growth initially, like just massive growth. And that kind of put the blinders on us to whether or not we were also doing the things to make a subscription product sustainable.
44:15 Speaker 00 And as a result, we ended up being too late to following up with some of the products and some of the features that create the type of habitual usage that's required for a recurring model. And so we had to work ourselves out of like a stall point. So I think that was like a case where the metrics ended up misleading us. And we actually weren't looking at everything that was happening underneath the surface in terms of how users were using the product, how they were thinking about the product and how those things might end up leading to that future ceiling that we were talking about. That's a good point of like not anticipating the saturation. I've also done some stupid growth hacks, which we can talk about.
44:56 Harry Stebbings? Oh, come on. Before we do a quick fire, tell me about a stupid growth hack. I love that.
45:01 Speaker 00 Well, early in the Facebook platform days, one of the apps or games that we had was this virtual gifting app. And where you could like send these virtual gifts. It was like dumb, but people enjoyed it. Right. And so at the time, through Facebook's platform and API is that when a user signed on to your app, there was essentially the ability to like auto message that person's friends, like up to 20 folks from that person. So what we did is when a new user installed the app, we would just pick, I think it was like 10 or 20 friends at random out of their friends list and send them a virtual gift from them. This was still before AWS. This thing started melting our servers within like four hours. Like it was just growing. And so we had to shut
45:45 Speaker 00 it off. The problem with this, besides it being incredibly spammy, was that afterwards, we find out that, we didn't think about this, is like, when you're choosing somebody at random like that, in some cases, we were choosing like ex-wives and ex-girlfriends and they were receiving like a virtual gift of like a rose from somebody. We created this confusion. And like after that, I was like, okay, that was one of the dumbest things I've ever done. It grew. It worked. We figured out that arbitrage opportunity did not translate into a sustainable system and created some really awkward conversations in the world. But that was one of the fun ones for, for a little bit. We'll not do that again.
46:23 Harry Stebbings? Right. That is amazing. Listen, Brian, I would love to move into a quickfire round. So I say a short statement and then you give me your immediate thoughts. Does that sound okay?
46:30 Speaker 00 Let's do it.
46:31 Harry Stebbings? So what tactic has not changed over the last five years? If you think there's one that continues super strong?
46:38 Speaker 00 Word of mouth. If you can get any form of virality, if you can get one user to tell another user, that has been around forever, will be around forever.
46:45 Harry Stebbings? What tactic has died a death?
46:47 Speaker 00 Oh, wow. Many.
46:49 Harry Stebbings? I feel SMS. SMS people feel intrusion nowadays.
46:53 Speaker 00 SMS feels the intrusion. However, it depends on how you define it. Like in some parts of the world, like WhatsApp, for example, is just a massive growth vector for folks. I've looked at companies that complete their entire growth strategy is on WhatsApp. That type of direct messaging, I think, still works in some parts of the world. I think when we talk at the tactic level of things that died, like you can basically tie it to some Type of change in the distribution channels. Just taking something as simple as importing somebody's address book as an example. It doesn't really work anymore because there's been so much misuse of that, that people are skeptical and fatigue and like all that kind of stuff. It's like, you can't really do that unless you've like built up trust with your users
47:37 Speaker 00 and have a really good reason.
47:39 Harry Stebbings? Who do you think is the single best growth practitioner that you've worked with? I know that's so hard to say, given Reforg.
47:46 Speaker 00 Oh geez.
47:46 Harry Stebbings? But who would you say is... Come on.
47:49 Speaker 00 Okay, I'll name a few on the different dimensions. Strategically would be Casey Winters. The best person that thinks about the psychological elements of growth would easily be Darius Contractor. And then the person, a very specialty, who I consider like a mad scientist. I call him G, but it's Guillaume Cabane. He was at Segment, Drift, like a bunch of others. But those three on different dimensions is who I would probably name.
48:19 Harry Stebbings? What do you think is the biggest misconception that people have with growth?
48:23 Speaker 00 Growth does not mean one thing. As we've talked through, you have to understand the different types of growth systems out there, the ones that work with what types of businesses. And then how do you map talent, metrics and other things to those systems? And so I think for a lot of cases, people just, they talk about growth as it's like a single thing. And that's like trying to say engineering is a single thing. But there's so many different types of engineering that if you were to try to describe the discipline and practice of engineering, you just like lose all of the substance.
48:55 Harry Stebbings? Will AI change the tooling incumbents of growth teams? Or will they enhance the existing incumbent?
49:02 Speaker 00 Both.
49:03 Harry Stebbings? Who's most strong and who's most vulnerable from the incumbent side?
49:07 Speaker 00 It's hard to not say Twitter right now from a vulnerability perspective. Strongest, I think this is a little topic de jour, but I think you gotta go Facebook for a few reasons. They still have the OG growth talent that they did from 15 years ago. Javier, Alex Schultz, right? Like, those people are still there. And so you got that. You've got the capital advantage. You've got the advantage that you can leverage billions of users on your other platforms. They still have like the most data. So I think you put all of those things together. I would probably put them in the strongest point. I think they're probably like the least vulnerable as long as the company priorities are pointed in the right direction.
49:49 Harry Stebbings? Why do you think Twitter is vulnerable though? I actually don't. I think elections coming up. I think, you know, we are early adopters, the tech ecosystems, early adopters. Majority of people don't actually know about threads, if we're honest. I mean, we're in Europe. It's not going to be here until early next year. I think Twitter is strong. Elon's brand is bigger and bigger. I wouldn't bet against Twitter.
50:09 Speaker 00 Yeah. So I played a fun game with a couple of folks. If you were have to predict Threads DAUs and Twitter's DAUs one year from now. Threads is at about 100 million signups and then Twitter's is, I think, 250 million, something like that. If you had to predict, what numbers would you choose?
50:25 Harry Stebbings? Oh, this is so unfair. I just interviewed Adam Mosseri, who's running Threads earlier.
50:29 Speaker 00 Oh, you did. Oh, yeah, that is unfair. Yeah.
50:33 Harry Stebbings? Honestly, I don't think Threads is going to work. I think it will fail pretty quickly. I don't think they'll get retention. And I think the majority of people on Twitter are actually 100 million of the Threads people that signed up are the 100 hardcore techies. And I think the other 900 million won't move, like the stickiness. I think people are also forgetting two things. One is the friendship graph and then the other is the interest graph and they don't overlap. On Instagram, I like Audi. I like Chanel, visually aesthetic, inspiring. And then I have my brain, which is Bellagio, is Marc Andreessen on Twitter. I don't want a correlation of them both in Threads. This is not how a next wave of social works. So for me, super simple to cut to your point, I would say Threads does not work.
51:16 Harry Stebbings? And I would say maybe it teeters along at 5 million DAU with hardcore, small numbers. And I would say Twitter has modest growth to 275, 300 with election spikes.
51:29 Speaker 00 Interesting. Yeah, I chose they're flat. I think Twitter's flat, 250 million. I actually agree. I lean in your direction, which is that I think people are. Overestimating the vulnerability of Twitter. But when you ask that question, it's like, I just don't think Twitter's going to grow. And that's why I think it's vulnerable, right?
51:46 Harry Stebbings? Have they seen, if you were to be head of growth at Twitter, what would you do?
51:51 Speaker 00 I think this gets back to what we were talking about earlier, which is like, you can have product market fit lives on two vectors, the strength of the fit and the size of the market. I think what you're really seeing, and I think it was like Eugene Wei who captured this well in his essay, which is they actually had really strong PM fit with a smaller market. Like they had these like subcultures of Twitter of like tech and politics and other things. And what they've done with a bunch of their changes, like the algorithmic feed and all that kind of stuff, is they're essentially searching for that PM fit with a larger market, a larger market of folks. The challenge with that is that you do that and there's a risk of breaking like your original PM fit.
52:35 Speaker 00 And that's going to be the big question if they keep pushing aggressively in that direction. So I think the challenge that they're caught in is the reason they're making all these changes is because of Elon's $44 billion buy and needing to make that money back. So he has to find PM fit with a larger market in order to make that back. And that's basically forcing essentially maybe unnatural plays into the game.
52:57 Harry Stebbings? Do you know how I'd do if I was Elon?
52:58 Speaker 00 What would you do?
52:59 Harry Stebbings? I would do an Instagram clone.
53:01 Speaker 00 Oh, God, I don't know what kind of tweets back and forth that would create between Zuck and Elon.
53:06 Harry Stebbings? I would do an Instagram clone and I would make sure that there were no hacked accounts and no fake accounts. And I would say it's like Instagram with no fake accounts.
53:16 Speaker 00 If threads doesn't work out, that just goes to show, so they have the talent. They've got the distribution to leverage. They've got the data and they've got the capital. If they are not able to break a network, create and break a network effect of Twitter, that just goes to show how strong network effects can be among like a certain market. So I think that's the interesting thing that's going to play out. I kind of agree with you. I think they probably went a little too fast on the demand side of this network. And now they've got to play a game of filling that network with the right creators. And I think The question is, can they do that fast enough to like actually get that flywheel moving in a sustainable direction? So it'll be interesting.
53:57 Harry Stebbings? Brian, final one. When you look at the last 12 months, not including Threads, when you look at growth strategies, what one have you been most impressed by across the landscape and why them?
54:09 Speaker 00 I have an unfortunately like discolored view of this because you name a company and I guarantee somebody is a Reforge member. And so what I often see is like things on the outside that look very smart choices where it was either a little bit luck or I also see what all the problems are. So.
54:30 Harry Stebbings? So I think Canva would be one for me. Canva talk and their.
54:34 Speaker 00 Canva has done an excellent job. Canva has done a very, a very, very good job and probably fair. The marketplace has done a pretty dang good job here in the US. The ones who had to really work for the growth tend to be the most talented teams, right? But there's these situations like OpenAI where they kind of captured lightning in a bottle. And I would put that more like, I wouldn't attribute amazing growth strategy or growth talent there. I would attribute that to amazing technology talent and product talent. But I think those two things are different. I think DoorDash is probably another one where they had to fricking work for it and they took on some people who had advantages that they did not have, like Uber Eats and other ones. And so that's probably another
55:19 Speaker 00 case where they had to work for it. Shopify probably has the best talent density at the moment. Luke Wavask is basically like probably one of the most amazing recruiters I know. And he's built the talent density there that easily say is probably the highest talent density team across tech at the moment.
55:38 Harry Stebbings? I totally agree. I'm a former guest on the show and so thrilled to hear it. Brian, I've absolutely loved doing this. Thank you so much for joining me today. And I'm glad I sent the schedule a couple of hours ago so you couldn't get too used to it because that wasn't very aligned to the schedule. But this was a pleasure to do. So thank you so much.
55:53 Speaker 00 Thanks for having me.
55:55 Harry Stebbings? I mean, that was so much fun, Stu. I've loved Brian's writing for a long time. And if you want to see the video version of that interview, you can check it out at YouTube by searching for 20VC. That's 2-0-V-C. But before we leave you today, listen to this.
56:07 Speaker 02 Mercury has been a breath of fresh air.
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Previous 20VC: Scaling Wait But Why to 600,000 Subs; Behind the Scenes on The Research Process, How to Learn Entirely New Topics Fast, The Writing Process and Building Good Habits & The Distribution Process and the Business Behind the Blog with Tim Urban Next 20VC: Does Value Accrue to Incumbents or Startups in the AI Race, Why Model Size Matters More Than Data Size, Why Artificial General Intelligence is Far Away, Why Carpenters Will Be Paid More Than Software Engineers & Future of Jobs with Richard Socher Page updated September 29, 2026 · transcript and summary are machine-generated
