Q3 2021 Snowflake Inc. Earnings Call

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Ladies and gentlemen, thank you for standing by and welcome to the Snowflake Q3, and fly 21 earnings call.

At this time all participants are in a listen only mode. After the speakers presentations and will be a question and answer session.

Ask a question during the session you will need to press star.

And one on your telephone.

Please be advised the todays conference is being recorded the.

The few requiring the further assistance. Please press star Zero I would now like and the conference over to your Speaker today, Jimmy section and head of Investor Relations. Thank you. Please go ahead.

Good afternoon, and thank you for joining us on Snowflakes Q3 fiscal 2021 earnings call. Joining me are Frank Slootman, Our chairman and Chief Executive Officer, and Mike Scarpelli, Our Chief Financial Officer. During today's call. We will review our financial results for third quarter over quarter of fiscal 2021, and discuss our guidance for the fourth quarter and full year fiscal 2021.

During today's call, we will make forward looking statements, including statements related to the expected performance of our business future financial results strategy 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 the form 10-Q for the quarter ended October 30, Onest 2020 that will be filed with the SEC today, 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.

The of new information future events or changes and our expectations.

We'd also like to point out that on todays 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 and.

Non-GAAP financial measures are presented in addition to and not as a substitute to for net for financial measures calculated in accordance with GAAP to see the reconciliation of these non-GAAP measures. Please refer to our earnings press release distributed earlier today, and our Investor presentation, which are posted the investors debt Snowflake dotcom a replay of today's call will also be posted on the web.

With that I would now like to turn the call over the Frank.

Thanks, Jamie and good afternoon, everybody and thanks for joining us on our inaugural earnings call.

Lets review the results, we saw strong consumption trends across our customer base and Q3 of the product revenue growing 115% year on year to $148 million and the net revenue retention rate of 162% cash.

A couple of this rapid growth, we continue to see improving unit economics of cash flow and operating efficiency our.

Our growth is driven by long term secular trends and data science and analytics enabled by cloud scale computing with the onslaught of digital transformation data operations have become the beating heart of the modern enterprise.

The pandemic has been more or less neutral to our business. Some businesses were negatively affected in terms of the non sentiment for the other stepped up to the data strategy given the new complexities of the health crisis and economic effects.

It bears repeating the snowflake is not a SaaS business model work consumption company and our reported revenue has a direct relationship with the consumption of our platform during the period because.

Because sumption model is variable non fixed meaning of modeled places no limits on how much of our platform and customer can consume and this contributed to our strong revenue retention of risk.

The technology is now ahead of the People's ability to take advantage of virtually unbound the capacity scale and performance.

Over the past year Snowflake has augment and its selling motion to campaign some of the largest enterprises and the institutions in the world Snowflake is well represented of now and eight of the Fortune 10, and we added 12 Fortune 500 customers in Q3, including five serve and Geico.

Interest and Snowflake is growing we hosted our Snowflake day, the club summit two weeks ago with over 40000 registrations.

Up from 15000 registrations other snowflake summit in June.

Shifting gears I'd like to take a moment share and introduce you to the Snowflake day, the clock because of the centerpiece of our mission and strategy.

As an industry, we have struggled to mobilize our data meaning of the spin hard to put data and the service of our enterprise and we set out to change that of.

We see it we've never had the data cloud in the history of computing, we are used to SaaS applications as application clouds, and the massive infrastructure clouds, and Kws Azure and Google cloud servers and storage you can consumed by the strength, but.

But the.

Data lives, absolutely everywhere and millions of places held hostage by the machines applications networks and clouds.

We have long needed to blend and join disparate data sets and Thats why we build data warehouses and the first place there were expensive capacity constraints and required tons of data preparation and manipulation prior to use.

The only the largest most demanding data states could afford these platforms. So the were never pervasive.

Snowflake changed that drastically scaling down to the smallest jobs and the radically change and the economics, where the highly elastic utility model.

Not only that everybody now four of these great powers Snowflake also remove constraints on date of volume plus the performance and current workload execution.

Even high end users reported being able to cut their existing spent and expensed their workloads dramatically at the same time of.

As compelling as snowflake was the turbo existing workloads old habits die hard.

Many customers are still evaluating data platforms, one workload at a time basically limiting data operations to their silos of flux steering the ship by its wick future work load will look different with machine learning and data science, becoming ultimate users. The workload of the time the tail mentality leached of billing the silos of.

Of the future.

The Snowflake data cloud is a data universe, a global data orbit were snowflake users effortlessly plug and discover explore and access data from an incredible growing variety of sources, it's a different way of thinking about the data needs of the future. This.

The Snowflake data cloud combines world class execution with unfettered data access customers need both.

We are seeing promising signs of adoption with already 23% of our customers using our data sharing capabilities. We also continue to onboard new data providers and in Q3, we added standard and Poors Global Morningstar and core logic to name a few and we now have over 100 data providers on our marketplace.

At the Snowflake data cloud summit, we heard from customers about the impact of the data cloud is having on their business a retail rewards customer has fully embraced the data cloud snowflake allows them to securely share data sets with media partners and from our customer facing applications to target the end users.

Commercial data providers are also turning to snowflake to reach new customers and monetize our data.

The making the data available and the snowflake data marketplace Experian helped retail customers accelerate their digital transformation efforts experience retail customers are now reaching shoppers and online insights garnered from snowflakes day, the marketplace to reach customers were no longer shopping and stores.

With highlights from product announcements from the Snowflake data cloud some of the November 1st.

We've grown our partnership with Salesforce. The previously announced the upper connector is now generally available and allows customers to more easily leasing salesforce data lift snowflake.

Secondly, we announced snow park, our new developer experience Snow Park will enable users to write code and of preferred language to build data transformations and score machine learning models all process by snowflake through.

Third we announced support and structured data in addition to our longstanding support for structured and semi structured data and.

And lastly, we are enhancing our data governance strategy with the introduction of roll access policies tagging and call and masking. This will help our customers control access by user type in a highly granular fashion very important given the heightened sensitivity around data governance.

These capabilities are essential to growth and the data cloud and you can expect more price platform enhancements from us going forward.

Before closing I would like to highlight the upcoming and release of our book the rise of the data clouds.

We wrote this book because of the data cloud is the centerpiece of our strategy and vision, we showcased many customers and numerous vertical industries with their snowflake journeys and experiences and it's meant to and enlighten and inspire something we called the art of the possible. The book will be available on December 4th.

In closing, we're pleased with the quarter and excited about the momentum coming out of the data cloud summit as we head into the final quarter of our fiscal year with that I will turn the call over to Mike. Thank you Frank before I discuss the results and guidance I would like to spend some time discussing are unique and powerful business model.

We are not of SaaS model, where our consumption model our business model is the key differentiator for us and it's designed to drive customer success, our customers purchase credits and when those credits are consumed we recognize the revenue. Unlike a ratable model, we only recognize revenue and the customer uses our platform for this reason.

There is no shelfware and our revenue.

For many customers. It takes several months up and until they are up and running at full capacity and this model gives and the flexibility to purchase the amount they plan and using without wasting credits or exceeding the original contract if they consume more than planned for these reasons, we do not focus on the same metrics at the SaaS business would.

We focus on product revenue and the remaining performance obligation.

Product revenue, which excludes professional services and other revenue is the most transparent disclosure we offer it gives the full insight into how our customers are actually using our product and the period reported if a customer purchases credits and does not consume their revenue will be zero dollars. We also focus on the remaining performance.

The obligation or our PEO.

Our PEO represents all of the contracted revenue not yet recognized including both deferred revenue and non cancelable contracted amounts that will be invoiced and recognized as revenue in future periods. Unlike most SaaS businesses billings is not a meaningful metric for us because of the because it has less core related to product revenue.

Due to the variability of consumption and we'd also like to mention that our GAAP financials will now be available on the snowflake marketplace and we encourage all of you to consumer financial information and the new way going forward when the publishing our quarterly results on the marketplace and conjunction with our earnings now, let's turn to our range.

Salts and guidance.

For Q3 product revenues were $148 million, representing a 115% year over year growth. Our remaining performance obligation was $928 million, representing 240% year over year growth with a weighted average life from multiyear contracts of 2.5 years.

This strong performance is driven by our customer base, realizing the value of our platform for their existing use cases, while also embracing the snowflake data cloud vision as I mentioned earlier, our business model allows our customers to consume their entire contract before the end of the term which is what we often see we also.

Continue to see customers willing to make more multi year commitments with us which is a direct result of the value of our customers can create with us as we continue to scale. We are increasingly focused on moving up market and you can see the benefits of those investments paying off and Q3, we saw the number of customers consume.

Looming greater than $1 million and trailing 12 and product revenue increased to 65 up from 31 and the same period last year.

Turning to margins on a non-GAAP basis, our product gross margin was 70% positively impacted by onetime credits received from the cloud service provider in connection with our new agreements.

Operating margin was negative 30% benefiting from lower than expected employee related costs and our adjusted free cash flow margin was negative 23% positively impacted by prepayments coming and lower than expected and stronger operating margin going forward, We will report and guide non-GAAP adjusted free cash flow.

Adjusted free cash flow will exclude the impact of cash paid for employer payroll tax items on employee stock transactions. This quarter, we saw eight and 800000 dollar impact from those items for a detailed bridge of cash flow from operations to adjusted free cash flow. Please refer to our investor presentation and our.

IR website, we ended the quarter and a strong cash position with approximately $5.1 billion and cash cash equivalents and short term and long term investments. This capital allows us to invest and new strategic initiatives, such as Snowflake ventures, which we announced last month Snowflake ventures mission is to enable.

More organizations to harness the power of the data cloud to do this we will invest in growth stage companies that demonstrate a commitment to mobilizing data provide value to our customers and expand opportunities for the day to cloud. Similarly, we will continue to evaluate strategic tuck in opportunities and M&A focused on.

Talent and technology, our acquisition strategy aligns with our product strategy everything must be done the snowflake way and that means delivering as one native product.

Now I would like to give an update on how we view covance impacting our forecast our forecast assumes our employees will continue to be working remotely for the foreseeable future. We have proven our ability to maintain productivity during the pandemic and no rush to return back to the office and regular travel leveraging the zoom and other collaboration tools.

We have been operating at a high level and able to smoothly onboard over 500 employees. During the pandemic. We believe we will eventually be back in the office, but until we have a new information and can guarantee or employee safety. We will continue to work from mostly.

Now, let's turn to guidance for the fourth quarter and full year fiscal 2021.

For the fourth quarter ending January 31, 2021, we expect product revenues of between 162 and $167 million representing year over year growth between 97, and 103% turning to margins, we expect on a non-GAAP basis and implied 70 per.

Per cent product gross margin negative, 30% operating margin and negative 8% adjusted free cash flow margin and we expect 283 million weighted average shares outstanding.

I would like to remind everyone that because of our consumption based business model, we do not recognize the revenue and immediately after the deal was booked for this reason you may not see of revenue beat flowing through to the next quarter like you would and a ratable business model, just because the customer consumes and a certain pattern one quarter and does not necessarily mean they will.

We continue those patterns going forward for the full year fiscal 2021, we expect the product revenues between 538 and $543 million representing year over year growth of between 113 and 115%.

Turning to margins, we expect on a non-GAAP basis, 68% product gross margin negative, 40% operating margin and negative 18% adjusted free cash flow margin and we expect 255 million weighted average shares outstanding with that operator, you can now of the line for questions.

And at this time I would like to remind everyone in order to ask a question press star one on your telephone keypad.

To withdraw your question press, the pound or hash key.

Please stand by and what we compile the acuity roster.

Your first question comes from the line of Heather Bellini from Goldman Sachs. Please go ahead.

Great. Thank you very much gentlemen, and congratulations on the first quarter out of the gate.

I wanted to ask a little bit you mentioned kind.

Kind of keeping your employees home as the result of kind of within the top banks are state, but wondering if you could share with us the little bit about.

What you've noticed in terms of the pace of consumption trends.

As the Pandemics and going on and as people prioritize moving to the cloud can can you share with us any anecdotal data about how customers might be even accelerate and their pace of.

Capacity usage with sales like thank you.

Yes, Frank.

Ill give you. One example, we have the data set on our Snowflake did a marketplace. The list the by a company called Star Schemer.

The provides detailed incident in the fatality of rates very very detailed and are updated continually.

And we saw almost our entire.

The customer base access that data within within days and weeks and.

The one that happens it's it drives consumption than that and that access house has continued.

To this day, so sometimes you have catalyst and specific data sets the really help customers.

Overlaid data run models and understand our demand environment better and.

And so on.

It's hard to generalize. This is just sort of a single anecdotes of kind of stands out to us.

I would add Heather that we do see and certain industries like we have some customers that are and the travel industry, we see their consumption down, but we have a lot of customers that are kind of more in the end of the.

Online consumer world that their business is booming and their consumption is is much higher than we're forecasting. So it all depends upon the industry of their end, but on average were seeing our customers consume more than we would expect that's why we ended up beating by what we did it was higher beef and I was expecting for the quarter.

Great. Thank you so much guys.

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Your next question comes from the line of Raimo Lenschow from Barclays. Please go ahead.

Hey, Thanks, Congrats from me EPS, both for the first quarter and Pat Thanks for the presentation of all lots of useful information in there and.

Frank question for you you've mentioned on the earlier in the balance the data for most of your kind of dealing with and the acknowledging also like unstructured data can you talk a little the little bit about the evolution. The clues when spoken of started out of was a very good relational cloud data warehouse and then when you guys keep the key much broader can you talk of the.

The best like how how do you see debt evolving how quickly you see customer adoptions and the and the other areas of of and working with data coming through as well and then I have one follow up from Mike.

Yes, so the the overarching.

Theme here is that we have evolved snowflake from the.

And the data warehouse in.

And the cloud to being a cloud data platform and the distinction there is a much expanding scope of workloads.

For those who have not been following of Snowflake that long, we actually got our start.

Processing semi structured data that was really big.

Big differentiator for US you know going back to 2015 16, yes, but certainly the structure relational data is the is the main stay.

Of our business, but when you following and cloud data platform strategy. What happens is of that our customers are sick and broader workload support from.

Broader data support and we also announced.

Couple of quarters ago support for geospatial data and the uptake of the of that new data type is just enormous shutters ferocious appetite in our customer base for us expanding.

The scope of our capabilities both in terms of workloads and in terms of debt types and our ability to use the external services. So it's a very broadly capable of platform customers don't want you know a multitude of platforms and their environments. They are very very intent of bringing as much data as the.

Possibly can onto snowflake and running as many workloads as they can on snowflake and we're running hard to enable debt.

Okay perfect. The thank you and then Mike on gross margins I got the 68% and gross margin kind of comment you gave can you talk a little bit about the puts and take and terms of tax and the long run obviously the bigger scale you have more negotiations our with the the cloud vendors how is that going to change the margins going forward. Thank you.

Sure. So as you saw for the most recent quarter, we just did 70% gross margin and the implied for the full year is 68, but we're actually going to do 70% margin in Q4.

As we talked about when we are going public I do think longer term in terms of model, we can get to the mid seventies, and it's really driven by a few things one is.

The better pricing with their cloud vendors, we did just renegotiate deals with two of our cloud vendors ADW asked and Azure, who are the majority of virtually all of our businesses run and there today and I do think as we can continue to grow we'll be able to renegotiate those again scale, we have a lot of deployments around the world, we're not even close to being at scale.

And especially as EMEA is starting to take off for us and we will get more scale and those which will drive better.

Better margins for US and then also we're seeing a lot better discipline in our field around discounting and if you see the average price per credit we're getting a continues to increase.

So those are the three things that are really going to drive that margin.

Okay perfect. Thank you congrats.

Your next question comes from Brent Bracelin from Piper Sandler. Please go ahead.

And one per frankly quick follow up per provides here Frank we're starting to pick up broader interest from snowflake and the insurance industry.

Which makes sense given this industry tends to be more data intensive and I guess could you talk about the opportunity you see for snowflake and insurance or any of the vertical and maybe that stood out this quarter, where you're seeing outsize traction.

Yes.

And involved and a lot of the insurance.

No campaigns and the.

They're very keen non on transformation and more so Dan just modernization.

Some of the many of the larger and insurance companies had very broad cross selling kit and all of these.

The do not half of the systems to from and analytical data standpoint, too to support debt to other very very and tantalum sorta dislodging dem sales from their debt our historical on premise systems and really gained the the.

The promise of data Sciences and machine learning.

And you need to have platforms.

Like snowflake to be able to enable that saw the out.

We announced a number of insurance accounts this quarter and we love the industry. The because as you said they are very data rich there is enormous potential for us to really.

Digitize, if you will really and bring digital transformation to the insurance industry, So super exciting.

Great and then and Mike just as we think about the ARPU of momentum this quarter I mean, much stronger than I think we kind of thought it would be and I know you had the benefit of a very large contract last quarter. So what drove the the acceleration and and kind of new bookings this quarter and and that upside and RPM.

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You know as were moving more into large enterprises and large enterprises really want to do multi year deals there.

They are not interested and having to go to procurement every year and so we saw a number of.

Large enterprises and commit to multiyear deals with us and we think that is going to be a trend that will continue.

And I will say it wasnt until this year that our sales force really started pushing more three year deals and we're going to continue to do that going forward and the future.

Good to see thank you.

Your next question comes from the line.

True Cosan from Deutsche Bank. Please go ahead.

Hey, the congrats on the quarter I mean, very impressive I kind of two.

The cash.

Pets environments and my first question just.

Well do you guys see.

How do you see the kind of momentum will competitors right now and.

And.

I guess, what's happening on premise world is that still kind of low hanging fruit.

Yes, Patrick as Frank.

Our competitive environment is very much dominated by the public cloud vendors and we.

We said that over and over.

And that really hasn't changed and the.

The only time debt, we're dealing with with on premise environments as customers are trying to figure out how the modernized and move off of those platforms. The.

And I really not viewed as of as options going forward. So it may be data and at our filter is biased those were our competitive dynamic is very much centered on the the three public cloud platforms.

The other is the vast majority of.

Of of competitive interaction net we that we have.

I would say the only time, we really come across the on from is where there there there of the incumbent and they're really not considering keeping them and they are evaluating with us and the other public cloud players Thats why we don't necessarily see them as competitive but they are definitely the incumbent and many of the cases.

Got it Thats breaker and I guess my second question the round the support of unstructured data may not sort of Thats, a really interesting announcement of I guess, what kind of use cases and you'd expect thing.

I guess in that category and in the net will come true.

And the things that you think customers will likely.

Launch of state will they like the.

Start with.

Well the of for sure and image data and video data and.

Social media.

And by the way you know the this is also aware of our ml services are going to become a machine learning sort of the they got to be really interesting because of say the.

Image scans from a from a webcam somewhere in the city and them and I am able to shoot that over two and external service and have a scan to letter of Thats and the recognizable and non person there.

Theres going to be enormous potential.

Forward to us and we're as I said earlier, we're getting pushed by our customers true to really bring these different data types of.

The onto our platform. The good they're just part of the types of analytical processes that debt the want to run.

So that's sort of the Werner we should use initially going out of each of these data types or are are large and all of this will allow the flat to the storage side of the of the equation as well.

That's great. Thank you very much the taking the questions.

Your next question comes from the line of Keith Weiss from Morgan Stanley. Please go ahead.

Excellent. Thank you guys sort of taking the question I wanted to talk a little bit about snow Park and another kind of recent.

Announcement that you guys made.

One in terms of.

How does this of fall kind of the broader story in terms of overall snowflake interest again more people engage with the overall platform and then if we think about the monetization strategy for something like Snow partners.

I guess the same extends to sort of like the the overall marketplace is this the all in the service of just like sort of the more workload to get on the platform. The more consumption of that data interest is just more compute and and that's really how you get paid on all of these.

Yes. This is Frank.

Basically you know, we're enabling a whole different range of.

Of users on the Snowflake query and right I mean are there the data engineers to share the that used the the EPS growth language.

To interrogate data and and there's a whole another world Altair the interrogate the data through their language of choice, and notably Java, and and Python and the use things.

Like data frames to process their day, that's a very different mode. It's highly programmatic programmatic a lot of data transformations and a lot of machine learning type of price.

Prophecies are executed through the languages solid Snow Park.

Will do and we will we will start hosting the language the runtimes inside the snowflake platform and all the becomes the the comfort of completely optimized experience it dramatically expenses the workload scope of snowflake. So it's a very very important.

The direction.

For us and you're correct in terms of how does this help.

And tire business model is as we've said over and over is based on consumption. So anything that drives consumption of our of our query engine and our platform.

Accrues to our business model. So so our whole strategy is driven to move the dial and consumption and this is definitely going to do and the we have many large customer who said that this is really really important to them because let's snowflake will bring to these environments is highly optimized.

Efficiency in terms of the economics, secondly, very very highly optimized performance of the performance and efficiency are highly related and the third one is the super important governance right and the is relates to privacy and security shelf of customers. They really want to lock down their environments from of government of standpoint of weather was the single platform. So to the extent the weakened.

Enabled the to workloads were real and consolidating these workloads onto the snowflake, that's really helping them.

Got it and matrix sneak in one follow up in terms of the partnerships. The you guys had the been signing any ones in particular that have been ramping up the more aggressively and others are maybe helping you guys with state of the new customer acquisition and and moving up market that we should be given the non.

Well the number one and our partner that has helped stimulate.

Tons of activity has been the relationship with Salesforce.

And.

We knew that was going to happen and it goes the sales force data is incredibly prominent.

And the Snowflake world because the data and typically gets overlaid with all kinds of different types of marketing data.

Sales force is not on the island and I think Thats one of the reasons why our relationship with Salesforce evolve so productively because they understood that that the data gets blended and overlaid with with data coming from other sources and other really then translates into new inside new signals.

That helped drive the business of sales force is as has driven a lot of new looks and new interest.

And our combined offerings.

Got it and Super interesting. Thank you guys.

Your next question comes from the line of Brad the back from Stifel.

Great. Thanks, very much Mike your comment earlier around less discounting how much of that is a function of of better execution in the sales by the sales force versus customers just being much more comfortable migrating to the cloud and you'd be able to take advantage of that thanks and I.

I'd say, a lot of and as or better discipline and our sales force, but then also.

Given the reference customers, we have and what customers are seeing the or more and willing to move to snowflake as well too which makes the procurement process easier.

Okay.

Great. Thank you very value today, the product were delivering today is so much better than what it was three years ago or two years ago continues and it becomes more the performance on it every year gets better and better and as a result customers should pay more for it.

Because the ship them, yes correct.

Excellent. Thank you very much.

Your next question comes from Mark Murphy from JP Morgan. Please go ahead.

Yes. Thank you I'll add my congrats Frank where do you think we are in the cycle of covert impacts specifically on the new logo bookings piece I think Chris debt. Then had said recently the customers that we're hesitant to start their cloud.

Cloud journey are moving faster now and so it looks like a bit better quarter free or customer ads are you feeling that incremental improvement in the new logo of bookings kind of relative to where that was in the March and April timeframe.

Yes, I think debt.

The the demand sentiment was a little stronger and.

And this period and that was in the in the first half of the year and Covance is definitely.

One aspect to us and should we think the public markets the view.

Also added to sort of the general energy and notoriety if you will.

Just force became kind of the.

Catalyst for a lot of people wanting to find out more and really.

Take the relationship to the next level. So all of it was a tailwind and in many ways and Thats certainly was one of the reason why we one of the company public is to really raise the stature of the company in the marketplace. Because we felt of the largest institution of enterprise and the world and we're also competing as the largest ones and the world also so these things are important.

Yes.

As a quick follow up.

Could you help us understand how aggressive your ambitions are going to be and the data science arena, you've touched on it a bit but for building and machine learning models and AI algorithms and also for handling the log of data or machine data is there is the equal customer pull in both areas or is it stronger and one of the other.

Oh, we do a tunnel work and and machine data lock data on the security Datalex is the is.

As a growing.

Use case that has a ton of interest and we already have a very very large deployments of those so net.

That's an area and that is very exciting as far as the machine learning growth.

While we are doing is we are really enabling our sales are structurally to really accommodated.

Machine learning services. So that we can really take advantage of all the technology that is out there we're not going to see from from Snowflake is that we're going to go buy something and then go it alone and sort of shut out our partners from our architecture. Our strategy is very much on the embracing and enabling all of the capability.

And that are out there customers have tons and tons of choice, Dick and Nick and use ready made services. They can use the tooling for building new services and that is and in contrast to some of the the competitors that we have in the marketplace. So we have very specifically chose and for that path, but we're going to be super Super active and data sciences, why because they are the ultimate consumer.

Of the Snowflake cloud data platform.

Thank you.

Your next question comes from the line of Patrick Walravens from JMP. Please go ahead.

Oh, great. Thank you and let me add my congratulations so Frank you mentioned at the beginning that you're very focused on moving up market and I'm. Just wondering if you could if you could provide some more color on what that and tales from an operational perspective from you guys.

Yes, all I know, we talked about the quite a bit.

During the during the Roadshow Brooklyn.

When we joined the company you.

The snowflake was mostly a sort of a commercial selling high density.

Relatively small contracts with high volume.

And and fast sales.

The sales cycles quick adoption and the company really like that model, but loss coming and as we just know that help in order to win and markets.

After the knock down the biggest most iconic logos and with.

Other cities stayed country or region that your rent. So we really have the pivot our organization or I should say enhance the organization to layer and.

The selling strategy and sales motion debt campaigns. These very large institutions and we went as far and we were a private company of the time of course.

No. We did open heart surgery on our sales organization and we separated between.

On the sales organization that campaign is the largest 250 accounts and the world and them from the rest of the large enterprises and number of shipment of the more on the low and also and Thats because the type of sales people that we have to hire the type of legal contractual posture that we have the security team that we have.

The the type of compensation plans revenue to have all different when you're comparing these large accounts because they are they are long campaigns and very political they're very challenging and requires tons of senior management involvement. So we've been working out and is now for for well over a year and as Mike pointed out and is in his prepared remarks, and we made the tone of prop.

Yes.

And we expect you know to become very heavily weighted overtime to the store.

And of that part of our business.

Because of these large accounts and in the amount of money that they will spending you type of services is going to be much larger than anybody is is currently really understand and because this is becoming so important so core to you know.

To how they do things so the out to its a very and important share.

Shipped or evolution whatever word you want you want to use so that we are very aggressively oriented towards the the the largest the.

The companys and and institutions and the world.

Okay. That's super helpful. Thank you.

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

Okay. Thank you very much and congratulations on the the first quarter here.

I wanted to ask you a little bit about the guidance for Q4, obviously, you saw really strong ARPU growth.

In Q3, and I'm curious if there were any.

Factors that had perhaps the a short term negative impact on the Q4 revenue guidance I know oftentimes the sign these big deals customers through volume based on the.

The accounts get effectively a lower.

Consumption credit rate I'm wondering I guess, if almost the rps strength that you saw this quarter and the the large commitments that were signed and if that had any type of negative.

Impact on your expected growth rate for revenue and in Q4.

You have to remember a lot of that our appeal, our new deals that we were booking and as I said before it takes customers to Pat we have a lot of big on Prem migrations that are going on and until those ramp up and it could take six months plus you don't really see any revenue from that and so most a lot of.

That won't flow through until the next fiscal year.

Got it helpful and.

The on data sharing I think you talked about and.

It's pretty healthy next year customers that are using snowflake for data sharing I guess a couple of questions there.

What are you seeing more at this point is the is it kind of the internal data sharing use case or is it. The the external I know you did talk about over 100 data providers and then secondly, I mean I know, it's still early but have you seen any turn the tide.

The trends were yes, once customers use data sharing you see consumption rise by orders of magnitude or just help us think through how much that consumption potential is once once customers move over to a data sharing the scale.

You know, it's Frank the important thing to understand is that.

For the gaming and providing data access to external sources of whether they are inside of an institution.

Or weather day external.

Is becoming a main part of data operations historically it hasn't been as we know we used cash.

File transfer protocols CPI cash to move data from 80 B. of Us logistically.

Incredibly hard you know it was very governance challenged people debt is because they have to.

But it absolutely did.

Didn't like and so you know here comes Snowflake, what would a frictionless seamless.

Data sharing model and all of the some of this like Hey, we part of our day to operations is that we both gain and provide access to.

And the case of large financial institutions, the one hundreds and hundreds.

Of of of datasets that the that the gain access to and provide access to the data sharing the as part of data operations were just for the first time now really providing an extremely strong model operational model to be able to do that and I know historically you know people just and then do as much of this because and with.

So damn hard now I will tell you that job one for most of our customers as well first I got to get my data to the cloud.

And then I got to do.

Due to database migrations, which is the which is usually the biggest part of the transitions. This is just modernization and then and we start thinking about transformations in terms of you know running processes that weve never run before things that are now possible that couldn't be done before and typically data sharing and and is sort of the from tier if you will of the.

The new things that are now possible that people have never even consider and before I mean, it was not even an option and they were so preoccupied with just just doing thanks in terms of blocking and tackling the they had never gotten around to really fully examining and understanding and what it is now possible. So it's usually.

The sharing is really not the first part of the conversation is something thats sort of evolve overtime and.

And what we are seeing though is that we're we're now getting into deals deals where you know people already have strong and commitments on the cloud relative to existing workloads and the data cloud and our data sharing capabilities are busting open accounts the nowhere normally on the work load basis.

We would not really have debt much opportunity or the customer incentive three of them even look at ourselves the salesforce loves that about of this conversation, where we're hitting a thousand okay. The just never fails to to trigger new interest. So we like it for all of those reasons.

Your next question comes from the line of Kidron from Oppenheimer and company. Please go ahead.

Thanks, Hey, guys and again congrats on the first great quarter out of the gate couple of questions from me and maybe one for you first must Frank.

One of go back to the machine learning and comments you made earlier I just want to make sure I understand this and get this rights do you intend or non intend on moving it to the machine learning algorithms space like data breaks or data robot.

And I want to make sure I understand your interaction with machine learning or you're going to be an enabler of or are you actually going to provide a full stack platform from machine learning.

Well, we're going to do both.

Other what I did say was like we don't just sort of want to go from the marketplace and say you are going to have to use our income and that said theres not people that operate and net mode. So we're we're going to have a much richer wider broader set of choices for you know for customer certainly one of my comments about Snow Park and then considering now we're gonna have.

No job of Python language, Runtimes and our platform, that's going to be an hour and the key enabler for people to to develop the.

These kind of capabilities and use the kind of capabilities that the other already using today. So it's really bring those workloads to the already the.

The already exist or that are being newly developed to bring the inside the.

The snowflake platform.

So.

We're not going to be a company, where we have our own flavor of everything and our partners are all going to be secondary.

We want to actively encourage.

The development on our platform participation on our platform because again we're of consumption company. So the way we drive our strategy is to drive activity on our platform right. I mean, if we got activity our platform, where there are probably drives it or apart and drives the yields. The same result, right. So we'd be crazy to know because.

Because the way our model works, we don't have the prior to prioritize our own product from.

Got it and maybe what the again for the other side of the changed and clearly your economics get much better and better the more and more data resides on the platform.

And so moving data and you apart from is absolutely critical for you. How do you think about the data integration layer, which is highly fragmented and has multiple layers to it how far down the data integration side do you want to move in order to enable better and faster and smooth the movement of data into the platform.

Well the this.

The data engineering side of our business is already a huge part of what drives the consumption on our platform and we're all everything that we're doing the snow Park is obviously no focus from that as well because so much of that work is going to be data transformation.

Oriented so and it's it's a huge day, but we're going to do things that are that are snowflake optimized right and sort of processes that are on all the way from from ingestion and transformation of the brain dead on the platform running analytical process to make that as of.

Seamless and us frictionless as possible and our partners and the ecosystem. They serve many mastered we only serve one net snowflake yes.

Kind of very good good luck guys. Thanks.

Your next question comes from the line of Gregg Moskowitz from the two.

Go ahead.

Okay. Thank you and I'll add my congratulations as well I wanted to go back if I could add to the topic of bringing on structure of data into the snowflake platform.

And that you mentioned.

I don't think began its life of the semi structured data company and I'm curious how much of the technical challenge. It is or has been for you to support and the transact on and make has videos to the et cetera and to do so at scale.

Well. It's obviously is the is not a no brainer otherwise, we probably would have done it.

A long time ago.

We our technical teams are now heavily invested in making this happen I mean, our announcement of those was very much. The very first time, we've talked about this this open late.

You know I expect debt in our next.

Snowflake somebody zone, which is in June of next year.

We will have extensive.

Technical details and presentations on the on this topic, so we'll be communicating.

On the topic in full detail at the time, we're certainly not not prepared and ready to do that right now.

Look forward to that and then just as a follow up 23% of customers already using data sharing really impressive force service that frankly hasn't been available all of that long how does this uptake compare to what your expectations were at the stage of and also where can this go longer term.

Yes, I think I think the longer term I mean, you were good I think everybody is going to be doing is as I. As I said earlier. This is going to become core to date. The operations. This is hold the whole notion of the data cloud is you're not is running the data sciences against your own data silos, you're going to be running of across disparate data sets, meaning data that lives inside of your.

World outside of your World and Thats really what data science is all about is to is to build these highly descriptive models that and then we use predictably and prescriptive weight.

True to really get closer to two business outcomes. So in order for the data cloud to really happen.

As the concept. This this is going to become incredibly mainstream that is our general strategic assumption.

About data it is not going to stay where it has been historically because we were essentially encumbered by technology and were not anymore. It's wide open. So I think customers are learning and slowly sort of gaining and appreciation and while the new possibilities RM and I said in my prepared marks technology is now well ahead of other people's ability to use it.

And people are scratching their heads like Wow. This is this is just unbelievable the scale of the scope the the power of that we have.

How do we use and and that's the sort of where we are really exciting, but but nobody sort of ahead of the playbook ready to throw out of it so the bit of a journey debt that were on everybody will be on.

That's great. Thank you.

Your next question comes from the line of Derrick Wood from Cowen and company.

Great. Thanks, and congrats on the strong quarter. My first question I wanted to ask about a couple of different regions first on Europe. I think you guys have been building out the major accounts focus there would love to hear about how that's tracking versus kind of what you've been experiencing and the us.

And then in the us regarding the fed I think you guys are the received from new fed ramp certifications to share can you just talk about how you're thinking about the opportunity with the government looking out over the next couple of years.

Yeah, We're we had a really good quarter in Europe very excited about debt.

Europe was definitely a region, where we have to sort of Iraq ourselves in terms of our large account orientation I.

From a Europe is even more sensitive to major account campaigning the goes that sort of how these markets operate they really looked and through their own icon identiv price is to see what kind of the physicians. They make and then the whole market kind of follow the saw you simply cannot afford to to to be in those markets and not kind of campaign of large and our.

Right and so it's a fairly.

The substantial sort of.

The removed for us to be able to have that posture, but we're we're seeing and pay off and I have very high expectations and I hope for Europe, and we're going to be spending time, there one weekend travel again.

To to help campaign those institutions, the very very good opportunity as far as the fed goes.

The hard part about federal government is always getting them on the cloud they just have historically the.

And incredibly slow to move to the cloud for all kinds of of reasons. So the the the fed ramp certifications that we have we of achieve some certification the helping we need higher level of certifications to to really enable the business.

Corridor.

And that is really sort of the gating factor if you will for for the fed really.

Becoming a solid contributor to the business, which are not yet.

Got it and then maybe one for Mike you had a nice rebound and net revenue retention rates, but has bumped around a bunch over the last few quarters. So can you just walk us through the the mechanical drivers in terms of what you've seen in the last couple of quarters and maybe how to think about how you see those numbers settling out over the next couple of quarters.

Well when we were going public day, we had mentioned that we fully expect it with the above 160%. This quarter. So kind of came into where we were expecting.

These are extremely high net revenue retention rates I think overtime, it will come down, but I'm not expecting a steep decline and I think it's going to be pretty stable for the next little while.

It's not something we're going to be guiding to I just knew after last quarter that this quarter was going to go higher because of as the cohort that had just come in from the two year ago period that.

It was just the nature of some of those customers.

Okay got it thanks.

Your next question comes from the line of Gray Powell from BTG. Please go ahead.

Great. Thanks for taking the questions and I'll Echo my congratulations on the and the results.

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So maybe a couple of questions from Mike.

As you look at your growth forecast over the.

The next 12 months, how much of the do you feel like you have visibility on from the installed base today.

The customers you just won and natural growth and usage and and then how much do you do you think you have to go out and win.

The.

First of all going into the quarter virtually all of our revenue is coming from our existing customers very little of comes from customers that are landed in the quarter and it's less than 5% come from on demand customers.

Over the next 12 months, it's still the vast majority of our revenue is coming from our existing customers that we have.

And we do see the growth and those customers share we need to sell the more but most of our growth is coming from our existing customers over the next 12 months longer term, it's super important that we acquire new customers because those will be the growth drivers in two three years. So.

Got it Okay, and then I just want extra I'm thinking about the Q4 guidance correctly. So if I just look at the last few quarters products revenue increased by about 23 million sequentially in both Q2 and Q3.

I would think that usage is seasonally stronger in Q4. So is there any reason where product revenue would only growth by 16 million sequentially and the quarter and just how should I, how should we think through that.

It all depends upon the type of customer you are and depending upon what you're doing there is also a number of our large customers that we've given.

The that are getting more mature right now too and the growth has slowed down somewhat with some of these large customers but.

There is seasonality within our customer base and I would not assume Q4's whats driving their consumption and all quite frankly and Q4. There is lot of holidays, you have Thanksgiving you have Christmas and you do see.

Decrease enough of the new years, you do see decreases because employees earn in the office driving analytics.

Got it okay, and that's really helpful. Thank you very much.

Your next question comes from the line of the the times from Canaccord. Please go ahead.

Hey, Thanks, guys I want to ask a follow up on the strong net revenue expansion Frank when you talk to CIO is at some of your larger customers I'm curious if you pick up any concern about the pace at which they are snowflake spend is growing.

Or.

Still that there's such price disparity versus the incumbent that it's not an issue and I'm curious kind of how you think about balancing that net and a consumption based model.

So here's the important thing and I already.

Mentioned it.

A little bit earlier, so snowflake is the variable.

Paradigm right in other words and those is not fix you and people.

People can consume as much in as little as they and appetite and.

Budget for which is why you have this buoyancy in the net revenue retention rate because people because they now can we start doing things of that could not do before the.

The big thing and by the way, it's not CIO is that our debt are upset the is usually cfos that are there and.

I understand how you go from from one period to the next and all of the thumb.

The number has doubled but the business is telling them no we need to do this so people are getting used to spending we need more money on this class of services than they ever imagined and the reason. This day now can and day now need to right now the does that take time that takes time for people to get used to that I mean I've talked to seek the.

And they said we spent 50000 last year, we're spending and million dollars. This shift out of Hell do I explained that well.

That is the those are the types of transitions that were going through we have customers, where we are the second largest line item behind Amazon Dot for us right and Thats, a little of getting used to force for customer that you're spending on the service like this at this rate but.

When data of becomes the beating heart of year enterprise.

No that it makes total sense is just that it doesn't make sense and the historical context and the takes time for us to transition to the is realization that like this is pretty down the important and.

Thats sort of free sometimes.

Sometimes the goes a little bit too quick and people like Holy Moly. This thing is is a little bit.

No to slick and too fast and it's just too easy to fire up.

Cluster of warehouse and sort of running this process.

Once a week, we're now running at every night, because the sea advantage and doing it right.

But we're seeing people getting used to large numbers I mean, I'm quite honestly and my own history and software and the stunned by the the size of the relationships that we're seeing in the business and it's it's an amazing thing.

But it does take time for people to really transition to the ruble realization that this the this is kind of a big economic footprint.

Yes, yes, it makes sense, obviously, good problems to have and maybe one quick follow up and the good we've talked about the network effects that come from the data exchange in the near term, what's more important on that front and in your view. It is it getting more customers to participate or is it getting more data providers on the network.

Yes, I don't know that we need to trade those off no quite honestly.

We can walk and chew gum, if you will so we're operating of multiples vector. So at the same time in terms of data providers that sometimes it's more of a qualitative and quantitative thanks.

Because of the not all created created equal so some of those and by the way, it's very vertically oriented and the types of data.

That we're dealing with all of its a fairly new on staying it's very important for us that we and rich the data cloud with new data from all the time because of the just going to be more and more customers who did the reason to be on snowflake is not just a world class execution capabilities that we have but they need.

Could be there because of their partners are there.

There are data providers are there.

After a while starts to break the bile because of the becomes a no brainer. The we have to of both if you don't have the work the workload execution capabilities and the data richness will not sales you need to have both.

Very helpful and congrats.

Thank you.

Your last question comes from the line of print sales from Jefferies.

Thanks and.

Just on the go to market as we go into next year in terms of your quota carrying sales capacity and your belt. How are you thinking about on what you are adding to the to the system are you accelerating.

The build out of here, given what you're seeing with the economy.

Starting to stabilize a little better.

Just maybe walk us through your thoughts and how you're thinking through the shape of that kind of market.

Well and what I would say is we're very much focused sales first our geography.

EMEA is one that we're investing very heavily and and adding a fair number of people there as a percentage of what they have we're clearly focused on going after the largest enterprises and the world and so we are continuing to add.

Perhaps there I would say, we really never slowed down given what was happening and the economy you can see that.

Year over year and Q.

Q3 of 2020, we had 900 people and our sales organization and Weve added roughly almost 300 people and to our sales organization over that period of time of year, and we will continue to add at that similar pace going forward.

Next year I would say the other area, we're really adding as we get more into the major accounts, writing a lot more SCS into our organization because of them majors require more one to one relationship where in the past we never did so I would say is we are really going after those larger accounts and enterprise more.

So then SMB yeah. The only thing I will add to that is that we're also in a mass of push to drive verticalization into and in our in our selling motions and that of course, that's going to be we overlaid and added by vertical as well. So you see our arc.

The the cell will grow and it's really nice debt, we have with we of geographically, we have and by by large enterprise accounts and we're going to have of by vertical so.

We're very excited about the company Verticalizing were and because we haven't great business and the technology side and the media side, the retail consumer packaged goods health care.

And so that's that's where from a lot of our selling capacity is going to grow in the coming years, and and Allied brand to that and we've really been focused and the last 12 months on the system integrators and the global system integrators, we're adding more people there the likes of Deloitte and Accenture building and real practices around snowflake, and where and content.

Moving to invest and those because they are starting to drive meaningful business to us.

Great welcome back thanks.

Yes.

And that was our last question, ladies and gentlemen. This concludes today's conference call. Thank you for participating you may now disconnect.

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And.

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