Brian Balfour: Startup Growth Secrets from HubSpot; Distribution Stratagies; Impact of AI | E1049

1. 0:00 – 0:27

   Intro

   1. BBBrian Balfour0:00

      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, those sparks are what give new companies and new things life and hope.

   2. HSHarry Stebbings0:14

      (instrumental music) Bryan, this is such a joy to do. I mean, I feel like I've interviewed like everyone from Reforge, and so I've been waiting for this show in anticipation. So thank you so much for joining me today.

   3. BBBrian Balfour0:25

      Thanks for having me. I'll do my best

2. 0:27 – 6:30

   Brian's Early Career and Growth Philosophy

   1. BBBrian Balfour0:27

      to, uh, live up to all the rest of the folks you've interviewed, but, uh, we'll see how this goes. (laughs)

   2. HSHarry Stebbings0:32

      Listen, I heard nothing but wonderful things. I wanna 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?

   3. BBBrian Balfour0:42

      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. It's a- it- like almost like a coaching lineage, like, all the way back to the social gaming days. And so I had started this company, uh, shortly after school called Viximo, and, uh, we were in the social gaming space, uh, for a while, and then it kinda transitioned into mobile gaming. And that was like the perfect petri dish to essentially, like, create growth people, because what the Facebook platform did was that it opened up a ton of, like, viral channels as well as, like, paid acquisition channels. The games were very driven by, like, product-driven levers, uh, like virality. It was a highly quantitative game. You were playing this high, like, arbitrage game. You were constantly seeking out, like, the things and the APIs that people e- out- still, like, didn't understand. And games are so focused on, um, like, the psych- 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. Um, i- combining it with the quantitative elements of growth as well as with the psychological elements of growth, right? And so those three things combined, especially in a highly- high-pressure, high-competitive environment is what really formed, I think, the, like, initial injection into, uh, like, the growth scene. And so as a founder of that company, we- 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, uh, there was just, like, that competitive nature of it that, like, really got to me combined with, like, my quantitative lean on, you know- like, on the world and my skillset. And so I just loved it, and I got into it and, uh, you know, been there ever since.

   4. HSHarry Stebbings3:16

      I mean, sounds like you should be a VC as well. But, uh, it is fascinating to see actually how many came from those early Facebook gaming days, so totally get you there. I do wanna ask, I think so much is gained in- 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, call yourself up that night before, what would you tell yourself knowing all that you know now?

   5. BBBrian Balfour3:41

      Oh, boy. Uh, probably two things. One is, like, there is, um- there's not an infinite world of growth options. It's actually f- uh, it's fairly well defined and constrained, and that's something that I've li- I've learned, um, pretty dramatically, especially through Reforge where I get to see ins- inside th- you know, the growth of thousands of different companies, including the top public ones all the way down to your early stage ones. 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 onto the menu. Knowing those sets of things I think 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, what is underneath them is what we call our Reforge growth loops, where other people call flywheels, but they're basically systems that work like compound interest, right? They are things that feed, uh, 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, right? And it doesn't- it doesn't look like much. And so what that does is it puts a lot of, uh, uh, 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, and this isn't moving to the 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. It- th- the hockey stick happens later, right? And so you have to look for those 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- this little campfire is gonna turn into some kind of raging, uh, thing that you- you can't even control, um, like later on. And so I think I would say those two things, and I- I still don't think I've fully learned, uh, the patience one is like- I think I'm still probably a little too impatient, um, o- on things, but I- I think that's part of being a founder as well is just- you just- I don't know, you just- you don't have- you don't have the patience for things.

   6. HSHarry Stebbings6:05

      I- I have to admit, um, I- I have these schedules, which I sent you a couple of hours ago, so I'm just gonna, like, abdicate away from it because I think I have- there's something I have to touch on with you. You mentioned now the compound interest and bluntly 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.

3. 6:30 – 16:52

   Understanding and Building Growth Strategies

   1. HSHarry Stebbings6:30

      How do you determine when something just isn't working and won't work versus consistency, just keep going?

   2. BBBrian Balfour6:39

      This is certainly a difficult question for anybody to answer, and I wish it was, like, a binary thing where we could pull up a spreadsheet and, and, and say, "If you're at this number, it's not working. If you're at..." and it's not, right? Like, I think like most things, um, there's a, there's a lot of science here but there's a little bit of art, uh, as well. And I think the, 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, I think in the content game or the podcast or whatever, maybe you're looking at traffic or downloads and, and all of those types of things. At least in, like, the content game on SEO, the things that you're actually wanting to start to look at is like, well, you know, "Is my domain authority increasing as I relea- is my rate of, like, new pages, uh, starting to increase over time?" And these are, like, the types of signals that as they grow, uh, they feed each other and, uh, and, and things like, 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, anything at all, whether we wanna talk about metrics or this question or all of that kind of stuff, uh, hiring, anything, you have to have a hypothesis i- about how your product grows, which is captured in what we call as, 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 a do- more than a dollar out?" And what a growth model says is, "When I put a user in, how do 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, right? So, uh, if I'm looking at a product like, uh, I don't know, what's it called? Loom is a, when I was an early investor and, and advisor in, right? Money does not help that company grow that much, right? The things that are helping that product grow are its organic viral and content loops, right? I se- I record a Loom video and then I send it to somebody, right? Uh, and then that person kind of picks up the product and they start using it. Now, 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, uh, 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 Reforge, right? And that's a one-to-many use case that has a lot more virality built into it. And so I can start to influence, like, these steps of the system by understanding what the system is and where the constraint, eh, where the constraint in the system is. The constraint also tells you who should you hire and when should you hire that person, uh, as pa- as part of the system, as well as what metrics to track, uh, along the way. But getting back to your original question, how do I know something is not, 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 the system goes from me having to add a ton of manual energy into it to it starting to, you know, act like compound interest and it, like, evolving itself. And so playing that out ends up being, um, the fundamental key, uh, part of the equation to understand, like, when to kill something or not.

   3. HSHarry Stebbings10:37

      Bryan, can I ask you, I think... I, I wa- I'm an early stage investor. I work with many, many, kind of, 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?

   4. BBBrian Balfour10:58

      Well, I, I would, I would first go back, which is, I actually think most peop- a lot of people don't understand what the machine is. And, and the reason is, is if you ask them to, uh, draw you a picture that answers how does the product grow, right, they'll either struggle to draw that picture or it'll, like, it'll look like such a jumbled mess that you as the recipient can't really understand it. That, that's actually a signal that not only did, have they kind of boiled it down and that they understand it, but they're not able to communicate it in a way that the rest of the team understands it. And if 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," right? Uh, because they don't really understand how, how things, like, map, uh, uh, actually, like, map to, uh, the equation. But understanding the constraint, um, ends up coming down to the quantitative part of this, right? The, the exercise I just, uh, that I just mentioned is more of the qualitative part is like, "Hey, can I draw a bunch of boxes and arrows that say, um, 'As a new user enters the system, they walk through these four steps and if they complete these four steps, another new user, like, come, like, comes out of it,'" right? That, that's kind of what that picture looks like. Um, the quantitative is now taking that picture and saying, "Okay, um, 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, well, where are we performing at 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 and how does that, 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, well, how easy is it to move these, uh, 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, um, that is, that you can pressure test are anything to do with, like, paid acquisition and paid loops. 'Cause what you can do is, you can run what you call spike tests where you basically, um, 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 system breaks, right? Like, what starts to perform l- like, less, right? So if I'm spending $100 a day on a paid acquisition loop, for example, um, it might look like it's performing pretty well, and then I ramp it up to 200, 300, 400, 500, 1,000, 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, som- something down funnel. It, it depends, right? And so you can, like, really understand, like, where, 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 just organically take a much longer time for plotting it out on the curve, the base of the curve before the inflection point looks much, much longer. 'Cause there's just, like, less levers that you can dial, um, manually (clears throat) and manual as, 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 sensitivity, sensitivities of all these levers, and then essentially trying to understand, like, what are things that you can try to understand how hard it is, uh, to essentially move these levers? And the combination of that starts to give you the indication of, okay, 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 it actually, the constraints actually tend to be... They follow patterns depending on the type of product. Very commonly with the product we were talking about, Loom, which is, like, a horizontal product, um, 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, uh, and understand what is the ideal use case to activate them on. Like, what is the thing that is, like, most relevant to them? But if you do activate on them, right, and, and it's somewhat viral, like Loom, the fact that it can be used by so many people, it 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 single market or a single use case. 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, that you're at. And so these things end up being fairly predictable when you've seen enough, uh, enough of the game play out, uh, enough time across enough companies.

   5. HSHarry Stebbings16:26

      You mentioned sensitivity of levers there. I have a contrarian thought on growth hires and timing, that you don't know if you... 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

4. 16:52 – 28:08

   Navigating Product Market Fit and Channel Strategy

   1. HSHarry Stebbings16:52

      data to understand. Do you agree with me, or do you agree with everyone else (laughs) that growth is a post product-market fit hire?

   2. BBBrian Balfour17:01

      It's an and not an or question. So I think this gets back to what is, what is your type... or what is the type of product and what is the system? So... And, and it also gets to the question is, what do you mean by hiring a growth person? Which is its own mess of a question in itself (laughs) . Uh, and so I think I agree with you that you have to have enough volume coming into the system to really understand what these, like, what these levers are in the product and what you can, and what you can play with, right? And sometimes pre-product-market fit, you, you need to hire a dedicated person that's just focused on bringing volume into the sy- i- bringing volume into the system. Sometimes you actually don't. You know, to give you an example, like, if I was to start... I, let's, uh... If I was to start an Amplitude competitor, for example, a n- a new analytics product, right? Uh, you know, that thing is, um... I think it's not... Th- that thing's not viral at all, right? Like, you're buying that thing for tens of thousands of dollars. There's a whole, like, setup cost, like, a- all that kind of stuff. There's probably a team that's really focused on building that, building that product and building that engine- y- you know, engineering. And... But you need somebody in that case... That, that, that growth model's gonna be very marketing-driven versus product-driven, and as a result, you need a totally different skillset of person required t- like, to focus on, you know, bringing volume into the system so that you can understand...... what-- if what you're building is on the right track or not, right? I'll use a counter-example, which is like, if you're working on, like, a new consumer social product, as an example, or even, like, some- even something like Loom, where the system, the machine is actually in- in the loops are actually very product driven. Well, 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 working, well then hiring a different type of growth person, a marketing or some other thing, it doesn't- it doesn't fucking matter, right? Like, you're- 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? Two, what is the machine, uh, that in- in 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, uh, 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 bro- 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 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."

   3. HSHarry Stebbings20:07

      It's a shit question, isn't it?

   4. BBBrian Balfour20:08

      (laughing)

   5. HSHarry Stebbings20:09

      I mean, what a bad question. Ah, what awful interviewing. I- I totally agree with you.

   6. BBBrian Balfour20:14

      Yeah (laughs) .

   7. HSHarry Stebbings20:14

      It's, like, totally company dependent and it sets you up for a, like, very challenging answer. My question to you is, you said about post PMF there for Loom. You've 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?

   8. BBBrian Balfour20:35

      Well, to add nuance to that, I would say that my quote is, "Product market fit is not enough to build a venture scale business," meaning, like, 100 million plus. I- I kind of pick a number out. 100 million plus in revenue within some, um, you know, reasonable time period. Um, and so I think there's, like, a few- few pieces of this. One is that I think everybody thinks about... Eh, 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- 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, "Ah, it's strong enough with a big enough market that, um, that this is like a venture... We're on, we're on the venture viable path." But there are companies that certainly live with very strong product market fit, but with a strong- with a small market that just aren't venture viable. And there are actually, I've seen companies that have a very large market but weak, uh, product market fit. And those are also not venture viable, but in neither of those cases they are viable businesses in the grand scheme of things. They're just not... This little tiny world that we live in, around venture, it's- it's not- it's- it's 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. Uh, and so, uh, you know, I see- I see this mistake less often now, but I think the mentality before was like, "Ah, I get product market fit, and then I'm gonna, like, bolt on a bunch of distribution and just like fuel it from there," right? Like, that- that- that was- that was the common thinking, and that kind of leads to all the mistakes we were talking about earlier, which is- which is like, "Oh, well, if I think about it as a bolt-on thing, then yeah, I think about it as like I build the product and then I just... I can test the dozen things and one of them's gonna work and phenomenal," right? Like, that- that'll- that'll play off. But that is not true. We cannot mold channels to products. We have to mold the product to the channel, right? Uh, and what I mean by that is Google, Facebook, Apple, you know, who- whoever owns all these huge distribution platforms, they do not give an F about your product, right? (laughs) Right? They are the ones determining the rules of the game, right? And so your product has to play to those rules, right? It has to mold to those- it 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- i- 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, you know, like a Pinterest or, you know, HubSpot was very content driven with like their SEO, like all that kind of stuff. You basically have to mold your- you have to mold your product to, uh, essentially fit with that channel. You have to be writing the content that's gonna rank or your users have to be generating the content that's gonna rank, like all of those types of things. You have to instrument your product in order to adapt, uh, 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 e- essentially saying that, um, 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 up front for. It just doesn't work when you do the math, right? So, even if I share a product with 10 friends, uh, that is... It costs like $10,000, the conversion rate on my, you know, share... First of all, I'm not going to probably share it with that many people. It's weird to share that type of product, uh, 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. And there are channels, like different variations of sales and other things, that work with higher priced products. And so you have to match, um, 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, uh, of that human- of that human touch, so that- that piece has to work too.

   9. HSHarry Stebbings25:04

      So, can I ask you, wh- when we say about pricing channel fit there, um, and kind of aligning the two...Would an example be like a luxury brand having a core channel in, uh, first class British Airways or Delta?

   10. BBBrian Balfour25:21

       (laughs)

   11. HSHarry Stebbings25:22

       I, I, I know it sounds stupid but that was the first thing that came to mind. High price point, high luxury, c- like good.

   12. BBBrian Balfour25:28

       (laughs)

   13. HSHarry Stebbings25:28

       Is, is that what we're talking about? 'Cause 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.

   14. BBBrian Balfour25:38

       You know, I live in a software driven world versus, you know, a, um, the luxury purse world. So, uh, in so mostly-

   15. HSHarry Stebbings25:46

       (laughs)

   16. BBBrian Balfour25:46

       ... my thinking and is very specifically targeted at software companies. And I think, I think for other companies there's probably a set of different, different rules that, that rule the roost. You know, in your example, an enterprise product, should they not do YouTube and stuff, it's more about what the purpose of, of like YouTube and stuff is driving for that company. You know, yes, it might be driving, uh, like awareness and, and these o- and, 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, you know, at scale of what's driving customers, it's gonna 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.

   17. HSHarry Stebbings26:41

       Yeah.

   18. BBBrian Balfour26:42

       And so you gotta get the core machine working, and then you can add these other things that help accelerate it, as an example. I think where the, you know, the focus piece of it is, is I can try, I can do a bunch of these, 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, that core machine working. Riverside is actually probably a good example of this, that the product that we're on right now. Um, you know, 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, uh, YouTube, potentially, you know, with my branding on it? Maybe they can pay to like take the branding off of it, right? That all of a sudden starts to look like a really interesting growth system 'cause I bring in a user, they're gonna record a bunch of videos. If I make it really easy to distribit- distribute to YouTube and there's some exposure to my brand on it, that's probably gonna bring in more customers. That starts to look a lot more interesting.

   19. HSHarry Stebbings27:48

       So I, I have to ask you, two things that ca- actually come from Kipp Bodnar, uh, at HubSpot, um-

   20. BBBrian Balfour27:55

       Kipp is.

   21. HSHarry Stebbings27:55

       ... related to channel. He's been on the show before.

   22. BBBrian Balfour27:58

       Yeah.

   23. HSHarry Stebbings27:58

       That one channel working really well will get you to 50 million in ARR.

   24. BBBrian Balfour28:02

       Mm-hmm.

   25. HSHarry Stebbings28:03

       Two channels working really well will get you to 100 million in ARR. First question,

5. 28:08 – 34:43

   Predictions, Saturation, and Evolving Strategies

   1. HSHarry Stebbings28:08

      what do you advise founders in terms of channel selection? How to know which channel to choose?

   2. BBBrian Balfour28:14

      I, so I agree with Kipp, right? Which is that, um, once you figure out kind of 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 fire power, your limited attention, your limited capital, your limited talent, on fueling that thing as fast as possible. Which is very counter to the adv- like a lot of the common advice which is like, ooh, you don't wanna be too reliant on one thing. You wanna diversify, like all of that kind of stuff. Y- that is a, that is a bad investor's point of view, right? Like, yes, that might work for money management, right? It does not work for growing a business because it ignores all of the complexity that comes with diversification of products or channels or any of these types, any of these types of things. Is like if you find something that's working, you better focus that fire power. Um, 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 like caught with your pants down in trying to find that second thing that Kipp is talking about too late. Because that, that creates this stall out effect and is really hard to, to, to reignite, um, it's really hard to like get yourself going from a stall out effect.

   3. HSHarry Stebbings29:37

      If we just dive on that, do you think it's obvious when channels are starting to deteriorate in effectiveness and growth?

   4. BBBrian Balfour29:45

      This is as, 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 and, uh, o- of, of what you're, of what you're doing. And, uh, it's, it's hard on multiple dimensions. One is that I think most people, I, 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, they, along their way on content, their, their path to really establishing that content loop, they hit ceilings along the way, right? And it wasn't like, you know, they stopped at that first ceiling and been like, "Oh," threw their hands up like, "We're done." Every, like every step of the way, there was some new idea, some innovation that unlocked like another pool, right? And so going beyond, you know, kind of digging beyond that, um, is really, really hard work 'cause you're basically trying things that others aren't trying. And that's like actually just very hard for both people and a, and a company, um, to do. So I actually think predicting saturation is one of like the hardest things, um, for companies to do. HubSpot, I would say is actually-L- like, one of the biggest things I learned there is, uh, they are p- probably one of the best, if not the best, at the ga- i- in the game at this, both from a growth and, um, product strategy perspective. If you take into account, they have not missed a earnings since they went public, which was, like, eight years ago. I don't know if most people that... Th- they have never missed in earnings. 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, um, 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, uh, maintaining 50% year over year growth for five, for five years." And what that led the company do is say, "Oh, we need to, like, kick off a multi-product strategy. And actually finding the second product is probably gonna take us a year or two to do, so we better start that (laughs) 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 that was the main thing that I actually, uh, that I, th- that I worked on. And so, a lot of it comes down to kind of looking into the future, playing out like you're, li- like playing out kind of your growth today and saying, "Okay, well, if I want to maintain some sort of growth, what does that mean a year or two years from now?" And then you got to start going through the exercise of working your way backwards of like, "Okay, well, what is, what has to be true for that to occur in our system? And what starts to feel like really unrealistic, uh, around those things? What does, like, what does feel realistic?" And that, that's just a really hard exercise, I think. Uh, that's a really hard exercise to go through, especially because you don't do it that often. Um, 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 o- ton of reps at these things.

   5. HSHarry Stebbings33:43

      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 gonna actually 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?"

   6. BBBrian Balfour34:12

      No. Definitely not.

   7. HSHarry Stebbings34:13

      Which one is the right approach?

   8. BBBrian Balfour34:14

      Okay. Biggest mistakes of this are, one, not starting early enough. Um, we already talked a little bit about that. Two, underestimating the amount of time that it takes to get a new channel or new product g- uh, going. And three, overre- three, over-resourcing it, and then four, um, essentially, uh, y- this is an area where I would actually take a couple bets, but not like ten

6. 34:43 – 46:47

   Inside Stories: Lessons from HubSpot and Reforge

   1. BBBrian Balfour34:43

      bets. The way that we did this at HubSpot, um, you know, when I came in there, my mission with a couple others was help, uh, 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, uh, t- to figure out. And the way that the... I did not come up with this. This really came from Dharmesh and Hallagan, the two founders, which was, um, the way that we est- the philosophy behind it was, "Okay, we are 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, 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, uh, and then, and then Hallagan, 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, um, every, like, month or couple 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, right? And then so on and so forth. And then at some point, the bet gets big enough where it's like, "Okay, now we gotta, now we have to integrate it into the core machine." 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 would fund, they initially funded a few bets for the first couple years, and, uh, sometimes they would work, sometimes they wouldn't, and they wouldn't pass to their series A funding and, and it was kind of, you know, like that- that natural evolution. But part of that, I think, is companies, I- I think probably the biggest one that kills these things is they over-resource them. They over-resource these things, which, you know, 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 wanna find a couple people, um, like a couple generalists, kind of separate them off, protect them a little bit from the rest of the company, and, uh, essentially let them loose with the right guardrails and checkpoints, with, uh, with a couple people. But yeah, over-resource, and look, we made this mistake at Reforge 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 we re- and- and- and- and go forward with it. It's just, ugh, it's one of those painful mistakes, uh, that especially with people who have something already going, they're like, "Oh, I've got resources, so let me just put-"You know, let me, let me leverage that. And they, m- th- they, 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, to, to find things along the way.

   2. HSHarry Stebbings37:43

      What do you do if this channel's 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, uh, execution. And they've done amazingly well on TikTok and YouTube Shorts, but there's no obvious, um, correlation to customer signups or to revenue. And so it's like, yeah, a ton of people are watching your videos, but what? And it's, I didn't really know how to advise them.

   3. BBBrian Balfour38:14

      Yeah.

   4. HSHarry Stebbings38:14

      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?

   5. BBBrian Balfour38:22

      Uh, it's adapt or kill. So we went through this at HubSpot. We were... You know, the first product we built, uh, it's now called, referred to as the Sales Hub. At the, at the time, it was essentially a bottoms up tool for sales folks that let them, you know, track their emails and, and contract opens and stuff. And at the time, tha- that thing was magical. Now it's like commonplace in every, every single, e- every single product. There was like, kind of like two things that were working for us that were driving quite a bit of growth at the time. Um, we had this like incentivized referral loop, so you got to like track a certain number of emails per month and if you hit the limit, then you could invite a couple of your colleagues and essentially get a few, uh, free months. That was working for a while, as well as, uh, you know, we actually, because of the bottoms up, low friction nature, we were getting, you know, paid acquisition to work. The problem that we ran into, uh, at that point was that even though it was growing, it- th- those two things actually had pretty good connection with, um, driving growth for that product. Uh, uh, we got to... I don't remember. It was like, maybe like 100,000 weekly active users or something, and then we looked at the user base and there was a huge mismatch between the types of used- a lot of the types of users that were being, 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 e- employees. And we had high conviction on that. But when we looked at the user base of this, we were like, "Oh, shit." Like, these, these two channels, these two growth mechanisms, yeah, we're, 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. Um, and so what we did is like, okay, well, uh, we've got some of these components working, some of these aren't. What if we held the market constant, like the mid-market, uh, 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, uh, adapted some of the product, uh, that we were doing. We redid our roadmap around core ro- like, some features for like, uh, uh, the sales leader and the sales admin, like all, like all those types of things that targeted more the mid-market. But then we had to change our channel, so, uh, we killed a lot of the paid acquisition. Uh, we kept a decent amount of the viral loops, uh, but we, uh, essentially added in more of a content motion, and then we changed our pricing. That was probably like the biggest thing. So once we changed the channel, um... Sorry. We, we, we layered in content and a little bit of inside sales, and then we, uh, had to change the pricing to match with that. Um, so we raised prices in a couple 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, which was the mid-market. So I think in your case, there's like, there's this whole a- exercise of like, oh, there's this really cool thing and like, do we have bets that like can adapt it, can mold it to what we're trying to sell and what, what our product is? Let's take a couple bets at that. But otherwise, honestly, with limited time, limited resources, like, you got to kill it, right? Uh, 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, and you need, you need, you need to eat the cake first (laughs) . So...

   6. HSHarry Stebbings42:19

      Speaking of though, like knowing what works and seeing the success in a channel, obviously, 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.

   7. BBBrian Balfour42:34

      Yeah.

   8. HSHarry Stebbings42:35

      I agree with you, but I'd love to hear, what do you think are the biggest ways that you see founders and growth teams really misunderstand or get metrics wrong?

   9. BBBrian Balfour42:44

      Yeah. The con-... Well, the first and foremost is metrics before strategy. I'm not, I won't go too deep on that 'cause I feel like that's like a common thing, um, that, that's the biggest thing wrong, which is your metrics are there to help answer the question, is your strategy working (laughs) , right? Um, and so they are not there to determine your strategy. You have to have a reasonable hypothesis of what your strategy is first, like what is, what is your core growth loop, like all of these things, and then you can say, "Well, what are the metrics that would, 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, um-To understand what your metrics should be, you have to understand the qualitative underpinnings. And a great example of this is, especially around retention. Um, like setting retention metrics, for example, actually it's, I would say 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, right? Um, s- and then, 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 and understanding of, like, your user of the problem of the natural frequency. Whereas I think most companies are like, uh, like, well, we're just gonna track it on like a weekly active, or a monthly active, or like a quarterly buyer case. Like, all that kinda stuff. And I'm like, well, okay. Well, like, what is, what is the problem? D- Does your user actually incur that problem that often in their lives, right? And, and like that, that ends up being like 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, right? So, you have to understand the usage of your product first. Like, those are the things you should be focusing on. Um, not necessarily the revenue metrics. This is a classic e- like, sub-example of outputs before inputs, uh, a- as, uh, as part of that. Finally is like, uh, a lot of people mix, especially once again in the SaaS space, uh, customers b- customers versus users, right? Uh, so there are, um, dynamics, uh, in some SaaS products that are very different. Like HubSpot, we had a customer, but we had multiple users, um, on that, like, 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? And 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. Just by focusing at the cus- 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, you're, you're two levels high. You're,

7. 46:47 – 51:17

   The Impact of AI on Growth

   1. BBBrian Balfour46:47

      you're, you're too high in altitude.

   2. HSHarry Stebbings46:48

      Speaking of actually growing the business. Over the last few, I don't know whatever we say, 6 to 12 months, AI has been the hottest thing in our ecosystem. And I'm just fascinated for you at the center of the world of growth running, you know, Reforge. Like, how do you think AI changes the way the growth teams operate and the world of growth?

   3. BBBrian Balfour47:12

      Uh, this is an interesting one because I think it changes both like a lot and not a lot at the same time. Um, and w- (laughs) and so what I mean by that is, uh, I think the surface level tactics and systems will definitely change a lot. Um, so I would say like, a lot of these analyses that, you know, seven years ago, eight 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 gonna get automated, right? Uh, like super, super simple.

   4. HSHarry Stebbings47:54

      Sorry, can I just interrupt you? How, how is finding your aha moment automated? Like, is it not highly nuanced and contextual dependent on the millions of infinite options of what a product could be?

   5. BBBrian Balfour48:05

      Right. I guess what I'm saying here is like before, um, you know, your top tier growth person, uh, seven or eight years ago would know, um, how to do that analysis essentially like by hand, right? Because the tooling and technology wasn't necessarily there to, to, to do it any other way, right? Um, 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 all of these things get essentially th- the friction to do them doesn't require the same skill set that it required you eight years ago. But this kinda gets to the dichotomy that I was talking about. The things that don't change, right, that I don't think AI is gonna really help you with that much is understanding like all of these qualitative underpinnings, uh, of your product, of your use case, of your problem, of your natural frequency, and then the psychological levers that you can tap into, um, to move a user's behavior. I think AI's gonna have a really hard time at like understanding that and doing that thinking. But in addition to that, I think I, I kinda put out this, uh, like a little bit of a lighthearted but serious tweet at some point, which was like-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, and other components of how we do those things actually, like, will change. And who knows? Maybe we get a fundamentally new distribution channel out of this wave of AI technology. If so, uh, like, that is like a fricking field day, should be a field day for growth people. Because when you have, uh, what a lot of people are focused on right now is like, oh, AI is going to take away traffic from Google. It's gonna reduce my marketing surface areas 'cause people are just gonna be interacting with a chatbot versus, you know, a website and landing pages and all that kind of stuff. Yes, that's true, but at the same time of, right, uh, it's gonna 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, those sparks are what give, uh, new companies and new things life and hope.

   6. HSHarry Stebbings51:07

      Well, it takes us back to what we said at the beginning really, which is, you know, the early days of Facebook and the Facebook gaming days, which is, you know-

   7. BBBrian Balfour51:14

      Totally.

   8. HSHarry Stebbings51:14

      ... Facebook was such an arbitrage. Yeah, 100%.

8. 51:17 – 57:13

   Reflections and Mistakes

   1. HSHarry Stebbings51:17

   2. BBBrian Balfour51:17

      Totally.

   3. HSHarry Stebbings51:17

      I, I agree with you, um, and I hope it does and I agree with you in terms of chaos injecting opportunity and innovation. Bri- you've had an amazing career. 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, Bryan? And how did it change your mindset?

   4. BBBrian Balfour51:38

      Uh, so, so my fundamental view is like, the only way to figure things out is to, like, create. Um, you can do some thinking upfront, right? But then you've got to get into, like, the making, um, 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." Like, we just need to get into the, we just need to get into the making of things (laughs) , right? I, I think, like, as a result is, like, I think a lot of people look back at your question that you asked and they're like, "Well, what is something that I thought long and hard about but I was wrong?" You know? Um, and as a result it, like, had a huge, had a huge cost. I just try to view things as like, it's just always a natural evol- like, being wrong is like a natural evolution to, um, you know, its next step. But I will answer your question directly to satisfy, to satisfy you. My biggest mistake at HubSpot was a little bit of what we touched on before, which is that 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 mark, market of the core business. I was pushing for, like, that virality and I kept going down that path and I created a lot of resistance. What I didn't see at the time was, you, you know, in the battle of things was that, um, 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 that probably left that product in a state that, uh, um, a, a disconnect with the core business for a little too long. Luckily, I actually got vetoed, um, over this and we, we maneuvered, we maneuvered the product and the business to a different direct, direction. At the time I disagreed with it, but now in hindsight I'm like, "I was the dumb one. (laughs) I was stupid." Uh, and so, like, that was a really, like, ba- that was, I think, like, a really bad decision. And 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. And that had huge growth initially, uh, like just massive growth and that, um, kind of put the blinders on us to whether or not, um, we were also doing the things to make a subscription product, um, sustainable. And as a result, we ended up being too late to, um, 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, um, that, that we, uh, that a little bit that we, uh, talked about. That, that was like a case where I think the metrics ended up misleading us and we actually weren't looking at everything that was happening underneath, uh, 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 and just, like, how difficult that is. I've also done some stupid growth hacks-

   5. HSHarry Stebbings55:07

      Yeah. I mean it-

   6. BBBrian Balfour55:07

      ... which we can talk about (laughs) , but, like, that's a, I think, different

   7. NANarrator55:10

      ... (laughs)

   8. HSHarry Stebbings55:10

      Oh, go... Oh, come on. Oh, come on. We, we got... Before we do a quick fire, tell me about a stupid growth hack. I love that.

   9. BBBrian Balfour55:14

      Well, early in the Facebook game (laughs) , early in the Facebook platform days, uh, 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? Um, and so, uh, at the time through Facebook's platform and API is that you could basically, when a user signed onto your app, there was essentially the ability to, like-... uh, auto message that person's friends, like up to 20 folks, uh, from that person. So what we did (laughs) -

   10. HSHarry Stebbings55:50

       (laughs)

   11. BBBrian Balfour55:50

       ... what we did is when a new user installed the app, we would just pick, uh, I think it was like 10 or 20 friends at random out of their friends list and send them a virtual, a virtual gift from them. And this thing, like started, this was still the, before AWS, this thing started melting our servers, like within like four hours. Like, it was just growing like, uh, uh, and so we had to shut it off. The problem with this, the problem with this, besides it being incredibly spammy, was that afterwards we find out that y- y- we didn't think about this as like, when you're choosing somebody at random like that, in some cases where you were choosing like ex-wives and ex-girlfriends and they were receiving like a virtual gift of like a rose from somebody, it created this confusion. Oh, yeah. A- and like after that I was like, "Okay, that was one of the dumbest things I've ever done." It grew. It worked. Uh, 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, look, you know, one of the, one of the fun, one of the fun ones for, for a little bit.

   12. HSHarry Stebbings56:59

       You, you, you sent, you, you, you sent your, you know, same sex boss a, a that big love heart. You're like, "Oh, oh."

   13. BBBrian Balfour57:04

       (laughs) Yeah. Oh, yeah. Oh, yeah.

   14. HSHarry Stebbings57:06

       "Is there something I can do to make up for an awkward one-on-one?" (laughs)

   15. BBBrian Balfour57:08

       Oh, oh, yeah. Oh, yeah, yeah. Th- n- not good. So, uh, we'll not, we'll not do that again.

   16. HSHarry Stebbings57:12

       Man, that is

9. 57:13 – 1:10:10

   Quick-Fire Round

   1. HSHarry Stebbings57:13

      amazing.

   2. BBBrian Balfour57:13

      (sniffs)

   3. HSHarry Stebbings57:13

      Listen, Bryan, I would love to move into a quick fire round. So I say a short statement, and then you give me your immediate thoughts. Does that sound okay?

   4. BBBrian Balfour57:19

      Let's do it.

   5. HSHarry Stebbings57:20

      Okay. So what tactic has not changed over the last five years? If you think there's one that continues super strong.

   6. BBBrian Balfour57:28

      Oh, if you get, if you, word of mouth. If you can get, uh, or, or any form of virality, if you can get one user to tell another user, like that will, has been around forever, will be around forever. N- no doubt.

   7. HSHarry Stebbings57:39

      What, what tactic has died a death? I feel SMS, SMS people feel intrusion nowadays.

   8. BBBrian Balfour57:46

      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, um, for folks. I've looked at companies that are like complete their entire growth strategy is on WhatsApp. So like that, that type of direct messaging I think still, still works in, in, in like some parts of, um, 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, um, in the distribution channel. So like, you know, there, there are things that used to work on Facebook ads or within Google or like some viral loops, right, for example, that used to work. Look, just taking something as, uh, taking something as simple as, uh, like importing somebody's address book, as an example. That 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 is like you can't really do that unless you've like built up trust with your users and have a really good reason. So, um, I, I think it's like all those types of things that, um, essentially have fundamentally died. It's either due to a change in the distribution channel, due or due to like some form of user, user fatigue.

   9. HSHarry Stebbings59:04

      I, I totally agree with you there. Tell me, what, who do you think is the single best growth practitioner that you've worked with? I know that's so hard to say given Reforge.

   10. BBBrian Balfour59:15

       Oh, geez.

   11. HSHarry Stebbings59:16

       But who would you say? Come on.

   12. BBBrian Balfour59:20

       (blows raspberry) Okay. I, I'll name a few on a different dimensions. Um, strategically would be Casey Winners. The best person that has, thinks about the psychological elements of growth, uh, would easily be Darius Contractor. The person like a- a very specialty who I, I consider like a mad scientist is, uh, um, I call him G but it's Guillaume Cabane. Uh, uh, he was at Segment Drift, uh, like, um, like a bunch of others. But I, I, those three on different dimensions is kind of, is, is how, is who I would probably name.

   13. HSHarry Stebbings59:59

       What do you think is the biggest misconception that people have with growth?

   14. BBBrian Balfour1:00:03

       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, uh, metrics and other things, um, to, to those systems. And so I think for a lot of cases, people just, you know, they talk about growth as it's like a single thing. Um, and, and that's like trying to say engineering is a single thing, but there's so many different types of engineering, right, that if you were trying to describe the discipline and practice of engineering altogether, you just like, you, you lose all of the substance.

   15. HSHarry Stebbings1:00:43

       Will AI change the tooling incumbents of growth teams? Or will they enhance the existing incumbents?

   16. BBBrian Balfour1:00:51

       Uh, both.

   17. HSHarry Stebbings1:00:52

       (inhales) Hmm. Who's most strong and who's most vulnerable from the incumbent side?

   18. BBBrian Balfour1:01:01

       (laughs) Oh. Uh, w- well, I mean, it's hard to s- not say Twitter right now from a vulnerability perspective. Uh (laughs) , so, um, I think this is a little topic du jour, but I, I think you gotta go Facebook for a few reasons. One is that they still have the OG growth talent that, that they did from 15 years ago. Uh, Javier, Alex Schultz, right? Like, those people are still there, right? Like, um, and so you got that.... um, you've, you've got the capital advantage. You've got the advantage that you can leverage billions of users on your o- other platforms. They still have, like, the most data. Uh, so I think you put all of those things together, I would probably put them in the strongest point. I think they're, I think they're probably, like, the least vulnerable, as long as they focus, uh, like, the company priorities are pointed in the right direction.

   19. HSHarry Stebbings1:02:00

       D- I agree. Why do you think Twitter's vulnerable though? I actually don't. I think an election's coming up. I think, you know, we are early adopters. The tech ecosystem's early adopters. M- majority of people don't actually, like, know about Threads, if we're honest. I mean, we're in Europe, it's not gonna be here until early next year. I think Twitter's strong. Elon's brand is bigger and bigger. I wouldn't bet against Twitter. I'll bet against, like, Salesforce.

   20. BBBrian Balfour1:02:25

       Yeah, so okay, I played a fun game with a couple folks. Uh, if you were to have to predict Threads' DAUs and Twitter's DAUs one year from now, Threads is at about 100 million sign-ups, so ... and then, and then Twitter's is, I think, at like 250 million, something like that. If you had to predict, wh- what numbers would you choose?

   21. HSHarry Stebbings1:02:44

       Oh, this is so on fact.

   22. BBBrian Balfour1:02:46

       (laughs)

   23. HSHarry Stebbings1:02:46

       I just interviewed Adam Mosseri, who's running Threads earlier today.

   24. BBBrian Balfour1:02:49

       Oh, you did? (laughs) Oh, yeah, that is-

   25. HSHarry Stebbings1:02:51

       Um, and I, I-

   26. BBBrian Balfour1:02:51

       ... that is unfair, yeah.

   27. HSHarry Stebbings1:02:54

       And dude, I really like him. He's a fucking great guy.

   28. BBBrian Balfour1:02:57

       (laughs)

   29. HSHarry Stebbings1:02:57

       Honestly, I don't think Threads is gonna work. Um, I think it will, uh, honestly fail pretty quickly. I don't think they'll get retention, and I think the majority of people on Twitter are actually, you know, 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's the interest graph, and they don't overlap. On Instagram, I like Audi, I like Chanel, I like visually aesthetic, inspiring, and I then I have my brain, which is Balaji, is Marc Andreessen on Twitter. I don't want a correlation of them both in Threads. This is not how, I don't, I think th- the next wave of social works. So for me, super simple, to cut to your point, I would say Threads does not work. Eh, maybe it te- teases along at five million DAU, with hardcore small numbers, uh, and I would say Twitter has modest growth to 275, 300 with election spikes.

   30. BBBrian Balfour1:04:04

       Hmm. Interesting. Yeah, I chose ... they're flat. T- I, I think Twitter's flat, 250 million. I actually agree. I'd lean in your direction, which is that I think people are, are, uh, overestimating, you know, the vulnerability of Twitter, but wh- when you ask that question, it's like, I, I just don't think Twitter's gonna grow, and that's why I think it's-

Episode duration: 1:10:10