Snowflake Inc. (NYSE:SNOW) Q3 2024 Earnings Call Transcript

Snowflake Inc. (NYSE:SNOW) Q3 2024 Earnings Call Transcript November 29, 2023

Snowflake Inc. beats earnings expectations. Reported EPS is $0.25, expectations were $0.15.

Operator: Good afternoon. Thank you for attending today’s Q3 FY 2024 Snowflake Earnings Conference Call. My name is Hannah and I will be your moderator for today’s call. All lines will be muted during the presentation portion of the call with an opportunity for questions-and-answers at the end. [Operator Instructions] I would now like to pass the conference over to our host, Jimmy Sexton, Head of Investor Relations at Snowflake. You may go ahead.

Jimmy Sexton: Good afternoon and thanks for joining us on Snowflake’s Q3 fiscal 2024 earnings call. With me in Bozeman, Montana are Frank Slootman, our Chairman and Chief Executive Officer; v, our Chief Financial Officer, and Christian Kleinerman, our Senior Vice President of Product, who will join us for the Q&A session. During today’s call, we will review our financial results for the third quarter of fiscal 2024 and discuss our guidance for the fourth quarter and full year fiscal 2024. During today’s call, we will make forward-looking statements, including statements related to the expected performance of our business, future financial results, strategy, products and features, long-term growth, our stock repurchase program and overall future prospects.

These statements are subject to risks and uncertainties, which could cause them to differ materially from actual results. Information concerning those risks is available in our earnings press release distributed after market close today and in our SEC filings, including our most recently filed Form 10-Q for the fiscal quarter ended July 31, 2023, and the Form 10-Q for the quarter ended of 2023 that we will file with the SEC. We caution you to not place undue reliance on forward-looking statements and undertake no duty or obligation to update any forward-looking statements as a result of new information, future events or changes in our expectations. We’d also like to point out that on today’s call, we will report both GAAP and non-GAAP results.

We use these non-GAAP financial measures internally for financial and operational decision-making purposes and as a means to evaluate period-to-period comparisons. Non-GAAP financial measures are presented in addition to and not as a substitute for financial measures calculated in accordance with GAAP. To see the reconciliations of these non-GAAP financial measures, please refer to our earnings press release distributed earlier today and our investor presentation, which are posted at investors.snowflake.com. A replay of today’s call will also be posted on the website. With that, I would now like to turn the call over to Frank.

Frank Slootman: Thanks, Jimmy. Welcome and good afternoon. Q3 product revenue grew 34% year-over-year to reach $698 million. Non-GAAP adjusted free cash flow was $111 million, representing 7% year-over-year growth. Results reflect strong execution in a broadly stabilizing macro environment. while Snowflake’s global revenue mix is highly diverse in terms of industries and geographies, the company derives an ever larger revenue share from mainstream enterprises and institutions. This, as compared to a newer crowd of digital natives, have made up many of Snowflake’s early adopters. We added 35 $1 million plus customers during the quarter, 9 of our top 10 customers grew sequentially. Generative AI is at the forefront of customer conversations, which in turn drives renewed emphasis on data strategy in preparation of these new technologies.

We said it many times, there’s no AI strategy without a data strategy. The intelligence we’re all aiming for results in the data, hence the quality of that underpinning is critical. Meanwhile, Snowflake has announced and showcased the plethora of new technologies that let customers mobilize AI. We’ve introduced Snowflake Cortex to leverage AI and machine learning on Snowflake. Cortex is a managed service for inferencing large language models. This opens up direct access to models and specialized operations by translation, sentiment and vector functions. Business analysts and data engineers can now use AI functionality without the fractured highly technical challenges of the AI landscape. Last summer, we introduced Snowpark Container Services, which also serves as the second pillar of our AI enablement strategy.

Developers can access any language, any library and flexible hardware inside the governance boundary of Snowflake. More than 70 customers are already using container services in preview with many more waiting in line. Snowflake makes the common AI use case is easy and the advanced use case is possible. We are well positioned for AI based on the scale and scope of our data cloud programmability and governance framework. There are hurdles challenging enterprise adoption of AI and ML. The first is broad access to quality data. Snowflake addresses this challenge through its data sharing architecture. 28% of all our customer share data, up from 22% a year ago and 73% of our $1 million-plus customers are data sharing up from 67% a year ago. AI models can only be as smart as data they are trained on.

Security and governance present another challenge for enterprise adoption of AI and the now Snowflake Horizon offers a unified security and governance solution built for AI. Horizon strictly and consistently enforces user privileges on data across use cases, including large language model applications, traditional ML models and ad hoc queries. As part of Horizon, we introduced universal search, which enables customers to search the data cloud. Customers can now discover data and metadata that exists across their accounts and in the Snowflake marketplace. Snowflake continues to win new workloads outside of its traditional. Snowpark’s consumption grew 47% quarter-over-quarter. Consumption in October was up over 500% since last year. Over 30% of customers use Snowflake to process unstructured data in October.

Consumption of unstructured data was up 17 times year-over-year. Our newest streaming capability, Dynamic Tables entered public preview earlier this year. Approximately 1,500 customers are using the feature and initial adoption is outpacing expectations. We have a number of major new capabilities becoming broadly available in Q4. Our native apps framework will go GA, UniStore for transaction processing, Snowpark Container Services and Apache Iceberg Tables will all enter public preview. These products unlock substantial new workload expansion opportunities. We are campaigning globally to expand our audience. This fall, our Data Cloud World Tour traveled to 26 cities worldwide. In-person attendance at these events reached 23,000 nearly double from last year.

Next up is our Build Developer Conference in early December, where we anticipate 35,000 registrations. Build is focused on building apps, data pipelines and AI/ML workflows. We hope to see you there. With that, I will turn the call over to Mike.

Mike Scarpelli: Thank you, Frank. In Q3, we saw strong consumption from a broad base of customers. Our performance was evenly split between large and small accounts largest customer stabilized as expected. Migrations drove growth in Q3. Our two fastest-growing customers who are both migrating workloads from a legacy vendor. One of these accounts is in their second year on the platform, the other in their eighth year on the platform. We added four customers with more than $5 million and two customers with more than $10 million in trailing 12-month product revenue in the quarter. Growth in September exceeded expectations. For three weeks, consumption grew faster than any other period in the past two years. Consumption continued to grow in the month of October.

Q3 represented a strong quarter for bookings execution. Remaining performance obligations grew 23% year-over-year to $3.7 billion. Of the $3.7 billion in RPO, we expect 57% to be recognized as revenue in the next 12 months. APJ and SMB drove growth in net new bookings. We are making significant progress in delivering margin expansion. Non-GAAP product gross margin of 78% was up approximately 300 basis points year-over-year. Improved terms from the cloud service providers have contributed to margin expansion. We also benefit from increasing consumption of higher-priced additions of Snowflake. In Q3, price per credit increased 4% year-over-year. Non-GAAP operating margin of 10% was ahead of expectations. Operating margin benefited from revenue outperformance and increased hiring scrutiny.

Non-GAAP adjusted free cash flow margin was 15%, benefiting from favorable timing of collections. We ended the quarter with $4.5 billion in cash, cash equivalents and short-term and long-term investments. Our strong cash position allows us to opportunistically repurchase shares. In Q3, we used $400 million to repurchase 2.6 million shares. Year-to-date, we have used $592 million to repurchase 4 million shares at an average price of $147.5. Now let’s turn to guidance. For the fourth quarter, we expect product revenue between $716 million and $721 million, representing year-over-year growth between 29% and 30%. We’re increasing our full-year guidance to approximately $2.65 billion, representing 37% year-over-year growth. Consumption trends have improved.

We are seeing stability in customer expansion patterns. Our guidance is based on observed patterns and assumes continued stability of consumption. For the fourth quarter, we expect operating margin of 4% and 360 million diluted weighted average shares outstanding. For the full-year, we are increasing our non-GAAP product gross margin guidance. We now expect non-GAAP gross margin of 77%. We still expect a product gross margin headwind in the fourth quarter associated with new products. We are increasing our fiscal 2024 non-GAAP operating margin guidance. We now expect non-GAAP operating margin of 7%. We are increasing our fiscal 2024 non-GAAP adjusted free cash flow margin. We now expect non-GAAP adjusted free cash flow margin of 27%. For the full-year, we expect diluted weighted average shares outstanding of 361 million.

We are on track to add more than 1,000 employees this year, inclusive of M&A. With that, operator, you can now open up the line for questions.

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Q&A Session

Operator: Absolutely. [Operator Instructions] Our first question is from the line of Mark Murphy with JPMorgan. Please proceed.

Mark Murphy: Thank you so much. I love the 11-minute earnings call, and congrats on a fantastic result. So Frank, we are hearing broadly that conversations are starting with generative AI and they’re stopping at data, because they find their data estates aren’t in good enough shape. Are you sensing more tangible uplift there around that concept that Snowflake might be on the front edge of AI projects and perhaps seeing that spill over into customer conversations or drive more pipeline for some of your other products like Snowpipes and Snowpark and data sharing?

Frank Slootman: Generally speaking, yes, one of the interesting things is that customers are now getting preoccupied with their data estates because they have to get them into shape where they can productively take advantage of the newer technologies, which we are now also showcasing and delivering where they can just turn it on and have well-governed frameworks to run them with all the things that they’re used to from Snowflake. So it’s definitely true that the frenzy and the high degree of interest in AI has a knock-on effect on the interest in data strategy, data platforms. And people are also not just looking at the quality of their data and the optimization of the organization curation of data but also what kind of data they need to be able to have access to. So people are taking a much broader view of their data estates as well in terms of what’s in it and what should be in it.

Mark Murphy: Thank you very much.

Operator: Thank you, Mr. Murphy. Our next question is from Keith Weiss with Morgan Stanley. Please proceed.

Unidentified Analyst: Great, thank you guys. [Indiscernible] on for Keith. Maybe just start off with a quick question on sort of you mentioned several times on the call, the stabilization that you are seeing in your — with the new growth. And we’ve obviously heard that from sort of your hyperscaler peers as well. When you’re looking at an account level, could you give us sort of an idea like how much of the stabilization is coming from cost optimization, scrutiny alleviating versus sort of existing customers who slow what migrations leaning in more versus customers leaning more into new products? Is there any way that you can kind of give us more color, what parts are playing out already and which are yet to come maybe into the next year?

Frank Slootman: Keith, one of the things, it is Frank. What I mentioned is our customer base has evolved in recent years to include much larger enterprises and institutions who are typically not prone to over consumption and unbridled expansion that they then later have to reset and rationalize. Because of that, the exposure to these drastic resets and optimization that we saw earlier in the year is getting less and less with each incremental quarter. Secondly, people have really driven themselves through these processes and rationalized themselves and are now in a good place to move forward. You can only optimize and rationalize so much. At some point, it’s diminishing returns. People get tired of us and they’re moving on to things that are now new and interesting, namely preparing for enabling AI and ML technologies.

Mike Scarpelli: I’ll add to that, too, that why we see that stabilization is nine out of our top 10 customers all grew quarterly sequentially. And the other point I’ll make is we are seeing a shift, as Frank mentioned. Our biggest customers are mature enterprises we’re seeing now and mature enterprises have always scrutinized cost. They always will. And so there’s nothing new there, and that will continue. And that’s just the way anyone should run a business.

Unidentified Analyst: Got it. That’s helpful. And then maybe one quick question on your sales and marketing headcount. Obviously, we noticed it’s basically flat quarter-over-quarter this quarter. But then again, it’s only sort of one number. Can you shed some light in terms of like what regions are you may be leaning more into versus getting more efficiencies or any sort of areas that you’re investing in still? Because obviously, your growth seems pretty healthy. So just some color on where you’re investing, would be helpful.

Mike Scarpelli: Yes. So first of all, in general, with sales and marketing heads, most of those typically are added right at the end of Q4 or even more so at the beginning of Q1, so people can get involved in our sales kickoff. And what I would say is we are continuing to invest very heavily in our sales and marketing function, in particular, in Europe. We talked about six months ago or so, we added a new leader there. We have been changing out some people and investing, and we’re continuing to, and we will continue to prune underperformers globally and invest more in the right people as we go forward. And APJ is another one that we continue to invest in.

Unidentified Analyst: Excellent. Thank you.

Operator: Thank you, Mr. Weiss. Our next question is from the line of Raimo Lenschow with Barclays. You may proceed.

Raimo Lenschow: Thank you. Congrats from me as well. Guys, you have like a crazy amount of new exciting products coming out. How do you think about the sales setup here now going forward? Because you’re going to be able to address lots of different areas from like classic data to kind of more AI. Does that mean your sales approach needs to change, Frank, here going forward? And it doesn’t sound like you are going to have a crazy sales force expansion here. Like how do you want to do that going forward and ensure that all these new products are actually finding the market? Thank you.

Frank Slootman: Yes that’s actually an excellent observation. We have historically had sort of one dominant selling motion that we sort of deployed everywhere and anywhere. It has served us well. But as you correctly observed, the market has really changed. When you go back to 2015, Snowflake really swam in swim lanes that were very narrowly defined and very well understood. Now we’re in the mega market, right? These are very, very broad-based platforms that are incredibly capable in many directions. And we’ve been working very hard, as you’ve seen in recent years, in delivering just an absolute ton of capabilities to enable these platforms in all these different directions. I mean, our drive towards applications and the whole programmability framework, the onslaught of AI and AM and our capabilities, all of that is coming to fruition.

Now we have a ton of irons in the fire, and they’re now all getting hot. So from a sales standpoint, we have much more specialization happening and that is going to literally going all over the world because it is impossible for a single person to be to be expert in all these technologies and all these disciplines. So we’re going to have people that have general purpose capabilities, sort of core skills, if you will, and then we will have teams of specialists that will augment these groups wherever they’re needed. So our basic selling motions and how they are supported will evolve rapidly in the coming year.

Raimo Lenschow: Okay, perfect. Makes sense. Thank you.

Operator: Thank you, Mr. Lenschow. Our next question is from the line of Kirk Materne with Evercore ISI. Please proceed.

Kirk Materne: Yes, thanks very much. Congrats on the quarter. I guess, Mike, could you just talk about the impact that some of these newer unstructured data workloads are having on consumption at all, meaning I assume it’s still a very, very small part of overall consumption when you look at it, but is that helping with the stabilization? Can they turn into sort of catalyst for acceleration as we get into ’24? Anything you to sort of dimensionalize the impact that has as we think out to next year? Thanks.

Mike Scarpelli: Well, they’re definitely helping with stabilization. I can’t quantify exactly what unstructured is doing, but it’s not just that. It’s also we’re starting to see the effects more of Snowpark that’s doing very well for us right now. Some of the new things we’re already seeing very early uptick in streaming and dynamic tables. We really, I would say, Streamlit is built into our forecast for next year. The other products because they’re new, we really don’t build much in for that because we need history before we can do that. And clearly, we think a lot of these new products that are just going into public preview now and GA next year will be a catalyst for growth for us in 2025.