Cloudflare, Inc. (NET) Earnings Call Transcript & Summary

All right. Good afternoon, and thank you for joining us at the Cloudflare session at the GS Communacopia & Technology Conference. I'm Gabriela Borges. I cover the emerging software vector here at Goldman. And I'm delighted to have on stage with me Thomas Seifert, CFO of Cloudflare. Thank you for your time.

Well, thanks for having me. Pleasure being here.

So Thomas, you said very consistently on joining Cloudflare. And looking at the architecture and continuing to be positively amazed by the amount of technology and the amount of functionality that the architecture can support. So I want to frame this question has a little bit of an R&D priorities question, which is there is so much TAM in the Wave 1, Wave 2 and Wave 3 products that the company can go after you'll have a reputation for being incredibly innovative at the leading edge. How do you think about R&D priorities in a way that allows you to maintain that innovation and also be focused on the options that can use the needle.

This into was the second time I've question today, I had it in 1 of the one-on-ones. And it's actually a very timely question because we're just about to kick off our planning session budget for next year and the next 3-year plan, actually what Phil and I did this morning before we came here. We're sitting down with Michelle working on the agenda for the next 2 days. I think the right answer is there is -- it's part -- part science and part is art to be very honest. So like every good company, we throw a lot of data science and methodology, the problem, your TAM analysis and all that good stuff. There's also a significant part of art to it at Cloudflare and that comes with our founder with Matthew to be very honest. The astonishing thing about Cloudflare is how little it pivoted over the last 11 years. If you think about it, it has been a story that continues to evolve, but it stayed true to its core of providing -- and help us to build a better Internet and everything around that, I mean, has evolved around a network architecture that is impressive. We might come to that in a minute. But Matthew seem to have a keen and deep understanding of what holds the Internet together from a technology and from a need perspective, we started to think about data compliance and data governance way ahead of before it became an issue and tried to build products around it, like our data localization suite. We talked about the importance of latency and you're minimizing the distance of the eyeballs that connect to the network and what that means in terms of the next wave of innovation. We got it actually wrong in the beginning. We thought it was all about speed and then it turned out to be data compliance and data governance, but it comes now full swing back when we talk about AI and the need of latency and being in this Goldilock between what can happen on the device and what can happen on the data center and we found [indiscernible]. So it's part art, and it's part science. But the surprising thing for me even after 6 years now is once we have a network that is architecture, the way the Cloudflare network is and distribute the way it is. And you have your unique software stack that allows you to run every product on the reserve and with that, the complete network surface becomes your decrease of freedom, how you manage cost, capacity, compute, storage, how you shift bandwidth across the planet is, I think, what is driving this to a very unique decree.

So you mentioned the 2024 leadership planning discussion.

Yes.

How would you compare and contrast the way you feel about -- the way you feel going into those planning discussions compared to this time last year? What do you think is different? What are your observations on what's changed the most?

That's an interesting question. The last couple of years were always exciting. So we, between COVID and post-pandemic and the macroeconomic issues. I think what stays at its core of all the discussions we had is the network and its innovation capability and how can we keep the flywheel of new products, new features and TAM expansion going. I think that has been consistent regardless of what are the distractions that happened around us. I think what evolves us is how we evolve the go-to-market. I remember when I joined in what since 2000 -- 6 years ago. So we truly got only our first enterprise customer in 2016, when [ Mitrani ] ran for President, paying capital truly became the first contracted customer, and that is not too long ago, if you think about today, this is where our revenue sits, and the largest customers are north of $20 million a year. So this evolution continues because even today, the largest customer is not buying all the products. So there's expansion. So the evolving and sophistication of the go-to-market is a theme that changes color from planning period to planning period that becomes a topic. How we instrument us has changed, and we are highly instrumented company today. So I can look literally into what is the margin on the product for a customer in a specific location. So how we instrument our -- the company in terms of understanding the levers to evolve it is driving -- is the driving theme. This year will be special because we are super excited about AI from a top line perspective, and that drives a lot of activity, but there's equal opportunity driving productivity within the company by deploying artificial intelligence to get more efficient. And I think this is -- that is a step-up in terms of difference of discussions for this year's budgeting and 3-year planning for us. What initiatives we are trying for, what projects we are focusing on.

Can you give us an example on the second piece of that, so using AI from a cost optimization or workflow automation.

We try to lead with examples. So this has been a topic of mine and a passion of mine for a very, very long time already way before I joined Cloudflare. So there's a lot of activities that we drive within the finance team across the company and how we look at contracts, automatic revenue recognition across -- we met with 2 companies that we are engaged with for the last 2 years already in that field. So a lot of work on the finance side, how we get to filings and disclosures faster, what we learn about how we script our earnings calls and the messaging. There's a lot of productivity in the go-to-market side. That is running a project. And then I think there's a significant opportunity putting efficiency in our engineering functions, how we code and how we get to a shippable code faster. So there is a joint project I run with our head of engineering, quiet a lot of opportunity and a lot of projects. It's -- we have to make sure that we pick the right ones and that we are not getting lost in too many and pick the ones that have the right leverage.

And is it fair to say that, I think about the comments that you've made before on Rule of 40 and solving for revenue growth plus profitability. And with all of the potential that you have on the cost side, is it fair to say that, that could be a story where you're solving for a Rule of 50, Rule of 60 over the medium term?

Well, I look at it from a productivity perspective, so we -- that helps us to lift significant profit productivity. And then we can decide how you deploy whatever you gain -- we're going to fall through the bottom line and how -- what do we reinvest. And as long as there is a an opportunity to grow at a significant rate. The best return on the dollar is making sure we continue to grow. But we also have a very -- we have a long-term model. We've committed to achieving north of 20% operating margin and north of 25% free cash flow margin. So we want to get there probably earlier on free cash flow than an operating margin, but this is the trade-off we are going to play. But in the first, the first step really is to the productivity potential we have. And that is significant, I think.

So I do want to spend time on the go-to-market, but before I do that, the implications for AI on the top line. One of the comments you've made is a small dollar opportunity today, but the potential is huge. And so how do you think about you've given the examples of customers using AI products, using Wave 1 products for AI use cases. You've given the examples of R2 for Wave 2. How should we think about that ramp in revenue tied to AI customers or Cloudflare customers using more AI in their workforce?

So how we ramp to revenue and that is always a little bit of a black box, do you have a step-up functions like this. I think what I learned to admire Cloudflare is. I remember it's also something I mentioned once already today. One of the -- my first interview with Matthew was really him helping me understand why this business model is so special. And me getting a deeper look into this uniqueness of how the hardware stack is architected, how software runs. And there was this comment he made and I said, Thomas, the real idea is never to discourage a bite of from going through the network. And once it moved to the network, we figure out a way to wrap value around it. And this is the whole idea of premium, right? That's why we have millions of free customers. It's not so much -- the idea will monetize it at some point in the future and get them to pay us dollars. It's the diversity of data and threat intelligence you harvest the long tail of the market you consolidate and then we take the data and negotiate, interesting co-location and bandwidth agreements with ISP. So AI is in a very similar banner. We do not want to discourage a bite of data or a model not to run on our network, and we'll figure out a way to monetize it moving forward. But really, the first inventive is to get as broad as possible from a use case and from an adoption perspective. And I think this is where we have made a significant amount of progress over the last couple of months. The idea that you have this network that found this Goldilocks on between data centers and devices and being right in the middle, a network that was never really designed to them to deliver content. It has to deliver content in order to get to high performance security and performance products. So we do so much compute already at the edge of our network today for inspection, decryption, encryption, compression, decompression of -- so there's so much compute performance on there. If you look at a product like our bot medication product. It's an AI product that has been running at the edge of an inference product that has been running at the edge of our network for a while. So we know what that means. The structure, the architecture of the network is destined to perform there. And now it's getting the use cases on the network, and then we'll find a way to monetize it. But coming back to how I started, never discourage a byte of data from moving through the network is the first step that we have to get right.

Have there been observations from either your customer base or your telecom partners on what the potential limitations of the networking inference that you have today could be? In other words, you're already talking about the amount of compute intensity that has to occur at the colocation zones. Is there a scenario where the step function of that changes in such a way that the network has to require more CapEx spend or requires a slightly different approach to investment to be able to take Cloudflare to the next level of compute processing, for example, for AI?

We don't think so. And Yes. This is 1 of the truly unique competitive moats, I think of the architecture is how it scales. So today, every server we add regardless of where we added in the world allows us to increase the efficiency of the network. It allows you to increase the service of the network and then you have more degrees of freedom, how you push compute and storage and bandwidth -- around the world. You might be in New York and Goldman Sachs is consuming too much of our capacity. So we offload free customers to the next site or our network is underutilized in Tokyo because people sleep, and we offload compute or storage tasks to the part of the network that is underutilized. We think how we scale AI on that network will not interfere with that. We keep the elasticity of the network. And it's literally every several we have today has a slot where you can plug in a cheap fuel card if you need to. So the scalability and the elasticity of the network is not changing with the workloads that we might be adding. And we think there is more opportunity for us in inference than there is in training. So that plays well into how the network is architecture today. So if you look at the simulations we have done in terms of CapEx needs moving forward, we think the efficiency -- and if you go back 4 years, our network CapEx ratio and the amount of dollars we spend in relationship to revenue has come down, has gone from the high teens to the very low teens. And we think that is going to continue to scale. We have no indication today that going to break, just the opposite. So it's 1 of the unique things about the network.

Well, there are 2 parts to the go-to-market that I want to spend time on. The first is, to your point, on winning your first enterprise customer back in 2016 and now the movement that you have up market. Talk to us about some of the progress that you're making with your new percent of revenue in being able to scale your enterprise go-to-market and particularly getting the synchronization right of iterating the product to be enterprise grade and making the decision maker -- or building relationships with the decision-makers of the enterprise simultaneously.

No, it's a journey. It's not like -- and that journey has already started to a certain degree before Mark came. I mean we were at the $1 billion run rate already when he came and but it needs to evolve. The customers are getting bigger in terms of ACV. They're getting more complex in terms of the products they buy. And this journey from what we call Act 1 to Act 2 to Act 3 requires that we also address, as you said, rightfully, different personas within customers. You have different responsible people for budgets. And we're also moving up the stack in terms of decision makers, especially in this world now where you have macroeconomic headwinds, people like my position becomes more important in the decision-making process of how dollars get allocated. So this is not only a matter of adjusting the sales motion, it's also a matter of how we adjust our messaging marketing and branding and campaign perspective. We made a change from the sales side that got a lot of attention, but we also upgraded our capabilities on the marketing side actually ahead of that already and Brent joined us from companies like AWS and FireEye before. And so we that needs in conjunction needs to move up. I think we have a very unique value proposition, especially when it comes to threat analytics. And what do we see and how do we interpret the world. We've made a big step forward in making use of the data we see through the acquisition of a company called Area in our product, we acquired a lot of threat intelligence skill set people who have been interpreting threat analytics and have been dealing with threats for a long time. So how we monetize and how we deploy threat analytics and our products and how we sell it even as a separate offering has increased. We published our first fishing report in this quarter. So this allows us to also retarget the personas that we need to get to in a very unique way. And I think it's part now also of the reason why our journey up the enterprise tech has been rather successful. So if you look at the pipeline today, there are probably more large deals in the pipeline than they ever were, and they are a result of this broader product portfolio, different go-to-market motion, talking to the right people and having more to talk about in a way, especially from a threat analytics perspective that has been helping.

And so it sounds like the threat analytics piece of this gives you more credibility with security buyers and large organizations. Is that a fair way to frame it?

I think it opens stores easier. You have a topic talk about. It started already last year when Russia invaded the Ukraine and the war started and the intelligence we saw what we saw on the ground that helped us to up-level messaging and has evolved from there. Yes.

Are there any other observations that you call out in terms of how the messaging is changing? We can certainly see some of it from the outside and but curious how you describe it.

I think it's more relevant. I think it's more acute to the needs. It addresses, it keeps in mind what their people we target need to talk about how can you up-level the information a CIO has at a customer when that CIO has to talk to his board and his constituency in terms of what messages he or she has to deliver.

As you've refined the messaging and as you've moved up market, I'm curious how you see Microsoft as a competitor, particularly given they are certainly talking more about AI use cases and introducing more secure service edge type products.

Yes. And I talked about SASE. Michael has been a big partner, a long partner valued partner. They were an investor in Cloudflare in the early phases. Them stepping into the SASE space gives credibility to a market. So that is a good thing for us. But it also is, at the same time, we took the serious and competitor, and we see the world a little bit different. One comes from the special play we have. So our place in the network that we operate this neutral ground being able to connect many clouds, I think, makes us -- gives us a very unique perspective. How we tie security and networking together is a very unique capability we have that we take full advantage from our first act product. protected the external facing infrastructure. Now the Act 2 products target the same on the internal facing properties of network. So how we tie things together puts us in a very unique perspective that I think allows us to compete really well. Again, everybody in that phase.

I'm curious if your sales people have seen a change in how customers think about Microsoft on the ground or if it's mostly just us from the outside and as an industry analyst?

I think it's too early to see any big changes. But if you look at -- I think it helps us to drive an even more differentiated messaging, if at all. This unique place you have of tying network and security together. What we see externally and internally facing this 1 control plane, the amount of threat intelligence that goes into the product sitting in front of enterprise customers, but a long, long tail of free customers. And some of these free customers are important people that journalists sit in interesting places of the world get attacked by nation sponsored, attack for or civil society organizations we sit in for pretty much all -- most of the election network in the United States. We had every election, presidential election campaign, A to C from Biden to Trump and anything in between. So we have a uniqueness about our networking and security comes together, that puts us in a good position to compete even against Microsoft.

One of the strategy pieces of this that I know you spent a lot of time on is how are we thoughtful on the packaging and bundling of the 50-plus products that sit within the Cloudflare warehouse. So would love to hear a little bit on what are your priorities today and how you think about solutions-based selling and organizing some of these products to make it easier for your sales folks to sell across new AIs cases as they come up market across security use cases? What are some of the things top of mind on the products and bundling side?

Well, you talked about the changes or changes are probably the wrong word. The dilution that needs to happen on the go-to-market side, bundling is a big part of it. And bundling is not a matter of bundling within 1 act. How do you bundle Zero Trust products, but how do we bundle across the different acts that I think is how do you use their application security products and the position we have and how do you bundle that within your offerings. That is where we spend a lot of time trying to understand and optimize that. How do you press that, how do you message this? What are the various bundles for various verticals? And how do you compensate? So bundling, how to bundle what systems we use in order to choose that how we price and how we compensate is probably 1 of the larger work streams that is active currently, and that's an important part for next year, getting that right.

When you get that right -- what do you think the implications are going to be for the unit economics of your business and net retention? Do you think we could see a step function change in trend as opposed to just a continuation of trend?

You're independent of bundling. We have done a really good job improving unit economics across the board. So we are really well instrumented when it comes to managing unit economics from an offering, from a revenue and from a cost perspective. I think the bigger opportunity -- the biggest opportunities are less on the unit economic side, is it going to help us accelerate our expansion metrics? Or how do we -- we -- when you have a customer that buys $20 million of product and that customer is not buying all the products you have, really ending the dynamics of getting that customer to expand in terms of speed opportunity, I think that is where the uplift is for us. So I would expect the biggest impact are -- is going to be in our D&R metrics. And that is where you should see improvement then moving forward, whether it's going to be step function wise, I don't know. I don't want to make that commitment, but 1 step at a time, but it will go up and expand for sure. Yes.

So I'll take the opportunity to ask you about the demand environment. The comments from the last earnings call talked about stability sentiment, no longer worsening, sales cycle is improving relative to 1Q. What do you think has changed over the last 3 to 4 months? And when you look at the underlying data that you use to forecast, any additional observations that you could share with us based on the last 2 months.

Yes. It's moving along. I cannot say that it improved in a material way. There are some pockets in the world, where things looking better and other -- their parts in Europe where things have not gone better, there are some parts in Europe, where it's deteriorating. So I think on average, it's just moving along. We are also in a very unique position. We've talked about this internally for a while. When you sell a product like an ERP system, the sales cycles are really, really long. You implement an ERP product 2 years, you put it on hold. It has significant implications from a customer perspective in terms of opportunity costs. Implementing a Cloudflare product goes really, really fast, right? So if you put your family blog post behind us, take 5 minutes, if Goldman comes and says we need to onboard our complete network infrastructure that takes a couple of hours. So putting us on hold and restarting us is -- goes rather quickly, and that's why we think we see changes in macro environments faster than others because putting a Cloudflare project on hold, the opportunity costs are not high, right? You Can decide tomorrow to restart and then you are done here a couple of hours later. That's why we think -- we see -- we saw this earlier, and we are probably experiencing changes in sales cycles more directly and more immediately than other, right? That is at least our interpretation of the data. But from a macro perspective, across everything we did, we have not seen significant changes neither to the worst, but not to the better in the third quarter.

You detailed some of the pockets of weakness. What are some of the pockets of strength?

Parts of Asia, Australia, New Zealand, Japan, South Korea are running well and North America has stabilized good momentum in Middle America, I would say, in pockets of South America, Europe, not so much.

How about if you were to cut the data from a large versus small or vertical or product standpoint?

For us not much difference from a vertical perspective. There is no vertical that is exceptionally strong or exceptionally weak. More difficult expansion with larger customers, easier on new logos, right, regardless of size. Yes.

Let me pull it and go to the audience.

[indiscernible]. Can you talk a little bit about how Act 3 right, will play into -- how Act 3 will play into some of these questions in terms of will it make the upsell, land and expand will have potentially less friction in the process for your sales force? Is it a bigger learning leap for them and therefore, there'll be a productivity issue. It will be an easier sale for certain verticals than others? How should we sort of expect this to look? How do you -- and how do you hope that it should look as we get further in that Act 2 and Act 3 journey.

So it's exciting from an opportunity perspective because the potential lever is really high, especially if you look at the combination of everything we talked about from an AI workload perspective, the combination of storage at the edge in order to run inference products is crucial. So we think the -- there are certain things that have been in flight for a while. And now they seem to come together really well for certain use cases. And I think AI is going to be 1 of the use cases that will demonstrate more than anything else that befits of this network and where we decide. And in that conjunction, the interplay of compute and storage performance and workers as a tool to deploy code at the edge of our network is going to shine. And I'm not going to -- I don't want to lean in too much today, but those of you who have been following us for a while and know that birthday week is coming up that we -- every -- in 2 weeks, we celebrate our 12th birthday now. And that is normally a period where we just tried to overwhelm everybody with new product launches and features. And I think that it will be all centered around. So moving forward, I think it will be a tailwind for the Act 3 products to be very honest. From a use case perspective, we will be very hesitant to commit dollars behind it. As I said before, the unique thing about us is that we think about the value of the byte in terms of what it can deliver from a nonmonetary perspective first before we think about monetization. But I think it will shine with the new workloads.

There is a little bit of a discussion at the Analyst Day about periods of time in Cloudflare's history where you focus more on new product introductions versus periods of time where you focus more on taking the existing product set and leveling it up? Help us understand how 2024 fits relative to that cadence, given all of your comments on the new products coming out of the pipeline, the AI-driven use cases, et cetera.

COVID was a good example of that, where there was 1 idea, we were still pushing it, but we took the foot of the accelerating way. We're pushing the network even further to say we are in locations today in some cities, we are in multiple locations, let's get into building, that was -- and then COVID came in, nobody wanted to be in buildings anymore so we decelerated for a while. I think '24 looks like it will be a product innovation year. There is so much excitement around some of the things that are in the pipeline and AI is 1 of them. I would -- I am -- if I see how the -- in preparation of this budgeting and 3-year planning period, there is the bottom-up approach of who needs money for what and what are all the ideas and where's the competition come from for this $1 that we have to spend, there's a lot of excitement in terms of new products and features. So I think '24 will be 1 of those years.

Is there a scenario where given your comments on the initial phase is not focused on monetization. It's focused on adoption and engagement and technology innovation. Is there a scenario where the pace of investment goes up and margins go down before revenue growth is followed?

No, I think that is exactly why we push adoption first. This allows us to learn we talked about a lot of the benefits of the business model. One benefit we have not been talking about is that because we see so much data and use cases, we're always -- we've always been in a position to invest behind demand and not ahead of it, right? So you -- with the use cases and the early adoption of technology, we get a good feeling for what we might need and we are not in a position where we need to buy a 1,000 GPU cards hoping that they would find capacity. So we are pushing our current infrastructure to the limit in terms of what it can digest. And then we learn of where we might need to rebalance the network or not. This is true for the network and the capacity regardless of when we started with storage and R2 was the same topic. We pushed the current network to the limit. We found a way to offload peak demand. And once you have thousands of use cases, you have a really good understanding of where the need is going to -- how the need is going to play out and you invest behind the demand curve. On the GPU side, we'll follow a very similar model and we have been following it for the last 12 months already. And you have to keep in mind, this is 1 really interesting interview with Matthew, we said -- we -- when it get started, we talked about us being an AI company, and I started talking about AI because everybody rolled his eyes and I learned this is not a good thing. We've been running our own inference models at BHF our network for 12 years, and maybe it was more about machine learning than generative AI. But we really understand well what it takes to run inference models at the edge of our network. So the amount of skills we have in-house the network without coming in a situation where we have to overinvest or invest ahead of a demand that might or might not appear.

Excellent. Thomas, thank you for your time. We'll leave it there.

Always a pleasure. Thank you, Gabriela.