The Art of SaaS Investing (with Jake Saper, Partner at Emergence Capital) 01:24:39

Is duct tape in? Oh, no, no, no, no, no. Oh, no. Stop it. Stop it. Sorry. I accidentally opened one of our old episodes and it started playing really loudly. Are we live?

I mean, we can be if you want to be. No. Open Periscope if you want to be live. That's not what this is. So do you guys want to know a super secret Zoom hack? Absolutely. We are recording everything you say. Great. Perfect. Can we release this? Can our listeners know?

Yeah, absolutely. There is a feature that is basically a beautification plugin. Yes, I've seen this. And it basically blurs your face to a very unnoticeable extent, but enough to get rid of any blemishes or wrinkles. So it's basically like digital Botox. I mean, I've been doing it for years. And I think when entrepreneurs meet me first on Zoom and they meet me in person...

There's a level of disappointment. Touch up my appearance. Here it is. Where is it? Managed participants? Yeah. So, Ben, how do we look? Touched up. Touched up. We... Well, this is great radio. I can tell you that much. So compelling. We were talking to an entrepreneur who...

Let's start a men's makeup company. So this is synergy here. Well, software may be eating his world. Indeed. Well, listeners, we are super, super lucky to have the one, the only Jake Saper with us on the show today. As you can tell, we decided just to launch right into it. But I'm recording from Seattle. I'm looking at David and Jake's smiling faces from the Wave Capital podcast room. It's good to see you guys. Nice to be here.

Great to have Jake here.

So, Jake, in addition to being my classmate from a long time ago, back in business school, and we had many great experiences together there, which we won't go into on the show, Jake is a partner at Emergence Capital, which, in my opinion, is the best early-stage SaaS investor in Silicon Valley. And we are super honored to have him on the show to talk about something that...

Ben and I have done and occasionally do in our current VC lives, but are by no means experts on, which is SaaS investing. So, Jake, when you joined Emergence? 2014. 2014, right? Almost five years. Yeah, almost five years. Wow. And you worked at Klein Perkins before that, our summer in business school. Before that, you did consulting and worked in energy, right? All true.

All true, all true. And Emergence, you don't have to just take my word for it that they're really great. They were early investors in companies like Salesforce, Viva Systems, SuccessFactors, Box, Zoom, Gusto, and Yammer. They've had quite a number of successes and many more to come. Most importantly, though, Jake...

played a lead role in the Silicon Valley sensation Soma the musical so if we have time we might get into that too sorry I had the most important thing I had to let's let's start with

My first question for you, which I sort of know the answer to, but our audience doesn't. How did you guys at Emergence decide to only focus on SaaS? It was not obvious when the firm started. And even on top of that, too, let's start from square zero. What is SaaS and what is not SaaS? Sure. Well, that's actually, interestingly, a harder question these days to answer. So...

Very technically speaking, SaaS obviously stands for software as a service. And it's the idea that you're delivering software on a continuous basis versus on more of an upfront license purchased basis. This has been conflated with cloud in the sense that you can deploy. SaaS is most commonly deployed in the cloud. The reality is SaaS is a business model and cloud is a deployment methodology. And

And so those two things are often conflated, but the reality is you can have a SaaS business model for an on prem product and you can have a cloud. You can have cloud. I think you could have something in the cloud that wasn't. I mean, obviously, you can a lot of things in the cloud that aren't SaaS.

Actually are. Yeah. At Microsoft, when we were doing Office for iPad, Mac, Windows, we were selling software as a service as desktop bits. Yeah. At first, when the world was transitioning to that, it always felt a little funny to me that it's, you know, we were watching the rise of these web applications that charge monthly, which made sense because the bits were shipped down every time you refresh the page. But

you know, it was kind of like, wait a minute, the software on my computer can be turned off. Okay. And then the world had to like jump over that a little bit. Right. Yeah. Yeah. And I think over time, people have come to embrace SaaS as a business model. It's really beneficial for

uh, for companies because they get a recurring revenue stream. So it's quite predictable investors like that. Um, and in fact, um, as an avid listener of the acquired podcast myself, uh, I'm familiar, uh, with the trends that the podcast industry has made more towards, uh, SAS of late, including this, uh, this very podcast, very podcast. Indeed. It's funny. So I remember, um,

When I first started at Madrona, which was 2010, which was probably right after Emergence got started... So Emergence actually got started in 2003. Oh, 2003. Oh, wow. I can tell the founding story. Wow, wow, wow. Okay, wow. That's... It takes a long time to build, you know, many things, including venture firms. But even in 2010, I remember, like, people were...

didn't understand the business model of SAS. People were very skeptical, especially public market investors and even VCs. And over the last 10 years, we've evolved to a point now where it's pretty widely accepted that SAS is the superior business model in the enterprise. And you're also seeing what's interesting is

SaaS started in the enterprise, but you're starting to see the adoption into consumer, right? So obviously Spotify is a SaaS model. Apple Music is a SaaS model. So it's kind of gratifying. It's not podcasting. It's gratifying as an enterprise investor where often things start with consumer products

And people, everyone knows that a consumer and then maybe it migrates into, you know, enterprise, the consumerization of enterprise to see something start with the enterprise and then move to consumer. So. So. OK, so. So tell us the origin story. This was not obvious in 2003. No. And the caveat I'll make before I tell the story is that I was not there. So I had I had very little to do with the early success of the firm. It was our founding partners, Gordon, Jason and Brian, who started the thing back in 2003.

Brian and Jason had been career venture capitalists and believed that there was an opportunity to build a focused venture fund.

Most venture funds at the time were generalist funds. And people had a lot of success with the generalist model. But as the industry matured and became a bit more commoditized, the thesis was, if you could actually build a firm that was focused on one thing, you'd have a competitive advantage. And you'd have a competitive advantage for two important reasons. The first is that you'd obviously have an ability to build content expertise and depth in something that other people may not have as much depth in.

But the second, and this is still a really core important part of the way we operate today, is if everyone in the firm is focused on one type of investing, you're uniquely able to collaborate. So venture is, generally speaking, a franchise model. Everyone does venture differently, but a lot of venture investors act in a very franchise-esque way in the sense that you join a firm, you get to use their brand and perhaps some other teammates, and you get a certain amount of capital to allocate, and then you go doing your investments, and then you see how you perform.

And that's not... And people have made a lot of money doing it that way. The reason why I believe the model has evolved in that way is because someone becomes the consumer expert or the healthcare expert or the SaaS expert or what have you. And so it doesn't make as much sense to collaborate. But if everyone's working on one thing, you can. Having said in many Monday meetings, Madrona has this model and it's a great model. But there are partners at Madrona who...

almost exclusively focused on the enterprise. They're partners who almost exclusively focus on consumer and a company of one type comes in the other. And, you know, at best, you're just going to defer to the people who know what they're talking about. At worst, you're going to say something that's like totally off the wall. Totally. So we actually, our whole model is very different than other firms in the sense that we do diligence together on every single deal.

So we bring entrepreneurs in early in the process. So instead of, you know, in most venture situations, if I meet an entrepreneur, I like them, I then do diligence on her for the next two weeks, and then I bring her in to pitch to the partnership on a Monday, and then we vote. Maybe you bring an associate or two in to help you, but it's not nobody else in the firm. None of the other partners are riding along with you. And at the end of it,

I am basically defending the investment to my team who has very few data points on the investment because they haven't been involved in diligence and they may not be experts on the topic. They may or may not have even read the investment memo that you sent them. Perhaps they haven't. In our case, we bring entrepreneurs in pretty early in the process. We have them do a full pitch to the partnership and then we all jointly decide, do we want to dive in and do diligence as a full team?

And if we do that, it's a bear hug. Everyone's involved. Everyone makes customer reference calls. Everyone makes management reference calls. Everyone goes and does a site visit and actually spends time with the company in person. And what's really cool about that model is when we go to make a decision, everyone's actually bringing primary data to the conversation, which is to say like, hey, I had this conversation and I learned this and then we can make a decision jointly.

And again, the reason we're able to do that is because we've chosen to focus on one general topic. So that's a bit of a... How many people is that that then get involved and do such a bear hug? Yeah. So our investment committee right now, there are six partners, six investing partners. And then we have 14 people on the investment committee more broadly. And that is...

principals, senior associates, associates. And then we also have a set of basically what we call our value-add team, which are really seasoned SaaS executives. So the guy who was the VP of sales enablement at Box and before that worked at Salesforce works for us now and works really closely with our portfolio companies on sales ops.

The woman who was the Cmo of Zenefits and the Vp of marketing at Yammer also is a partner with us and basically spends a lot of her time consulting with our portfolio comes on marketing stuff, and so they're also part of the investment decision and kind of help us inform our decision making process. Awesome. I want to get back to the origin story more into that later. Yeah, okay, back to the origin. Sorry. Yes, that was a long time. So

The two founders that had been longtime VCs realized, hey, we should try this focus thing and see if that works. And then the third guy, Gordon Ritter, had been an entrepreneur a number of times. His most recent company that he had founded was called Software as a Service. That was actually the name of the company. That was the name of the company. And he co-founded it. Did he transfer the trademark to Emergence? Unfortunately, he didn't. We own no trademarks. Although we have one that we're actually working on now, which I can talk about in a second. But he started that company with a gentleman named Mark Benioff. Ah, okay.

So listeners might have heard of Mr. Benioff and his tower. Yeah. So Mark Benioff is the founder and current co-CEO of Salesforce. And basically what happened with that company, SAS, that they had founded Software as a Service, it basically got rolled into Salesforce and was the initial platform that became known as the force.com platform.

And so the three of these folks took a step back and said, hey, I think this whole cloud thing is going to be more than just one company. I think it might be a whole movement from on-prem to the cloud. So why don't we start our focus venture firm with that thesis? And so that was around...

distribution, not around business model to start. Correct. So the idea at the time was this concept of multi-tenancy. And that concept was a super powerful concept. So instead of single tenancy, which is basically the way single tenancy on-prem, which was the way that most things work, this was install software on a computer and then the next computer.

Exactly. So the very famous initial logo for Salesforce was that no software. The no software. Brilliant. It was such an amazing stake to put in the ground. I think, David, you and I were having this conversation around you don't ever achieve sort of fervent fans without taking a stake on something and taking a stance and going out on a limb. And Salesforce...

raising their hand and saying no software in the era of, you know, software is eating the world or a little bit before that. But I think like everyone was woken up to this idea that like software is the interesting, you know, movement right now. And they're saying opposite. Yeah. This is making me realize too, you know, we have a whole list of content calendar of, you know, acquired episodes. We're going to do Salesforce is not on the list. Oh man. Oh man. We got to put it on there. We need to tell this whole story. Yes. Okay. So back to, so, so,

The thesis, there's a distribution, a technical thesis, but people haven't realized the power of the business model yet. Yeah, I think that's right.

people start to realize the power of the business model once Salesforce goes public. Yep. And starts to see the power of recurring revenue and the ability to forecast really clearly and all those things. And I think that started to create a bit of an ecosystem. And so what happened from there, one of the benefits of being early investors in Salesforce is that we got to see that ecosystem evolve really closely. Yeah.

And so a number of our early investments were actually built around the Salesforce ecosystem. So built on top of that force.com platform that was originally a software service. Viva is one of those. So Viva is started basically as a focused version of Salesforce. So it was Salesforce just for the pharmaceutical industry. So the pharma industry has specific regulatory requirements where you have to make sure your sales reps are abiding by certain policies and what have you.

And instead of trying to customize a horizontal piece of software like Salesforce, the idea was, can you build something really focused on the pharmaceutical sales rep sector? And on top of force.com. And leverage the force.com so you don't have to build your own infrastructure. And that turned out to be one of the

best businesses, I believe in history. So we just for context, we I'm mostly very biased, but the numbers actually support it. So we invested six million dollars in the company back, I believe it was 2008 or 2009. And that was actually the only capital the company ever raised. The company went public in 2013 at a three and a half billion dollar valuation. And the company is currently trading at a 17 billion dollar valuation. Incredible on six million dollars of capital.

And so there's benefits. And I know one of the things we were going to talk about, I'm happy to talk about an hour later, was the benefit of thinking about horizontal SaaS companies versus vertical SaaS companies. This is obviously, we believe Viva is kind of the definitive example of a vertical SaaS company. And there are definitely trade-offs when you're going that route. But

But we view vertical SaaS. So if the original kind of if SaaS 1.0 was horizontal SaaS and Salesforce obviously is the definitive company there, although companies like the one we're using right now, Zoom, I would also consider to be a horizontal SaaS product. So that's definitely not a dead sector. There's a lot of interesting stuff happening there. Slack, what have you. Yeah, exactly. SaaS 2.0 is vertical SaaS in our minds and Viva typifies that.

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The next thing I wanted to talk to you about that I think you guys are, are, you know, also, and I'm not just saying this cause you're here in the room. I really believe like you are one of the best venture firms, I think because of this, uh, focus and history about being thesis driven. So you guys have a few, a handful of theses about how you view what SAS and the enterprise is going to play out over the next, you know, X number of years. How do you think of it? How did, how did that culture evolve within emergence? Um,

And what are your current theses and how did they kind of evolve and get developed within the firm? Yeah. So, I mean, it started with the founding, right? So the idea that we had a thesis to start and that allowed us to have some early success, kind of it reinforces things. And it's like, oh, well, this is working, so let's keep doing it. Yeah.

So the culture was kind of started from the beginning. From a process perspective, we have what we call a priority theme process. And the idea is at any given point, the firm can have no more than three priority themes as a whole firm. And so and priority themes are themes where we dedicate full form firm resources to pursuing them, to writing about them, to learning about them and researching, to obviously investing behind them. But but

But behind that, we also have these kind of bubbling up themes, right? Where each of us has a hunch about something. We don't have enough data to say we want to kind of put the full force of the firm behind it. But we all have some hunches and we're kind of constantly experimenting. And what happens is we have quarterly off-sites and everyone kind of presents

periodically on whatever kind of theme is bubbling up in their mind. And they start experimenting. They may make an investment in it and see how that goes, learn more. And then over time, if they have enough confidence and they can kind of get the machine behind them, we may try to elevate it to a priority theme. Now, what happens then is you got to de-elevate one of them. Wow. We intentionally try to put constraints to keep us focused. Mm-hmm.

Are you willing to share what they are right now? Sure. Yeah, yeah. No, for sure. Happy to. So our current three priority themes. So the first is we still are huge believers in this concept of vertical SaaS or what we call industry cloud. Mm-hmm.

And we think there's still a lot a lot of room to run there There's a lot of industries that haven't seen the benefit of that yet one I know you when you first joined you spent a lot of time on that is how to really construction tech Yeah construction tech certainly very popular and one of the first investments that I was involved with was a company called drone deploy Which is drone software focused on farmers and construction workers primarily it allows them to fly drones autonomously map their fields or their sites and then make decisions and

And yeah, so that was that was, you know, there and there's obviously been a bunch of exits in construction recently. And that that's actually, you know, proven to be a pretty attractive sector. And there's a bunch of other ones. So that's kind of, you know, current, you know, the one priority theme. The second priority theme that we're pursuing right now is something we call the deskless workforce. And this makes a lot of intuitive sense. But the concept is the 80% of the world's workforce doesn't actually sit at a desk.

And 95% of the world's software has been built for people who sit at desks. So there's a mismatch. It doesn't take a genius to find that out. So the argument would be that once people start to build software that's actually being actively used by that 80%,

The size of the addressable software market that could be created could actually dwarf what we currently have, which is really humbling to think about. There's lots of questions around how that could happen, where it will happen, all those types of things. But we're pretty actively involved in making investments in that. And we just had our first and what we believe to be the first billion dollar outcome in

Deskless Worker, Deskless Workforce theme. We had invested in a company called ServiceMax that was also built on theforce.com. It was acquired by GE now a year and a half ago for about a billion dollars. And that was a kind of what we call the field service software company. But we're super actively excited about this Deskless Workforce idea. And that will also encompass a bunch of new modalities that will encompass

you know, augmented glasses. It'll, you know, Microsoft had the big HoloLens 2 launch. Note that it was enterprise focused. Exactly. And I actually think perfectly in this theme. You must be a business to buy one. It's kind of funny. They have no consumer channel. There's no ability other than through procurement to actually go get one of the HoloLens 2. And in fact, it reminds me a lot of Apple sort of doubling down with the

later edition of the Apple Watches on fitness as sort of the primary use case rather than it does all these things and it's a platform that you can figure out whatever it is. They're like, no, no, no. We know what it is now. It's enterprise. It's training. We're not even putting up a website for it that you can buy it. This is back to the focus concept. In fact, we have three core values as a firm. You'll notice things are in threes. Part of that is because

I was a consultant. I really like three bullet points. Refounding partners. Everything's in threes. Everything's in threes. But our first core value as a firm is that we all focus to drive conviction.

This concept is, you know, we all jointly focus to drive conviction in founders, in themes, in markets, etc. And, you know, I like the idea of, you know, basically what you described, Ben, with HoloLens is they decided we're not going to try to be everything to everyone. We're going to try to focus. We know what we're going to do and we're going to do it really well. And that's part of the ethos of our firm as well.

Cool. Okay, so that's second core theme number two. Core theme number three is a theme that we have completely made up. So the title will be one that is probably new to many of you, but I'm really excited to talk about it. And the theme is something we call coaching networks. And the idea is that...

In much of the software that has been built using machine learning today in the enterprise has been focused on automating away low-level tasks. And there's value in that. I mean, there's a lot of what we call static tasks that are repetitive, often human-machine, that will likely be automated away. This is like UiPath. UiPath automation anywhere. And there's a lot of companies that are doing really well doing that. Yep.

And we think that's a great market. But what we think is actually an even better market and a longer term, more defensible software play is using that same machine learning technology to augment workers or coach them as they perform their tasks in real time. So the idea would be, as you and I are having this conversation, as the three of us are having this conversation, you can imagine a coaching network that could pop up and say, hey, Jake, you've been talking too long. Let Ben interject here. Ben's got something great to say.

Would learn whether or not I did or didn't do it. See, I already talked over him, which is why there's obviously no coaching network involved here. You know, learn whether or not I did it or not. And then importantly, would correlate my behaviors to some sort of business outcome. So did the product get sold? Did the, you know, did the...

want to work for us, whatever that thing is, and then be able to make those correlations happen across everyone in the network that's actually performing that task and then be able to make recommendations based upon everyone's behavior. And the beauty of this idea is

is not only that it's a much more positive way to view the world and kind of automating everything away. And we also think there's a lot of retraining possibilities here because you actually can start doing a task without a lot of training because this actually acts as a bit of a digital apprentice. But from a business model perspective, what makes me so excited about this is that finally, the enterprise has the ability to capture network effects. If you think about the consumer giants, Google, Facebook, etc.,

you know salesforce has performed really well but it's still not anywhere close to the size of the consumer yeah it's not a network it's a platform for sure right and it's got you know all the lock-in that comes from all the best applications are are you know they call it the operating system of of the business where all the best applications are sort of available through uh salesforce in the same way they used to be available through windows uh

So there's sort of lock-in, but you're right. It's not a network effect in the same way that every single business that comes on would be directly better for every other business who is an existing customer, the same way that a Facebook would be.

Exactly. And so our belief is that coaching networks, perhaps for the first time, will create an opportunity to actually have true network effects in the enterprise. So, you know, Ben's familiar with this company, but one of our companies that's in Seattle that is squarely in the coaching networks space is called Textio. Yeah, I was going to bring it up. Yeah. And Textio does something called augmented writing. And basically the concept is anytime you write something in business, you generally have a purpose. You're trying to achieve something. Mm-hmm.

And the words you're using are generally going to be correlated with whether or not you achieve your purpose. It's a really intuitive concept. So the idea is, can you get enough data on what was written and what the outcomes were to be able to make recommendations to people as they're writing on how to write to be more likely to achieve whatever goal that is? And in the spirit of focus, their first focus was on job posts. Yep. Turns out the job posts you write are highly predictive of who will apply to your job. Yep.

And so what they did was they created and there's a story around how they created this proprietary data set, which is super cool. But they started and got a bunch of data on kind of how job posts have performed. And they're now at a place where they have, you know, I think it's tens of thousands of daily users.

And the idea is every time a new person is contributing a job post to the system that's coached by Textio, Textio is learning how that performs. And that learning actually benefits not just everyone in that company, but literally everyone that is a Textio user across all of their companies. And so we've created this really powerful network effect. It's interesting. So there's two things this brings up for me. One is, did you guys ever look at a company, this is old school, called Compendium? Yes. I didn't look at it as an investor, but I'm familiar with it.

So Compendium had this idea. It was founded by one of the exact target co-founders. It was this idea that as you are writing a blog post, it could sort of know what your business outcomes are, understand the SEO necessary to achieve those business outcomes and tell you if what you were writing was actually helping you to achieve stuff. And it could tell you, you need to throw in more of these words. You need to do, you know, this paragraph is irrelevant for what you're trying to do. But super, super early in, um,

in this world, machine learning wasn't a, uh, you know, wasn't widely available yet. And I don't think, uh, the technology was there yet, but it's almost like the, to answer the question, why now for this thesis of coaching networks is the technology has sort of caught up with the, um, sort of future looking notion of what if,

You know, what if any little bit of work that somebody did could be well understood by the broader community and then leveraged in their work as well? That's exactly right. So the two reasons for why now on this, the first is the technology exists now. Processing power, you know, is cheap enough. Storage power is cheap enough. You know, things are now in the cloud. So there's kind of a tech gap.

There's a tech reason as to why now. But the second reason is that there are now enough sensors to be able to make this work. Because you need sensors on two ends. You need the sensors for the human behavior. And then you need the sensor on what was the business outcome. Right? So one of the actual really important sensors that's being deployed today to make this possible is the product we're using right now with Zoom. Right?

So many sales reps are now having conversations on Zoom. And you're able to track...

your tonality of voice, how your movements look, et cetera, et cetera. And then you can correlate that with the system of record, the Salesforce or whatever else you have to be able to figure out what those correlations are. And so, and those sensors aren't just obviously exist in video form now. We have all sorts of sensors that we're wearing on our body and other places. And that is allowing us to gather the human behavior data, which we can then correlate with outcomes. Super cool. It's an interesting, the second thing I've been thinking about, and this reinforces that point even more, is that

that if let's imagine machine learning doesn't exist and uh jake you're an enterprise and you have a bunch of customers and i come to you and say um hey i'd like all your customers and i'm going to sell them something now you'd say like no or maybe you'd say like well let's enter into like a channel partner agreement because like you're taking you're disintermediating me in some capacity by doing that but with this world of uh i like how you coined it coaching networks it's

There is so much value to be brought by a network effect on the back end in the way that the software works that if I'm to come to you and say, "Hey, I want some of your customers

you're going to get so much value by just using my software and distributing it that you're like, Oh yeah, no, I'll, I'll totally use that. Like I don't look at this as disintermediation. I look at it as bringing tremendous value to me and I don't have to, it's not like the sort of textio brand is the main primary brand that's now interacting with your customers. It's more like, uh, uh,

uh, there's so much value that happens on the backend by getting larger and larger as a company that, uh, that it, it, it encourages people to distribute for you. Yes. And there's, and this is a term from business school that David will appreciate. There's a concept of FOMO that exists here. Oh, that's a business school term. Okay. Yeah. I don't know. I learned a lot about it. I paid a lot of money to learn that term. Um, so,

But the concept of fear of missing out, it's incredible because if you are a large Fortune 500 today who's trying to compete in the talent market and you're not using Textio and most of your competitors are, then you're not... And they're all getting the benefit of each other's knowledge and you're just playing on your own little island. And so there's this concept of like, well, I mean, I'm missing out relative to what my competitors are doing. Yeah.

And that, that creates this really positive flywheel effect. And it's beneficial. Like it is a true network effect in the sense that every new user makes it the product better for everyone else. So, okay. So, uh, this is a perfect seg into my next question for you, which I am also like super genuinely curious about the other ones. You weren't genuinely curious about it. No, no, I made it. Yeah. Uh, no, but, um,

is the perfect example here. I remember meeting with, um, meeting with Texio, uh, when I was at Madrona, uh, and, um, amazing team, great idea. And, and, and you guys had this thesis which, which helped you, um, look at the lens of the opportunity. Uh,

When you were looking at an individual company, how do you evaluate the market for a SaaS company? And Textio is the perfect example because we also thought the team was great. We also thought this vision of the future was awesome, but we couldn't get there on the market for job listings. And we were probably wrong, right? But how do you think about that?

about that? Yeah, it's a great question and one that we wrestle with ourselves, obviously, all the time. So it starts with the way we think about all of our diligence efforts is it starts with what is the customer value being created? So even if that customer value that's being created is being created for the first time,

right? Because there's not a comp. There's not an existing market for tech CEO. So you have to, you can't download a Gartner report and see what that looks like, right? And the reality is the best opportunities, there's not going to be a Gartner report. Right, exactly. Particularly for early stage investing. So you have to understand what is the customer value that's being created. So you talk to customers and say, hey, what was life like before you use this product? What is life like now?

You can understand what that value being created is, and the company may or may not be capturing enough of that value from a pricing perspective, but that's a separate conversation. But if there's enough value being created, you can see a path towards capturing some of that value. And if there's enough value being created and you believe there's enough people like that for whom that value could be created, then you can see a path towards a market being created. That being said, you still may have to make a second leap forward.

which is to believe that great entrepreneurs will find new markets. And Viva is actually a great example. So when we first invested in the CRM for pharmaceutical space, it was a counterintuitive bet because the most generous market sizing there was $500 million, which is not a big enough market size. I mean, obviously, the company is now a $17 billion public company. So they did something different. But when you...

But part of the reason why that was a non-obvious bet is because people said this is too small of a market. Best case scenario, this gets acquired, which is not what we're going for. No offense to the title of the podcast. Now we've expanded to IPOs. And the best companies we cover on Acquired are the ones that are... It's not even just the IPOs. It's like the enduring big, huge platform company.

It's like that's what we're all trying to build. It's really a misnamed podcast at the end. Yeah. But I have a lot of affection towards the name. I don't know why. I think your name starts with an A. Yeah, exactly. It's great. But so you have to believe that people like Kieran and Jensen, the founders of Textio, are going to create...

a new market. Another example in this is we're investors in a company called Guru, which is another coaching networks company focused really on distributing knowledge to customer facing teams. So it's knowledge management, but really with a focus on customer facing teams.

And when we made that investment, it was also controversial from a market perspective. Because if you look at knowledge management, that is a market that does exist. And it's not a very good one. So if you look back, there has not been a massive... There have been a lot of companies who have built knowledge management systems. Talk more about that. What's a knowledge management system? So I'll talk about what it is classically and how Guru is doing it differently. So classically, knowledge management has been a wiki. Okay.

or an intranet, right? SharePoint. SharePoint, exactly. Confluence is another example. You know, basically, it's a third-party place where you store all of your organizational knowledge. And that has classically looked like things like HR policies and IT policies and all that type of stuff. Occasionally, you'll get, you know, data that's relevant to a sales process on the product or, you know, support or what have you. Yeah.

And that's basically what that was a state of play when Guru came to pass. And unsurprisingly, those products have not built great companies. And I'm not a not super inspiring product. It's not a super inspiring product. And I think part of the reason that is, is because the products aren't used very much. Right. Like if you create, think about in your own organization, there may there probably is a wiki or an intranet.

intranet and you probably don't go to it very much right because it's it's this it's this other place I'd much rather it's funny that we even were developing one for for Pioneer Square Labs I could refer to it I often just email people and ask them exactly the very same question I could look up exactly and it grew we call it the shoulder tap like how do we avoid the shoulder tap I

And the idea is there's two reasons why you're tapping on a shoulder. The first is because you don't want to go to, you know, you don't want to get, you don't want to break out of your workflow and go somewhere else. And the second is because the knowledge that is in this third party place is probably old, right? There's probably something newer because people don't use it. So they don't update it. So as a result, no one's built an exciting company knowledge management today. So if you look at the market and you say, should we make an investment here? The answer is no. Yep.

So what we saw in Guru and what Rick and Mitch at Guru have built is something that tries to solve those two fundamental problems, knowledge management. So the core concept behind Guru is that the knowledge you need should live where you work.

And so they basically just capitalized on a new UI. So instead of building Guru as a third-party knowledge management website like everyone else, they built it as basically having two core UIs. The first was a Chrome browser extension. So this Chrome extension just sits alongside you and basically is a little co-pilot or coach that understands what you are doing.

and can proactively pop up the knowledge you need while you're in an interaction. So if you're a support rep who's going back and forth with a customer in Zendesk, it's always there. It's just kind of sitting alongside you, understands the conversation you're having back and forth, and will proactively pop a piece of knowledge and say, hey,

you know, here's the playbook. Here's the piece of knowledge, what we call card that is probably useful in this situation. And then it learns, does the support rep use that knowledge, modify that knowledge or ignore that knowledge? That's cool. Is there a little like at the end of it? Yes. No. Like, was this helpful? You don't even, so there is, but, but here's the beauty of machine learning, David, you don't actually need that because you can learn, you can correlate, did they use the knowledge and then what happened with the ticket?

Did the ticket close? How quickly did it close? What was the customer NPS, et cetera? So you don't even need the rep to say what's good or bad. So the centerpiece of this thesis, like you know, was it a successful outcome on the ticket? Did it work? And the next time a support rep anywhere across the world faces that same problem or a similar problem, Guru will know which card to elevate based upon your own behavior. Cool. So this concept of being in line, the other UI they have is a Slack interface basically. I was going to ask. Always there. Yeah. And so when you're in Slack, it'll pop up automatically and give you the knowledge you need.

That's a long way of saying that was another non-obvious market bet and we had to get comfortable, but it all came down to customer value and having the conversations with customers as well as being thesis driven. We had this coaching networks thesis. We believed we were actually hunting for a company like Guru proactively. Cool. Which is how you met them in Philadelphia, right? They're in Philly. Yeah.

And Jake, you guys are typically series A and B investors. And so you sort of see evidence of product market fit in at least one vertical as you're sort of thinking about, can I imagine this thing scaling? You don't have to make a complete fresh bet on a pre-product market fit company with this notion. That's right. So yeah, our sweet spot is product market fit.

which generally happens around the A, sometimes it happens around the B. But what we like to do is get involved when we feel, when we can talk to some customers and see, okay, there's some value being created here. You don't necessarily know how you're gonna scale it yet,

But we've got this whole engine of go-to-market SaaS expertise that we're going to just bear hug you with, to use that term again. But it really feels that way, I think. You join to our team, and then we sit down with you and do a super deep dive on all your various go-to-market strategies...

We bring a bunch of potential hires to you for VPs of sales or VPs of marketing or SDRs or what have you. We try to help you figure out channel partnerships and pricing strategy, all this stuff that basically every SaaS company deals with at the series A and series B. We've architected our team to be sort of laser focused on helping with those problems.

It's interesting and helpful for founders to probably use a similar framework that you use in market sizing. When you're a talented person with only a limited number of years on this earth where you can be working and you have to decide what I'm going to spend my time on and what I'm going to start or what I'm going to go join. And it's interesting to think about sort of opportunity sizing. I won't say market sizing, but from a bottoms-up perspective instead of a top-down where it's almost like

TAM is backward looking, whereas value provided on a unit basis, and then trying to extrapolate that to how many units could there eventually be is really forward looking. That's such a good way to put it. TAM is a very backward looking metric. We really don't like top down market sizing. We think it guides you in the wrong direction. I mean, the two companies we talked about today, if we had done top down, we wouldn't have made the investments.

At the very least, it's a sort of derivative form of thinking, right? It's the Gartner thinking. Yeah. Okay. So we've talked about theses. We've talked about markets. Let's talk now about building SaaS companies. So I want to start with, let's start at the beginning. Where are good breeding grounds for SaaS entrepreneurs?

With the caveat that just in any form of entrepreneurs, like great companies and great founders come from anywhere. Yeah. But there are pockets to, you know. Well, so from a SAS training ground perspective, Salesforce is still a really great place. There are some incredible people that go through that boot camp and come out and just know how to execute. Mm hmm.

There have also been some great entrepreneurs that have come out of Salesforce. Although I wouldn't say we're at a place yet where there's sort of a thriving large ecosystem where Salesforce is just minting new entrepreneurs. They're minting great VPs of sales and great VPs of marketing. Mm-hmm.

And there's some great entrepreneurs as well. But I wouldn't say that there's... I don't think there's yet been a PayPal mafia of SaaS. Do you think there will be? Or is it like... Maybe... Okay, to put a finer point on this. We think about this at Wave a lot. When you guys are looking at founding teams... And you look at product market fit when you invest. But the team's still super important. And you look at companies early. You meet them...

Are you more concerned with domain expertise in the... Experience and expertise in the domain of, say, it's a vertical SaaS company...

or sass company building like nuts and bolts execution dna obviously you want both but like what do you think is more important yeah so the best companies obviously have that pairing so in viva's case peter gassner who's the ceo there was a deep expert in crm and the force.com and all that type of stuff and then matt wallach who was the president was like a pharma person through and through

And so for vertical SaaS companies, our belief is that you do have to have both. And there's a third, you know, we call the talent trifecta for vertical SaaS companies or industry cloud companies. And the third, obviously, someone who can help build a tech, you know, as a TO. And so we believe that, you know, basically all vertical SaaS companies will need that. If I had to choose between, you know, the domain expert and the, you know, the kind of great SaaS leader,

I think, you know, if you have a great domain expert who has all the great makings of an entrepreneur, you know, someone who's hungry and, you know, charismatic, charismatic and can, yeah, can enroll. And that, that actually is an important point. Like the, the single most important thing that I look for in evaluating a CEO for potential investment is what I call enrollment. Hmm.

So what is their ability to enroll or basically create followership? And there's three important things they have to create followership on, obviously. You guys are all about the threes. I love it. I know. I'm obsessed with the threes. It's too bad there's already a Trinity Ventures out there. Unfortunately, they took our name. Yeah.

But so first thing that you want to look for from an enrollment perspective is, you know, can they can they attract customers? You know, obviously, that's it. That's an obvious one, because for the first, you know, foresee the early foreseeable future for a SaaS company, founder selling is most important.

The second is, can they invest? Can they attract investment capital? Right? Because even after you make the investment, you want to believe that you can't raise their next. You can't raise their next. Exactly. Although, interestingly, I think this depends a little bit on the market and whether or not you think they'll have to raise a lot of money. And the third one is people. And that's the most important one. Like, do you fundamentally believe...

that this founder will be able to attract incredible people because I can bring them great people from our network. Yep. But they have to convince... They have to close them. I can lead the horse to water. Yeah. But ultimately, the water has to close the horse. I'm not sure how that analogy... The water has to be tasty enough to... Exactly. To be consumed. To a discerning horse. Exactly. Jake, I think this is so on point. And to give sort of the founder perspective, I think, and just founder psychology on it, when I was...

taunt and wearing the CEO hat there and spinning out a PSL, Mike Galgan, who's my co-founder there, he sold a quant of to Microsoft. He's had a bunch of sort of successful exits over the years. And his way of phrasing that to me was, your job as the CEO is to marshal resources that you don't yet deserve. Your company is nothing right now. Like, you don't... I mean...

Deserve is kind of a funny way to phrase it. But like, why should that incredible person come and work for your company that is nothing? Why should that investor put money to your company that's nothing? Why should that customer sign on with you? And your job is like to go and push each one of those things just one inch further than you sort of deserve at that moment. And then leverage the fact that you pushed it one inch further on one vector to go and attract the next. And it's sort of this like,

this uh almost game you're playing of going round and round and round and trying to push everything forward in sequence with the rest of it as fast as you can yes that's that's such a good way to describe it um and it leads me so there's there's a north star metric i use to make investment decisions uh that relates directly to this this concept um and that metric um is very admittedly a subjective one but it is would i work for this person that's such a good uh uh who um

Uh, somebody, uh, I remember reading years ago, I think it was maybe Bijan at Spark also uses this and, uh, it's just such a good reductive, like,

And the thing I found to make it, I mean, it's great because, I mean, A, I am working for the entrepreneur. Yeah. And I'd spend a lot of time serving that entrepreneur for a decade. Because the VC. So I am. But especially in your guys' case, it really is true. We do, our second core value is that we strive to be the most important partner to our founders. And we take that really seriously. So each of us only makes one investment a year.

And the idea is you make that one investment and you go super deep. And are you guys dogmatic about it? You make an investment, you cannot make another investment that year? There's not a hard and fast rule. There are some years where people will make two investments, but certainly no more than two. And the average is about 1.2. So it averages out to be about one. So we take it really...

it really, really seriously. I serve the founders I've talked about on this podcast already. And it'd be interesting to hear their perspective. But I view myself as very much in service to them. And I spend a lot of my time serving them. But even more important than that, I need to ensure that really top tier talent will work for them. And

And I don't know if I'm top tier talent, but I have an idea of what that could look like. And actually, I am fortunate to live with someone who is top tier talent. So my wife is a SaaS executive herself, and she is my secret weapon in so many ways, perhaps not so secret. But I really like her to spend time with founders before we invest.

uh, for two reasons. One is, um, this whole thing is just a family thing like this. Like, I mean, what we do is so personal. Uh, you can't, there's no line between professional and personal for me in this job. And so it's really important that my wife knows my founders, my founders know my wife. And, uh, and in some cases, uh, there's actually like some interesting business, uh, collaborations that have happened between those relationships. And I want to get to know their spouses as well. Um, but also this is also just a total aside, uh,

a point that I didn't realize till, you know, starting wave and you probably didn't realize till becoming a partner at emergence, like it's family and that like the vast majority of my family's, you know, current and potential future net worth is tied up in our investment decisions. Like, you know? Yeah. Yeah. And so that, you know, that's another reason why I think Danny, my wife likes to meet the entrepreneurs before we, before we fund them. Investment committee. Totally. She's, she's my investment. I mean, the other thing, um, is, uh,

If this entrepreneur can attract Danny to want to work for him or her, then for me, that's gold.

just because I obviously hold her in such high regard. But if they can do that, then that tells me that there is something here, which again, it's a strange way to think about investing, but it's... No, it's too. My wife, Jenny, she tells me, hey, always be sourcing. And she's always sourcing for us too. Totally. Okay. So we're talking about domain expertise. Obviously, you want both, but it sounds like it's what you're saying.

I mean, it could be either the domain expert or the SaaS, you know, but you need that. It could be either. I would say it's easier to interrupt. Yeah, you need the enrollment thing. It's on balance. I think it's slightly easier to compliment a great domain founder who knows the problem that people are dealing with, with great, you know, a COO from, you know, Salesforce or Box or something that has seen it before than it is to do the opposite.

Because you really want the founder to have extreme customer empathy with the problem. And if the person's just a SaaS expert and they're not an expert in the problem the customer faces, it's harder to build that. Yep. That makes total sense. Okay. So that's team. Now let's talk about like, I think I'm a great team, building a SaaS product.

I really want a great partner like emergence. You're not gonna even consider investing in me until I have product market fit. What do I do between my team is pulled together, ready to go. And when I'm ready to come see you, how do I build the, and,

And I would say even within getting investment not being the goal, more around like, how should I in my early pre-product market fit stage, you know, how should I put together a great SaaS business? And I think the funny thing is a lot of entrepreneurs have a great idea for something.

in their heads now, because SaaS is so standard, they're like, well, of course, the business model would be sort of like a monthly recurring subscription type thing. But I think a lot of people when they're first at the outset, don't even realize, oh my God, I'm running a SaaS company. And so once you sort of have that realization, what's the like set of things that you should start looking at? And there's a million blog posts about SaaS metrics, but what are the things that you really think as a SaaS investor are important to create a successful SaaS business and find product market fit?

Yeah. So the metrics, I can talk all day about the metrics, but the... We'll get to the metrics. We'll get to the metrics. Yeah. But when I think about the single most important piece of advice I would give to someone who has founded a company and is at the seed stages and is pre-product market fit, and I'm going to sound like a broken record on this, but focus. The only thing you have...

is focus relative to all the big companies out there, even medium sized companies out there who are doing a bunch of other things and have to support legacy businesses. All you have is an ability to focus. And so I would much rather see a company really laser focused on solving a fairly narrow problem. And Textio is a perfect text. It's obviously a great example. And then execute on that super well. And then I'll believe that they'll be able to expand from there.

Far too many companies come in. It's fine to have the broad change the world pitch. You need that and you also need to believe it, but you got to start with a focus. You can't start with this kind of what my partner Gordon calls peanut butter approach where you're kind of trying to do everything for everyone. And this is even more important in machine learning land. A lot of the companies I'm backing these days have some ML at their core,

And what I think I've seen a lot of is kind of generic ML for the enterprise. And that's bad, not only from a go-to-market perspective, the same reasons why that's bad in SAS 1.0 land, but it's bad from a product perspective. Because for a machine learning company, your recommendations are only as good as your data is relevant. Right.

Right. So if the recommendations you're trying to give are for a bunch of different problems and the data set you have isn't relevant to those problems, the recommendations aren't going to be great. Take Guru and Zendesk, right? Like, you know, Zendesk is probably a pretty good use case for them, right? Because you have clear outcomes. You have a process you can insert yourself into like...

Yeah. I assume they didn't start doing everything as a knowledge base from day one. Yeah, exactly. And if you think about how we built the product, Guru is being used in all sorts of ways. People use it for HR policies and IT policies and what have you. But when we think about that, when we're building what we call AI suggest, which is this proactive suggestion engine that is driven by machine learning, which originally said, we're just going to focus on support. Mm-hmm.

We're just going to really go super deep on support and make sure that our data sets and support are super relevant just to support for a specific type of customer in a specific stage so that we can turn on the machine and it just works beautifully. And then, you know, we're moving to sales and we're gonna have an AI sales engine now. But the idea is we started with something. We got really good at it and we're not moving to the next thing until we are sure that we're awesome at the first thing. Makes sense. Yeah.

Okay, so now let's get to you've done that you focused, you've built a product, it's got, you know, usage, you think it's great. Now, I come see Jake. Obviously, all the things we talked about earlier are probably foremost in your mind about evaluating, you know, through the lens of your thesis, evaluating the team, you know, doing the market thinking from a bottoms up perspective about the market.

But there also are metrics. And metrics are the way most investors, I would assume you as well, judge product market fit. There are a million blog posts out there about SaaS metrics. Is the orthodoxy right? Or what are the most important ones to you? Yeah. Well, let me start with the non-metric one that I think is the harder one to judge and therefore isn't talked about as much. Product market fit is not a function of metrics. Product market fit is a function of

love. Yep. Right. It's a function of as my partner, Riley said, we were talking about this the other day, like at Airbnb, they basically

And Brian, the CEO, wanted, for many, many years, he would go to Riley. Riley was the head of data science and be like, I need a metric to show love. Give me a metric for love. And Riley's like, I can't give you a metric for love. It is literally impossible for me to give you a metric for love. That's like a broader life point as well. And Riley believes it too. How do I know when? His point when we were arguing about this, he was like, yeah, love is the most important thing.

but like you cannot mention it. Yeah, it's all you need. It's all you need. Okay, great. Continue. So, but yes, I mean, so I will tell you the way we look at metrics and I'll talk about the ones that are important in a second. But the single most important way that we build conviction and investment is in talking to customers and hearing from the voice of the customer. Hey, this is what my life was like before. This is what my life is like today. I was talking to, I was doing a customer reference a couple weeks ago

to the customer. This is a bit twisted, but the customer who was the buyer for the product sent his when it came time to renew the product, sent his team who are the users of the product an email saying, hey, I'm sorry, but we're not gonna be able to renew the product this year. Just

just to kind of screw with them and the response that he got from his team was a bunch of like expletives and capital letters that's and from a vc's perspective that's what you want to see you just want to that's what you want to hear right when i was our summer in business school i worked for meritech which is a growth stage investor does everything but but historically has done a lot of enterprise and sas companies and i will never forget uh rob ward who's a

He's an amazing, fantastic investor there. He told me about one of the biggest lessons I took away was when we were doing customer calls. And he was like, you know, I'm always looking for the Tableau 10. And he was like, when I did customer calls for Tableau, literally, everybody I talked to was trying to jump through the phone and come and beat me over the head with a hammer. They're like, you do not understand how much this has impacted me. And he's like, that's what I'm always looking for. And it's really hard to find. Yeah.

But yes, that is the gold standard. So first and foremost, before the metrics, you want to hear that. From a metrics perspective, there are kind of three common metrics that people care about in SaaS. And I won't spend a ton of time on it because you're right, David. We've written a bunch on our website and as have everyone else. So the first one is just ARR growth rate. Do you have a favorite we can recommend of a good rundown of SaaS metrics? Yeah.

Yeah. My partner, Joe Floyd, wrote a piece on how to raise a Series A in SaaS that's on our website. And I think there's some good metrics in there and what those benchmarks should look like. But the first one that's really obvious is what is your growth rate? And the core kind of way in which revenue levels are judged in SaaS is what's called annual recurring revenue or monthly recurring revenue, ARR or MRR. MRR is just MRR times 12.

So that is kind of what is your current run rate. If you add up all the value and you annualize the value of your current contracts, what does that total to? So it's sort of like a forward-looking gap revenue metric, but it's the standard metric in SaaS today. So understanding what is the growth rate of that number. So how quickly are you adding new customers, and how does that look relative to how customers are leaving you? And generally speaking, when you come to a Series A, that number you want to be above 10% month over month.

So you want to be growing your error number at least 10% month over month. So that equates to a batted exponential math in my head, but you're probably like tripling or quadrupling every year. Yeah. Tripling or so. Yeah. Cause you're human. Right. Right. Despite your Samson like hair, you're just human, David.

The secret is out. That's the crime that this is just an audio podcast is you can't see how incredibly lustrous... That's why we're doing more live shows. That's good for your audience. You're too kind. So, yeah, the classic phrase in SaaS is triple, triple, double, double. So the idea would be you triple year one, you triple year two, then you double three and four. Okay. And that's kind of...

the path for, you know, the classic path for success in AR growth. So that's metric number one. Metric number two, which is related but important to call out separately, would be what we call net retention. And so this is basically a function of how quickly and by how much volume your customers are leaving you versus how quickly and by how much volume your customers are upselling. Expanding. Expanding, exactly. Yeah.

So you basically, no surprise here, but you definitely want your upsells to cancel out your churn. Ideally, you want better. Are you looking for better in every case? Negative churn? Negative net churn, exactly, is a way to think about it. So you want that. So what that means is that if you had no sales team tomorrow...

that your cohort would expand naturally. This is a shared point with marketplaces. That is a thing... Well, we invest before there's a product. But Airbnb learned that we learned at Rover. At a certain point, if it has a successful marketplace, you're just like, man, if we all stop coming to work tomorrow, this thing keeps growing. And that's great. And obviously, that's not...

very few of our sales companies will do that, but the basic concept is... It's also... This is a bit of a proxy for customer love. I mean, all of this is a bit of a proxy for customer love. But,

But that's really, really important. So one of the ways we visualize that is through what's called a cohort analysis. And I think that exists on Joe's blog, the one I recommended. But if it doesn't, I can send something in the show notes. But it's basically a way to visualize cohort by cohort. So for all the customers that joined in this month, you kind of visualize how does that graph expand or contract over time. And you want to see what we call a smile. Yeah.

You want to see that you're the, the later cohorts are, are getting bigger. And so there's this kind of like crooked smile that happens with that graph. Um, so that's net retention. Um,

let's see so the third the third metric that um i spend uh a lot of my time and we spend a lot of our time thinking about is sales and marketing efficiency okay so how how efficiently are you selling your product um because you can have that's probably the most fixable right well it is and it's not so if if there is a fundamental um there's a fundamental imbalance in uh let me put it this way um

If you have to push so hard to sell your product, there's no market pull at all. It's hard to scale in a reasonably capital efficient way. Yeah. Right. It's just like if you've got something that's great, but it takes you three years to convince every customer that they should buy it.

then you're going to have to raise so much money to get to a size that it's not good for anybody. Got it. Yeah. You got with all the stuff that we'll talk about next that you focus on after you invest that you can help optimize and help the team like you can't do two orders of magnitude improvement on this metric. You can fix the operational inefficiencies. Yeah. But you can't fix market pull. Yeah.

And in some ways, sales and marketing efficiency is a proxy for market pull. How do we measure? How do you measure sales and marketing efficiency? Is that the cost to acquire a customer? Is that... Yeah, it's a really simple metric. And I'm generally a fan of trying to simplify these things as much as humanly possible. Mm-hmm.

So, the way we look at it is simply what were your new and sometimes we consider new and upsell bookings over the course of a given quarter. So, how much new annualized revenue did you add over the course of that quarter divided by the spend you had on sales and marketing? Mm-hmm.

And basically, and it's really simple, you want that ratio to be more than one. But don't you want it to be the previous quarter spend on sales and marketing? It depends on the length of the sales cycle. So if the sales cycle is more than a quarter, then it's more accurate to do the previous quarter. But generally speaking, just standardize things. And for most SaaS companies, most SaaS companies have...

you know, mid-market and SMB SaaS companies generally have a 90 day or less sales cycle. And so you can do the same quarter. But generally speaking, you want that sales and marketing efficiency number to be above one. Because really simply, you just want to be able to say, okay, for every dollar I throw into this machine, I get more than a dollar back. Right.

So that's the third. But if you're growing really fast, it's going to be below one. Correct. That could mask. It does. And the other thing that's hard about it is when you add a bunch of new sales reps, when you're growing really quickly, let's say you do a big fundraise, you hire a bunch of sales reps to grow faster, that sales and marketing efficiency number by definition is going to tank. Yeah. Because you got a bunch of people who are ramping up and don't know what they're doing. Same in marketplaces too, honestly. We don't have quite the same metric, but at Rover for many years, investors would look at Rover and they'd be like, this is terrible, right? Because they were judging on something similar to this. And it's like,

No, the opportunity is so big. We're investing so much in growth. The way to look at it is you can actually, and this is one of the nice things about SaaS, is you can actually individualize it on a per rep basis. And you can see, okay, because if you look at all the new reps that are coming on board, yeah, you don't, you know, you can't, they're still ramping. So you can't, you can't do the math. But if I've got a rep who's fully ramped, and I know that, you know, it's,

I can understand how efficient they are with their selling, basically. And one metric I do like to look at is the ratio of kind of attained quota, basically how much new bookings they're getting over the course of a year, divided by their OTE or their on-track earnings. Because that tells you, okay, this is how much they're adding based upon how much they're costing the company. And generally speaking, I want to see that number above four.

Meaning, you know, if my fully loaded sales rep costs me $250K a year, I want them to be adding a million dollars annually. AR. Makes sense. Can I just say for a minute, popping up a level, it's insane that like...

all of the people who run these businesses are dramatically different. The products that they make are dramatically different. The segments they serve, the value they bring, all these things vary wildly. And yet when you boil them all down and fit them in the same sort of, here's how you measure each of them, like good ones all sort of look the same. And I'm sure there's some like normal distribution of what, you know, that you're looking for things and sort of like

two sigma or two and a half sigma away from the mean in the sort of northerly direction. And there are the sales forces that are like three or four sigma away from the mean or something like that. But like, it's nuts to me that this can all be standardized. Well, I think that we give some false precision to this because it gives us some comfort. Yeah.

Just to be clear. Yeah. Like the reality is, you know, there are outlier businesses. So Viva, for example, their sales and marketing efficiency numbers were absolutely insane because they sold seven figure contracts and they'd had these referral effects where like, you know, if Pfizer is using you, then Bristol Myers-Woobs is going to use you. It doesn't really cost you that much to do it. Wow. And so part of the reason why they didn't spend any money is because they had these insane sales and marketing efficiency numbers and still do if you look at their public reports.

So as a result, you know, like it's really hard to benchmark that. And so our business is a business of outliers. The outliers drive most of the returns and the outliers are hard to benchmark. So I just want to caveat by saying all this is a little bit false precision. It is important and we use it. But this is why I go back to customer love because some of these metrics maybe may give you false indicators. There's a last metric I want to add, which is the one that I think is least talked about in SAS, but I think it's arguably I'm coming to believe is amongst the most important.

And it's actually a consumer metric. Wow. I know. You heard it here first. You heard it here first, folks. The metric that I spend a lot of my time focused on in diligence and as a board member is utilization or usage. Yeah. It always, you know, as someone who's mostly leaned consumer over my career as an investor, when I would work with enterprise companies at Madrona,

this is the thing that I was always like, there's something missing here. Like, yeah, you're selling to the CIO or whoever, but like if people don't use this thing, you're pushing a boulder up a hill. Yeah. And so, and so that, yeah, there's, there's two reasons why I think usage is important. One is, I guess I could find a third to make it three, but in my head, it's only two at the moment. So the,

The first reason, obviously, is it's a leading indicator for churn, right? So if people aren't using your product very much, it doesn't matter. Eventually, it's going to catch up to you, as you said. The second reason why it's important, and this is more specific to machine learning-driven companies, is utilization actually creates a data flywheel that makes the product better. So let's just take Textio or Guru, for example. If in the case of Guru, every time they popped up a recommended piece of knowledge, no one used it.

it was just ignored, then not only are people not getting value out of the product, but more, almost perhaps more importantly, the system isn't learning any new data. The system isn't seeing, okay, they tried this knowledge and it worked or it didn't work and therefore I can improve over time. It's just a static machine learning data set. The data set itself is not expanding. And so usage is important both as a leading indicator of churn, but also really critically as a way to make the product better. Mm-hmm, mm-hmm.

Well, I think there's also... I got your third right here, which is... It's a proxy for value. Yeah, of course. I mean, it's back to customer love. Yeah, yeah. And so, you know, I look at things like very consumery metrics, like Dow-Mal ratios. So daily active user to over-monthly active user, which just tells you of the percentage of folks who are using your product with any frequency, how many of them are using it really frequently. Yep, yep. Totally. Okay. So now we got metrics. Let's talk about...

After you guys invest, what's like some of the topics I want to cover? Pricing, distribution,

uh and and um operational and executive like help let's so let's uh let's start with distribution that's probably well at least distribution in the consumer world is uh the hardest thing that nobody talks about i imagine it's similar in in your world but but let's talk about it yeah well can i level up just one more thing before we dive into that yeah so um

Right after we invest, there's a stage before we talk about distribution and pricing and other types of more tactical things. There's an alignment phase. Cool. And so the first thing we do after we make an investment in a company is we bring the executive team into our office. And we do this with not just the deal sponsor, but other partners around the table. Again, because we're trying to kind of act as a team here. We bring everyone together and we do a vision and values exercise with the executive team.

And that starts with the IPO press release. And so we have each of the founders, or sorry, each of the executives independently write their own IPO press release. And we ensure that we ask them not to share it with each other ahead of time. And then we all sit around a table and each of them reads their IPO press release.

And we start to realize, okay, there's some really fundamentally different assumptions that people are baking in to how this company will grow. If someone says, everyone's going to say we're going to be at 200 million ARR in five years and we're going to be ringing the bell and whatever. But someone may say, we're going to be at 200 million ARR and we're going to have 200 awesome customers.

And then someone may say, we're going to be a two million ARR. We're going to have 20,000 awesome customers or three different verticals or verticals or geographies or what have you. And the reality is, you know, a lot of that stuff will get sorted out down the line, but you can start to tease out, you know, fundamental misalignments up front and just start having that conversation. Then we do kind of a we do a back solving exercise, which is like, OK, if this is the goal, what are all the things need to happen to get here?

And then we do an analysis of what are the potential barriers that could prevent us from getting there. And then we do an analysis of what are the crazy accelerants that could just change everything. Like if we hired this type of person or if this regulation changed or what have you. And then at the end of that, we have this really cool document and conversation that we had, which is like, okay, this is a rough game plan. It's not like we're committing to a board plan right now, but it gets everyone, the board and everyone else aligned. So we start there.

Oh, yeah. Do you bring other previous board members in that experience? Or is it really just you guys in the executive team? No, it is varied. But in the past two that I've done, we've actually brought in the existing board members as well. And it's kind of a full team exercise. The key thing is to make sure that everyone feels comfortable sharing and

and that there doesn't feel like any pressure. You know, if someone is, you know, a more junior member of the executive team, you still want that person to be contributing as much because their voice is just as important. And so it's about kind of creating that safe place. And so we kind of set a, this is again back to grad school, we try to set like D school norms. When we start the event, we have lots of, you know, post-it notes and other things to make it feel a little less weighty. Yeah.

But so that's where we start. We start, we start there. And then that's also a good place for us to understand. And we also understand this through diligence. Okay. What are the key challenges the company's facing? And for us, it generally does start with distribution or what we call go to market. Um,

So generally speaking, there's a bunch of different go-to-market models that now exist in SaaS. There's the Viva million-dollar contract total enterprise sale model. Your very active sales reps, humans who are selling to other humans. Correct. Humans selling to other humans. That you employ. That you employ, that take a long time, potentially a long time, but are really high value, super complex sales.

really complex buyer situation with lots of people informing that buying decision, et cetera, et cetera. So that's kind of on one end. And on the other end, you've got freemium. You've got the Yammer, the Zoom, the Slack, et cetera, et cetera.

and and you know we've seen and then there's everything in between obviously there's hybrid models and what have you what's interesting and is that even the freemium companies so even slack and zoom for example and I'm close my wife works at slack and obviously we're investors in zoom so I've seen the story fairly close

you know, both of those companies started with a really strong freemium model, you know, just people and they both obviously still have a really strong freemium model. But what both of those companies I think have seen over time is that you kind of have to layer on people and a sales model to actually build a business into, you know, a predictable business. Stuart Butterfield, I think famously, I don't know if he denies this now, but I think someone

somewhat famously, you know, has a quote that he's never going to hire sales reps. It's so, you know, of all these companies, like all these CEOs, they always say that and it always changes. Well, I mean, the irony is that my wife runs mid-market SMB sales at Slack. So I'm like, well, I mean, she exists. Yeah. But I think you just start to realize that you need, you know, kind of proper process in place. And so

When we're evaluating a company or once we've made the investment, we generally try to align with the founder on, okay, what is the model that exists today and how do we think that model should evolve over time? And so we kind of work on that. We kind of work towards whatever the kind of agreed playbook looks like. Then there's some process stuff that we do. So my colleague, Doug Landis, who I mentioned was a VP of sales ops and enablement at Box and before at Salesforce,

we'll actually go in and help people rewrite their initial sales pitch um and help them redefine what we call their icp or ideal customer profile um and and and figure out kind of what the sales cadence should look like um and then the faga who's the the cmo woman i mentioned before uh will do similar things on kind of the top of funnel marketing pipe and you know different ways to do demand gen strategies and product marketing stuff etc so we kind of get we get fairly tactical um

But the other way in which we end up spending a lot of our time with our companies and distribution is actually just hiring. And we think that is so, so important. Like I think, you know, one of the most important things that we believe we can do to meaningfully affect the outcome of a company is to bring in help them bring in incredible people more so than introducing the customers. We introduce folks to customers. I think that's valuable.

but what I think is much, much, much more valuable is teaching you how to fish. Yeah, right. You serve the fish, but you also bring in some great fishing poles. And that is just... I think that's an undersung thing. A lot of founders when...

I always ask, how can I help you? And the, you know, common response is love customer intros. I'm like, happy to do customer intros. But that's a bandaid, right? What you really need is someone who can be doing the customer intros for you in-house. The other thing is where venture capitalists sit structurally in the ecosystem, you sort of get to thin slice and meet so many talented people for no reason at all because it makes sense for them to know you and it makes sense for you to know them that you end up with this really robust, uh, uh,

network of sort of talented executives and maybe future founders or maybe past founders that sort of nobody else really has access to because it doesn't make sense on a repeatable basis over all these years for them to know all those people.

Yeah. I mean, we've invested in almost 100 enterprise software companies over the course of the past decade and a half. And so we've seen every model and we have worked with many of the best people and many people who aren't as great, but we're able to know who is great and who is not. And we're also able to understand who is great for what situation. So one of the things we actually just did a whole exercise on this yesterday, we spent a lot of time doing what we call bodybuilding.

which is a phrase that I did not know what that meant when like I joined five years and like it's time for bodybuilding and I was like, well, what is this? Um,

But basically, we also... One of these many... It's like when people are referred to as an athlete. You're like, all right. Yeah, exactly. Exactly. I sort of get it. It's a little weirdly macho male skewed. Yeah, exactly. Exactly. Yeah, we probably should change that title. But trust me, it's the least athletic thing you can imagine. We sit around a table and we describe the type of profile that we are looking to fill within a company. Mm-hmm.

And we get really specific. So it's not just like I'm looking for a VP of marketing. It's I'm looking for a VP of marketing who majors in product marketing and has some experience with performance marketing, but is really majoring in product marketing and has done this from 10 to 30 million ARR. And the good news about our focus is that we then can just open up LinkedIn. And we also have a CRM system we use to track people as well and say, okay,

Here's the 15 people. And then we start the intro process. So from a distribution perspective, I think bringing on great talent is the most important thing we can do. Let's jump to pricing. The first version of pricing is usually like, you know, I don't know. Let's try this. Right? And then, you know... And it's always too low. Yeah. It's not right. Let's put it that way. And, you know, it's funny. Like for us...

We encourage our companies to think about it a lot, but we also tell them not to overthink it. When you're just building the product, price it too low, get people to use it. But then at your stage, when your product market fits, pricing becomes really important. Super important. And we spend a lot of time with our companies helping them think through pricing models. So I agree with you that most companies are pricing too low. And I think initially for many companies, it's okay to do that. There are some companies...

for whom it is not okay to do that. And specifically, these are industry cloud companies. So vertical companies that have a really well-connected buyer set, it's really dangerous to price too low up front. Because if you give the first buyer a discount and the first buyer is best friends with the buyer at the other one, because this is the Bristol-Myers-Scribd and Pfizer scenario. This actually literally happened. So one of the first customers was going to be Pfizer.

Pfizer came to Viva and said, hey, we love your product. We'd love to buy. Give us the Pfizer discount. We're your second customer. And Peter said, no. Peter, the CEO, said, no, it's a million dollars. And he went back and forth until eventually Pfizer walked, which was a really stressful thing when you're a young company and you got a million dollar contract. Pfizer left. And then six months later, Bristol-Myers-Wilson comes along and says, hey, I've got this million dollar. I've got this product. I want to buy your product, et cetera. And eventually Bristol-Myers bought it.

for the full price. And then lo and behold, Pfizer comes three months back later. Right. But if they'd sold to Pfizer for, Oh, okay, we'll do it for 200,000. Like that changes the whole trajectory of the company. Exactly. So, so pricing is a really nuanced thing in, in, in industry cloud companies. We, we believe that it's really important to hold the line up front. Um, for other companies, you can do more AB testing and we encourage that. Um, it's, it's important to AB test to figure out what the value will look like, particularly for given customer segments, because different customers will pay different things. Um,

One mistake that we see companies doing is making pricing basically single axis, meaning only having one dimension along which people price. So here's the product that's like... This is the per seat model. It's either per seat. So our recommendation, generally speaking, is that you want a two axis pricing model. Either volume based pricing, which is most commonly per seat.

Sorry, volume-based pricing and typically feature-based pricing is the other dimension. So, you know, the gold, platinum, diamond products or whatever you want to call it with different levels of features. And having that two-dimensional matrix makes cross-company comparison harder and

And so it allows you to experiment a little bit more with pricing. It also allows you to align yourself with the value that you're creating. So the volume-based pricing, if the company is growing and doing well, you want to be able to capture some of that value. Two quick other thoughts on pricing. The first is you got to figure out your level of pricing, not just with A-B testing, but also with an ROI analysis. So you do have to go to your customer and work with them to figure out how much value am I actually creating?

and then you can back solve and figure out. And generally speaking, folks can charge or should be charging anywhere between 10 and 25% of the value they're creating. So you got to figure out what that is. You don't want your pricing model to be based upon the ROI because then you get into this really weird situation where you have to prove ROI every time. But it's a way to set levels and then back into it with that two-axis pricing. The second thing I'll say about pricing is that this per seat pricing model, I believe, will die in the age of coaching networks. And the reason I think that's the case is

because you're you in coaching networks you want to incentivize as much usage as possible because the users the product makes the product better Percy pricing disincentivizes utilization you still need a volume access I think about shouldn't be proceed any sort of information based stuff like like pitch book or crunch base or whatever like you're yeah you're incentivized to have one is he and not share it

There's ways to do volume-based pricing that are not per seat based. So in the case of Textio, for example, they charge on how many people you plan to hire that year, regardless of how many people you use Textio for, because they want you to use Textio for everyone. But you're aligned with the growth of the company. Yep. Makes sense. Well, Jake, there's a lot more that I know we could pick your brain on, but I think we will let you go about the rest of your day here in a minute.

Thank you so much for coming and joining us. And I think one thing I'd love to offer for listeners is, you know, how can they get in touch with you if they feel, you know, hey, you know, I'm right about that right time where I should get to know great SaaS investors. Where can they reach out?

yeah um i guess i will give my email out uh and when you when you talk about it do you do like i guess so my email is j saper at m cap dot com and i like i i just i'm thinking about on twitter where you like you know do the at separately so people can't click and spam you but i guess it's it's verbal so it's fine but yeah i'd say i'd say email me um

Or, I mean, obviously the best way is to go through someone I'm connected with. I respond to every email. I believe that that is my job to do. So I will respond to you if you email me. My odds of meeting with you are going to be higher if it comes through a trusted source.

Yeah. And I'd say also maybe I guess my original intent in that, too, is like, where can they find you on Twitter? You know, where are the interwebs? Where can they follow your thinking? Yeah. So I have been writing a lot on this coaching networks concept. And it's on it's both on LinkedIn, but also on on the emergence website, which is MCAP dot com.

And I'll be writing a bunch more. E-M-C-A-P.com. I will be writing, and me and my partner Gordon are both writing a bunch on kind of the how-to of how this next generation of companies will be built. So I would love to talk to folks that are actually building this stuff. Great. Very cool.

Well, thank you, Jake. Really. Thank you, sir. This has been awesome. This was fun. Super fun. We're gonna have to have you back to, you know, one thing, obviously emergence. And I know you are super thoughtful too about is, um, you know, building venture firms and you guys are big into the Kauffman program and, uh, definitely want to talk about all that. Let's do another episode. We'll do another episode. Yeah. I, I love this place. Um, I just want, like, I just want to say one last thing about my love for this, this podcast. Um,

which I guess I'm a long-time listener, first-time caster, etc. But I'm just so proud of what you guys have built. And the thing I want to say about it is the evident joy

that you guys have when creating this this beautiful thing you've created comes through in the audio so clearly like sitting here I can see both of your smiles but the cool thing about what you're doing is that the smiles are actually audible through what you're building and it makes the listener smile as well so thank you oh well thanks Jake very high compliment thank you sir um

Listeners, if you feel the way that Jake does, you should scream it from the hilltops. We just got a robust discussion of network effects and please do feel free to share that you're an LP or you like the show or anything like that. And thank you so much for being Limited Partners. We'll talk to you next time. We will.

Bye.