Battery Ventures "State of the OpenCloud 2023" Report - Part 1

Live from Schenectady, New York, it's SaaS Talk with the Metrics Brothers, Growth and CAC.

And I'm Growth, better known as Ray Reich, founder and CEO of Benchmarket.

And I'm CAC, better known as Dave Kellogg, independent consultant, EIR at Balderton Capital, and author of Kellogg.

And together we are the Metrix Brothers.

And quite a pair at that. Now, Brother Ray, I did notice, given that I am CAC, I did notice that you were kind of channeling your inner CAC persona on a recent LinkedIn post. What's up with that?

Well, first of all, I'm really excited that you're reading my LinkedIn post. But second, come on, Dave, you know that younger brothers like me are always trying to be more like their older brother, my CAC brother.

Hold on there, Brother Ray. I know imitation's a form of flattery, but you may be taking this too far. You got to stay in your growth swim lane.

Well, I think it might be a good time to pivot out of this conversation because the topic for today sure doesn't highlight growth as something we are in the middle of right now. And specifically, this report highlights a lack of growth because it's one of the key components of the recent Battery Ventures State of the Open Cloud report. You good with that one, Dave?

I am good with this one, Ray. And this report kind of slipped in under radar, I think, because there have been a lot of good reports published lately. And this one came out in early November. The blog post about it was on November 9th. And I think it's a great blog post and more importantly, a great 48-page report for us to review.

Okay, then I say let's get right into the report. Let's go. The Metrics Brothers is proudly sponsored by BenchmarkIt, the B2B AI and software industry's largest, broadest, and most contextualized benchmarking index. Dave Kellogg and Ray Grothe write, have put the Metrics Brothers podcast on hiatus for the remainder of 2026. All episodes we have ever recorded are still available on your favorite podcasting app. You can reach Dave at Kellogg and Ray on LinkedIn at Ray Reich. Thank you so much for listening to the Metrics Brothers podcast.

Cool. So look, the blog post that comes with the report, asks a very interesting question at the beginning. It says, and I read from the post, what if the new, more challenging macroeconomic environment coupled with powerful new technologies like AI means that we should rethink the metrics we've gotten used to and encourage companies to reevaluate the right set of benchmarks to survive and thrive? It's a really big question. It's a really interesting question. This report doesn't fully answer it in my mind, but it certainly starts to touch on the answer. I look forward to going through this one with you.

Well, you know, I know that other kind of thought leaders in the industry have been talking about the need to develop a new SaaS Metrics Playbook 2.0. And I think we just need to refine some of the metrics we have. So let's get into it and see what we think after we see this Battery report. So you wanted to highlight the first page that jumped out at you?

Sure. And just to help the readers, the formal name of the report, if you're Googling for it, is Battery Ventures Open Cloud, one word, Report 2023. And that's the document we'll be discussing today. Again, this has been a bit of a sleeper in my mind because OpenView and others have put out big reports lately. And this one kind of snuck in under the radar. They also put out a pricing report in September. But this is the Open Cloud Report. And it starts with a bang here. We're going to refer to PDF page numbers. Actually, you know what? I'm going to refer to their slide number, the bottom left corner, the blue number, not the PDF page number on slide 5. We see that growth is being reset and boy, is it cold out there. It shows in the period, basically in the 2021 period, mostly 2021, net new ARR growth, which is an interesting metric, not one we talk about a lot, Ray, runs in the 50% range. And then as we kind of hit the wall in Q2 '22, it drops to 37%, then to 19%. And then by Q4 '22, so all of the past year, it's gone negative. The growth rate in net new ARR is shrinking and shrinking fast. By Q3, it's down to 25%.

Well, you know, as I was looking at this report, what really jumped out at me was their estimate for Q3 '23 and Q4 '23. I thought the worst was behind us, Dave, but if you look at this slide 5, 24% decrease in net new ARR in Q3. That, number one, it blew me away that they're predicting that dire of reduction in growth rates. But then they coupled that with their Tech Spend Research Report they put out about 3 months ago. And it said that 56% of CIOs out there are going to be even more conservative in their tech spend next year than they were this year. So I'm just wondering what '24 portends for us.

Yeah, and I just wanna be clear. So look, I do translate this chart to saying, you know, kind of baby, it's cold out. But let's just be very clear on what the metric is. It's not ending ARR. We're not saying that ending ARR is shrinking. That would be catastrophic, I would argue. We're talking about the net new ARR, and we're talking about the growth rate of net new ARR. So it's kind of a second derivative sort of metric, right? And that has come down. So basically in plain English, in Q3, if this forecast is correct, SaaS companies will add 25% less new ARR to the bucket than the net new ARR to the bucket than they did a year ago. So it's the deceleration in growth of the add.

And I just want to clearly define what net new ARR is. That's new ARR plus expansion ARR minus downsell minus churn, right, Dave?

Yeah, I do a slightly different taxonomy, but yeah, I just say it's new. I say it's net new ARR to me is new ARR minus churn ARR. And both of those have 2 subflavors, right? New ARR comes from 2 places, from new customers and existing customers. And churn comes from 2 places, from shrinking customers and lost customers. But yes, we're saying the same thing.

Okay. You know, we always try to make these episodes 20 minutes. I think there might be a reason today where we might have to go into a second half of this episode. So let's keep moving though, okay?

Yep, let's do it. I know you felt the whole time we're gonna need 2 episodes, and I think you're right. So let's take our time. And do justice to the material.

Why don't you take— because this is a slide you picked out. Why don't you take a shot here at slide 6 in the report, page 7 in the report?

Got it. So, so, so page versus slide. So page is the PDF page number. Slide number is the number in blue at the bottom left, just for those following along in their HEM books. This chart basically shows that the market is going to platforms. And I think it's true. I think you have to be careful about interpreting too much from this data. By the way, the data itself is interesting. So they're measuring platformization at Datadog by the percent of customers using more than 2 and more than 4 products. So an interesting metric, not uncommon in a multi-product company. For CrowdStrike, they're looking at it by basically how product additions and acquisitions have increased their TAM. And then for Palo Alto Networks, they're looking at the number of new product releases per year. So 3 interesting metrics to kind of measure How companies are going multi-product. I do believe there's a trend in the industry towards platformization. For example, if you looked at Gong's category, conversation intelligence, you have a number of vendors all kind of converging together. Gong, Clari, ZoomInfo, all trying to say, hey, we can do conversations and we can do forecasting and we can do data. So we try to bring together those 3 categories. I think there's even a 4th one. So, we're seeing this platformization. Obviously, that means, look, for vendors, it means one of two things. Either you need to be a leader and play in that market, or you need to be truly best of breed in one of the submarkets, but there's kind of no middle ground.

You know, the thing that jumps out at me, because I love trying to convert data insights into strategy, but I've been doing some research here on multi-product portfolio companies and how that impacts both retention and expansion. And I think Datadog is a perfect story of this because They have very high NRR. I think they're still on the 130 to 140%. But Dave, you know what really jumped out at me on this slide was the CrowdStrike thing that you highlighted. They showed their initial TAM was about $22 billion, and by all the additional products they've introduced over the last few years, they actually did more than tripling of their TAM. So that inherently is going to provide them amazing expansion and growth opportunities because they got 3 times the market to go after.

Absolutely, Ray. And back to your point on Datadog, yeah, I think one of the better ways to drive NRR is being multi-product, right? Because in the absence of being multi-product, you're basically just increasing price on what you're selling today, either because you're increasing prices on it or you've got a usage-based model and usage is going up. But if you really want to drive over time sustained NRR, it's very helpful to build out a product platform as Datadog is doing. And this is a great way to measure the success of that strategy. Or I should say major if I want to sound like Ray.

Yeah, well, this Midwestern in me, we're never going to be able to beat it out of me, Dave. But hey, what's the next slide you want to cover?

So slide 7 has some interesting stuff. As a former operator, they do the average GAAP EBIT margin expansion chart where they show that in '21, the average EBIT margin was 21% negative, and in '23, it's 10% negative. So an 11% improvement. And the thing I find interesting about this is that 9 of those 11 points are coming from, well, sales and marketing and G&A, but actually 6 of those points are coming from sales and marketing and G&A are contributing to 9 of those points. So, IER&D is bearing very little pain, 1%, and COGS, relatively little pain, 2%. But the improvements, sales and marketing getting squeezed, G&A is getting squeezed, in this desire to drive up EBIT and/or free cash flow.

Yeah, well, as another former operator, and I was on the revenue side of the house, this scared the hell out of me because I see the, you know, 5%, uh, which is by far the largest contributor to increase EBITDA, is from sales and marketing. And we're going to hit a couple slides going back that we're going to be reducing sales and marketing as a percentage of revenue by significant amounts. So Headcount reductions are coming, my friend.

Yeah. And look, the only good news is growth targets are coming down, or certainly growth is coming down. So it's not like we're holding the growth rates and cutting. Growth has come down. If you look on the left side of this chart from, you know, I don't know, I want to say high 20s. No, well, not high 20s, but 22 maybe at a peak down to 15. So growth has been cut by a third while we are whacking away at the sales and marketing budgets as well. The most interesting part to me is that R&D escaped effectively unscathed.

I know, but we're going to talk a little bit about that too, because I think AI is going to dramatically increase the productivity of the R&D group. And maybe that's just they have more releases with less bugs and it means less engineers. But that's a— that's another slide, Dave. You want to go to the next one?

Sure. So slide 8, page 9 in the PDF, the market is rewarding efficiency. This slide discusses the premium for being Rule of 40 compliant. And there's a lot of different ways to analyze Rule of 40. I happen to like this one a lot because it's simple. And they basically just say, what is presumably the median multiple for enterprise value divided by next year's revenues? And they split it into companies that are not Rule of 40 compliant, i.e., that have a Rule of 40 score less than 40, and companies that are Rule of 40 compliant, i.e., companies that have a Rule of 40 score greater than 40. And I don't know if they're using the standard formula, which is ARR growth plus free cash flow. We can come back to the Rule of 40 definition. might be revenue plus free cash flow. But in any case, the point of the slide is that you get a 50% to 60% value today. You get a 63% valuation premium, i.e., the average Rule of 40 compliant company is trading at 9x forward revenues, and the average non-compliant Rule of 40 company is trading at 5.5x. So there's quite a premium here. You know, if you want your SaaS company to be worth approaching 10x revenues, you better be Rule of 40 compliant. Otherwise, you're probably worth more like 5.

Yeah, I love that. Then on the right-hand side of that, you know, I love the R-squared. It's kind of a coefficient, a determinant coefficient, or linear regression model, whatever you want to call it. But what's interesting there is how the Rule of 40 is correlated to revenue multiples, enterprise value to next 12 months revenue multiples. And Dave, in 2021, The Rule of 40 only had like a 0.01, and it's from 0 to 1, right? In '22, it went up to a 0.33 correlation or R-squared factor, which is right beneath the growth of 0.35. And in this year right now, it's up to 0.35. So to me, it looks like the number 2 factor in enterprise value to next 12-month revenue multiples.

Yeah, I mean, look, it's explaining— the way I think of R-squared is how much of, uh, the variance does it explain. between the dependent and the independent variable in a kind of least squared fit. And the answer here is explaining 35%. So that's a pretty large percentage to be explaining. So yeah, I like R squared too, formerly known as the coefficient of determination. And it's telling you how much of the— sorry, of the independent variable is explained by the dependent variable. And 0.35 is a pretty high score, i.e., it matters a lot to valuation in plain English.

Not only is he my older brother, he's also my stats professor. Thank you very much.

Happy to help.

Okay. Now this, this particular slide, you love this. To me, it was an eye chart. So why don't you start with, I guess you would call it slide number 10 here?

So yeah. So slide 10 is a battery chart that they've used before. And it basically shows kind of the size funnel or really a valuation funnel of software companies. And they break them into 3 buckets. One, global private software unicorns, i.e., unicorns, i.e., private unicorns. are on the left. And then in the middle, we saw the bucket is software IPOs, and on the right, it's public software companies. And the idea is that, look, if you're sitting there on the left as a private unicorn, one day you want to be there on the right. So what's that funnel look like? And there's almost 2 funnels on this chart. One is segmenting vertically by size. The other is, as you move across, what are these conversion rates, right? And for example, in the $3 billion-plus valuation, There's 115 private companies. There's currently 46 software IPOs, not currently, but in the past decade, 46 IPOs happened in that bucket. And today there are 56 public companies in that bucket. If you look, however, at the $1 billion to $3 billion bucket, or the billion-dollar-plus bucket, I should call it, because it's more of a funnel, there are 1,000 companies in it. And there have been only 95 IPOs and only 74 public companies. So, I'm not doing the best job explaining this, Ray, but what it says to me is there's a whole ton of private companies that think they're worth $1 billion, and a lot of them are going to find out they're not. And I can explain why in a minute, but before we do that, let's get your reaction to this chart as well.

Well, number one, it's interesting that they called out that $1 billion in ARR is the new $100 million. So scale matters more now than ever before. The other thing that jumped out at me, and by the way, I told you before we started today's episode, this is probably my favorite report I've read this year. But when I looked into the global private software unicorns, the other thing I noticed was some of those are based upon the last round. A simple example is Gong, which was $6 billion plus in their latest round. That's not the current value. So what's gonna be really interesting to me, Dave, is to see what the conversion rate is over the next 2 to 3 years from the left-hand side funnel, private company unicorns, to software IPOs. I think that conversion rate is going to go down, my friend.

Yeah, so, so a couple more things on this slide, Ray. So, so first, I, I think the $1 billion is the new $100 million is a little bit overstated, as you mentioned. Look, back in the day, for those with long memories, when I worked at Business Objects, we went public in 1995 off Guess how much revenue, Ray? Want to guess what it took in 1995?

Um, between $70 and $100 million.

$30 million.

$30 million.

We went public at $30 million. $30 million growing to $50 million or $30 million growing to $60 million. So we had high growth rate. But yeah, you could go public at a very small size back in the day. Then in more recent times, in the 2010s plus, I always felt like the bar was around $200 million. I think the bar has crept up to $300 million plus. I don't think it's a billion. I don't think you need a billion dollars in ARR to go public. In fact, the most recent IPO, Klaviyo, went out closer to half a billion than a billion. But the bar is high. It takes a long time to build a $300 billion company. So that's the first thing. The second thing in this chart, and this could be a long rant, is that I've always hated the notion of unicorn because I don't like talking about private companies by valuation, which is a very venture investor viewpoint. I like talking to them about revenue, like a very operator viewpoint. And the danger in talking about valuation— there's a ton of them, but, but the single biggest one in my mind is that you're basically taking the price of the most recent preferred shared round, multiplying that price by the sum of all the preferred and all the common shares. And that's just bad math, right? It's kind of saying, well, if the company went public, the preferred would convert to common, which it would. And then that would be valid math. But if this company does not go public and, you know, say it only sells for $500 million, the common in many cases will get zero, right? Because the preferred has preferences. That's why it's called preferred. For example, they'll have a liquidation preference. They may have a participating preferred preference where they get their money back, plus then participate in splitting up the leftovers. So there's a lot of various so-called structure that really invalidates this notion That in my mind invalidates the very notion of unicorn, which is you should not— and everyone does it, but you should not do it in my opinion— take the, you know, the total number of shares that mix preferred and common and then go multiply that by the preferred share price. Um, and that in my opinion is why we have so many kind of faux unicorns, because they're not really unicorns. Um, it's kind of a math trick.

Well, to be honest, unicorns don't really exist, Dave, just so you know.

Well, that was the whole idea. By the way, that's a hilarious point, Ray. When the phrase was coined or the term was coined, the point was they were supposed to be rare. That, oh my God, there's a billion-dollar private company, billion-dollar valuation private company. That never happens. And then boom, thanks to increasing the IPO bar basically, and then the ZIRP environment, which drove valuations up, now all of a sudden we got 1,000 companies that think they're worth a billion dollars. And, uh, a lot of these people are going to have to dig out of what I might call valuation hangovers.

Now, Dave, I can't think of a better way to end the first half of this topic because we're going to do a second episode. So go and listen to the second episode right after that. But when my metrics brother CAC tells me that's a good point and you laugh, my day has been made. So thank you for doing this first half of the episode, and I'll see you in just a couple minutes to do the second half.

Yeah, I'll see you for part 2. Thanks for joining. The Metrics Brothers: AI, SaaS, and More is a production of The Metrics Brothers Growth and CAC and a member of the Benchmarket Podcast Network. By accessing this podcast, you acknowledge that The Metrics Brothers make no warranty, guarantee, or representation as to the accuracy or sufficiency of the information provided or the humor content of the jokes told. Ray, information, opinions, and recommendations presented are, according to our spouses, probably wrong and provided for information purposes only. This podcast should not be considered professional or for that matter, unprofessional advice. We disclaim any and all liability for any direct, indirect, indirect, misdirect, incidental, special, ordinary, consequential, inconsequential, or other damages arising out of any use of, or God help you, reliance upon the information presented here. Ray Grothreich is based in New York City and available on X @rayreich. Dave Kellogg is based in Silicon Valley and available on X @kakellogg. Kellogg. Schedectity, which is French for unspellable, is not our actual production location. Thanks for listening.