Snowflake Inc. (SNOW) Earnings Call Transcript & Summary

All right. Fantastic. We will go ahead and kick off the new flex session at the Goldman Sachs Communacopia Conference on Gabriela Borges piled our software franchise, delighted to have with me on stage Shraamiswami, CEO, Brian Robins, CFO. Thank you both for being here.

Thank you.

I want to start with some of your conversations in the field. Tell us a little bit about what you're hearing. If we look at the modern data tech stack today versus 2024 or 2025, the pace of innovation has changed. So tell us a little bit about what you're seeing in those conversations and hearing in those conversations about the customer journey to go from old to actually new, meaning AI-enabled. .

Yes. There's always been a lot of demand for data modernization. But the migration strikes tear in the heart of pretty much every CIO or CD honestly, like everyone in engineering, just takes whatever highly uncertain outcome and so on. I think AI is having a pretty profound impact on how quickly you can get those done. -- and expectations, not just from me or my team, I've talked before about how I want migrations to be mostly automated, but even customers are expecting it. we have a very large manufacturing client, for example, do a Teradata migration planning aggressively to finish it in less than 3 quarters. This is not something you would have heard of [indiscernible] . That's like -- that's part 1 of a lot more is possible, let's go get it done. But what is equally interesting is now the ability to have conversations at a data platform level, that's a level of snowflake. We just stayed out generally off a lot of these kinds of conversations is having them award how we can deliver business value. It is everything from like how can we automate invoice processing at a really large energy manufacturer because processes like this, they are always super manual, super spotty. They would do like spot checks here and there. they estimate that on $10 billion that they pay out every year, there'll be a percentage point more efficient, except that, that's an astronomical amount of money. -- is talking about that or talking about supply chain optimization or talking about how do you implement a custom CDP a whole lot faster. It's having conversations like that, that I think are very, very distinctly 2026. compared to previous one. Where honestly, most CEOs wouldn't even bother to talk to me, it's like a data vendor, who cares? I think that change is what is remarkable about this moment.

I want to come back to custom CDP, but let's stay on the migrations, try for a moment. When we came to our conference in June, a lot of the system integrators we were talking to spoke about how migrations can now be fixed cost instead of variable comp because of coating tools. Tell us a little bit more about the shift from variable cost migrations to fixed cost migrations? And how we think about the impact that coding tools, and then that sat nicely into Coco specifically can have on that piece of migration.

I would say this is a larger trend. AI fundamentally is making software industrialized. And I won't underestimate even now the threat that it poses to every tech company, every software company, it's a profound, profound shift. What it has also done is it has obliterated the distance between what a data platform like Snowflake is and what applications running on top of data can be. Now stuff that people build on top of Snowflake will not look like your standard package SASSA. It will have its own look and feel. We can talk about that. But the other thing that it's done is it has also pushed the distance between the data platform and actually what used to be called services because you can begin to automate a lot of things. And in as much as software, it represents like what we humanity call intelligence. That's what they do. They put workflows. They put data structures into place. They organize our thinking, AI accelerates that massively, which is why a number of folks because they can now bring the power of coding agents or basically saying, wait, I can compress the time of something like a migration massively and also feel very confident that the weird problems that will come up during any real migration, the little odds and ends can also be fixed equally quickly. And they're sensing an opportunity because the majority of the industry is still operating on time and materials, a lot of time and a lot of materials and a lot of money. And so the progressive system integrators are going, I can guarantee outcome. This is what we do as well. where we are saying we can deliver outcomes for our customers, simply because the ability to get things done fast is much better now than before, but also the ability to deal with unknown things is just also a whole lot better. It's the combination of these that I think will drive a massive change through the services industry. Not that I think services will go away is just going to look dramatically different, a lot smaller than what it did before. but 1 that is much more tied to what are the outcomes that customers want?

Let me ask about cocoa specifically because Brian, then we can bring you into the conversation as it pertains to how you think about guidance. So Sri, we started talking about, look, it's not just the number of customers in the installed base that are using cocoa, but it's actually the depth of usage and the net new use cases that you're also solving for. So I guess part 1 would be tell us a little bit about how you as an executive team push to deepen and strengthen the usage of cocoa within any given customer?

Yes. So a lot of it is what we have learned to ourselves. I think I've talked about this previously, part of a huge unlock for Snowflake the company was having a coding agent available to every single person within the company. It was not a specialized tool -- and so we saw burst of creativity and innovation in every department. And that's been very helpful for us just to understand what is possible with AI. And the nice thing about harnesses in general. And I think the reason they're going to have a profound impact on everyone, including all of you, is the work that you do now is visible, observable within 1 system, which also means that it is optimizable, -- it is automatable. And so we have a lot of insight into what is the customer doing? What are we doing with cocoa? Are we doing repeat things. For example, we now make recommendations for here's a skill you should be building because you seem to be doing this very often. And it's a quick hop from there to get our set of skills that your colleagues are using. This is something you can use to make yourself more effective at work. And so we can understand things like the depth of usage and then tie it back to things that we can do. At the end of the day, lives about what's an action that you can take that can produce an outcome that you want. And so we have things like hands-on labs that have proven to be highly, highly effective. This is basically a 2- to 3-hour tutorial run by 1 of our more technical people with the customer. And because of that, the customer gets more effective in what they do. Their data teams are happier. They get more work done. -- simpler to debug annoying problems that are and parcel of their life. But it also gives us a clear road map for this is what it takes to drive truly deep adoption with each of the customers that matters to us.

I'll just add on to that. One of the things that Coco has done is this open up the aperture to who we sell to from a persona perspective. And so a year ago, when I joined Sniflake, I hardly had any customer conversations today, every week, I'm meeting with 3 to 5 CFOs and talking to them about what we're doing internally on cocoa and what the art of the possible is. And I think there's no better way to actually expand Coco or cowork adoption by showing people how you're using it internally. And as Sreedhar said, these skills that we're making can be applied to vast sets of data that our customers to actually get them started to use that. And so I think once you show them what you do internally the art of the possible and how quickly you can speed up things, they're extremely interested.

And Brian Srira used the word burst there. So look, it's a new product cycle. And you're going to have customers that are experimenting, you're going to have questions around gross retention durability. I think you've already said gross retention is held stable even as Cocoa -- my question for you as an analyst, we try to model cocoa, and we also try to model the impact of that migration and the speed of migration is having on your business. What advice would you give us as we try to think about some of the blue sky scenarios over the next 18 months? And how do you derisk the forecast from customers getting really excited about cocoa. But ultimately, it's still very competitive, and you've got experimentation could that usage pattern actually fade over time?

Absolutely. It's something that we struggle with internally as well when you launch a new product, if you ask anybody how to model that, it's -- we don't have that much data. It's difficult Fortunately, we have an amazing team internally that has been doing this for a very long period of time and have built very sophisticated models to understand what new product adoption will look like and it compares that to historically what new products have done. We'll then take that and then basically model up what a scenario is. And then we have a very wide and deep group that discuss what we'll put in guidance from that perspective. And so when we do come up with guidance for the core platform like the migrations, it's based on observed behavior. And we have years and years of data with that and can get pretty close for the new products. We try to be a bit conservative. So we don't take a month worth of data and extract that out and say this is what's going to be like all for this year and next year. But now that we've had 2 quarters of data, we feel more confident and what we can extract from that observed behavior.

When you and I first met, we started talking about the customer cohorts and how -- look, it sometimes takes year 1 is the initial ramp and then year 2 is really when a customer gets full swing snowflake adoption. Has anything changed as you look at the speed at which these customers are ramping?

I think from a cohort perspective, -- if you look at all the verticals across the company, we still have the same sort of vertical penetration, if you will, in the financial services, manufacturing, government and so forth. As far as ramping with the use of cocoa and Ai we're seeing customers ramp much quicker than what they've ramped historically. And so whether it's our partner network or what we're doing internally, what Sreedhar talked about is outcome-based pricing is really built the credibility with our customers if someone comes to me and says, I can guarantee you x for this set price. And I know historically that took a lot of time and a lot of materials and so forth, like I'm all in, and we're seeing that from a customer perspective. We do track internally, how long it takes for them to get up to their consumption run rate. And we're seeing those curves get steeper and steeper and steeper. And so customers are deploying quicker. They're consuming quicker. They're using partners, us and themselves are using our agents to actually do that. And so it's really exciting to see.

And that's a lot of where our go-to-market teams have to go our CRO often talks about shifting right towards outcome. It just means that Snowflake as a company and their team, in particular, has to focus a lot more on how do we get use cases live with customers? How do we get it to scale within customers? And what do we have to do? And it's increasingly a result of many things that used to occupy a lot of time getting ready for a meeting, doing research about what does the customer have? What's their data estate, how do you maintain it? . All of that getting easier, faster. And similarly for solution engineers, they would spend a lot of time building a little demo that would take forever. Now they can be conjured up kind of on demand -- and so there's this big shift. We have even created basically new job functions. One of them is called an activation engineer, an activation solution engineer that are expressly charged with what Brian said, which is how do you get a new logo to go live on Snowflake much faster than what they would otherwise. And so that is a trend that we want to keep leaning into and pushing.

I would also say selling into or actually describing what we do to all these personas. If you go to a CFO and show them what are the possible is, they're immediately saying, How do I get that up and running like yesterday. -- when Streeter goes and talks to a number of CEOs, they want it yesterday. And so the sense of urgency around getting these results are also super fun. .

Let's talk a little bit about custom apps. So Sridhar, you started talking about custom CDP. And certainly, there's been a debate in the application level on what is the future of applications? How do we think about packaged apps versus headless architectures versus some of the interesting things that customers are building on top of like. Some of the things that you announced at Summit, workflow orchestration agents on the application layer as well. Tell us about how you see the app layer evolving.

I mean, first of all, I think this is a time of just a lot of innovation with what is possible because let's face it, building any kind of meaningful application before, again, was just a hard thing to do. Now pretty much any of us can pick up a coding agent and say, Hey, I want not just a web like an Android or an iOS app. And dealing with the app stores is the most time-consuming part of doing something like that now. The apps themselves are easy. So we are playing it on with lots of different formulations, including things like should the notion of an application be rethought as a handful of self-evolving skills running on top of a data substrate. What I mean, let me give you a specific example. I'd say like, Oh, you want an internal survey application, easy enough to imagine. What do you want to do in a survey application, especially if it's just internal you want to know who your employees are. You want to know like how you target, let's say, a particular group, you want to manage visibility into the results that are coming. It's not that complicated. Now if you have a snowflake deployment like we do, absolutely, our Workday hierarchy is mirrored in Snowflake. So that's where you get that from. You set up a couple of tables to store surveys, distort results and figure out notifications -- and admin does something and then an ops person as these people are allowed to send out surveys and of people go to send out actual surveys. Now I didn't really talk about you can conjure that up on demand by saying, oh, if somebody clicks on this link, bring up this react app for them to respond to the survey. And so what would be an actual SaaS procurement is a handful of skills that can be installed on top of data that is already sitting in Snowflake. It's governed. You don't have to worry about, hey, does everyone have access to this data? You can manage the visibility. -- can also do follow-up analysis on it. If it's freeform text and you want to run AI on it, that's not an issue. So you see where this is going. I think it just makes many, many more things possible. This is not to say that this is the end all be all solution for everything. But to the extent that our vision consistently for multiple years has been we want to be the place where you can bring together all of your data and get a 360 view analytic view of the data, it sets us up very nicely to rethink what is an application of the future. For what it's worth, we think our sales force data also into Snowflake -- and so if I want to create an annotation application, that's not part of Salesforce, but acts partly on Salesforce data and can push it back, that too is possible. it's a very different way of thinking about what's in plc. The first time I tell people, an application can be reduced to a handful of skills, you get a blank stare, like really, what does that mean? And similarly, these skills don't have to be static. As you look at how people are using them, they can get additional functionality over time. They can self evolve. That's how a lot of support systems are like my teams, their Saudi systems are evolving. They built the first version. They built some skills, put some data. They looked at how they were analyzing it. Then they created newer skills, and they said, "Oh, half of these things can be automated by agents looking at stuff first as opposed to having a human look at it. And now that's a very different notion of what an application is. It is something that is evolving as it goes along. So I think the world is rich with possibility, and there's just going to be a lot of innovation everywhere. And as a platform, we focus on what are like these little nuggets that we can lay out there that is going to comment some right person in 1 of our customers, they hear something else that I can build with it. We learn from them and then figure out how to make it more broadly available to other customers. You see this feedback loop and where it's going.