Snowflake Inc. (NYSE: SNOW) Summary Research Report

Buy Recommendation (with caveat)

Hi Everyone,

I hope you all had a nice week. In this week’s edition of the Seifel Capital Newsletter, we will review an investment analysis of Snowflake, Inc. You can access the detailed report here, and the other detailed reports that I have released here. For those of you who just tried to frantically buy the stock after seeing “Buy Recommendation,” don’t be alarmed when nothing shows up after entering the “SNOW” ticker in your favorite brokerage platform. The company just issued its initial S-1 on August 24, 2020 (along with a number of other exciting companies), and it usually takes about five weeks from the initial filing for the stock to start trading on the open market (i.e. end of September / early October).

For those of you who wish to learn more about the IPO process, I highly recommend reading this article by Jamin Ball of Redpoint Ventures. Jamin does does an excellent job (as always) of breaking down the process. Also, if you haven’t already, I recommend signing up for Jamin’s newsletter Clouded Judgement - the best high level summary of the SaaS space out there.

Also, for additional information and a unique perspective, my friends at Public Comps wrote an excellent S-1 & IPO Teardown on Snowflake - check it out!

For those of you familiar with this newsletter, you will notice the format is slightly different this week. I do not provide an Investment Framework since the shares are not yet trading, so there is currently no “Market View.” However, for those of you who make it through to the end of this summary report, you will notice that I added a new segment to the analysis (hint: you will get insight into some of the important criteria I look for in a company).

With that being said, I urge you all to at least skim through the detailed report that is linked above. It contains a vast amount of high quality data and information that I could not include in this newsletter.

As always, please make sure to share this newsletter, share this post, or subscribe (if you have not already) if you like the content! You can use the buttons here to do so:

DISCLAIMER:

All investment strategies and investments involve risk of loss. Nothing contained in this website should be construed as investment advice. Any reference to an investment's past or potential performance is not, and should not be construed as, a recommendation or as a guarantee of any specific outcome or profit.

Please enjoy this report on Snowflake Inc. (SNOW)!

Executive Summary

Snowflake is a fully-managed, cloud-native, Data Warehouse as a Service (“DWaaS”) company. The company was founded to break down data silos and resolve the issue of data governance that had always negatively impacted the data warehouse space. The company solves these issues through its Data Cloud Platform. It is a platform that enables the company’s customers to consolidate data into a single repository where the customer can then generate business insights, build data-driven applications, and share data either internally or across the cloud platform. A major advantage of Snowflake’s architecture is that it separates storage and compute, meaning that many warehouses can all access the same data source simultaneously. Additionally, it is the first multi-cloud data warehouse and is available globally on all three major cloud providers. Its multi-cloud architecture is an advantage over AWS, Microsoft Azure, and Google Big Query, which lock customers into their own cloud network. Snowflake’s model gives customers the ability to work with different cloud providers that fit their variety of needs. With a common and interchangeable code base, Snowflake features global data replication, which means users can move data to any cloud, in any region, without having to re-code applications or learn new skills. The company has grown revenue at a 133% CAGR over the past two years and has shown significant margin improvements as a result of continuing to scale its business. It benefits from one of the highest expansion rates in the SaaS industry and is one of the best companies at balancing growth and profitability, as indicated by its 109% Rule of 40. The company filed its initial S-1 on August 24, 2020 and is expected to go public either at the end of September or early October. Investors would be prudent to let the stock form a base after its issue date before considering acquiring shares. However, this stock should provide substantial appreciation to every investor’s portfolio over time.

IPO Information

• Estimated Price Range: $75 - $85 [$80 midpoint]

• Shares to be Registered: 32.2MM Class A Shares (includes 4.2MM shares that underwriters have option to purchase); 240.5MM Class B Shares – 278.78MM total shares

  • Additional Shares Issued as Part of Private Placement to Salesforce Ventures LLC and Berkshire Hathaway: $250MM each, (~6.25MM shares at midpoint)

• Total Potential Proceeds (including Private Placement): $2.9B - $3.2B [$3.1B midpoint]

• Estimated Market Cap: $20.9B - $23.7B [$22.3B midpoint]

  • Enterprise Value / ARR = 41.9x; Enterprise Value / NTM Revenue (SCM estimate): 26.4x

  • *Note: Almost $10 billion increase in valuation since February, when Salesforce led a financing round at a $12.4 billion valuation.

Overview and Vision

Snowflake, Inc. offers a single, integrated cloud data platform as a service, which provides users with database storage, compute and query processing, and cloud services. It is able to provide instant, secure, governed access to an entire network of data, and is built to enable a variety of data workloads, including a single platform for developing modern data applications. It combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a lower cost than legacy solutions. The company’s vision, as stated in the S-1, is: “We believe in a data connected world where organizations have seamless access to explore, share, and unlock the value of data.” To execute on their vision, the company has pioneered the Data Cloud, which is an ecosystem where Snowflake customers, partners, and data providers can “break down data silos and derive value from rapidly growing data sets in secure, governed, and compliant ways.”

While working at Oracle Corporation, co-founders Benoit Dageville and Thierry Cruanes realized that legacy data warehouse solutions were limited in computation capabilities & storage because they were physically constrained by the amount of hardware and server space companies had available to them. Thus, companies could not scale their business with these solutions without incurring substantial costs. The founders determined that they needed to develop a platform that could: 1) Handle vast data volumes resulting from digitization of the economy, 2) Deliver superior performance to legacy products, 3) Have high utility across data management, 4) Be instantly elastic (to accommodate changes in data loads), and 5) Be user friendly.

Industry Overview

Market Opportunity

The company states in its S-1 that the total addressable market (“TAM”) for the Cloud Data Platform is $81B as of January 31, 2020, based on a ground up analysis in which it applied the ACV of three different customer cohorts to the total number of companies in each cohort that existed in the S&P Capital IQ database.

Alternatively, Snowflake’s platform immediately addresses the markets for Analytics Data Management and Integration Platforms and Business Intelligence and Analytics Tools. IDC estimates these two end markets will have a combined value of $56B by the end of 2020 and $84B by the end of 2023, yielding a 14.5% CAGR. These figures do not account for the platform’s data sharing capabilities, which is a large and untapped market.

The global DWaaS market yields higher growth opportunities for Snowflake, as the market is expected to grow at a 29.2% CAGR from $1.4B in 2019 to $23.8B in 2020.

Competitors: Snowflake competes primarily with the data warehouse platforms of the three major cloud providers: Amazon (AWS Redshift), Microsoft (Microsoft Azure Synapse), and Google (Google BigQuery). More information on the market opportunity and competitors can be found in the detailed report.

Data Warehouses and the Changing Industry Landscape

Industry Trends Make Legacy Solutions Obsolete

• Data is Paramount to Modern Business Success: To stay competitive, all businesses need to be capturing, analyzing, and mobilizing data in real time.

• Data Proliferation is Providing Better Insights: According to IDC, there will be 175 zettabytes of data by 2025, representing a CAGR of 27% from 33 zettabytes of data in 2018.

• Accelerating Cloud Adoption: The IDC states that 49% of data will be stored in public cloud environments by 2025 while only 30% of data is stored in public clouds today. Additionally, 90% of Global 1000 Organizations will have a multi-cloud management strategy by 2024 according to a 2019 IDC report.

• Everyone Consumes Data: The democratization of data is critical in a world where data is becoming more prevalent due to the evolving digital economy and increase in digital application for employees across an organization.

• Inefficient Pricing Models for Technology Consumption: The fixed pricing model adopted by subscription-based companies were inefficient, as customers ended up paying for unused or underutilized software.

Limitations of Legacy Solutions

Companies have previously utilized legacy on-prem database architectures to meet their data needs, however these solutions have structural capacity and scalability constraints. These systems simply weren’t built to handle a digitized environment with increasing cloud-based workloads. As a result, these companies have suffered from data silos, governance issues, and blind spots in business performance. Limitations of legacy databases and big data architectures include:

• Incapable of Handling Various Data Types: Legacy database architectures were designed for structured data types from internal business systems that did not require much manipulation.

• Capacity Constrained: Legacy solutions combined the storage and compute layers together within its architecture. This resulted in storage capacity constraints, data redundancies (inefficient use of resources), and insufficient compute power to ingest and properly transform the large volumes of data generated by organizations.

• Minimal Efficiency: The legacy solutions cannot support a variety of use cases and users at the same time due to inelastic storage and compute resources.

• Inefficiencies Resulting in Bloated Costs: The legacy solutions are inefficient from a time and cost standpoint, as companies need to manually organize data before it can be used. The solutions that focused on cost lacked adequate performance, not providing the query processing and technologies that database architectures had historically.

• Not User Friendly: Complex infrastructure configuration often result in project failures. These architectures were built on complex programming languages and required data scientists or engineers to spend time and resources on fixing the issues.

• Expensive Maintenance: The underlying infrastructure of both legacy database and big data architectures constantly require maintenance, upgrades, patches, and system configuration.

• Inability to Support Global and Multi-Cloud Environments: Legacy solutions were purpose-built for specific infrastructures, so data could not be distributed globally or shared across public clouds.

• No Data Sharing: Data sharing on legacy solutions would result in data copies (more storage space), data security issues, and poor governance.

The Next Frontier: The Data Cloud

The Data Cloud seeks to address the major shortfalls discussed above. Specifically, this paradigm shift will break down data silos that have been a hindrance for organizations as data has become an increasingly important part of their business and competitive advantage.

Snowflake’s Solution: The Cloud Data Platform

Snowflake’s Cloud Data Platform is built on a cloud-native architecture (born in the cloud) that capitalizes on the superior scalability and performance provided by the public cloud. This platform solves the issue of data silos by allowing customers to consolidate data into single, organized repositories. This platform results in faster business insights and actions, can power applications, and provides for data sharing across clouds and geographies. Snowflake’s platform solves the problems inherent in legacy solutions by being built with the following characteristics:

1. Diverse Data Types: The platform can ingest, integrate, and optimize both structured and semi-structured data without sacrificing performance of flexibility.

2. Scale with Large Data Volumes: Utilizing the public cloud enables the platform to support growing data sets without sacrificing performance.

3. Simultaneous Usage: The platform supports simultaneous usage by many users and use cases as needed by being built on an architecture that makes compute resources available dynamically.

4. Efficient: Snowflake’s platform uses advanced optimizations so data is only accessed when needed. This optimizes compute resources and as a result, cost for customers. The bifurcation of storage and compute is the key here. It provides for centralized data to be accessible simultaneously by many users without compromising the integrity of the data or system performance.

5. User Friendly: Quick start time within seconds provides for a user-friendly experience. Additionally, customers achieve a higher ROI on their investment, as they are only charged for the resources they use. The familiar programming model and query language save organizations time and money, as it does not need to hire additionally professionals to manage the system.

6. Platform-as-a-Service: The service delivery model reduces customer overhead, reducing expenses, time and resources previously incurred for legacy solutions. Regular automated platform updates with no downtime further enhances the value of the offering.

7. Multi-Cloud, Global Solution: Snowflake’s platform is available on all three major public clouds (AWS, Azure, GCP) across 22 regional deployments, all of which are interconnected into the single Cloud Data Platform. This provides for a consistent user experience.

8. Seamless and Secure Data Sharing: Snowflake’s solution enables customers to govern and secure sharing of live data internally and externally, across customers and partners. This is usually done without copying or moving the underlying data, which maintains data integrity and minimizes storage costs.

A more in-depth review of the platform and technology can be found in the detailed report.

Company Overview

Business Model

Snowflake delivers a platform as a service over the internet. The company generates the substantial majority of its revenue from fees charged to customers based on the storage, compute, and data transfer resources consumed on the platform as a single, integrated offering. SCM believes this usage-based payment model is attractive for the modern cloud company, as it gives customers the ability to realize value proportional to the cost of services. Customers have voiced their support of the usage-based model, as they only pay for the compute and storage resources they actually use. Equally beneficial for both Snowflake and its customers, the platform requires near-zero maintenance. This is margin accretive for Snowflake, as they do not need to employ a data support team requisite to handle these issues. It is beneficial for customers, as it allows them to focus on deriving value from their data rather than managing its infrastructure.

Go-To-Market (“GTM”) / Land-and-Expand (“L&E”) Strategy

Snowflake’s GTM / L&E strategy is focused on 1) acquiring new customers and 2) driving continued use of its platform for existing customers.

Once the platform is adopted (Snowflake “lands”), the company focuses on increasing the migration of additional customer workloads to its platform to increase consumption (“expands”). The company has undoubtedly been successful with this strategy, as evidenced by its dollar-based net revenue retention rate (“DBNRR”) exceeding 150% for at least each of the past eight quarters.

Snowflake offers a self-service demo & trial through its website, which has been one of the primary methods by which organizations initially adopt the platform. This process takes no longer than five minutes and allows for account signups by middle market and enterprise customers for free without having to talk to a representative.

Two additional strategies the company employs are 1) Upselling to existing customers and 2) Shifting towards higher average contract value (“ACV”) customers. Its upselling efforts are focused on increasing the migration of customer workloads and have proven successful given the company’s industry leading DBNRR. Snowflake’s efforts to transition to higher ACV customers will be discussed further in the Customer Profile section below, however it has been successful in this regard, as well.

Network Effects

By enabling companies to share data both inside the company and outside the company to other customers on the platform, the Data Cloud Platform benefits from powerful network effects. These network effects accelerate organic demand for the platform and is, in SCM’s view, its core competitive advantage. The Data Cloud will continue to grow as organizations seek more efficient data management by moving their siloed data from cloud-based repositories and on-prem data centers to the Data Cloud. This is where the network effect comes in: the more customers that adopt the platform, the more data can be exchanged with other Snowflake customers, partners, and data providers. This creates immense value for all users and is an enticing factor for other companies to join the platform. Once on the platform, customers can augment their analysis with third-party data sets and unify third-party data sets with their own internal data to analyze and measure the impact of business decisions and performance.

Key Business Metrics (Yes, these numbers are real. I double checked them myself)

1. Product Revenue: : Product revenue is a key metric as it directly reflects platform consumption, which is inherently variable at the customers’ discretion. Unlike a lot of other companies, Snowflake’s revenue is agnostic to customer contract amount and duration. Thus, product revenue recognized in a period is an important indicator of customer satisfaction and the value customers derived from the platform.

   1. The company has grown its revenue at a 133% CAGR over the past two years; T12 Revenue has grown from $165.5MM to $378.6MM, or 129%.

2. Remaining Performance Obligation (RPO): RPO is the amount of contracted future revenue that has not yet been recognized by the company. It includes both deferred revenue and non-cancelable contracted amounts that will still be invoiced and then recognized as revenue in future periods.

   1. The company has grown its RPO at a 235% CAGR over the past two years.

3. Total Customers: The total number of customers is an important indicator of Snowflake’s business growth and future revenue trends. Each customer account that has a corresponding capacity contract is counted as a unique customer at the end of every period. Customers that consume the platform only under on-demand arrangements are not counted towards the total number of customers.

   1. The company has grown its total customers at a 134% CAGR over the past two years.

4. Net Revenue Retention Rate (“DBNRR”): The company monitors its dollar-based net revenue retention rate to measure the growth in platform usage by existing customers. It is an important measure of the health of its business and future growth prospects. DBNRR is measured as the total revenue from a specific customer cohort in the current period divided by the total revenue contributed a year before from that same cohort. This figure accounts for churn, as customers in the cohort which used the platform in the first year, but not the second year, are still included in the calculation.

   1. The company has achieved a DBNRR of at least 158% over the past two years. Additionally, the simple average of its DBNRR over the period is 180%. These figures are simply eye-popping.

5. Customers with Trailing 12-Month (“T12”) Product Revenue Greater than $1MM: Large customer relationships allow the company to scale and creates operating leverage in the business model. Compared with smaller customers, large customers present a greater opportunity for Snowflake to upsell additional capacity because they have larger budgets, a wider range of potential use cases, and greater potential for migrating new workloads to the platform over time. The company counts the number of customers under capacity arrangements that contributed more than $1MM in product revenue in the T12 period as a measure of its ability to scale with its customers and attract large enterprises to the platform. This strategy will optimize sales & marketing spend, reducing the overall cost structure over time.

   1. The company has grown this large enterprise customer cohort at a 121% CAGR over the past two years.

Additional Key Metrics and Results from FY Q2 2021 Earnings:

• Revenue Growth: $133.1MM vs. $60.3MM (+121% YoY)

• Gross Margin: 62.1% vs. 52.7% (+ 940 Bps YoY)

• EBIT: -$77.7MM (-58.4% Margin) vs. -$95.6MM (-158% Margin)

  • Margin improvement from decreased S&M and infrastructure costs

• Rule of 40 (T12 FCF): 109% (137% Revenue Growth, -28% FCF Margins)

• LTM Payback: 22 months

• ARR (Q2 Revenue x 4): $532MM

• Total Customers: 3,117

• TTM $1M+ Customers: 56 vs. 22 (+155% YoY) represented 46% and 47% of revenue, respectively

• Daily Queries: 507MM average across all customer accounts for July 2020 vs. 254MM July 2019 (+99.6% YoY)

• Net Promoter Score (NPS): 71

  • Proxy for measuring customers’ brand loyalty and satisfaction with a company’s product or service, on a scale from -100 to 100

How Snowflake Meets SCM Investment Requirements

1. Competitive Advantage / Moat: Network effects of data sharing

2. Superior Product: As confirmed by customers, the product is superior to the major cloud providers

3. Excellent / Improving Unit Economics: 109% Rule of 40, improving Gross Margins, average payback despite currently high S&M expenses.

4. Efficient, Frictionless Go-to-Market and Land-and-Expand Strategy: Free trial and demo period, along with a focus on large enterprises and usage-based pricing result in DBNER greater than 150%, which is best in-class.

5. High Quality Management Team: Frank Slootman achieved a 55% revenue CAGR over six years at ServiceNow, two of the founders still work on the management team, Management will still own 30% of the company post-offering.

6. Pricing Power: Too early to tell, SCM will keep an eye on gross cash profit margins

7. Recurring Revenue Base: DBNER > 150% every quarter for at least the past two years

8. Sticky Solution: The company did not reveal churn statistics in its S-1, however the network effects inherent to the platform, along with the ability to create bespoke data applications, should make customers want to stay on the platform

9. Innovation: The Cloud Data Platform is disrupting the data warehouse industry

10. Industry - Top Performing Industry & Large and Expanding TAM (Industry Economics): Total TAM is expected to be $84B by 2023, and the DWaaS market is expected to grow at a CAGR > 29% over the next 10 years

11. Top One or Two Companies in the Industry (Competitive Positioning): Customers are leaving AWS, Azure, and GCP for Snowflake, that is an encouraging sign

12. Rapidly Improving Metrics / Path to Profitability: EBIT margin improved from -158% to -58% over the past year. Continued margin efficiency and operating leverage in the sales organization should push the company to profitability.

13. Customer Diversification: Only one customer represents more than 10% of revenue, and the company’s goal is to make sure that no customer exceeds that threshold.

14. Balance Sheet - A lot of Cash / Little-to-No Debt: Pre-offering, the company had $138MM in Cash & Equivalents and no debt as of July 31, 2020. Their cash can cover all current liabilities (aside from deferred revenue).

15. Low CapEx / Funding Requirements: Aside from the need to acquire additional office space and certain intangible assets, the company does not have CapEx needs as it is a cloud-native solution. However, negative operating cash flow is a big funding requirement for the company.

16. Customer’s View of Company: The company’s Net Promoter Score of 71 is one of the best out there.

Investment Thesis

1. Network Effects: This is the key for SCM. The ability to share data with external parties (i.e. customers, partners, etc.) enhances the value of the platform. This means that the more customers that get on to the platform, the more valuable it becomes. Also, the ability for customers to create bespoke data applications make the platform sticky for customers.

2. Superior Solution: Snowflake’s product is vastly superior, in terms of performance, according to numerous customer reviews who switched from major cloud providers to Snowflake for its data warehousing needs. Additionally, customers can avoid vendor lock-in by using Snowflake instead of a major cloud provider.

3. Revenue Growth: Snowflake is one of the fastest growing companies out there, evidenced by its 121% YoY growth in CY Q2 2020, and 174% YoY for FY 2020. This is directly a result of expanding within current customers, as well as winning business from large enterprises.

4. Land-and-Expand: The company’s ability to expand within current customers is remarkable, evidenced by its current 158% DBNER. It is the lowest DBNER over the past two years. The company will continue achieving high expansion rates as it grows its large enterprise customer base. This metric will level off over time, but there is still a massive runway.

5. Pricing Model: A usage-based pricing model is optimal for customers, as there are no wasted costs and each dollar spent generates a return in business outcomes. Additionally, Snowflake is a rare company that allows customers to roll over unused usage.

6. Customer Profile and Acquisition Strategy: Focusing on large enterprise customer acquisition will not only result in more operating leverage through lower relative S&M expenses, it will also give the company a longer runway to expand once they land with these customers. Both dynamics are margin accretive.

7. Massive and Expanding TAM: The $84B TAM for the company provides for a long runway of growth, even if somehow major cloud providers can keep up and improve their product. Additionally, the DWaaS market is expected to achieve a 29% CAGR over the next 10 years, which Snowflake will be a main beneficiary of.

8. Industry Tailwinds: The proliferation of data in an increasingly digitized economy will provide for substantial growth over the long run. According to IDC, there will be 175 zettabytes of data by 2025, representing a CAGR of 27% from 33 zettabytes of data in 2018. Organizations need a solution like Snowflake to organize, store, maintain, and create actionable insights from this data. The evolution of IoT, 5G, and edge computing will further this growth in data.

9. Management Team: Although they are not founder-led, two of the co-founders still play a prominent role in the company. Additionally, Frank Slootman (CEO) had tremendous success at ServiceNow, growing the organization from $100MM to over $1.4B in Revenue over just six years (55% CAGR – that’s pretty good). Additionally, the management team mostly not be selling shares as part of the offering.

10. Outstanding Operating Metrics: In addition to the excellent revenue growth and DBNER, the company continues to execute on key performance metrics. Its ACV of ~$160K is one of the highest of all SaaS companies, it grew total customers by 101% YoY in the last Quarter, it achieved a 109% Rule of 40, and 22 months payback period despite high S&M expenses. The company is truly clicking on all cylinders.

Appendix - Financial Summary and Valuation