Overview:
Key Takeaways:
INVESTMENT THESIS
BASE CASE ASSUMPTION
Overview:
Oppenheimer: Snowflake hosted its Summit conference and investor event this week, where it highlighted (1) its growing TAM opportunity as a data cloud, (2) long-term evolution to combine both OLTP and OLAP data warehousing, (3) expanding use cases to include cybersecurity-as-a-workload, and (4) ability to query on-prem data with S3-compatible storage.
It also reiterated FY29 targets ($10B revenue, 20% OM, 25% FCF margin), while noting the long-term benefits of HW/SW optimizations to incremental workload deployment on Snowflake. While seeing these as lofty targets, we believe the path to achieve them is possible given the growth levers laid out (>$1M customer growth, G2K penetration, growing TAM, etc.). Overall, we come away comfortable with our thesis and positive on Snowflake’s platform direction and prospects. Maintain Outperform.
Key Takeaways:
Product announcements. Snowflake made the following announcements: (1) Snowpark for Python, (2) a “native application framework” for developers to build and deploy new applications, (3) Unistore (including Hybrid Tables) in an effort to combine OLTP and OLAP data, and (4) expanding querying to S3-compatible onprem storage. The company also views cybersecurity as a workload and envisions security applications leveraging and deployed on Snowflake data cloud.
TAM. Snowflake noted multiple secular tailwinds driving long-term TAM, including DBMS percent share increase of total software spend, and Cloud and OLAP percent share increase of DBMS spend. As such, it expects a TAM of $248B by CY26E with workloads segregated by data warehousing/data lake (70% mix), data science/ML apps (20%), collaboration (6%), and cybersecurity (4%). Data Cloud opportunity is larger still.
$10B target unchanged. Management maintained its $10B FY29 product revenue target, or 35% seven-year CAGR. While lofty, we see a path for Snowflake to achieve its goal given systemic shift toward digitization and public clouds. It also laid out a framework to achieve this target, including ~1,400 $1M customers in FY29 (206 in F1Q23) at an average spend of ~$5.5M/customer ($3.5M currently).
Margin drivers. Diving into updated FY29 margin targets provided last month (78% product GM, 20% OM, 25% FCF margin), the company noted the following drivers —YoY percent price increase in compute price-per-credit (4% in FY22 vs. 8%/12% in FY21/FY20), mix shift toward Enterprise/Business Critical tiers (83% combined in FY22 vs. 58% FY20), and operating leverage from increase in >$1M customers.
Bottom line. While the product announcements were not ground-breaking, they highlight Snowflake’s steady innovation and shift toward a broader platform. Still, the path to $10B FY29 revenue target appears more attainable vs. a year ago. The company continues to deliver strong and unparalleled adoption metrics, and is finally delivering on operating profitability.
INVESTMENT THESIS
Snowflake offers a unified Cloud Data Platform (CDP) that eliminates data silos and consolidates data into a single source of truth, thereby enabling data analytics across multiple use cases.
Our bullish view is predicated on our belief that Snowflake: (1) can take advantage of secular themes (rising importance of data, public cloud reliance for scale, on-demand IT consumption etc.); (2) will gain share as it expands its TAM to address use cases beyond data warehousing (data lakes, data
science, data engineering, data applications, data exchange); and (3) will execute on its land-and expand model by driving strong customer growth and expansion, with a focus on larger enterprises.
BASE CASE ASSUMPTION
- Dollar-Based Net Retention (Product) rates >120% with steadily growing usage across depts/new use cases
- Strong new customer growth (>30% YoY)
- Solid large-customer (>$100K and >$1M ARR) customer traction with growing Fortune 500 penetration
- Snowflake remains ahead of cloud providers and legacy data warehouse incumbents in product innovation, enabling a strong competitive moat for data warehousing use case
- Steady progress toward achieving operating and FCF profitability
UPSIDE SCENARIO
- Dollar-Based Net Retention (Product) >140% with widespread usage across depts. and for new use cases
- Strong new customer growth (>50% YoY) with more customers anding on higher tiers (Business Critical, VPS)
- Robust large-customer (>$100K and >$1M ARR) customer traction
- Product innovation drives strong traction for data warehouse, data engineering, data lake, data science, data applications, and data exchange use cases
- Operating and FCF profitability is achieved faster than expected (by FY22) even with continued planned product/sales investments
Our $230 PT assumes a CY23E EV/sales multiple of ~25x, well above the midpoint of its high-growth peer group (~10.0x). We believe this reflects SNOW’s technological leadership and competitive moat in the cloud data warehouse market, growing developer mindshare, execution track record, robust growth prospects (above the peer group), and potential for upside (based on share gains into its large TAM).
If market growth expectations or product innovation slows, mindshare among developers could be affected while usage could decline, affecting revenue growth. The competitive landscape is quickly evolving and intense (cloud providers, legacy incumbents), putting pressure on SNOW to execute on its land-and-expand strategy and expand usage with larger enterprises and to new use cases. It also has significant operating and FCF losses, relies on public cloud infrastructure, and faces seasonality and revenue concentration risks.
