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

26:26And it wasn't like they stopped at that first seal and been like, oh, they're the hands up like we're done. 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 like actually just very hard for both people in a company to do. So I actually think predicting saturation is one of like 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 at the game in the game at this.

27:10Both from a growth and product strategy perspective. If you take into account, they have not missed eight earnings since they went public, which was like eight years ago. They have never missed in earnings. It's a perfect record as far as 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 emotion is not going to get us to our five -year goal, which was maintaining 50 % year -over -year growth for five years.

27:53And what that led the company to do is say, oh, we need to kick off a multi -product strategy. And actually finding the second product is probably going to take us a year or two to do. So 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?

28:30And 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, what does feel realistic? There's just a really hard exercise, I think, to go through, especially because you don't do with that often. And so it's like one of these low frequency low wrap things and there's just not that many people in the world that has a ton of reps at these things. If we get to that critical and flashing moment of predicting saturation in a channel, what do we do then?

29:02Do we go right? We're predicting saturation and we're going to diverge 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? Biggest mistakes of this are one not starting early enough to 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 two more of a product Let's motion.

29:58We had those two missions to figure out. I did not come up with this. This really came from Dar Mashin, Haligan, the two founders, which was the philosophy behind it was, okay, we're gonna start with multiple bets. We are gonna treat each one of these bets like a new venture investment. We are gonna seed fund this. And so they would lay like me just 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 Haligan JD, who was the COO, they would act like our board, essentially, and we'd have to go do board meetings internally to them every month or a couple months.

30:38And then at the end of the year, we'd have to come pitch for a series A. And so the next year would be equivalent to 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 that's typically around the series B phase. I would probably say 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.

31:10But 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 people, like a couple generalists, separate them off, protect them a little bit from the rest of the company, essentially let them loose with the right guardrails and checkpoints, so with a couple people. And look, we made this mistake at ReForge with one of our new product bets.

31:45And last year, I had to kill it, fully reset it, hand pick 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. What do you do if this channel's working, but it's not driving back to the core?

32:19And what I mean by that is like, I was with a company this morning and Enterprise Company and they've actually got a really impressive short form video execution and they've done amazing 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. 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? Yeah, it's adaptor 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.

32:55But at the time, it was essentially a bottoms up tool for sales folks that let them track their emails and contract open stuff. And at the time, that thing was magical. We got to a hundred thousand 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 2000 employees and we had high conviction on that 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.

33:51And 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. We did our roadmap around some features for like 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 areas.

34:42I think like minimum seat limits all those types of things and then the system started to work Or 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 Do we have bets that like an adaptive and mold it to what we're trying to sell and what our product is? Let's take a couple 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 Speaking though like knowing what worse and seeing the success in the channel the decision around whether it's successful Not as long as you made by the matrix that you see and how you interpret them You said before that people often get metrics wrong What do you think of the biggest ways that you see founders and growth themes really misunderstand or get metrics wrong?

35:39Well, 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.

36:15And 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 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 in understanding of your user of the problem of the natural frequency.

37:02Whereas 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.

37:37Revenue does not create usage. 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 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 Hub Spot, 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?

38:20This 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 defined 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 up 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.

38:57You're two levels higher, two high and altitude. 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 the growth teams operate and the world of growth? 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 in a ha moment are, for example, which comes down to some form of a regression analysis.

39:40Like, those types of things. All those things are going to get automated. Super, super simple. So, it can kind of just interrupt you. How is finding you a harm moment automated? Is it not highly nuanced and contextual, dependent on the millions of infinite options of what a product could be? 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.

40:12The 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. 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?

40:54Like you try to anticipate the saturation, right? Like those things do not change, right? 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 freaking field day for growth people because what a lot of people are focused on right now is like all 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 the 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 when you think about and I think less lessons learned from often mistakes.

42:01What is the biggest growth decision you've made that went wrong, Brian? And how did it change your mindset? 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 gotta 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?

42:34And 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 mistake at Hub Spot 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 Ment 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 us 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.

43:29And so what that did is it probably left that product in a state that disconnected the core business for a little too long. Luckily, I actually got vetoed over this and we maneuvered the product in the business to a different direction. At the time, I disagreed with it, but now in hindsight, I'm like, I was the dumb one. I was stupid. And so 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.

44:15And 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 of the product. about the product and how those things might end up leading to that future ceiling that we were talking about.

44:50That's a good point of not anticipating the saturation. I've all done some stupid growth hacks, which we can talk about. Oh, come on, we go before we do a quick fight. Tell me about a stupid growth hack. I love that. 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 send these virtual gifts, it was dumb, but people enjoyed it, right? And so at the time through Facebook's platform and API is that when a user signed onto your app, there was essentially the ability to like auto message that person's friends like up to 20 folks from that person.

45:26So 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 friend's 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 it off. The problem with this besides it being incredibly spammy was that afterwards we find out that we didn't think about this as like when you're choosing somebody I random like that in some cases we were choosing like X wives and X girlfriends and they were receiving like a virtual gift of like a rose from somebody They created this confusion.

46:04Like 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 a little... We'll not do that again. Right, that is amazing. There's a brunner. I would love to move into a quick fire round. So I say short statement and then you give me your immediate thoughts. Does that sound okay? What's it? It's a what Titanic has not changed over the last five years. If you think there's one that continues super strong.

46:38Word of mouth. If you can get any form of irality, if you can get one user to tell another user, that has been around forever, will be around forever. What Titanic has died of death? Oh, wow. Many. I feel SMS. SMS people feel intrusion that is. 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 factor 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.

47:25It doesn't really work anymore because there's been so much misuse of that that people are skeptical and fatigue and like all I kind of stuff Is like you can't really do that unless you've like built up trust with your users and have a really good reason Who do you think is a single bass growth practitioner that you've worked with? I know that's so hard to say given Reforged. But who would you say? Come on Okay, I'll name a few on a different dimensions strategically would be Casey Winners. The best person that thinks about the psychological elements of growth would easily be Darius Contractor.

48:03And then the person, very speciality, I consider like a mad scientist. I call him G, but it's G. O'MCABANE. He was at segment drift, like a bunch of others. But those three on different dimensions is who I would probably name. What do you think is the biggest misconception that people have with growth? 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.

48:44And that's like trying to say engineering is a single thing, but there's so many different types of engineering that if you were trying to describe the discipline and practice of engineering, you just like lose all of the substance. Will AI change the tooling incumbents of growth teams or will they enhance the existing incumbent? Both. Who's most strong and who's most vulnerable from the incumbent side? It's hard to not say Twitter right now from a vulnerability perspective. Strongest? I think this is a little topic -desure, but I think you've got to go Facebook for a few reasons. they still have the OG growth talent that they did from 15 years ago.

49:23Javier, 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. Why do you mean Twitter's vulnerable? I actually don't. I think elections coming up. I think, you know, we are early adopters. The tech ecosystem's early adopters.

49:58Majority people don't actually know about threats if we're honest. I mean, we're in Europe. It's not going to be here until early next year. I think Twitter's strong. Elon's brand is bigger and bigger. I wouldn't bet against Twitter. Yeah, so I played a fun game with a couple folks if you were have to predict threads DAU's and Twitter's DAU's one year from now threads is at about a hundred million signups and then Twitter's is I think 250 million something like that if you had to predict what numbers would you choose? Oh, this is so on fact I just issued out of Missouri who's running threads out of here.

50:29Oh, you see? Oh, yeah, that is I bet is unfair. Yeah, honestly, I don't think threads is gonna 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 signed up are the 100 hardcore techies and I think the other 900 million won't move like the stickiness. I mean 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 Bellagy, it's Mark Andrew on Twitter.

51:06I don't want a correlation of them both in threads. This is not how a nice wave of social works. So for me, super simple to cut to your point. I would say threads does not work and I would say maybe it teaches along at 5 million DAU with hardcore small numbers. And I would say Twitter has more disc growth to 275 300 with election spikes. Interesting. Yeah, I chose their flat. I think Twitter's flat, 250 million. I actually agree, I lean in your direction, which is that I think people are overestimating, you know, the vulnerability or trouble. But when you ask that question, it's like, I just don't think Twitter's going to grow.

51:44And that's why I think it's vulnerable, right? Have they seen, if you would be ahead of growth at Twisted, what would you do? 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 assay, which is they actually had really strong pre -emphit with a smaller market. Like they had these like sub -cultures 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.

52:29The challenge with that is that you do that and there's a risk of breaking like your original PM fit 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 by 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. Do you know how to do if I was Elon? What would you do? I would do an Instagram clone. Oh God.

53:02I don't know what kind of tweets back and forth that would create between Zach and Elon. 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. If Reds doesn't work out, that just goes to show. So they have the talent. they've got the distribution, the 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 gonna play out.

53:38I 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. Brian, final one, when you look at the last 12 months, not including threads, when you look at gross strategies, what one of you been most impressed by across the landscape and why them? I haven't unfortunately like discolored view of this because you name a company and a guarantee somebody is a a reforge member.

54:17And 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 I think Tanva would be one for me. Tanva talk and there is... Tanva has done an excellent job. Tanva has done a very, 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. Now, we put that more, like, I wouldn't attribute amazing growth strategy or growth talent there.

55:02I would attribute that to amazing technology talent in product talent, but I think those two things are different. I think DoorDash is probably another one where they had to frickin' work for it, and they took on some people who had advantages that they did not have like over eats and other ones. And so that's probably another case where they had to work for it. Shopify probably has the best talent density at the moment. Luke Lovaska 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.

55:38I totally agree out the former guests 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 can get to use to it because that wasn't very aligned to the schedule but this was a pleasure to do so thank you so much. Thanks for having me. I mean that was so much fun too. 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 on YouTube by searching for 20VC that's 20VC but before we leave you today listen to this.

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