Snowflake Inc. (SNOW) Q4 2022 Earnings Call Transcript

Ladies and gentlemen, thank you for being here. My name is Brent, and I will be your conference operator today. I would like to welcome everyone to the Q4 Fiscal Year 2022 Snowflake Earnings Conference Call. All lines have been muted to minimize background noise. After the speakers’ remarks, there will be a session for questions and answers. Thank you. Now, I am pleased to hand over today's call to Mr. Jimmy Sexton, Head of Investor Relations. Sir, you may proceed.

Good afternoon and thank you for joining us on Snowflake’s Q4 fiscal 2022 Earnings Call. With me in Bozeman, Montana are Frank Slootman, our Chairman and Chief Executive Officer; Mike Scarpelli, 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 fourth quarter fiscal 2022 and discuss our guidance for the first quarter and full year of fiscal 2023. 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 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 and the Form 10-K for the fiscal year ended January 31, 2022, that we will file with the SEC. We caution you not to 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 reconciliations of GAAP to 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.

Thanks, Jimmy. Good afternoon, everybody. We finished fiscal 2022 with record-breaking consumption and bookings results. Product revenue surpassed $1.1 billion for the full year, growing 106% year-over-year. Remaining performance obligations were $2.6 billion, representing year-on-year growth of 99%. Q4 was our strongest bookings quarter-to-date and included a number of large multiyear commitments. Our net revenue retention rate reached 178%, driven by continued growth from our largest customers. In the quarter, we added 14 Fortune 500 and 21 Global 2000 customers. Key enterprise wins included the California Department of Public Health and KPMG, who is also a new alliance partner. We closed the year with $150 million non-GAAP adjusted free cash flow peaked high, growing with improving unit economics and operational efficiency. Snowflake’s growth is driven by digital transformation and long-term secular trends in data science and analytics enabled by cloud-scale computing and Snowflake’s cloud-native architecture. Snowflake is a single data operations platform that addresses a broad spectrum of workload types and incredible performance, economy, and governance. As a platform, Snowflake enables the data cloud: a world without silos and the promise of unfettered data science. In the most recent Dresner Advisory Survey, 100% of Snowflake customers surveyed said they would recommend Snowflake to other organizations for the fifth year in a row. Our focus is to continually enable more workload types, use cases, and data types. This fully aligns with our consumption model, which drives work to the data and allows data to work. During the fourth quarter, we announced several product development milestones, including: Snowpark, our developer framework that helps data scientists and developers transform and program data. Snowpark for Python is now in private preview, and Snowpark for Java on AWS is now generally available. ITAR, we now support compliance with the international traffic and arms regulations in our Microsoft Azure government and AWS GovCloud regions. Generally available data governance capabilities, including object tagging and conditional data masking; object tagging, in particular, is important for the cataloging of data and resource consumption governance; and continued advancements with higher concurrency and lower latency workloads. Snowflake data sharing is seeing continued traction in the field. In fiscal 2022, the number of stable edges grew 130% year-on-year. 18% of our growing customer base has at least one stable edge, which is up from 13% a year ago. Snowflake’s Data Marketplace listings grew 195% this year, now with more than 1,100 data listings from over 230 providers. Our Snowflake Data Marketplace fuels our rich application development ecosystem and is powered by the Snowflake program. To date, there are over 285 Powered by Snowflake partners, including new members Yext and Habu. We continue to elevate our go-to-market functions with an industry-specific focus. In the fourth quarter, we hosted our first Media Data Cloud Summit. The event highlighted real-world customer use cases. Companies like Experian, Roku, and Warner Music Group showed how they are leveraging the media data cloud to protect consumer data and drive advertising subscriber growth. Our priority for the year is essentially unchanged and is as follows: first, the enablement and expansion of our workload types. Nothing is more core to our mission to develop the data cloud. The existing workload types, such as data lake, data engineering, and data science, will develop continuously to become more functional, efficient, and performance-driven. New workload types will be announced later this year. Our focus on Snowpark and enabling workloads driven by languages such as Java and Python fall under this header. Today, we announced our intent to acquire Streamlit to accelerate data applications development on Snowflake. Streamlit enables data scientists to build, deploy, and share data applications. Data scientists will be able to govern data to build applications powered by Snowflake. 1.5 million applications have already been built on Streamlit, and we will continue to invest in the open-source framework that developers love. We’ve agreed to pay $800 million with a mix of cash and stock. The transaction is subject to customary closing conditions. Secondly, we’re expanding our use cases by vertical industry as well as functions such as IT, sales, marketing, finance, and engineering. We are continuing to drive collaboration through data sharing with leading enterprise software companies to drive this trend. Third, as of February 1, we have also verticalized part of our selling motion to address our largest customers by industry. Lastly, we’ll continue to deepen and broaden our geographical scope, expecting faster-growing contributions coming from outside the United States. We’re excited about starting a new Snowflake fiscal year.

Thank you, Frank. Q4 was another quarter of exceptional execution and a strong finish to our fiscal year. Q4 product revenues were $360 million, representing 102% year-over-year growth. Remaining performance obligations accelerated to 99% year-over-year, reaching $2.6 billion. Of the $2.6 billion in RPO, we expect approximately 52% to be recognized as revenue in the next 12 months, representing 85% year-over-year growth. For Q4 product revenue, we anticipated holiday season headwinds. However, we did see a slower-than-expected return to normal consumption in January. We also introduced platform enhancements that improved efficiency better than expected, which lowered credit consumption. Our increased net revenue retention rate of 178% includes 15 new $1 million customers and reflects durable growth among our largest customers. Similar to last quarter, six of our top ten customers’ product revenue grew faster than the company overall. Our industry vertical investments are yielding strong results. Q4 was our largest bookings quarter to date, and the outperformance spanned across all our core verticals: financial services, retail and CP&G, advertising and media, health care, and technology, which accounted for 85% of net new bookings in Q4. Large deal volume continues to increase in these verticals. In the quarter, we closed seven deals at or above $30 million in total contract value, up from just one in Q4 of last year. Significant contractual commitments give us confidence that our largest customers’ consumption will continue to grow. In Q4, we saw a number of customers with greater than $1 million in trailing 12-month product revenue increased to 184, up from 148 last quarter. Turning to margins. On a non-GAAP basis, our product gross margin was 74.99%, up nearly 500 basis points from last year. Enterprise success and growing scale across regions contribute to steady gross margin improvement. Operating margin was 5%, benefiting from revenue outperformance and hiring linearity. Our adjusted free cash flow margin was 27%, positively impacted by strong collections and operating margin outperformance. We do experience free cash flow seasonality, and Q1 and Q4 will continue to be our strongest free cash flow quarters. Given the record bookings in Q4, you should expect to see outsized adjusted free cash in Q1 of this year. We are proud of our free cash flow progress, and we will continue to invest for growth with a focus on efficiency. We are committed to showing leverage year-on-year. We ended the year in a strong cash position, with approximately $5.1 billion in cash, cash equivalents and short-term and long-term investments. Going forward, we are using our strong cash position to transition to a net share settlement for vesting of employee RSUs in almost all countries. This will help us further manage dilution, which has already been running below 1% year-on-year on a fully diluted basis. Now let’s turn to guidance, which includes the full impact of the Streamlit acquisition. For the first quarter of fiscal 2023, we expect product revenues between $385 million and $388 million, representing year-over-year growth between 79% and 81%. Turning to margins. We expect, on a non-GAAP basis, a negative 2% operating margin, and we expect 359 million diluted weighted average shares outstanding. For the full fiscal 2023, we expect product revenue between $1.88 billion and $1.9 billion, representing year-over-year growth between 65% and 67%. As we have mentioned before, certain product improvements create a revenue headwind for our business. We undertake these initiatives because they benefit our customers and expand our long-term market opportunity. Last year, we mentioned improvements in storage compression that reduced storage costs for our customers. Similarly, phased throughout this year, we are rolling out platform improvements within our cloud deployments. No two customers are the same, but our initial testing has shown performance improvements ranging on average from 10% to 20%. We have assumed approximately $97 million revenue impact in our full-year forecast, but there is still uncertainty around the full impact these improvements can have. While these efforts negatively impact our revenue in the near term, over time, they lead customers to deploy more workloads to Snowflake due to the improved economics. Turning to profitability for the full year fiscal 2023, we expect, on a non-GAAP basis, a 74.5% product gross margin, a 1% operating margin, and a 15% adjusted free cash flow margin. We expect 360 million diluted weighted average shares outstanding. Our gross margin guidance includes performance improvements and investments in additional deployments around the world, most notably, government deployments and international. In order to support our continued growth initiatives, we plan on adding more than 1,500 net new employees during the year. Lastly, we will host our in-person Investor Day the week of June 13 in Las Vegas in conjunction with Snowflake Summit, our annual users' conference. If you are interested in attending, please e-mail [email protected]. With that, operator, you can now open up the line for questions.

Your first question comes from the line of Rod Cuestas with Deutsche Bank. You can go ahead.

Great, thanks. It’s actually Brad Zelnick for Deutsche Bank. Congrats on an amazing quarter and a strong finish to the year. Mike, I wanted to drill down a little bit more into the platform enhancements that you talked about that resulted in optimization and consumption efficiency in the quarter. And you mentioned, I think it had a 10% to 20% impact, and you called out the $97 million that I think you baked in that’s going forward. To what extent does that compare to the expectations you had in your forecast? But more importantly, how should we think about the slope of the curve and cadence of future improvements that clearly benefit the customer but the impact that then has on the model? I guess maybe the confidence that you have in calling out $97 million. Thanks.

Yes. Good question. So first of all, as an example, for Q4, there was a rollout of what we call our warehouse scheduling service. We only rolled that out for three weeks, and we saw a $2 million improvement – impact, an improvement for our customers using less but doing the same number of queries because it’s much more efficient when you’re scheduling queries to run them, and rolling that out for next year. That is much bigger than what we were anticipating, and the full year impact of that next year is quite significant. But what we generally see is when we do these things, there’s usually a lag of about six months when we start to see more workloads move to Snowflake. And then there are other platform improvements that we’re doing that we rolled out in beta at the end of the quarter, and it's starting to be rolled out now throughout the year. The gross impact is actually more like $160 million, but I do expect that will be offset by over $60 million in additional workloads coming from our customers. And in terms of what we’re expecting, we knew these were going to come next year, and we never gave any guidance for next year yet. So it’s within what we were guiding. I just want to remind people of these.

Very helpful context, Mike. And I mean, the growth that you’re delivering at scale, I think, is unprecedented. Maybe a real quick follow-up for Frank. As we contemplate the results and the guide for next year, is the Streamlit acquisition, which congratulations on it, by the way. Any response to competitive changes in the market or is this something that has been teed up in part of the vision for a while? Thanks.

Hey Brad, it’s Frank. No, this is definitely part of a strategy focus that we’ve been talking about and making announcements on for the better part of last year, and that’s the focus of driving workloads really from the developer to Snowflake. We’ve been obviously super successful driving it from the data engineering, data warehousing, and data analytics side. But with the initiatives around Snowpark, all the programmability options for us to really address the Python developer community, this is going to be a superb asset for Snowflake. So we have to address workloads across the spectrum, and this is going to help us do that in places where we historically have not been as well represented as we’ve been in other areas. Yes.

It’s a great asset. Congrats on the deal. Thanks for taking my questions, guys.

Your next question comes from the line of Mark Murphy with JPMorgan. Your line is open.

Yes. Thank you very much. And I’ll add my congrats on just a very strong bookings quarter that you’re reporting here, especially on the RPO line. I wanted to ask about the comment on the slower-than-normal return to consumption growth in January. Plenty of other software companies saw slower consumption over the holidays. I’m curious, did you get any sense of what occurred in January that might have driven that behavior, perhaps relating to Omicron or other factors? And have you seen that change in any direction so far in February?

So as I said, we did see kind of a little bit more of a holiday effect going into January, whether people were taking longer vacations, I don’t know, but we did see it return to normal in January. You do see about 70% of our work is really driven by machines; the other 30% is human-driven, and we can see the machine layer stays consistent on a daily basis, and it’s the human interaction that changes. We did see a decrease in human interaction early in January, which leads us to believe people were taking vacations. As an example, last week, we looked at it on a daily basis, which was President’s Week and ski week for a number of people. We see it decrease there as well, too. But then we see a return in a week like this.

Okay, understood. And just as a quick follow-up. I think recently, you’ve had a favorable spread where retention seems like it’s giving you 70 points or more of revenue growth. But you’ve had the product revenue growing around 100%. Do you have any sense of how that relationship could end up playing out in fiscal year 2023, just given the dynamics with the platform improvements?

I don’t even try to compare net retention with revenue growth rates. But I will say definitely, our net revenue retention will go down next year because of all these improvements. It will stay above 150, but it’s not going to stay in the 170s.

Your next question comes from the line of Gregg Moskowitz with Mizuho. Your line is open.

Okay. Thank you very much for taking my questions. Frank, actually, as of February 1, you implemented changes with respect to verticalizing your sales motion. Can you elaborate on that? It sounds like you’re seeing real progress with respect to verticalization. Just trying to get a sense of how substantial these changes may be as you kind of go after that opportunity.

Yes. First of all, this is not a reorientation of our entire selling motion. It’s really the upper stratum in terms of our large account focus. We really replaced the geographical backbone with an industry equivalent of that because we don’t think, for a large account, that the geographical breakdown really adds anything. We’ve been talking on this call probably for the last four quarters about how we are really, in all aspects of our business, bringing a much stronger industry aperture to everything we’re doing. The sales organization has been working all of last year on making this transition happen. So by the time February 1 came around, everybody was fully up to speed; we’re locked and loaded to let that go. But the broader context of the industry orientation is that our selling motions and really our whole posture towards the industry is really shifting from a workload-oriented way of thinking to really thinking about what are the use cases that the customer needs to address? I will tell you that in my almost three years here; initially, all the conversations were around architecture and moving workloads from on-premise to the cloud and how our database migrations are. Today, 9 out of 10 conversations are industry-specific, very, very industry-specific, oftentimes not necessarily with IT types, but with business people and data science types, people who are really trying to drive predictive insights into the business, things that are becoming possible that have never been done before. So the company really wants to evolve towards this posture in the marketplace. It doesn’t mean that we’re going to walk away from a workload transition; that is our bread and butter, and we’re going to be doing that forever because we’re still in the very early stages of that transition as well. But we believe the industry posture is all about us assuming the customer’s point of view rather than our own, and we think that’s the correct way to do things.

Super helpful. Thanks for that. And then just as a follow-up. So obviously, having Java available on Snowpark is great. We think eventually getting Python to be GA is going to become a big deal, and Streamlit clearly enhances your exposure to Python. But what are your expectations of adoption of Snowpark over the next 12 months? How do you see this progressing?

Yes, sure. Hi, this is Christian. I don’t know how to project it as a percentage of the overall consumption. But if you just look at current adoption, Java is trending quite well. We see migrations from Spark from Hadoop and other workloads. And I can also share that for Python, right now, we have way more customers requesting access to the review than we can onboard currently. So the interest is super high, and they generate a lot of consumption. Trends are very positive.

Your next question comes from the line of Keith Weiss with Morgan Stanley. Your line is open.

In the guidance, is there a significant revenue contribution? And is there any significant sort of operating margin lag that we could be aware of?

Keith, your first part of your question was cut off. We couldn’t hear it. Could you start from the beginning and rephrase that?

Sorry. Yes, so I was just asking about the FY2023 guidance. You mentioned that Streamlit was in the guide but didn’t give us much detail in terms of how it was in the guide. Is there a significant revenue contribution or operating margin impact that we should expect from the acquisition?

Yes. There is about $25 million in expenses associated with Streamlit. There is no revenue. Streamlit has no de minimis figure; it’s less than 100,000, and we won’t be having a product ready on Streamlit until the end of the year, so we’re not factoring in any revenue that could come sooner.

Got it, got it. And then when we think about the impacts from the platform improvements, obviously, you’re calling out the revenue impact from the way that we look at the numbers and the net dollar expansion rate. I would assume that, that’s also going to see an impact. Any way you can help us kind of understand what the impact on that is going to be on a go-forward basis?

Yes. Well, I did say earlier on one of the questions that the net revenue retention is definitely going to come down. We’re not going to guide to net revenue retention. It’s hard to do. I’ll just say it will be above 150, but it’s definitely going to drop below 170.

Your next question comes from the line of Kamil Mielczarek with William Blair. Your line is open.

Hi. Thanks for taking my questions, and congrats on the strong year. So you delivered very strong net expansion rates, impressively, I think, accelerating up an already strong level this quarter. Can you provide some detail around some of the specific drivers? And how should we think about the relative contribution among the adoption of these workloads, more data being loaded onto platforms for existing use cases and maybe expansion into newer departments within existing customers?

Well, you see the net expansion rate of 178% for the quarter. That is really driven by expansion, obviously, within existing customers, and it’s a combination of new workloads or new divisions within companies. And it’s across the board, with new use cases as well, too, in there. I can’t give really much more color than that.

That’s helpful. And just a follow-up on the customer count. So your net new customer growth, I think, was down slightly in the last two quarters. I realize that the long-term expectation is for Fortune 500 and other $1 million customers to generate the majority of your revenue; I think 77% was the long-term target. How should we think about the pace of total customer growth going forward? Is it beginning to stabilize? And are we getting to a point where maybe you’ve landed a large portion of the Fortune 500, and the focus begins to shift more from landing new customers and more towards expanding within existing?

Yes. So to be honest, we don’t focus on the absolute number of customers. It’s more on the quality of customers. And as we’ve talked about before, Fortune 500 is not a great metric because it’s too U.S.-centric, and we’re actually focused more on Global 2000. Doesn’t mean we’re not focused on Fortune 500. And I will say Global 2000 excludes the public sector and the large private enterprises. So it’s really going after quality large customers is what we’re going after. And you will see fluctuation in the number of new customers we land in the quarter, but that fluctuation tends to be from small customers. And I just want to remind you, too, that these sales cycles into these large customers, we don’t find an opportunity in the quarter and close it in the quarter for a new deal. These are one, two, sometimes three-year sales cycles to break into these large organizations, and those are the ones that become the $10 million-plus customers. And as I said, we now have 184 paying us north of $1 million a year, and we’re very pleased with that growth up from 148. We see, based upon the ones that are just on the cusp of $1 million, that number will continue to increase.

That’s great. Thank you, and congrats again.

Your next question comes from the line of Derrick Wood with Cowen. Your line is open.

Thanks. First question, Mike, just wanted to touch back on the seasonality and consumption. Can you just talk about how the consumption piece came in versus your expectations and maybe compare that with how new bookings and sales productivity came in versus expectations?

I would say the quarter actually came in pretty much where we were expecting, slightly off from consumption in January, but not a huge amount. I will say, and I called it out, we were surprised at an enhancement we rolled out the profound impact of it. It was only out for a few weeks in January and had a $2 million impact. Other than that, we landed from a revenue standpoint where we were forecasting and guiding. I was really surprised with the strength in bookings in the quarter. You saw that we closed over $1.2 billion in contract value in the quarter, growing our RPO to $2.6 billion. That was well above what we were planning internally. The other thing I want to call out, too, is we co-sold with the cloud vendors, $1.2 billion in contract value for the year as well.

Great. Helpful color. And for Frank or Christian, wondering how you’re thinking about the opportunity around security. I guess as you look into the New Year, I mean, how much demand are you seeing around customers wanting to build security data lakes or security analytics on your platform? And is there anything you guys may look to do to lean in more aggressively?

Yes, we’re going to make announcements on this topic later on this year. But that has been raised in priority and focus quite a lot for Snowflake. It’s one of the best add-on selling motions that we have in large accounts. Snowflake is just an ideal platform for hosting that type of capability. So, you will see us lean into that opportunity a lot more going forward.

Thanks for taking my questions.

Your next question comes from the line of DJ Heinz with Canaccord Genuity. Your line is open.

Hey guys. Frank, a two-part for you on the data sharing stuff. So the customers that have embraced data sharing, how long does it typically take for them to get there? Like can that happen quick, or is it typically more with customers that have been on the platform for a bit? And then the follow-up, the part two would be, how much of an inflection in consumption does that typically drive?

Your first question, most of the time, not all the time, but most of the time, our customers have other priorities regarding transitioning their databases and their workloads before they get onto data sharing if they weren’t doing that before. But it’s also quite possible that we have workloads that are driven by data sharing as a core premise. And obviously, then it’s something that is a starting point, and that comes several iterations later. So it’s all… and so historically, our business has been very much a modernization play from existing workloads, and we have to wait some time before people sort of get their CLX under them, and they sort of move on to these opportunities. But that is starting to change, as we said in our prepared remarks. We now have 18% of our customers having at least one stable edge as part of their platform, and that was up from 13% last year. So the data cloud is really happening, and that is what a rapidly growing customer base underneath it. I forgot what was the second part of your question?

Just how much of an inflection that is in consumption?

Well, it hasn’t been an extraordinary inflection in consumption in terms of data sharing driving consumption per se. But data sharing is a core underlying capability of an overall workload footprint. So it’s really important in that sense rather than separating data sharing out as a specific workload driver.

Yes, so of the $800 million for Streamlit, how much is cash? It’s roughly 80-20, 80% stock, 20% cash.

Your next question comes from the line of Kash Rangan with GIS. Your line is open.

Hi, this is Kash here, guys. Thank you so much for taking my question. I’m curious to get your, Frank, your best-case scenario for Streamlit, the green vision, two or three years from now. What is Streamlit going to allow Snowflake to pursue in the machine learning data center that would consider it to be a success? And Mike, a question for you. I know that you mentioned that you’re passing along savings back to customers, but customers are also coming back and doing more workloads with you guys. So if you can just run to the rationale of why do you think renewal rate, net retention rates are going to go below 150 because it’s coming off of a very verified base and you, after all, earned the goodwill and trust of your customer. Thank you so much.

I’ll answer first, and then I’m going to turn it over to Christian, who is very passionate about Streamlit and what it can do for us. So in terms of your question on the enhancement we’re doing, listen, we’re running at 178% net revenue retention. These are extremely high numbers, it’s just the law of numbers for new customers that are coming into the pool. Remember, that looks back two years ago; a customer has to be on for two years. That number will come down. And the efficiencies we’re talking about, 10% to 15%, 20% depend upon the customer based upon the platform, that has to come down, that number. And as I said, it will remain above 150 for quite some time, but I do think it’s going to drop below 170 for the full year on average next year.

Okay, and I’ll comment – Christian here, comment on Streamlit. If you recall at Investor Day last June, we shared our vision to help organizations of all sizes build applications, data applications and data experiences on Snowflake. What we see with Streamlit is their super easy-to-use framework powering all sorts of applications, both for internal consumption of data within companies, but also coming to our marketplace and helping entire businesses. Some of them are industry vertical businesses, some of them horizontal experiences. But at the end of the day, unlocking the power of data and creating new data experiences.

Your next question comes from the line of Tyler Radke with Citi. Your line is open.

Thanks for taking the question. So Mike, your long-term free cash flow guide at Analyst Day was for 15% at $10 billion of product revenue, and it looks like you’re guiding to a 15% free cash flow margin for FY 2023. So maybe just give us a sense for what’s driving that big outperformance and how you’re able to achieve that so much sooner? Is it mainly the efficiencies that you’ve discovered over the last year? Just help us understand that.

A couple of things, we’re entering into larger customer relationships, and you can see customer consumption is picking up, resulting in the renewing contracts early, which drives that free cash flow. I do fully expect, as I said on the last call, that we will be revisiting our longer-term free cash flow and operating margin guidance. I do expect it will come up considerably, as I told you guys before; I’m not going to give you a number now. And I want to remind people to not be surprised when there’s a really big free cash flow number in Q1 because of how big our bookings were. But over the year, that 15% is the full year, and there is seasonality with Q1 and Q4 being the highest of the four quarters.

Got it. And maybe just on the quarter, as you recap this past year, how did the number of replacement deals of a legacy on-prem data warehouse grow? And just kind of what are you seeing in the pipeline as well on the legacy replacements?

Well, most of our net new customers tend to be a replacement of some legacy. Some can be cloud Gen 1 cloud products as well, but most of the large Global 2000 tend to be on-premise replacements. You can see that in our G2K ads and our Fortune 500 ads. But there is a lot of growth as well within existing customers, and that continues to be very strong for us as well.

Your next question comes from the line of Raimo Lenschow with Barclays. Your line is open.

Hey, thank you. Quick – two quick questions, if I may squeeze it in. Mike, if you look at other vendors, if they have product improvements that actually save their customer costs, they usually have like a sharing model of like the customer gains something and you gained something through maybe like price increases, et cetera. Is that something that over time could happen? Or are you really happy to continue to benefit back to customers? And then for Frank, just briefly, any update on the unstructured data opportunity? Because I remember that was a big focus for this year. Thank you.

Yes. So our whole philosophy is any improvement we do will benefit the customer, but it benefits us long term too because anything we do allows them to do more with the credits they bought at the price they pay, a certain price per credit. They can run more queries per credit they buy. And what happens is when customers see their performance per credit, and it’s trending, that it’s getting cheaper for them to run things. They realize they can do other things cheaper in Snowflake, and they move more data into us to run more queries. And so we have no intention on for existing customers increasing their pricing. What I will say is on new customers coming in, we will be very disciplined in terms of discounting with new customers.

On the topic, Raimo, on unstructured data, the uptake has been quite strong on that. We were expecting it, and that’s exactly what’s been happening. I mean, there are some really interesting new opportunities where data models are looking for relationships between unstructured data types and other types of data types, things that just weren’t possible before that are now enabled by the platform. So we’re driving this hard, and we have tremendous expectations for unstructured data in general and the potential for data science, innovation, and new data applications. Also in the context of the Streamlit acquisition, this is going to get very interesting for us.

Your next question comes from the line of Brent Bracelin with Piper Sandler. Your line is open.

Thank you and good afternoon. Frank, I wanted to go back to the workload discussion. I think one of the things that stood out to us over the last quarter was just the number of enterprises turning to Snowflake for supply chain, customer support, sales enablement, even machine learning workloads. I get data warehouse migrations will be the bread and butter business, but how big of an opportunity do you see in expanding the Snowflake footprint into these departmental areas? And how fast are those workloads shifting to Snowflake? Any color there would be helpful. Thanks.

I think it’s important for everybody on the call to understand that we are in the super early innings in terms of the total opportunity. What people are going to attempt to do with data is because the technology is running out front. There are many things that have never been done before. And it’s not like throwing a switch all of a sudden; everything is blinking green. We’re in conversations almost every day now with customers that are trying to do predictive things with data that they’ve never done before. A lot of the challenges they have is with skill sets that translate from their core business. The data side and the gaps that exist there to make that all happen. So there’s this very normal, natural friction in the evolution of that, that we’re trying to learn how to do these strengths. You see that in the world of machine learning a lot. It gets talked about, but it’s actually incredibly hard to drive these benefits in a highly predictable manner. There are lots and lots of attempts at it, and people are not already on the first attempt, seeing exactly what they were hoping for. But the march is inexorable in the sense that this is where it’s all going. I really think that a lot of the bread and butter that we do today, which is running large, highly-scaled analytical batch processes populating dashboards. When we come in in the morning, we get to see yesterday’s data. We’re running these workflows really, really well now compared to what we were doing in the past, but what is coming in terms of the potential is enormous. And as I said, it is early days in terms of this entire opportunity.

Helpful color there. And then just, Mike, a follow-up on platform enhancements. As you think about the impact to the guide, how much of it is mostly the warehouse scheduling feature versus other, let’s say, lower CPU pricing resources you’re passing on to clients? Just trying to think through what you’ve baked in. And is it mostly just scheduling or other things as well?

Yes. What I’d say from the gross impact, roughly 40% is coming from warehouse scheduling on a net basis, about 30%, and then the balance is coming from other software improvements and hardware improvements that we see happening.

Your next question comes from the line of Kirk Materne with Evercore ISI. Your line is open.

Yes, thanks very much. Frank, I was wondering if you can just talk about the GSIs and the progress you’re seeing there. I think Accenture had a milestone trained post pretty recently. Just what can they do for you from this sort of a demand gen perspective in fiscal 2023? And then just, Mike, on the platform improvements, can you just kind of conceptualize us how you think about that from a return perspective? Obviously, it’s a $100 million headwind. This year, I think you mentioned you start to see a pickup of six months later. How should we kind of think about sort of the benefit you get from delivering those improvements to your customers? Thanks.

So the way we look at it, the benefit is, first of all, the customers see an immediate price performance improvement. Our customers are always looking at price performance. When they compare our price performance versus running it whether in another cloud or running it on-prem in their existing data warehouses, they make the move to move more things into us. As a reminder, we have landed hundreds of customers to do these big on-prem Teradata migrations. I think we’ve only completed – we’re completely shut down a little over 30 of those, maybe in the mid-30s now. There are piles of other workloads that they plan on moving, and when customers see the price performance, they will accelerate the movement of those other workloads to us, and we have historically seen that. As I said, I do anticipate that we will see some of the same. As a reminder, we see the gross impact of about $162 million for the year, and we think we will make up about $65.5 million in revenue. A lot of that does – there is a lag, and that depends on the customer. It could be a one-month lag. It could be a six-month lag before they realize that and move more workloads. But based upon what we’re seeing, we think there will be about $65 million coming back in to get to that net $96.7 million, if you want to be precise what we’re estimating.

On your question about GSIs, I know you mentioned Accenture in particular; we’re expecting a much higher contribution and partnership with Accenture going forward. We’ve had outstanding relationships with many others, notably Deloitte. We also announced a relationship with KPMG. The intersection with the large SIs and these large Global 2000 accounts is inevitable. You will see more and more of that business intersecting with Snowflake, and those relationships becoming very, very large over time. Things that we’ve seen before in other companies is absolutely going to happen for Snowflake as well.

Your next question comes from the line of Karl Keirstead with UBS. Your line is open.

Well, thanks. Two questions. So Mike to start, does the Q1 April product revenue guide of $388 million assume a more conservative view on usage ramps, given what you flagged in early January? Or does it assume basically a return to normal activity seasonality?

Well, it includes about $10 million revenue hit because of these product enhancements that we see. And it’s based upon what we’re seeing today in terms of how customers are returning after vacations.

Okay. And then as a second question, if I could just press a little bit on the context of passing on these platform improvements. Companies normally don’t willingly make changes that cut 5% out of the revenues. So I’m curious, were you getting pushback from customers around price performance relative to alternative products, and you decided to try to alleviate that price pushback by making this change? Like what’s the broader context for doing this because it’s very rare?

I’m going to let Christian talk from a product standpoint why he and others feel this is very, and including me, feel this is the right thing to do for our customers and pays off in the long-term.

Yes. So, hi Karl, we’ve been doing this since the very beginning of Snowflake. We’ve always focused on improving the performance of the system, and we are very cognizant that it improves the economics for our customers. The rationale behind it is that there’s so much more data being created every day. The marginal cost and effort of getting value out of the data decreases; we know there’s a lot more value for companies to generate out of the data. We see it time and time again. The more we improve the economics of the platform, the more use cases come to Snowflake. So we’re looking at this with a very long-term view.

Let me say one thing, it’s Frank. This is not philanthropy. We are very much doing this because it stimulates demand. By the way, we can prove that to ourselves by going back years because we’ve done this over and over, and it does stimulate demand, but it doesn’t do it in real-time; there’s a lag involved in this process.

I will add, I think this is probably the biggest magnitude impact at one time in any platform improvement that we’ve done since I’ve been here.

First, the scale of the business.

Your next question comes from the line of Phil Winslow with Credit Suisse. Your line is open.

I'm through the pain; yes, like that, thanks.

Your next question comes from the line of Brad Reback with Stifel. Your line is open.

Great, thanks very much. Mike, I think earlier in the call, you had mentioned about 30% of the workloads are machine-to-machine. Can you give us a sense of where that’s been historically and where you think that can go to over time?

What I said was about 70% of the queries in the work are machine scheduled. They’re automated processes that happen because you want to refresh queries every so often, and about 30% is human-driven, and that’s been pretty consistent for quite some time. Haven’t seen any change there.

Yes. We also think we’re projecting workloads also under the influence of Python becoming available and more developer-centric workload coming our way, but which tends to be more interactive. You balance that out with machine learning models that we believe are going to be more scheduled in terms of generating predictive results and so on. So we think that breakdown might well hold over a period.

Got it. Sorry for getting that transposed. And one other thing I hope I’m not trying to transposing as well. I think you also said that there was $1.2 billion co-sold with the hyperscalers for the year. I think last quarter, you talked about $500 million, which would obviously imply you added $700 million – that seems like a really big number.

Yes. We were very – and we sold in total for the quarter over $1.2 billion just for the quarter, and roughly $700 million was co-sold with the hyperscalers. I would say zero was GCP, and the balance was Azure.

Your next question comes from the line of Ari Terjanian with Cleveland Research. Your line is open.

Yes, thanks for taking the question. Congrats on the close of the year. I just wanted to double-click on international. Could you provide more color if the consumption trends you saw in terms of the holiday seasonality were consistent across geos? And then just more color on your plans for FY 2023 and the geographic expansion this year. Thank you.

So I didn’t really notice anything by geo in terms of differences. And I will admit, I didn’t really dig into that, but I can’t think of anything, or I would have heard something from someone. In terms of – we continue to focus on international expansion. We think Europe is set to have a very good year this year. APJ, we’ve been investing a lot there. I mentioned we are opening new deployments. We’re getting requests to open deployments, a new one in India, for instance, there’s one in Brazil that we’ll be opening this year. We’re looking at another one in Asia as well in Europe; there’s another one or two that we’ll be opening. The reason we’re opening these is we’re seeing the opportunity. I do expect international will become a bigger portion of our revenue over time. It’s just that our growth within the U.S. continues to be phenomenal, especially in our enterprise segment.

Right, right. And then just one follow-up, if I may. Can you remind us, could you just fill out what were the impact of platform enhancements, both gross and net on FY 2022 product revenues?

Well, I just said about $2 million was Q4 for one of the enhancements we rolled out in January for about three weeks. That wasn’t even to all of our customers; it’s now rolled out fully. The other one we talked about at our Investor Day was the storage compression, which we did see a reduction in storage, bringing that down to about 10, but it ends up computing becomes a higher percent, and that helps our margins.

Ladies and gentlemen, there are no further questions. Thank you for your participation. This concludes today’s conference call. You may now disconnect.