Snowflake is a cloud-based platform whose vision is to enable organizations to have seamless access to explore, share, and unlock data value. With the mission to break down data silos. The company runs through a consumption-based revenue model, enhanced by its professional services. Primarily an enterprise solution, Snowflake leverages on direct sales.
Vision, Mission And Values
To realize this vision, Snowflake helps customers break down data silos. Why is this important in the first place? The core problem that Snowflake solves is the fruit of the massive amount of data generated in the digital era.
Where does the opportunity come from? Some of the key problems that Snowflake helps solve and that were the foundation of its core value propositions are:
- Lack of formats that enable data to be used in other contexts: for many organizations, data is stored in formats that are not compatible to be used in several contexts, this is one of the reasons for data silos.
- Inability to handle large volumes of data, especially in cases where organizations try to deal with big data, querying it becomes time-consuming and resource-intensive.
- Inability to address and support as many use cases as possible within the organization.
- High management costs of that data.
- The difficulty of use.
All the aspects above, enabled Snowflake to get clear about the value customers get from its product:
The above are some of the reasons that enabled companies like Snowflake to pursue their vision. In short, Snowflake helps its customers consolidate data within a single interface, platform, to generate use cases available across the company.
Snowflake also introduces a model that is more in line with cloud-based businesses. Rather than being subscription-driven, those are primarily based on consumption. Thus customers are charged based on the resources they are using at that moment.
The key value proposition of Snowflake stands in the fact that it offers a ready to use, a complete platform to its customers so that they don’t have to bear the maintenance costs and can integrate the data in the cloud provided by Snowflake across the company.
Snowflake claims positive network effects for its platform, as more customers join in, thus making the data on its cloud exchanged with other customers, thus enhancing the overall value of the platform.
With some core use cases:
- Data engineering.
- Data lake.
- Data warehousing.
- Data science.
- Data applications.
- And data sharing.
Below a quick demo of how the Snowflake platform looks like:
Below some key facts about how Snowflake’s customers look like:
As Snowflake’s platform evolved over the years, it added more and more use cases. As of now, customers can opt to use its platform for any of the main use cases available (data engineering, data lakes, data warehousing, data science, data applications, and data exchange), or use the platform as an end-to-end solution.
The whole Snowflake architecture is broken down into three main parts: centralized storage, multi-cluster compute, and cloud services. The centralized storage is where all the data, be it structured or semi-structured is stored, and its kept consistent.
From there, instead, the other layer, the multi-cluster compute is the one that makes it possible to develop multiple use cases, accessing the single copy of the data (available on the centralized storage). And the cloud services layer makes it possible for the platform to keep a consistent and user-friendly customer experience.
Below some key facts about Snowflake’s revenue model:
- As a cloud platform, it runs on the consumption-based of the product. Indeed as of July 2020, most of the revenues (over 93%) came from product usage.
- Revenue growth from 2019 to 2020 was driven primarily by increased consumption of the platform, and sales prices increased 11% year over year (Snowflake instructed its sales force to apply fewer discounts for customer acquisition/retention).
- As of July 2020, 56 customers with product revenue of greater than $1 million represented approximately 46% of Snowflake’s total product revenues.
- Professional services made up the remaining chunk of revenues (less than 7%) as Snowflake ramped up its professional services to support its customers toward its usage.
How does Snowflake spend money to generate its revenues?
Below the answer:
It’s interesting to notice that Snowflake’s professional services cost of revenues equals its revenues (over $14 million of both costs of revenues and revenues from professional services). In short, Snowflake is using its professional services, not as an additional revenue stream, but as an enabler for its product revenues. It seems, the company is charging for professional services at cost, while its keeping higher gross margins on its product (as the professional services organization might be scaled, margins might improve).
Snowflake’s cost of product, instead, is comprised primarily of third-party cloud infrastructure expenses and headcount of support and engineering people that help deliver the platform in the first place.
How costs of revenues are managed is critical, as this will affect gross margins, which is one of the financial metrics that investors look the most.
For instance, from 2019 to 2020, gross margins increased from 49% to 62%. That happened primarily due to:
- Better discipline over discounting (improved sales discipline).
- Higher volume-based discounts for purchases of third-party cloud infrastructure (scale-based savings).
- Increased scale across cloud infrastructure regions.
Sales And Marketing Model
Snowflake is an enterprise cloud solution, as such it primarily leverages on business development and direct sales to rump up its sales. The direct sales team is primarily comprised of:
- Field sales.
- Inside sales.
- Sales executives.
Sales teams are organized across the regions served by Snowflake with the aim of acquiring new customers and drive existing customers to increase their platform usage.
The direct sales team is enhanced by the marketing side, where the platform is self-service at various levels within an organization (for instance, companies can activate a trial via Snowflake’s website), and from there, the direct sales team can engage with the C-suite level executives to secure larger contracts.
Another core marketing and distribution channel for Snowflake is its Partner Network, made of channel partners, system integrators, and technology partners, that help the company to source leads and increase the platform adoption.
Research And Development Model
The R&D part of the organization mainly comprises:
- Software engineering.
- User experience.
- Product management.
- Data science.
- Technical program management and technical writing
As of July 2020, Snowflake’s R&D team counted 384 employees.
- Snowflake is a cloud-based platform that organizes data for companies across various industries to break data silos.
- Snowflake’s vision is to enable organizations to have seamless access to explore, share, and unlock the value of data.
- Its revenues primarily follow a consumption-based model, where customers pay based on the resources they use. Snowflake also built up the team offering professional services, which helps increase its platform’s adoption.
- Snowflake’s solution is primarily an enterprise product; its adoption is increased via direct sales. At the same time, the company also uses a self-serving model for the activation of its platform.
- Vision and Mission: Snowflake’s vision is to provide organizations with seamless access to explore, share, and unlock the value of data while breaking down data silos. Its mission revolves around solving the challenges posed by massive data generation in the digital era.
- Value Propositions: Snowflake addresses problems like incompatible data formats, handling large data volumes efficiently, supporting diverse use cases, managing data costs, and usability difficulties. Its core value propositions include data volume handling, performance, a utility-based payment model, instant elasticity, and ease of use.
- Platform Evolution: Snowflake has evolved from a cloud data warehousing solution to a multi-cloud data platform offering various use cases such as data engineering, data lakes, data warehousing, data science, data applications, and data sharing.
- Architecture: Snowflake’s architecture consists of three layers: centralized storage for consistent data storage, multi-cluster compute enabling multiple use cases, and cloud services providing a user-friendly experience.
- Customers: Snowflake’s customer base has grown significantly over the years, with thousands of customers across various industries. It has a mix of customers generating different revenue levels.
- Revenue Model: Snowflake’s revenue primarily comes from product/software usage, following a consumption-based model. It generates a significant portion of its revenue from customers paying based on the resources they consume.
- Cost Structure: Snowflake’s cost structure is primarily skewed towards the product business, which generates higher revenue and gross margins. The company uses professional services to enhance its product business, even though professional services operate at negative gross margins.
- Sales and Marketing: Snowflake leverages direct sales, business development, and a partner network to market and sell its enterprise cloud solution. It uses a combination of direct engagement and self-service activations to attract and retain customers.
- Research and Development: Snowflake invests in research and development, comprising software engineering, user experience, product management, data science, and more. The R&D team focuses on enhancing the platform’s features and capabilities.
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