Snowflake shares fall on slower product revenue growth forecast for fourth quarter

Dec 4 (Reuters) - Snowflake shares slumped 8% in premarket trading on Thursday after the cloud data analytics company forecast slower product revenue growth for the fourth quarter, partly hit by discounts offered on the large, long-term deals.

 

Chief Executive Officer Sridhar Ramaswamy said on Wednesday that the company provides more favorable pricing for larger volumes or longer-term contracts, noting that these "don’t tend to have an immediate impact on revenue."

 

However, at least 13 brokerages raised their price targets on the stock, encouraged by the signs of adoption in the company’s AI offerings.

 

If premarket losses hold, Snowflake could lose around $7 billion from its market value of nearly $90 billion. The company’s shares have risen over 70% so far this year.

 

The company also announced a $200 million multi-year agreement with Anthropic to bring Claude models to its platform.

 

Snowflake’s product revenue was "undoubtedly decent" but was slightly below investor expectations after peers like Datadog, Confluent and MongoDB showed impressive performance, analysts at Scotiabank said in a note.

 

The company said over 7,300 businesses engage with its AI features weekly, while its agentic AI solution, Snowflake Intelligence, has attracted around 1,200 customers within a month of launch.

 

"While it remains very early innings, we are encouraged by the signs of traction SNOW is showing with AI use cases," said analysts at Truist Securities.

 

Its third-quarter revenue of $1.21 billion exceeded LSEG-compiled estimates of $1.18 billion.

 

The company expects fourth-quarter product revenue growth of 27%, while it reported 29% growth in the October quarter.

 

Products offered by companies like Snowflake help clients to store, process and consolidate data that helps in producing business insights.

 

Snowflake trades at 165.11 times the estimates of its earnings for the next 12 months, compared with 65.86 times for peers Datadog and 76.07 times for MongoDB.

 

(Reporting by Jaspreet Singh in Bengaluru; Editing by Vijay Kishore)