Snowflake's Earnings Report Tonight: AI Engine Ignited, Q2 Guidance is the Real Test

Cloud data analytics giant Snowflake (NYSE: SNOW) is set to report its FY2027 first quarter financial results (ending in April 2026) after the U.S. market closes on Wednesday. Wall Street is widely expecting solid results for this quarter, but analysts caution that the market's focus will quickly look through the quarterly numbers to the second quarter guidance—which is the key variable in determining the stock's direction.

Meeting targets is the baseline, with limited room for outperformance

The Wall Street consensus estimates Snowflake's first quarter product revenue to be around $1.265 billion, a year-over-year increase of about 27%, closely aligning with the company's official guidance range ($1.262 billion to $1.267 billion).

Barclays analyst Raimo Lenschow believes that there is about a 2.5% room for outperformance this quarter, mainly benefiting from the acquisition of Observe at the beginning of the year, which brought an additional $10 million in revenue. He estimates Snowflake's net new product revenue for the quarter to be about $70 million, higher than the consensus expectation of $39 million. "The results are expected to slightly exceed expectations again, but we are not sure whether this will be enough to be a catalyst for stock prices in the near term."

In terms of profitability, the consensus expectation for Non-GAAP operating margin is about 9%, essentially flat compared to the same period last year; Non-GAAP earnings per share are estimated to be around $0.32. Jefferies estimates free cash flow to be around $309 million, higher than the consensus of $276 million.

Q2 Guidance: The trap of high base numbers and Wall Street's expectations divide

Three investment banks unanimously regard the guidance for the second quarter as the most important observation window for this earnings report.

The root of the problem lies in the high base number left a year ago. In the second quarter of the fiscal year 2026, Snowflake achieved a net new product revenue of $94 million due to large-scale platform migration by customers and the contribution of the Crunchy Data acquisition—this number is an outlier in the company's history.

The current market consensus expects second quarter product revenue to be around $1.374 billion, a year-over-year increase of 26%, implying a net new addition of about $102 million. Jefferies analyst Brent Thill points out the fragility of this expectation: "If the first quarter only achieves the normal outperformance of about 3%, coupled with the company's habitually conservative quarterly outlook, the actual growth rate for the second quarter may only be 24%, lower than the consensus of 26%."

Based on this, Jefferies has set up three scenarios for investors: first, the first quarter achieves a significant outperformance; second, the management provides guidance stronger than historical patterns; third, improper expectation management leads to second quarter guidance falling short of expectations. Thill sets the "passing mark" at a product revenue growth rate of no less than 26% for the second quarter.

Cortex Code: The underestimated consumer growth engine

If there is one potential surprise factor for this earnings report, research from several institutions points to the same name—Cortex Code.

This AI programming agent product, released at the beginning of this year, deeply embeds Anthropic's Claude model into the Snowflake data platform, using a token-based billing model. Snowflake's CEO has publicly stated that within just 9 weeks after the product's launch, 50% of customers are using Cortex Code, with the current number of active accounts being around 4,400.

UBS analyst Karl Keirstead, initially skeptical, visited 10 Snowflake customers and partners and ultimately came to an unexpected conclusion.

"The feedback on this product is unique," he wrote in his report. "Previously, Snowflake launched products like Snowpark, which were also highly anticipated at the beginning, but received lukewarm feedback after customer interviews. Cortex Code has made us feel a real difference."

Customer feedback was frank and telling. One company said, "Unfortunately, because of using Cortex Code, our expenses have increased. We are using it for optimization, but the more optimization you do, the more queries you run, creating a cycle." Another company described, "You can generate code on the platform and run it on the platform, which increases consumption while accelerating."

The main application scenarios for Cortex Code include: accelerating data pipeline development, optimizing warehouse resource use, building Streamlit applications, and helping new users get started with the Snowflake platform faster.