Key Takeaways
- Co-founder Benoit Dageville offloaded 874 shares of SNOW on March 23 at $170.01 per share, generating approximately $148,588 through a pre-established 10b5-1 trading arrangement
- Chief Accounting Officer Emily Ho simultaneously sold 2,141 shares at roughly $173.97 each, collecting around $372,470 and reducing her holdings by 4.59%
- Shares have tumbled approximately 7% in the last week, currently trading near $161.21—significantly below the 52-week peak of $280.67
- Fourth-quarter performance exceeded expectations with $0.32 EPS beating forecasts and $1.28 billion revenue climbing 30.1% year-over-year, yet shares failed to rally
- Class-action lawsuits and persistent insider transactions are creating headwinds, though Wall Street maintains a “Moderate Buy” stance with a $248.58 average price target
The cloud data platform company faced renewed scrutiny last week as two executives executed stock sales on identical dates, coinciding with a sharp weekly decline that has investors questioning the stock’s near-term trajectory.
Co-founder and Chief Architect Benoit Dageville executed a sale of 874 shares on March 23, priced at $170.01, generating proceeds of approximately $148,588. This transaction followed a predetermined 10b5-1 plan established in March 2025, indicating the sale was scheduled rather than opportunistic. Additionally, Dageville transferred 598 and 287 shares on March 20, valued at $175.40 each, to satisfy tax withholding requirements.
Following these transactions, Dageville maintains direct ownership of 65,742 shares. His indirect holdings remain substantial—750,000 shares through The Selene GRAT No. 1, more than 3 million via The Snow Trust UTA, while his spouse controls an additional 750,000 shares through The Thira GRAT No. 1.
Simultaneously, Chief Accounting Officer Emily Ho divested 2,141 shares at a mean price of $173.97, generating roughly $372,470 in proceeds. This sale reduced her position by 4.59%, leaving her with 44,553 shares valued at approximately $7.75 million.
Impressive Quarterly Results Fail to Boost Shares
These insider transactions occurred against the backdrop of robust fourth-quarter performance. Snowflake delivered earnings per share of $0.32, surpassing the Street’s $0.27 expectation by a nickel. Quarterly revenue reached $1.28 billion, marking a 30.1% annual increase and exceeding the $1.25 billion consensus forecast. Remaining performance obligations surged 42% to $9.77 billion, driven partly by a substantial $400 million agreement with a financial services client.
Despite these fundamentals, the stock has struggled to gain momentum. Trading at $161.21, SNOW has retreated significantly from its 52-week high of $280.67 and remains underwater relative to both its 50-day moving average of $182.41 and 200-day average of $218.51.
Wall Street analysts have systematically reduced their price objectives following the earnings announcement. Wells Fargo slashed its target from $290 to $210. BTIG lowered expectations from $312 to $235. Scotiabank reduced its forecast from $290 to $205. Nevertheless, most analysts preserved their constructive ratings. Consensus among 42 analysts points to a $248.58 target price, with 33 maintaining Buy recommendations, five at Hold, and two at Sell.
Litigation Compounds Stock Pressure
Multiple law firms have initiated or publicized class-action proceedings against Snowflake, targeting shareholders who purchased shares between June 27, 2023 and February 28, 2024. Lead-plaintiff application deadlines are scheduled around April 27, 2026. The proliferation of legal actions—from firms such as Rosen, Pomerantz, Schall, and others—has introduced additional regulatory overhang for the stock.
On the institutional front, Vanguard expanded its holdings by 1.45 million shares during Q4, elevating its total position above 30 million shares. Jennison Associates increased its stake by 27.7% to 11.6 million shares. Institutional ownership accounts for 65.1% of outstanding shares.
The company’s AI-focused initiative, Project SnowWork, continues in limited preview mode, designed to deliver data-grounded AI agents for enterprise business applications.
