ZoomInfo Technologies Inc. (GTM) Earnings Call Transcript & Summary

It's on now, Thank you. Thank you very much, Henry and Graham, welcome back to Goldman Sachs Communacopia and Technology Conference. I think last year, you guys were the last presentation. You closed out the conference, this time you got second of the conference. And it's been action-packed, to say the least, so far. We're just halfway through the conference. Our registration stats are up, we're not a tech company, but we're up like 4%, 5%. We exceeded 3,000 registrations, client activity, enthusiasm for digging into AI themes, very, very, very strong. We've had record number of requests from meetings that sort of things. So thank you for -- it's not possible without content. So thank you for being part of the content and presenting yourself here.

Thank you for having us.

Yes. Absolutely. Henry welcome back. And congrats to you, Graham, officially, I think I was making the call last time that we were all together and saying, he did a good job, maybe you should be CFO.

Thank you, Kash.

Yes. Appreciate it.

I ask you the same question, Henry. And the answer, probably it will be dynamic because the environment has changed. Where do you see ZoomInfo at 5 years from now? I'm sure that has changed if I answered the question probably 3, 4 years ago as we did, I think in 2022, 2023, 2024, 2025, where do you see the company?

So thank you, you asked me this question last year, and I didn't take the bait because we were in the process of changing a bunch of things and re-working a bunch of things, and I thought it was more useful to tell people what I was going to do over the next 6 to 12 months. But this time, I will. In 5 years, I believe ZoomInfo will be synonymous with AI and go to market. And that means a lot of different things. But what I expect is we changed our ticker earlier this year from ZI to GTM. And we expect that the products that we're building today and delivering to our customers and our data asset will become synonymous to building AI and go to market. Between now and then, we expect to accelerate revenue growth, expand our margin and continue to be big buyers of our own stock particularly when they're at prices that are below our intrinsic value like now. But that's how we think about the future, how will we deliver AI to go to market and how do we become synonymous with if I'm going to build AI and go-to-market, ZoomInfo is a necessary component to that.

That's the vision 5 years from now. We're definitely seeing an evolution of the story as we speak in the past few quarters. Definitely, the product strategy has changed. The business model is looking to change. You're a year into the new business model, I mean you're on part of your business model, the upmarket motion is trending very nicely for you guys, Copilot is ramping quite well. What are the primary initiatives to continue to -- that will continue helping drive the growth momentum that you've seen operate in the last couple of quarters?

Yes. So there's a couple of sort of key things. One, like you mentioned, we've really shifted the focus of the business upmarket. Today, the upmarket component of our business is 72%. It's growing 4% a year, and accelerating the down market portion of our business. We're driving more self-service, more PLG, more AI-driven service components down there to reduce the cost to serve and the cost to acquire. When we think about the growth algorithm, there are a number of things that we're focused on. I think the first one is just data. Our proprietary data asset is a necessary component to any AI-driven initiative that touches go-to-market. And you see that in our OS Operations numbers, which are growing 20% year-over-year. What we're seeing there is customers coming to us and saying, particularly in the highest end of the enterprise today, customers coming to us and saying, "We're building AI for our Go-To-Market teams but the universe of data that we have inside of our CRM is not going to be enough for us to be able to properly deliver the insights and the automation that we need for our sellers, for our marketers, for account managers."

And what is it Henry -- so what is the [indiscernible] of missing that you were able to feather?

Yes. So first, if you go -- there are so many things. If you go into your CRM data today, it is a static representation of whatever your seller decided to put in the CRM system. And so what you see today is a lot of AI solutions that are getting momentum where they rely solely on first-party data to support use cases, chat use cases where I can put in my knowledge base, I can put in my past support tickets and my interactions with customers. And AI will do a better job of answering the next incoming question, from a customer than a human support agent. In Go-To-Market, my first-party data in my CRM system doesn't have all of my buyers. It doesn't have my entire total addressable market. The data that it does have is static. It's not being updated. It's not being enriched. And if you just look across this room or in the conference, there's a large percentage of people who are in seat, at new jobs, at new companies that weren't in seat at those jobs a year ago or 6 months ago, that change doesn't get automatically reflected inside of the CRM system. And so the CRM system is out of date. At the company level, companies are growing. They're shrinking. They're doing M&A. None of that gets automatically reflected in the CRM. But let's just pretend in a universe that the CRM did have perfect data on what was in there. There's a whole universe of things happening outside of the CRM that are critical for a seller or account manager, a marketer to know in order to architect and automate the Go-To-Market motion using AI. So for example, company's earnings calls. The company has an earnings call and said it's growing in Latin America or it just did a risk. That's an important statistic or important knowledge to know before I go engage the company for an upsell or renewal motion. Company visits your website, research as a competitor, research is another solution, hires a new CEO, mentioned something on a podcast that's relevant to your business, all of that context, doesn't live inside of your CRM and is necessary for a go-to-market AI motion. And so what you have to be able to bring together is your first-party data. The CRM data is necessary. And it needs to be married to third-party data that give sellers and marketers and account managers, a view of the world that doesn't exist exclusively inside of the CRM system. So how do you do that? I think, first, if I go inside of any enterprise CRM today and I go look up the company Cisco, I'll probably get 17 different records of Cisco. There's a Cisco opportunity, a Cisco new business, a Cisco trial, when you're trying to build automation around when should I engage with Cisco, what should I say, who are the important people. I need 1 record of Cisco. And 1 of the core engines inside of ZoomInfo is the ability to take data from a large contributory network of hundreds of thousands of users, a contributory network of tens of thousands of customers sharing CRM, marketing automation, sales automation data then a variety of data acquisition sources of data that we're acquiring and bring that together to publish on 1 Cisco with all of that information. And so in Go-To-Market Studio, what we brought together is the unified go-to-market data warehouse that brings in that first-party data, your CRM, your calls, your e-mails, your transcripts, brings it all together and marries it to ZoomInfo to create effectively a virtual CRM layer, that's self-reinforcing, self-healing, self refreshing, so that sellers, marketers, go-to-market professionals now have that foundation that they can start building AI automation and agents on top of -- effectively...

That data warehouse, how long you've been building this data layer?

Last 2.5 years. And the key around that data layer is it's go-to-market...

This is not the old ZoomInfo database. It's like CRM interaction data with...

With [ ontology ] , that's AI specific that understands go-to-market, understands when there's an account and an opportunity. Those are still 1 entity. That understands the go-to-market nomenclature and then can bring that all together in 1 place.

Tell us more about it, because on earnings conference calls, we don't have the latitude to go to these kinds of elaborations, but tell us how you built it? And how you used AI to -- Mark's going to be on stage in about an hour, we're going to be talking about is how they build the data cloud, how they used AI agents on top, practically become -- and [ Eric ] is going to be here on stage exactly the same stage in about 30 minutes. So we're going to be getting into this and tell us how you built this layer, and how defensible is the technology that you use?

Yes. So first, let me just take you through the journey over the last 3 years, we've rebuilt our product organization. We've rebuilt our engineering organization, we've embedded AI throughout that organization. So the way a product gets built today actually starts with an AI written PRD that gets passed through engineering, engineering is leveraging technology to drive velocity in the way that they're building. But we have a data layer, a post-gres data layer at the core of this. The data from a customer CRM data comes in. We use that technology from a matching and enrichment perspective to marry that to ZoomInfo data, and then that builds the layer that then the go-to-market practitioner can build on top of. And I'll give you just like an example here, when we talk about sort of architecting a go-to-market motion. If I'm a customer, let's say, I sell to roofing contractors, I need a database that gives me all of the roofing contractors in the U.S. I have that from ZoomInfo. I bring in my data, so I know which of those roofing contractors I'm doing business with. And then on top of that, I want to architect something. And so I want to say, "Hey, I want to look at every single time somebody from 1 of these roofing contractors come to my website or hires a new CFO or adds a vehicle to their fleet, I want to do something in an automated way. Sometimes, I want to send that to a sales representative to take action. Sometimes, I want to just use an AI agent to send an e-mail or make a phone call or launch a marketing campaign. Once I have that data layer there, I can start architecting the signal that I want to take action on top of. And then you need to activate. And so that activation layer is where am I actually going to take the action. Am I going to have a sales rep work there? Am I going to have a marketing campaign automatically kick off? Or am I going to have a AI agent interact with the company. One of the things that we realized when we built Go-To-Market Studio is if you actually go out to marketers and sellers and you ask them in your account-based marketing campaigns, what are the top 10 ways that you activate those campaigns. This is a study by Gartner. The 5 of the 6 top ways they do it is with sales, with an SDR, with an account executive, with a seller doing some action. And Copilot has become the interface for sellers to take action. And so when they architect that go-to-market motion, they can push it into Copilot, where inside a Copilot a seller can start taking action against the architected plays. But that all starts with a data foundation that has to be robust and accurate and singular, and its entity matching. And we feel like we're incredibly well positioned to deliver that in the upmarket and throughout our customer base.

Got it. And the role of third-party foundation models in this layer, what would it be?

Yes, great question. I forgot to include that. In that same contractor example. One of the things that we're seeing customers really change their perspective on which historically, I would build out messaging based on like an industry and a persona type. So I would say, okay, if I'm contacting roofing contractors with over 5 vehicles in their fleet. I'm going to talk -- and it's the owner. I'm going to talk -- I'm going to send them through this track of e-mails that go out, or this track of calls that go out. And it would be industry and kind of persona specific, but there will be broad swaths. What customers want today is row-by-row personalization in their interaction with customers. And so when I have that data foundation, I have all the engagements I've had with those contractors, I know when they visited my website, I know what they said on calls, I know what they've said in e-mail, I now leverage the foundational model to say, row by row across every roofing contractor, take into consideration all of the engagements that we've had, all of the things you know about that company, everything Zoominfo knows, all the first-party data and write me row-by-row personalization from a messaging perspective per customer, create for me, the ads in a unique way row-by-row.

You can do this with a natural language?

You can do this with the prompt. Yes.

So that will -- the prompt will basically open up a connector through an API call into the Zoominfo -- Go-To-Market pilot and then produce the results.

And then it produces a line by line across that universe. You create the universe, you get the talk track row by row, using the foundational models or you could do other really interesting things, too. Sometimes there's a data attributes that doesn't exist inside of ZoomInfo, that's important to a client. For example, maybe I want to know I'm going to go outside of the roofing contractor example, but I want to know that a company is SOC 2 Type 2...

You must have known a roofing project.

We did have roofing project at the top of mind.

I did an HVAC project.

Also a great use case for us. But let's say, I want to know every company that's SOC 2 Type 2 compliant, I don't have that data asset that lives inside of ZoomInfo. We haven't cataloged it. I can use the model, the foundational models to go out, look at those rows of data and then tell -- bring in a data attribute. This is SOC2, this is not. This is, this is not. I've seen our customer say, "We really want to engage with customers that have very complex go-to-market model." So they have PLG and upmarket and downmarket, and they have multiple product SKUs. So go out, research the company and then give me a score of 1 to 10 based on the complexity of their go-to-market model and then use that in the messaging. And so now you have this universe of companies you're going to engage with, you can create new attributes using AI and then you could create row-by-row personalization that goes all the way to create a unique campaign asset, create for me a deck that I'm going to present at that company when I go to meet them, that's where we're leveraging AI throughout that.

This is a very different conversation than the 1 we had last year, and the 1 that we had 2 years ago. I mean, here you have incredible innovation, AI infusion into your product suite. Whereas in 2020 and 2021, which is growth was so easy to come by, but then we're working harder now and not getting the -- and it's not just ZoomInfo-specific issue. It's Salesforce too, Workday. It's all over the place. But what is your -- if you take a step back, we're working harder, innovating faster today. But the growth is not there in the industry. is it because -- an investor's take this, "Well, AI is taking over, blah, blah, blah, right?" Is it that? Or is it just that we overbought and the industry is just working through over consumption, is it just a matter of working with that cycle and then we're going to get back to something normal?

It is that we overbought and we're working through that cycle. Just last week, I went -- I had 2 customer calls back-to-back both of them, the first 1 has 27 go-to-market technologies that they bought. They have no idea what the things do. And so they have, this 1 and that 1, it does this little thing and that little thing and they're just begging us to help them rationalize that technology stack. The second call, I took exactly the same thing, we buy a little thing from them, and a little thing from them. There are numerous problems with situation that particularly software companies got themselves in by overbuying these technologies. The first 1 is, obviously, we're not using all of them. And then the second 1 is the promise of these technologies really was help me prioritize my next best action, who should I be prioritizing conversations with across my customer base? Well, when I have 27 tools, each 1 of them with siloed data about my customer, I get no overall view of the customer. I instead have a little bit here, a little bit there, a little bit here, a little bit there. And so 1 of our foundational premises around Go-To-Market Studio with that foundational layer is, let's consolidate all of that data in this 1 place from a -- with a go-to-market lens on it, so you can make sense of the interactions across your tool set instead of just -- historically, I would just use ZoomInfo. And there was an insight somewhere else, but I didn't know it. I didn't have visibility into it. And so one, we're trying to help people get value out of those tools. But still customers have a tremendous amount of go-to-market [ techs pool ] that they're trying to consolidate and a new leader comes in and they have a different vision for how they want to consolidate. They maybe push out 1 or 2 tools, they realize it's the wrong 1 or 2 tools, they bring back 1 or 2 tools, so we're still kind of fighting through the overbuying that happened.

Graham, how do you keep up with this guy. It's going 100 miles an hour.

I do my best.

And more serious question is, I guess you've got the inside rack on what the CFO job is because you've been prepping for it, now taking over the job function completely, what is the mandate?

Yes. The way I view this is the end of last year, maybe the first quarter or 2, this year was really a story of stabilization. And now we're going to go build on that stable foundation. I think our upmarket opportunity is increasingly evident, and we're set up to go continue to capture that. Beyond that, I want to be focused on optimizing our downmarket business, getting that to a place where it's a smaller and healthier version of itself. And then effectively managing the balance sheet. I think you can do all of those things, and we've been doing all those things for a couple of quarters now. We're going to get to a place where we have an opportunity to meaningfully reaccelerate revenue growth, expand margins, buy back shares and essentially create this compounding effect on free cash flow per share.

Well explained. What is the -- I guess, the trade-off is, I mean although up market is growing nicely, you don't want to lose the downmarket. So what is the trade-off between -- what is an acceptable level of growth you want in the downmarket versus the upmarket? And how important is that trade-off to your growth outlook.

Yes. I'll start with the upmarket. It's growing 4% right now. I think as we get into 2026 and 2027, we're really focused on getting the upmarket business to a place where it's growing high single digit, low double digit. I think we can get there just by getting growth in that segment to 100% -- sorry, retention in that segment to 100% plus, and we're pretty close to that already. Downmarket...

[indiscernible], right? Net expansion, right? That's net expansion?

Net retention, yes, net dollar retention. And then the downmarket business, I think we've been very cautious about not relying on that as a contributor to our near-term growth. It's more sensitive to macro and other trends. but it's still a really valuable business. We want those customers from a logo acquisition perspective. Some of them will graduate into being healthier upmarket customers with better LTV outlooks. As well as contributors to our data asset. So I think about the downmarket business right now is 28% of the total mix of our business and declining. The next milestone is let's get it to be about 25%, and then over the next few years, get it to 20% or 1/5 of our business. I think when we're at that point, it should be closer to 0% growth, maybe down 1 point or up 1 point in a given period. So it's less dilutive to overall growth. Downmarket business has lower margins by a pretty significant gap relative to our upmarket business. So we have this unique opportunity to shift our business up market to a place where there's better growth opportunity, better margin opportunity, but still be competitive in acquiring downmarket business.

And how do you delineatre upmarket versus downmarket? It seems like a binary thing, but I'm sure that there's a lot more gray, shades of gray.

Yes. It actually is pretty binary. Upmarket is what we traditionally referred to as our enterprise and our mid-market customer segments. So really, it's any customer of ours that has 100 or more employees. We define as upmarket and a customer with 99 or fewer employees, we define as downmarket.

100-plus that's not enterprise market. It's like upmarket, meaning?

Right.

And Henry, what is the biggest wins you have secured in recent times that give you conviction that this new AI strategy is indeed working. I know you talked about the roofing. But any other like a Fortune 1000 Global 2000...

Yes. We talked about on our last call, we closed our largest deal in the history of ZoomInfo.

Largest TCV, right?

Largest TCV deal in the history of -- largest ACV too?

No.

Close. Largest TCV deal in the history of ZoomInfo. And that deal was -- one of the things that we saw with Copilot was -- and this was a Copilot, almost wall-to-wall deal at the company. It also was our operations data into the company, also our marketing solution into the company. So it was a platform sale. And I think that the thing that we've seen and we saw there was when -- 1 of the things that happened from an overbuying perspective between 2020 and 2022, was customers have brought on account executives, account managers and CSMs onto the ZoomInfo platform. If you went across the user base and you talk to SDR, CSMs, AMs and AEs and you ask them, is Zoominfo indispensable to your day-to-day workflow? SDRs would have told you absolutely it's indispensable. And account managers and account executives and CSMs, they would tell you like, I use it here and there, but I wouldn't call it indispensable. And so what we realized was that it was critical to the future of ZoomInfo to get into the core workflow of account executives and account managers. And so when we rolled out the first version of Copilot, that our intention was that over time, this would be a solution that sat in the middle of an account executive and account manager workflow in the same way that it sits in the workflow of a sales development rep, and what we saw -- what we've seen now with our usage statistics on Copilot is now account executives and account managers have this levels of usage and Copilot as sales development reps. And so we feel really good that we built a mousetrap that gets into their workflow. And we're continuing to iterate on Copilot, there'll be a big launch later this month that add more adjusted technology into the platform that gives sellers a view over their territory. And we think we're going to continue to embed within account executives and account managers which is actually kind of an insane thought because today, there isn't a pane of glass that account executives and account managers work out of every day. They work a little bit in CRM, a little bit on the Internet, a little bit in ZoomInfo, a lot in Excel spreadsheet, that's where they track their renewal opportunities, their prospecting opportunities, a little bit in email. And so what we've endeavored to do with Copilot is to give them 1 interface that brings all of that together and allows them to ask questions of their territories, build decks and artifact, build an account plan, write back to CRM and so we're working really hard to build that pane of glass for account executives and account managers...

Is that live, that new agentic capability?

That new agentic capability is live.

And where is it used...

The first iteration of Copilot has agentic technology in it, the new version of Copilot adds and expand that particularly around building artifacts, writing back to CRM, building decks, building account plan, building a point of view for your next call, and who you should be engaging with. We're releasing that in 2 weeks. So we feel really good about that type. But back to the large deal that technology has allowed us to expand outside of SDRs and into account executives and account managers. So from a seat perspective, we're now able to have real expansion within our customer accounts, and that large account with account executives, account managers, CSMs and sales development reps.

Got it. Is this maybe a main leading, but is this casting possibly halo effect on the core data platform that since you've added so much value around it, could there be a renaissance of the core data platform.

I think there's 2 Renaissance -- What's the plural of Renaissance? Renaissances, that we're seeing. One is high-quality data is incredibly important to go-to-market practitioners. And so we've had record win-back performance for the last 4 quarters in a row where customers went to a low-priced, lower quality provider and then very frustratingly came back or got frustrated there and came back to us. And so we're seeing high-quality data become more and more important. And the second thing we see is that we're hearing from a smattering of our customers, "Hey, the Google's AIO overviews and the LLM have taken 30% of the traffic away from our website. And so now we're not seeing the same amount of traffic to our website anymore. And so that's not converting into demand the way that it used to." And so what we're hearing from our customers is, oh, we're reaccelerating the hiring of our sales development reps, go outbound and reaccelerate demand that we lost because we lost this traffic to our website.

This is what your customers are saying?

Our customers are saying. We're hiring more SDRs now because we now have this demand gap and how do you make up a demand gap if you're not going to get it through SEO and through the traditional search engines, you have to go out and create it. You go out and create it with SDRs. And so we're seeing more and more customers now accelerate the hiring of SDRs to go outbound and create demand that is now lacking because the traffic to their website has gone down.

I thought SDRs could be replicated with the Copilot.

Inbound SDR can be replicated pretty well. So if you get a lead in from the website, certainly somebody can communicate and schedule a meeting, but outbound SDRs I haven't seen anybody replicate that with AI.

So to counter AI, people are hiring?

People are hiring, yes, that is actually -- yes.

Wow. Okay. That's -- Graham, back to you. Copilot now -- decent adoption, over 10% of the customer base according to my information. What is the unit economics of the Copilot product, if you do track it and the margin profile of Copilot [indiscernible]

Yes. First and foremost, we built Copilot to deliver durable value to our customers. So net revenue retention of Copilot will be the kind of primary metric that we track. The first year of Copilot kind of being out in the wild was largely a story of migrating the existing customer base over to Copilot while also selling it as new business. We were really successful doing that. We were able to get uplift on a per seat basis from existing customers as they migrated over to Copilot. Now we're starting to enter that next phase where folks have been on Copilot for 6 months or a year, and we're starting to see renewal outcomes. We've been tracking the leading indicators of these renewal outcomes for a year now, seat utilization, frequency of usage. We have more bespoke metrics that track specific actions and conversions. And all of those were positive and historically have led to more positive retention outcomes. What we're starting to see now at the very end of Q2, at a smaller scale and then in Q3, it's starting to ramp up some in Q4, will step up a lot. We're starting to see like these first renewal cohorts show up on Copilot, and we are seeing early signs that the renewal outcomes are better. If you think about the unit economics there, they're pretty similar to the rest of our business, high margins, but if we can actually go and realize better retention, better customer lifetime value from Copilot customers over time that can deliver improving margins.

Got it. Anybody wants to jump in a question? I got a couple of ones, yes. The only I wanted ask you was, curious, since you've been in the industry for a long time, foundation models. First, there was 1, then there were 2, 3, now it's like -- I can't keep track. now a big deal. Microsoft is it with AI. What do you make the flooding of foundation models, seemingly all are trying to do the same thing. Is this posting an opportunity for companies like ZoomInfo that you think that the cost of compute and the cost of access intelligence is going to come down? What do you make of this? If you project this trend out, what does it mean for your company and more broadly the software industry, the applications industry.

Yes. So I think, one, we do see cost of the models coming down exponentially over time...

Are you getting the economics.

We are, absolutely. And then -- and also, the way we kind of about all the different models is there are some models that are of lower cost that can do a certain task very well and maintain that lower cost. -- there are some tasks that need a more -- a newer model. And so we're balancing the different models across the different tasks to get the best cost efficient outcome. And so some things we're using Anthropic for, there are some things we're using Open AI for, there are some things that we're using Google Gemini for, depending on the task and depending on the costs related to those calls. I think that's 1 thing. I think the second thing is it also means you should be building on the edge of the model. because when a new model comes out, things that you weren't able to do with the existing model, you're going to be able to do with the next model. And so you should also always be pushing the boundaries of things that are almost not possible with the existing model or not possible because the next model that will come out, we'll solve those things. And so we're seeing a lot of that. It would be very difficult to build artifacts, using the first iteration or even the second iteration of these models, you couldn't build a deck. You couldn't build an account plan. Today, out of the box, you can build an account plan if you give it the right context and right prompt. And so we're continuing to evolve the functionality of the product as the LLM evolve as well.

Yes. It's hard to forecast the future. But clearly, we do not see this coming a year ago, nobody saw these things coming. And it's going to be equally futile if somebody try to paint a picture, the seeming contract, there for my own question, where do you see the company 5 years. But I guess it's easier to see 5 years out than it is to see 6 months, 9 months, 12 months out, right? But as you connect the dots, clearly, the cost of input is going down, intelligence is more accessible as an adjunct, what do you make of this software, is that hypothesis, which I don't feel it, but I'm curious to get your -- but maybe you do -- different views on software -- what do you make of AI?

I hope I wasn't sitting in the seat, if I believe that. Someone with conviction on that's not going to be the case should be sitting here.

It's meant to be provocative.

Yes. I think that. There are a of things that AI is going to give people capability to do, that they don't have the capability to do today. When I think about software being dead, I think, number one, that vastly under estimates the workflow domain knowledge necessary to build great software platforms for specific use cases. And so when we think about the software that we're building, we have to deeply understand our customers and their workflows in order to build the right types of software for them. And that's going to be -- we have really great people who are really focused on that problem set. And are constantly evolving that. And then it's got to be maintained, and you have to go to the new model, and you have to spread out the cost across different models. All of that work that has to go into building a great output from these models is going to continue to exist and people will rely on third-party vendors to do that. That MIT study that literally everybody in the world is talking about, said, that when you partner with third parties to build these solutions, I can't remember what is 3x more likely to be successful than if you try to build something in a homegrown way. That's the same thing with software. It's the same thing we've always seen when people try to build something in a homegrown way versus leveraging a vendor with expertise. I think that construct will continue.

May your words proved to be true.

From my lips to God's ears.

Yes. On that note, I wish you really well for the next -- in achieving your vision in 2030. And thank you once again for your investment in Goldman Sachs.

Thank you, Kash.

Thanks, Kash.

A big round of applause.