Snowflake Inc. (SNOW) Earnings Call Transcript & Summary

Michael Scarpelli, CFO of Snowflake, needs no introduction. I think this is your first Goldman Sachs technology conference, right?. Isn't it, in person? This is your first?

As for Snowflake, this is my first Goldman Sachs tech conference.

Thank you. Welcome.

But I did a few at ServiceNow and even Data Domain.

Welcome to the first Goldman Sachs Communacopia and Technology Conference as CFO of Snowflake.

Thank you.

Thanks for coming. I know you had your big user conference a couple of months back, a lot of announcements, et cetera. So what is the management team's wildest aspiration? What are the aspirations for the company 5 years from now?

We believe that we will be a meaningful player in being a -- the data cloud. Really, we want to be a place where people can develop applications directly in Snowflake. We think -- and a lot of the stuff that we have coming out in our pipeline over the next 12 months, it will be either public preview or GA, things like Unistore or containerized services, streaming dynamic tables, stream let. We're pretty excited about what's happening with Snowflake. And by the way, these are all things we've been working on for many years, like Unistore has been a 4-plus year project for us. Iceberg Tables is another one that we've been working on for a number of years. A lot of people ask us, why can't you do these things quicker? Well, there's a whole -- when you're working at the infrastructure layer, you just have to get everything right. You can't be wrong. And at the end of the day, we're 1 product, and everything works together and everything you do at the infrastructure layer benefits everything. And so it just takes time and this whole private preview, public preview, why do we do that? We learn a lot. Like Iceberg Tables, we came out in private preview with that. We learned a lot from customers, and we completely rearchitected it, and it just takes years to do. And so you need to be patient in the world we live in because you want to do it right, and it's really important, too, because one of the benefits of Snowflake is it just works, and it's very easy for our customers to use and we don't want to lose that. So we're not going to rush to get things to market until we're ready.

And which are the -- you can guess what question I'm going to ask which is what key features do you think is the most exciting to you? Well, you probably tested these things, private preview as a CFO, you probably have teams...

I'm very pleased with the uptick we're seeing in Snowpark. We really have only been in GA for Snowpark for Python for about a year now, but it still takes time. We've done a lot of these technical wins. With POC it showed that we are cheaper, and it takes time to do the migrations. We have a lot of migrations that are happening right now that will go into production. And I think we'll be meaningful contributors to the growth of what we're seeing already within Snowpark. But I'm really excited about containerized services that will be coming out middle of next year, and that really enables 2 things. It enables our customers to be able to bring their own large language models into Snowflake to fine-tune on their data where they know the data is going to be secure and stay in Snowflake, that's not going to get outside of Snowflake. That's one of the biggest concerns we hear from enterprises is training their models on their data. They're afraid of it getting into the public domain. I know highly regulated industries, think banking like you and health care and others are super concerned. So they're not rushing to do things. They're going to be very methodical on how they think about the different use cases for generative AI in their businesses. The other thing, containerized services makes it easier for people to build applications on top of the data in Snowflake. And then it enables to that independent software developers can build applications that can monetize it through our marketplace to make it easy for people to procure those applications in our marketplace. A lot of -- I'm pretty excited about it.

A couple of things.

And by the way, we've been working on this for a while. But more importantly, what's going to continue is data sharing. Data sharing is a key differentiator for Snowflake. That is a great lead generation for us, and we really see that taking off in financial services, in particular. But we're already starting to see a lot of customers coming to us because of what other customers are doing on data sharing. We're seeing a lot of our customers who are actually telling their suppliers of data they want them on Snowflake. Or the people who buy their data, we want you on Snowflake to do it through data sharing.

Network effect.

It's a huge network effect data sharing. And a lot of people talk about data sharing, but we're really the only ones who do it where the data actually never moves, that always resides in -- the custodian of that data always retains that data.

Now Snowpark, you've said for a product that's been GA for the less than a year, it's doing quite well. What use cases are you seeing the most with Snowpark, what are people using Snowpark for?

A lot of data engineering use cases, starting to see some data science use cases. We're replacing a lot of open source smart EMR and starting to see some Databricks as well too and stuff.

You said something that intrigued me.

What's that.

You mentioned a company by name there.

Well, I'm just...

So since you mentioned them, you brought it up, I'm curious to get -- so they had a conference recently and they talked about performance -- price performance advantage for the SQL warehousing product versus not a very large company.

It's funny to say that. We never see their SQL product and they undercut the pricing on that to try to win stuff, but we just don't see it. First of all, I think Databricks is a very good company. I'm not going to say anything bad about them. What they do very well is in the data science. They still do a lot of ETL. They coexist in so many of our accounts. We've brought them in. You go talk to -- I know in your bank uses both Snowflake and Databricks and will tell you that this is where -- how we use Databricks, this is how we use Snowflake. You go talk to most of our accounts, and they really see them as very, very different products and we do too.

Had dinner with our engineering organization yesterday, some of the senior leaders, that's exactly what they said.

I guarantee you talk to Nema and he'll tell you that. But you go talk to AT&T or whoever, and they'll tell you that they're very -- they don't see them as competing products.

Exactly.

By the way, it's a massive market we're playing in. It's not a winner take all. There's going to be many winners in this space.

Exactly. That's good to know that -- good to know that. With -- with those announcements, the stream of things that came out at your user conference, the Unistore, let's talk about that, that -- that could be a big, huge opportunity. The size of the relational database market is just so massive. And it felt like you had taken a little bit longer to crack the code on that or maybe it was a little bit tougher where are we with beta customers, whatnot? How close are you with the technology to unlock that market.

Yes. We're actually very pleased. We actually have 10 customers that are using it internally in production today. It will go into public preview soon. I don't think that's going to be very different. That's going to be new use cases and new development work will go into Unistore. I don't think that this as going in and replacing traditional OLAP databases. This is going to be -- it's not going to have the performance of a Oracle. It's going to -- think about like 10 millisecond latency is where we think the performance needs to be. And so we're pretty -- and it's going to be more data-heavy analytic type of use cases that we see it being used for.

Got it. Got it. Since you have a good feel for the pulse of the customer I had to preface why I'm asking you the question this way. Jan Hatzius who you might know, our Chief Economist, he's been calling for a soft landing for quite some time, and everybody has been calling for a recession. He's been pretty spot on so far. Inflation seems to have come down, not to the degree that people might want, but it's come down quite a bit. There's a sense that things are stabilizing. I hear the word stabilization from practically every single company. The last 18 months interest rates went up massively. None of us has been through really that big of a rate increase cycle in our adulthood. Next 12 months, let's say, things are normal, stable, stable. What do -- what do you think budgets look like for next year? As you talk to customers? Are they looking to finally come out of this funk and spend after 2 years of being frozen to submission by the fears unfounded of a recession?

Yes. I can't comment in general about the economy and what's happening. All I can tell you is what I see in our customer base. We talked about on the call, we definitely saw a shift in sentiment. I would say it was really kind of July we started seeing customers ring. A lot of customers during the uncertainty in the early part of the year were just buying monthly as they went when they had fully consumed under their contract and their contract enables them to just buy monthly, and we call it just doing capacity purchases. We really saw customers who could have elected to do that in July that said, no, I'll sign a new contract now. I know I have one customer that will fully consume and it's one of our big customers in January, but I know they want to do something this quarter right now are willing to do a longer-term commit. So the sentiment seems good with customers. And I think it's them having more certainty in their businesses, not as doom and gloom as people were thinking maybe 12 months ago, 9 months ago. So the pulse from our sales force is things are improving right now. In terms of -- I think it's still a little early to see what that's going to mean in consumption. We talked about it on the call that we definitely see stability now in terms of consumption. We're not forecasting a recovery right now, but definitely stability. A lot of people talk about optimizations, probably optimizations and AI are probably the 2 most overused words. We've been talking -- we've seen optimization since day 1 in our installed base of customers. If you go back I think 3 investor days, before anyone we were talking about optimization.

Even a protocol warehouse is optimization to me.

Optimizations happen for a number of reasons. Some we drive those optimizations and those are performance improvements in the software. And we think those are actually the more meaningful ones. Customers do optimizations. And optimizations typically happen for a few reasons. When you do a migration to Snowflake, you want to tag your data that goes into the Snowflake you index it, everything. And as you add more data, there's turnover in headcount, people get lazy. They don't tag the data properly to indexes. So when things get out of indexing and your queries take longer to run, we go back in and you can -- some customers will call that an optimization where they reindex everything. So they clean it up so your queries run more efficiently. That's a common one. People look at retention policies. People look at, can I write my queries more efficiently. And by the way, we learned too, we had one of our customers they figured out this way to do what we call a delta merge that makes the running of things much more efficient. And as a result of that, we're now rolling that out in our software itself. So all of our customers get the benefit of -- those are types of optimization, but every one of these things improve the price performance of Snowflake.

And that's really good to see. So when you look at net expansion rates, let's look at consumption for a second. Did things continue to show the rate of improvement as you exited and as you announced your earnings in the past couple of months?

I'm very pleased with what we're seeing in the consumption patterns of our customers right now. I'll tell you this is webcast. I looked this morning, our top 10 customers, 7 out of the top 10 are above what I was forecasting would be, 3 were below net-net, they're above. So I'm pleased that when I look at the -- I really look at the week-over-week to get a comparable. It continues to grow and is growing very nicely right now.

Good. And we cannot unfortunately mention this e-commerce company by name, we cannot. We just cannot. But there has been stuff in the media. I don't know if you can...

I can, Instacart.

I didn't say that. I just cannot say that. Anything you want to offer to our clients by way of clarity.

Well, if you actually read the F-64 page, it's pretty clear. Don't mix payment terms up with consumption. What happened with Instacart is I think they -- don't quote me on this, but there was some -- they paid $51 million. And then it's -- they said they estimate they're going to pay us $15 million this year. But the reality is, the reason they paid us $51 million is because they made 2 payments in that year because their contract the way it worked, and we went in and we had done a big optimization for them, and we had been telling them for a number of years because I know, I was very involved with Nick, the CFO on driving that optimization. And we took a bunch of costs out, but they still consumed $28 million, $28 million of Snowflake and then it dropped to $11 million. That was the -- we did the optimization, but they're now -- they're tracking back up. They'll consume $25 million roughly this year. It's starting to grow again. But that was through a massive optimization we did there, and a lot of that was because of a lot of inefficiencies, the way they had set up Snowflake.

That seems to be a pattern across everybody's customer base. I mean it looks like everybody -- Amy Hood was here earlier today with Microsoft, and she said that we're reaching anniversary effect of optimization, the worst of the optimization.

I'm not saying we're over with that because as I said, optimizations have always existed in Snowflake. It depends upon the customer. Our second biggest customer is one of the most efficient customers, and they're very technical. And I don't see any waste in what they're doing, but some other customers, they just grow so quickly. And what I would say is there's a lot more trained people on Snowflake today than there was 3 years ago. And a lot of the people that people hire have lived through optimizations. So these people are going to know the pitfalls of what not to do and what's best practices. And the more people we have trained on Snowflake it will lessen the effect of those optimizations. It's a customer-driven optimization.

Mike, maybe we can pivot gears a little bit to the competitive landscape? And maybe first on the hyperscalers, how would you characterize the competition from the hyperscalers and core data warehousing, particularly maybe around GCP, BigQuery, what does that look like today?

GCP is definitely the most competitive BigQuery. It has been since day 1. AWS, obviously, is about 78% of our business is in AWS, 20% in Microsoft Azure and 2% in Google. Google could be a lot bigger, but they are very -- the most competitive. I've been -- we actually will fully consume on our contract before it expires in end of May, June '24. I think we'll fully consume the 5-year commitment we had made in October, November. I'm working with them on a new contract. Hopefully, we can come to terms on more, I would just say we're still going to compete but actually have maybe better ground rules in the field to see what we can do, something closer to Microsoft or AWS. Microsoft, it was huge that we signed a new contract with them because it's much better for the field where their reps are now getting paid on -- It's not one for one, but they're still getting some compensation. And as you know, salespeople are very coin-operated, so it's important they get paid. So hopefully, we'll be in a better place with Google in the next 3 to 4 months.

Makes a lot of sense. And then maybe on...

And by the way, they're much more expensive -- it's way more expensive and -- for us. If I look at my -- it's not product margin, it's contribution margin. AWS and Microsoft run about 82%, 83% contribution margin. When I just look at what their costs are, GCP environment for me runs at 58%. That's a material price difference. And then egress charges for GCP are crazy. They're almost double what others are.

Just one question, Matt, and you can go back here. Have you looked at Oracle?

We are actually spending a lot of time looking at OCI for a number of reasons. Some of our customers would like us to be there. We're still -- we've done the first phase of technical analysis, and it looks good, and we're -- stay tuned.

And Mike...

I think that would actually -- because I know they've committed to be the cheapest cloud for us, so we'll see.

On Databricks, right? So you talked about how there's still a lot of overlap in existing customers accounts, but it does seem like a lot of the innovation coming out of Snowflake with Snowpark Container Services, getting more into the data science use case, predictive analytics. And then on the flip side, Databricks getting into the market with Db SQL, like are you seeing some degree of overlap in terms of kind of RFPs? Are you seeing them more frequently? How would you characterize the competitive landscape today versus 3 years ago?

We -- well, it's definitely more competitive today. A lot of that is because of what we're doing with Snowpark. We never -- it's always BigQuery, Microsoft not even as much AWS. And we're going into a Global 2000 looking at doing a big on-prem migration, Databricks is not there. Where we compete with Databricks is within our existing accounts on a workload-by-workload basis. We do compete with them, and we have to show that we are more price performance than them.

This is in data warehousing, Right?

In data warehousing type applications. The reality is, though, is you need to really understand all of your costs of Databricks because remember, they're selling the software and you still have your cloud costs that you need to pay for. And it all comes down to price performance.

I think you talked a little bit about...

I think they're very strong on the data science side. They're very strong. That's probably their core competency.

You talk a lot about migrations to the platform, from legacy incumbents, right? It seems like you're gaining a lot of traction with the GSIs in that capacity. So can you just talk a little bit about the runway you still have to displace some of these legacy providers? And who are you displacing those?

So we still displace a lot of Teradata. You look at -- and there's still a lot of Teradata out there. It's going to be years and years before Teradata is fully shut down. I'm not even going to say it's going to be fully shut down. I don't know. There's going to be some people who just resist. Did you know we're still replacing Netezza. We replaced a lot of Hadoop -- we replaced a lot of SQL server. We've replaced a lot of first-gen cloud. There's been a number of failed Synapse implementation. We still replace a lot of Redshift and we replaced BigQuery.

Is it because these implementations were smaller in scope because of the products didn't work as advertised and then you go in replacement, you're getting -- because if you just queries...

They hit scale, and they don't have the scalability, Redshift. Synapse, just -- there's very, very, very few successful implementations of Synapse out there. Even I think Microsoft has back away now, they're talking Fabric which is going to be another 2 to 3 years. Architecturally, that looks better, but still that's a long ways before it's actually going to be a product out there. And BigQuery is just expensive. And Google has actually been raising prices with people, too. They kind of give them those cheap prices coming in and then when it comes up for renewal. And once again, we show price performance on Snowflake.

So Mike, maybe we can talk about kind of this $10 billion product revenue guide, right? So you guys came out with this target back at the time of IPO. But since then, you've announced a number of new products, Snowpark container services, document AI, a Native App Framework, you acquired Streamlit. So it seems like there's a lot more levers for growth than you had at the time of IPO. So what's kind of -- how would you characterize kind of your conviction in your ability to hit that $10 billion relative to maybe last year, even the year subsequent -- prior to that.

I feel good about our ability to hit that. Obviously, we're in a consumption model and who knows what new technologies could come out within 2 years from now? I don't know. And it's not about -- I'm not worried about the people we see in front of us. Usually, the real competition comes from a new company that's kind of in stealth mode right now. I don't know. This was one of the biggest things I always worried when I was at ServiceNow and it still shocks me today that there's really been no competition for ServiceNow. I feel good, especially with the products that we have coming out, the acquisitions we've done. I'm super pleased with Neeva in particular, but Streamlit was a great thing. As I mentioned, I think it's been a home run that Meta open-sourced Llama 2. I can't believe all of our...

What is the home run?

The fact that Meta open-sourced Llama 2. That's huge.

How are you benefiting from that?

Because it enables our customers without having to go through any type of procurement process to bring their Llama 2 into Snowflake to fine-tune it on their data where it stays in Snowflake. And by the way, we think that model is pretty much the same as ChatGPT. They're probably a few months behind right now. So that's been a real home run.

So that's a source of demand. The training models on your data.

Absolutely. That's one of the biggest...

That is unstructured data. So are you talking about Snowpark or just the regular...

The regular data.

Tell me -- so okay, I've not heard...

I'm not the technologist.

No, it's interesting. I didn't think that they would be training their LLMs on your architecture. Is that a trend you're seeing?

In talking to all of our technical people, yes, I think it's going to be very common. That was one of the things why NVIDIA wanted to -- the partnership with them is really their Nemo software to be running in Snowflake containerized services that you can bring your large language models and work more efficiently with the NVIDIA GPUs.

That's the -- the interview between Frank and...

Yes. That's what it was all about.

It was crazy. I was just blown away by what they were -- we all are trying to think that it's unstructured data, content generation, poetry writing, image generation, video generation, code generation. But this one, like looking at structure data...

This is looking at structured data. And then what I was saying the acquisition. So super pleased with the Neeva acquisition because of the level of talent that we got there, but also bringing the enterprise -- what was interesting was the enterprise search capability. They were trying to build a search engine to compete with Google, which was going to be though ad-free but it would be paid. And just -- by the way, this is the guy who built the whole ad business at Google for 16 years. And so we're going to be their enterprise search capabilities for customers to be able to find their own data in Snowflake but also understanding listings in the marketplace. I'm very excited about that. That team under Sridhar, who was the founder, Sridhar Ramaswamy. He's running all of our AI and ML initiatives. The acquisition we did of Applica that people don't talk a lot about, but that really enables that -- our document AI, which enables you to be able to take PDFs and contracts and be able to search for terms and put it into a structured format, being able to take simple text to convert it to SQL code. That's all part of what these guys have demoed in the company. I'm not going to use -- I'm trying not to use the word Gen AI because every investor is talking about it. It's so overused. Until enterprises really figure out what they're going to do, it's hard to talk about it.

That's true. Any questions? Yes, Nancy. Let's bring a mic over to...

Mike. Can you just talk about some -- how you're thinking about the pricing of some of these ancillary tools and products? Will they all be consumption-based or will you think about that a little differently and embed that into the offer?

Good question. Everything is consumption based. And that's the beautiful thing as we roll out a new product. There's no procurement process we need to go through because they -- people buy capacity and they can just consume based upon that. Obviously, we -- in essence, we sell a credit in which a credit equates to 1 hour on 1 node of CPU server. GPU pricing, we're trying to figure out what -- how many credits it's going to be per node of GPU because it's much more expensive, but really, that's what we sell. And anything we do is going to drive compute.

[indiscernible]

It's on the menu and you can use your point. So it's the view of like Snowpark today. It's not a new procurement cycle.

Can you provide a little bit of color just on how it works with the AWS cost and how it's bundled into the pricing? And over time, how you're thinking about the diversification between AWS, Microsoft and Google. I know there was some announcement just on how there would be an interest from the company to have a little bit more diversification from Microsoft?

So the way the pricing works is that's included in our COGS, a customer never -- does not get -- when you use Snowflake, you get 1 bill, Snowflake. We pay the egress charges if you're moving data from, say, many of our customers are multi-cloud. If you're moving data from Azure to AWS or vice versa, you just get 1 monthly Snowflake bill and we pay all the costs directly. In terms of -- right now, as I think I said earlier, 78% of our business is AWS, 20% is Microsoft, 2% is Google. I think AWS will always be our biggest just because of where they're at. But definitely, Microsoft is growing. I would love Google to have a better go-to-market with us because I think they could be bigger. But I think it will always be AWS, Microsoft. And if it's not Google, it may be OCI one day, I don't know. We'll see. But that will be a while.

We'll wrap it up on that Mike, thank you so much.

Thank you.