124 - How AI and Market Shifts Are Breaking the SaaS Business Model w/Dave Lambert

Show Notes

Vic sit down with Dave Lambert of RightSide Capital Management to discuss venture capital trends, SaaS investing, and how the startup landscape is evolving. Dave breaks down RightSide’s data-driven investment approach, focusing on ultra-diversified portfolios and quick decision-making. They explore the impact of AI on capital efficiency, why per-seat SaaS pricing is becoming obsolete, and how macroeconomic factors shape startup success. The conversation also covers shifts in fundraising, the growing role of healthcare SaaS, and why founders must prioritize profitability over endless funding rounds.

• Right Side Capital Website - https://www.rightsidecapital.com/
• Dave’s Email - http://[e-mail]

Dave Lambert, Managing Director and Co-Founder of Right Side Capital Bio:

Dave Lambert is a Managing Director and Co-Founder of Right Side Capital. His firm is one of the most active pre-VC stage investment firms in the US and has invested in 2000+ pre-VC stage startups since 2012. 

Right Side Capital is known for using a quantitative, data-driven investment selection process that lets them give firm yes/no decisions to founders in about a week, and for the fact that each of their investments funds invests in many hundreds of startups.

Prior to founding Right Side Capital, Dave was founder and CEO of a computer hardware company in the 1990s, and software company in the 2000s.

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Thank you.

Okay.

Welcome to Health Further.

Today, we have another guest episode, Dave Lambert.

Dave and his firm, RightSide, have been partnered with JumpStart, IVC firm for a long time.

Dave, thanks for doing this.

Really appreciate it.

Happy to be here.

So it's a fun times in venture and SAS models, maybe for the audience, just give a little perspective on your background, how you came to be a VC.

And it's sort of a little bit on our right side.

We'll get into it more, but just a quick synopsis of your background.

Yeah, yeah, yeah.

My sort of one to two minute history is I grew up in Denver, Colorado, came out to the San Francisco Bay area to go to college in the late eighties.

To early nineties and then for the next 17 years.

I was mostly an entrepreneur.

I was CEO and founder of 2 tech startups.

1 was a computer hardware company.

The other was a software company in the 2000s.

I was a moderately active angel investor from the mid nineties to mid two thousands as well.

And then, you know, right side capital, uh, started working on that in the late two thousands.

We launched in the early 2010s and right side capital is a quantitative data driven approach to what we call pre VC stage investing.

So I think the sort of three unique things about us.

Um, our number 1 that we focus on these small round sizes.

So it's primarily 150, 000 to 500, 000 dollar total round sizes.

So that's sort of an area that's largely ignored by the professional fund world.

Uh, the 2nd, unique aspect about us is this quantitative data driven decision making process.

So we gather up a lot of quantitative data points about a company, and that lets us make a yes or no decision usually in about a week or less.

And then we use that the 3rd thing is we use that to build out ultra diversified portfolio.

So each of our funds has many hundreds of companies in it.

We're currently investing from our fund 6, but we have over 2000 portfolio companies since the early 2010s.

Yeah, excellent.

Very good.

So maybe let's just unpack for a minute how those kind of aspects of your background and right side, um, offered maybe a different alternative to teams of founders trying to raise money.

So, uh, you were a founder yourself and now you've evolved first angel investing and now fund investing.

Uh, and that quick decision making is very unique in the market and I think really welcome from founders with, you know, tell me that that it's possible and let's move forward or tell me that it's not right.

And I'll move on.

But just an answer, you know, obviously I prefer yes, but no, a fast no is also useful.

Um, and then that.

several hundred assets in the portfolio, those three differentiators, how have they benefited right side or how is that, um, useful?

Why is that important to right sides results?

Yeah.

So I think, you know, our sort of part of our core philosophy is Both from being in the startup world and having been on the investor side, you know, my partners and I came to the conclusion early on about two things.

One is we were talking back in the late two thousands about the fact about sort of power law distributions and about how skewed the return curve was.

And that the math sort of works a bit differently on top of power law distributions.

So we knew.

You know, capturing these tail outliers was a key part of the investment strategy that we would wanted to design.

So, basically, our philosophy is that most of the returns are locked in the.

Really one in 20 to one in 100 outcomes in a, in very early stage venture portfolios.

And we were even going earlier than traditional early stage venture.

And you can't have a portfolio of 15 or 20 companies or even 30 and think you're going to get a one in a hundred with high certainty.

So our idea was, well, let's have hundreds of companies and we'll get our fair share of those one in one hundreds and certainly of the one in twenties.

And then if we could do that.

And so both of us, how do we do that?

Well, you have to make quick decisions if you're going to have ultra diversified portfolios and what sort of the data logic and philosophy behind doing that and basically both, uh, you know, a lot of it's from both entrepreneurial sort of entrepreneurial investor and economic theory and engineering sort of backgrounds from myself and one of my other key co founders came to the conclusion early on that it.

For startups at this early stage, you can't know a lot more than the starting point at which you're investing.

And there's so many variables of uncertainty.

That our belief is that, you know, humans were really using our brains to fool ourselves to believe that we can predict all these various variables of uncertainty, not just that we can predict them, but we can predict them far out in time, you know, and that that could be the case when, you know.

Nobel Prize winners in economics can't predict economies six and twelve months out.

And we felt there's more variables of uncertainty with startups almost than an economy, or there's more uncertainty with them.

Um, so anyway, that's sort of the, the reasons and the premise behind everything.

Yeah,

so a lot of my audience is, uh, learning about venture.

Maybe they're running, maybe they're a physician or running a health system or.

Um, they're in a startup, but they don't know the power line in detail, maybe just unpack that a minute.

So one out of 100 companies, um, will drive some very large return.

Um, and then, uh, so it's like, it's kind of the 80 20.

rule Pareto policy, uh, thesis, but then, you know, even more so where like 9 percent of the return is in that top 10 percent and even the 1 percent of a hundred is, is, uh, massive.

And so that's, is that a fair representation of how you would characterize it

or?

That is, most people don't even understand the Pareto distribution correctly because The Pareto is the 80 20 rule.

If you say, you know, 80 percent of our returns are from our top 20 percent of outcomes, but within that top 20, 80 percent of those returns are also in the top 20.

So even in a Pareto it's yeah, 80 is in the top 20, but that means 16 is in the top 4 percent or, you know, or, uh, you know, Uh, of that, or sorry, more than 80, it would be, yeah, 80 percent of the 80, 64 is in that top 4%.

So it's just a lot more skewed than people intuit.

And so you can't really solve that at these very early stages by just saying, well, I'm going to pick those one in a hundred outcomes, but I'm going to do it.

One out of 10 or 20, we just feel.

One of the ways that I would maybe simplify the right side model, but it's probably unfair, but just for illustration purposes.

If you were to not know anything about a hundred assets that you might invest in in the next year or two, let's say, say three years, um, if you want, if you really thought it was a power law and one out of a hundred is going of these unknown assets are going to be really good picking a normal portfolio of 12 or 15.

Out of that would be foolish, right?

Like you sort of blindly grab 15 of the hundred and pray, hope, um, that they're positive

expectation investments still, but it's, they're really, it's really risky to have a portfolio,

right?

Right.

Well, that's what most people don't get.

Yeah.

Right.

So if you, if you lower the investment amount and get exposure to not 15, but.

100, then you have much more freedom of, um, opportunity.

You're going to be in whatever that is, six, seven times more assets.

And then you begin to, uh, make the law of large numbers move in your favor as opposed to against you.

Yeah, exactly.

And I mean, most people misinterpret what we're doing and sort of use the term, the derogatory term shotgun approach.

And that sort of implies you're just shooting and aiming at any and everything.

And you'll just take whatever you get.

And that's not true.

Like we're very picky and we say no to almost everything.

We look at most of the things we look at still.

So you can still have very selective, uh, sort of target investment criteria and profiles you're going after and build out ultra diversified portfolios.

So that, you know, we aim, we sort of do both of those and we've come up with this quantitative data driven way.

Yeah.

The other thing that I, uh, Bristle at is people talking about doing an index of all of the, you know, let me just grab, like you would in this public markets, I'm going to buy the S& P 500 and I'll get a broad collection that represents the overall market in venture.

That's a negative thing.

Cause the overall market's not going to return an appropriately risk adjusted return.

And so you don't want to just invest in.

Everything that comes across your desk, you have to be selective.

Yeah,

there's also a high bar to even just, a somewhat high bar to even just have become a public company in the first place.

So there's been a lot of narrowing and winnowing down of companies to get there.

Anyone can decide they want to go fundraise for a startup.

So you, you can't just say, I'm going to index everyone who just thinks they have an idea worth funding.

Yeah.

And then, um, part of what the magic at right side is, is you have focused on SaaS companies.

And maybe talk about that.

Um, I can guess about why but maybe you talk about why that niche Made sense.

Yeah, I think there's two or three reasons why we evolved to be very sass focused You know, we're not exclusively sass investors, but very heavily emphasis on that throughout our history Um, I think one is personally I knew the model well So my software company in the 2000s we pivoted a couple years in and had a we didn't even call ourselves I don't know the term sass was being thrown around then but we pivoted to a subscription Business model and part of our sort of the dna of right side capital in the early 2010s Was that the investor world as a whole still underappreciated how much stronger and bulletproof subscription business models were, whether relative to transactional ones.

You know, back at that point in time, companies with SaaS business models that were public weren't trading.

They were trading at slightly higher multiples than their transactional, transactional comparables, but nothing like today.

And so.

So that was one of our basic premises.

And then also it turns out that in the very early 2010s, it was cheaper to build a consumer product than a B2C company than a B2B company, because, you know, there were really huge headwinds selling into the enterprise space.

They were reluctant to buy from startups.

And if you could just get a tech crunch article written about your.

Consumer app or or startup, you got 30, 000 users overnight, you know, and as the 2010 sort of played out and the cost to build software products got less expensive.

The, the barrier and cost to build a B2B product actually became much cheaper than B2C because you could acquire customers by just doing the calls yourselves as founders and selling them.

And the cost to acquire initial users for a consumer startup became very expensive.

You didn't get 30, 000 by getting an article written about you anymore.

It

got much more crowded, much more noise.

Yeah.

So

I think it's a combination of sort of a realization of sort of an underappreciation of SaaS.

And so we felt they were mostly all undervalued.

In the early 2010s to us sort of being at the right place in the right time.

And that's really also just following the market.

You know, if the market had gone such that consumer became a lot less expensive and is more capital efficient to build consumer startups.

Maybe we would have actually almost certainly we would have had an emphasis on consumer, but because that was where the capital efficient trend went, we naturally became pretty heavily focused on B2B SAS.

And then that focus on the business model being not 100%, but a large portion of what you invest in is is B2B SaaS that then allows you to sort of take that data driven approach.

And you can use that, uh, business model to inform what metrics you're looking at, even if a company is in healthcare or gaming or fintech or, I mean, almost different industries, you get diversification across the industry, but that same business model, um, is that close?

Like some of the metrics you're asking sort of are tied.

The unit economics translate across industries and verticals a lot.

So, you know, I don't care who you're selling to.

If your price point is, once you start getting below 300 a month, it's really challenging to have a short enough sales cycle to sell.

I mean, even once you're under 500, it can be challenging, but you know, so if you're going to have a product and it's 149 a month product.

And you're planning on doing that with the sales force, your, your chances of success are really slim.

It's just hard to do and it doesn't matter what industry you're selling into.

So those are sort of true facts across that, that are true on B2B SaaS.

Yeah.

For where you're selling to.

And there's a lot of other examples.

So the, um, that makes sense.

The unit economics are really driven by.

The unit price and then some kind of how long is this is one customer going to last, which would be the lifetime value of that customer and that compared to the cost it takes to to get that new customer and there's a ratio there that needs to be the right right level.

But I think, you know, one of the things we've learned in the 2010s and in the early 2020s.

Sorry, is that, uh, you know, macro matters.

And we also were in an environment in the 2010s where there were a lot of tailwinds at the back of the SaaS business model.

And I think there were two main ones that were going on that people weren't aware of or didn't appreciate as much.

And I'd say we didn't.

You know, just like you don't realize you're in a bubble when you're in a bubble usually, um, and one of those that we did, we're aware of that was this transition in the psychology of enterprise customers in 2013 and 14, if you had a 3, 000 a month or a 5, 000 a month product that you were trying to sell to large enterprise and you were a startup.

Your sales cycle could be two years, like large enterprises, mid large enterprises did not engage with startups.

If someone bought your product, they felt like they could get fired if that product didn't work out and it was at risk.

And somewhere between there and the end of the 2010s.

There was a sea change and it became acceptable and mid to large size startups realize not as it only is it just acceptable, but the efficiency gains are enormous.

If we start using lots of SAS products and people realize they won't get fired, you know, they use one from a startup and that startup stops existing.

Like you can adjust to that and that presented major tailwinds and then the other tailwind that we didn't.

Weren't aware that was happening.

I think nobody was with, was the labor war that sort of broke out in the tech world from like the zero interest rate policy being around for so long.

So, you know, SAS was sold by seats and you had existing customer bases with.

You know, no recession happening for a decade.

So, and these labor wars, so the number of seats were growing.

So it was really easy to be a SAS business and just to have revenue go up continually, even from your existing customer base, they were gaining employees, which were seats and both those tailwinds turned around completely.

Post the valuation bubble popping in late 21, 2021, early 2022.

So I think that that purchasing tailwind still existed for much of 2022, like all of our portfolio companies for the most part hit their numbers.

And then in 2023.

Almost every company of ours missed their numbers because in 23 and 24 companies tightened their budgets when interest rates started rising and they said, Hmm, we're going to put a ban and any new costs on new projects and all of a sudden there was a headwind to selling to new customers that hadn't been there before.

And then in addition to that, you had this shedding of all these excess jobs, and you had a lot of startups going under that were laying off people and those are all seats.

And so you had both an elimination of the, the tailwinds became headwinds for selling new customers and your existing customers started shedding seats instead of gaining seats from laying off people.

And then that has funneled into companies shedding seats.

because of AI efficiency.

Right,

right.

So that trend is going to continue.

I

mean, just to connect it back to where we started, if you built a portfolio of 150, 200 assets, when you had those strong tailwinds, You might have gotten, uh, maybe another, another two or three really outsized winners in that 150.

Uh, not because you chose particularly differently, but, but all boats rose a little bit.

Yep.

Um, and now it's, it's a harder market.

You have to be more selective or more careful.

Uh, is that, is that Yeah,

that's very much true.

I think people didn't realize the extent to which not only did you have these, the two tail ones that I said, but you had also Rising valuation multiples, the whole 2010s.

So yeah, you could be mediocre and have good results, you know, uh, a true thing to say.

Yeah, we didn't, we should have covered this a bit, but you have, um, a lot of experience investing in SAS or, uh, businesses.

14 years, I think I wrote down over 2, 000 investments

across

eight different funds and over a thousand active portfolio companies today.

So you have a very wide perspective of how this entire SaaS market is evolving in a way that not many other people do really.

Yep.

I would say that's definitely.

Now, RightSide also has really worked hard at adding other things besides capital and support for your portfolio companies.

Maybe just talk about how you think about that and then some of the, some of the handholds or support pieces that you provide.

Yeah, and when we started investing in 2012, it was just the three founders, RightSide Capital, and there was, we were sort of limited in what we could do.

We all had a lot of entrepreneurial experience.

So we could help there.

But as the decade went on and we got larger and we had more budget, we started looking around and saying, all right, what are the areas where we thought, you know, we could impact the outcomes and returns of our investment the most and be most beneficial to our company.

So the first two things we highlighted were sales help.

Because most of what we're investing in are technical founders who aren't that experienced with the basic blocking and talking and tackling of selling.

So we brought in someone who's an experienced VP of sales, chief revenue officer to provide free sales help and support on all things sales related.

And then we thought fundraising was the next thing.

And we had always had later stage investors reaching out to us or paying us saying, Hey, you guys can be a great source of deal flow when you have such a large portfolio.

You can, you know, you only have so much time to connect the dots.

So we brought someone in who

I'm living that every day today.

Yeah.

So we decided we have a large enough portfolio that we have someone who's put a lot of structure and process behind that now.

And the large, largest part of what they do is exclusively building out our investor network, keeping track of what it is their current focus is on, because that focuses are on, because for any given investor that can change in any given six month period.

And then working with our companies that are raising at all different stages and helping connect them to the right sets of next round investors, whatever.

I would think it's a curation process for like, You want to get, uh, the right investor connected with the right portfolio company or several portfolio companies so that it matches up

completely.

Cause if we blast a company out to a list of 140 investors and it's not a good match, a, that doesn't do much for that company and B, then those investors start feeling that we're sort of, you know, so we do a lot of work to curate them and we get a lot of feedback from our later stage investors, whether they're a seed investor or a series B investor.

But hey, you know, the stuff we send them is almost always right in their wheelhouse and therefore our emails to them get opened with a higher rate because everyone's email boxes are, you know, filled to the rim these days.

And, uh, yeah, it helps our portfolio companies out a lot.

So, in addition to that, now we offer some, you know, marketing help and support.

We have monthly webinars.

But, you know, the two things we identified earliest on were, you know, you have to be able to sell and you have to be able to raise next rounds of funding.

Excellent.

Now, um, let's talk about healthcare.

You invest across industries.

The way we got together is you're interested in healthcare.

Maybe talk about your views of healthcare and how it compares maybe to other industries in a SaaS investing perspective.

Yeah, we are interested.

I think, you know, if you look at us historically, there's two areas that were slightly underweight.

Compared to, you know, the rest of the world and in the SAS world, and that's probably FinTech and healthcare because those are two areas that as it got cheaper to build products, you're still often selling into a regulated environment and longer sales cycles.

And so it's.

You know, it's, we were mostly investing since the late 2010s in companies that already have revenue, and it was hard to get to a point where we already have revenue, um, in those sectors, or it's harder.

So we have a little less exposure, but healthcare is attractive to us on many fronts.

One, it's just, we have an aging population.

It's going to be a growing sector, almost guaranteed for decades to come.

Number two, uh, it's got a unique dynamic in that there are acquirers that every size and every stage you grow to.

There are a lot of sort of verticals and sectors where you can outgrow your acquirers.

And, you know, maybe most of the acquisitions in that space happen at 50 to 150 million ranges.

But at healthcare, there's almost always buyers at every stage, whether it's other private companies, private equity firms, you know, there's a lot of large strategic buyers.

So that makes it attractive.

Yeah.

Okay.

Excellent.

And so, um, let's talk about Uh, I think you've referred to it as risk capital in the past, but like the amount of money it takes to go from like zero to one in a software business and how that's evolved from the 1990s through the 2000s to today, obviously everyone understands it's come down, but I don't know if, if people listening understand the extent to which it's come down.

So you've been in this market since.

I don't, I don't want to teach you exactly, but, but before 2000, and, um, you were building software businesses then.

So just give a frame of reference, uh, so that, uh, you know, a doctor or a healthcare person can understand how it, how it's evolved.

Yeah.

That's, I think that people can appreciate the change there as much.

I'll go through that.

Cause we're, I think we're both good, but we were also in the right place at the right time.

So if you go back to the.