Cloud platforms are designed to scale at a fast pace. The option to build other SaaS/PaaS solutions using cloud platforms highlights a huge portion of their valuation.
Snowflake has capabilities similar to other cloud platforms with outsized valuation multiples.
The scale and network effects advantage of cloud platforms provides a huge growth option that is tough to quantify.
Snowflake’s design as a data cloud platform justifies its current valuation.
The bullish case for Snowflake (SNOW) revolves around three features inherent in its design: the platform (multiple use cases, horizontal integration), speed (IaaS abstraction), and collaboration (Data Exchange, Data Applications). Snowflake’s platform ensures easy usability, scalability, and ROI optimization for its customers. Platforms are mostly built for easy scalability of projects built on top of them. A cloud platform improves on this feature due to its global reach. A data cloud platform takes it a step further as most data analytics problems are mostly about extracting actionable insights and solving problems to improve business performance. Forrester recently published a report demonstrating the ROI-generating capabilities of Snowflake’s platform. The report highlighted one of the highest ROI to be derived from deploying Snowflake. Combining these capabilities with its performance advantage and collaboration features to drive platform adoption provides ample competitive moats to build Snowflake’s future free cash flows. I am projecting Snowflake to grow to ~$4B in annual revenue in the next five years. This gives Snowflake a convincing valuation of ~15x EV/CY’2025 revenue. The recent capital raise from its IPO improves my conviction that Snowflake has the resources to scale its platform towards achieving its long-term vision.
Snowflake is a cloud data platform that provides data solutions for enterprises of all sizes. The proliferation of structured and unstructured data has driven the demand for data warehousing solutions. Snowflake is more than a data warehousing solution. As a platform, new solutions can be built and integrated into Snowflake based on the demand of its customers. The need to centralize data management remains a huge task faced by many enterprises. This has driven Snowflake’s rapid growth in recent years. Snowflake’s offerings are highly regarded due to its ability to connect to multiple cloud IaaS/PaaS, including AWS, Azure, and GCP. This helps enterprises prevent vendor lock-in. Unlike most of its competitors, Snowflake is built from the ground up to be cloud-native. This design advantage is attractive to developers and customers with data governance issues. It is also essential to enterprise CIOs and CTOs that care about its product evolution and platform stability.
According to IDC, there will be 175 zettabytes of data by 2025, representing a CAGR of 27% from 33 zettabytes of data in 2018. This data contains valuable insights for organizations, including key business and performance metrics, customer attributes and behavior, and product strengths and capabilities. – Source – Snowflake S1
Snowflake’s platform business model explains a considerable portion of its value creation potential. Snowflake has chosen to solve the most challenging problems faced by big data and legacy data warehousing solutions. In its IPO prospectus, it highlighted a lot of limitations faced by existing solutions. These limitations have hindered the massive adoption of data engineering and data science platforms. By improving upon these limitations, Snowflake appears to be positioning itself in the league of platforms that solve problems cutting across a business vertical. Similar players include Salesforce (CRM) in sales, Workday (WDAY) in HR, and CrowdStrike (CRWD) in cybersecurity. This positioning also serves as an excellent way to decide on peer companies to determine Snowflake’s valuation. Understanding the vast growth potential provided by its platform (capabilities in data ingestion, analytics, data processing, storage and compute optimization, data exchange platform for data sharing and monetization, and data app development) explains a sizeable portion of its valuation. If the network effects projections pan out as painted by its huge TAM, platform usage growth will ensure sustainable revenue growth by existing customers. This isn’t far-fetched as Snowflake’s platform computation pace and metered pricing feature ensures customers only pay for what they use. The usage-based pricing model will help Snowflake close the gap on public cloud platforms with a considerable cost advantage. This is not tough to fathom, given its tremendous dollar net expansion rate (~ 158%).
Snowflake’s cloud focus highlights its competitive positioning. As a pure-play data cloud platform, Snowflake has developed deep capabilities to collaborate and scale efficiently using IaaS resources provided by public cloud platforms. While public cloud platforms have competing offerings, I believe competition won’t be as intense as projected. Incubating a company like Snowflake is the reason cloud IaaS and PaaS solutions like AWS are built. As Snowflake scales, the consumption of the underlying resources of these platforms also grows. This is a win-win for both parties. Other competitors like Teradata (NYSE:TDC) and Cloudera (NYSE:CLDR) are migrating their on-prem customers to their cloud platform. Most enterprise CTOs will tend to favor cloud-native platforms when building their digital transformation strategy. I see this as a competitive edge for Snowflake.
Snowflake’s positioning as a cloud data platform serves as the best yardstick to select peer comparisons for its valuation. Most cloud platforms are built from the ground up to have features that ensure gravity-defying revenue growth. Network effects are the most apparent moat of cloud platforms. Network effects ensure all large and mid-sized enterprises join the winning team when adopting solutions to scale their businesses. In Snowflake’s case, the growing trend of data migration from on-prem data platforms to cloud platforms will kickstart this trend. This trend will be accelerated as the quality of data engineering, science, and analytics solutions in cloud environments improves. Two unique features of Snowflake’s cloud platform will drive this paradigm shift: cloud agnosticism and speed. The two features complement each other because mastering IaaS compute, storage, and networking resources provided by public cloud platforms offers unique insights to scale data computation and optimize resource consumption.
For the peer-based valuation, I will be selecting all the companies in the chart above. We can also include Datadog (NASDAQ:DDOG) and Twilio (TWLO). These platforms are Supercarriers. Supercarriers are built to move and protect resources across the oceans (cloud replaces oceans). Cloud platforms, like supercarriers, provide solutions that can be deployed across the world. They scale fast, and once the flywheel hits the escape velocity, their competitive moats are bolted in. The future points to a world where enterprises across the globe share datasets, AI/ML models, and insights. Platforms that enable these trends will drive superior results and returns for their users. As the flywheel accelerates, the quality of insights generated by these platforms will make it counterintuitive to build small scale analytics solutions. Recall that these platforms are ingesting data across the globe. They are also ingesting the data at a massive scale with robust collaborative features. This effectively makes their first-mover advantage as cloud data platforms, a solid competitive moat.
When we include the significant ROI that can be derived from a data cloud, the valuation is even more compelling as enterprises worldwide adopt a data-driven culture. In addition to this, another appealing part of platforms is that standalone SaaS companies can be built on top of them. Like Salesforce has enabled the growth of Veeva (VEEV) and Zuora (ZUO), the optionality to be derived from building a SaaS/PaaS on Snowflake is huge.
I reckon that Snowflake won’t have to wait for new solutions to be built on top of its platform. Platforms in adjacent segments will drive network effects as they seek cloud data platforms to fulfill the warehousing and management part of their data analytics engagements.
As a result, the upper ballpark of Snowflake’s peer-based valuation can be calibrated on a scale of one to Salesforce’s enterprise value. I am projecting Snowflake to grow its yearly revenue to $4B by 2025. This will justify its valuation, which is akin to ServiceNow (NYSE:NOW) and Workday. This also implies a multiple of 15x EV/FY’2025 revenue. This is my base case.
In the bullish case, the growth of unstructured data will drive the massive adoption of Snowflake’s platform. The huge volume of datasets available in its marketplace will attract developers and ML experts to its platform. This will help Snowflake build parity features in data analytics and advanced AL/ML similar to offerings provided by public cloud platforms.
In the bearish scenario, public cloud platforms and other competitors impact SNOW’s ability to grow market share. The adoption of open source solutions will commoditize the potential gains from new capabilities in data analytics. SNOW’s valuation tracks the growth and multiples of players like Cloudera and Teradata.
Snowflake’s cloud-native approach to data analytics means its risk factor will be more about consumption growth. Snowflake was designed to scale fast. It only needs to get its go-to-market strategy right for the “network effects” thesis to play out. Snowflake has done the bulk of the heavy lifting on the technology side, explaining why most of its investment has been channeled into sales and marketing in recent quarters. Lack of GAAP profits will continue to drive trading volatility in quarters with mixed billings guide.
Snowflake’s huge dollar net expansion rate shows that customers are growing their usage of its platform. I remain wary of the innovation happening in the ML/AI space. My experience with platforms like BigQuery (offered by Google (NASDAQ:GOOG)) gives me the feeling that Snowflake needs to be at parity with competitors in this area. Developing parity features in data analytics (ML/AI) will come at a huge cost.
Snowflake was designed to optimize the IaaS integration headache of solutions built in the data management space. This gives it the features of a platform of platforms or a system of records (SOR). From the table above, Snowflake can be likened to an OLAP (online analytical processing) system of records. Its cloud-native architecture means it can compete favorably with pure-play DMAs like Teradata and Cloudera. Its cloud innovation serves as a competitive difference. Its advances in IaaS resource optimization will be tough to rival because similar projects will have to build IaaS solutions with the scale and network latency of Azure/AWS/GCP. This feature is one of the reasons why cloud-native platforms are trading at sky-high valuations. The competitive moat that this feature gives is most pronounced when the SoR helps enterprises across the globe to scale/optimize their business processes. Salesforce has the bulk of these capabilities. Workday and ServiceNow also have an ample supply of this capability. Datadog’s ability to leverage this capability has been challenged by the growing shift towards adopting open source tools in the DevOps space. The narrative that scaling IT security spend is tough to justify to enterprise CFOs might mute CrowdStrike’s ability to leverage this feature.
Final Note (Author’s Bias)
Unlike other cloud platforms, I am more willing to give Snowflake more valuation laxity because of my strong conviction that data analytics drives true business value. I am convinced the ROI of investing in industry-leading data analytics platforms won’t be tough to justify. I also believe that the growth of data will be a natural catalyst that will drive the adoption of leading data management platforms. Lastly, I believe the network effects from a fully horizontally integrated pure-play data management platform will be tough to quantify or replicate as the flywheel spins.
Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.