Snowflake Q1 Earnings Beat Expectations, AI-Driven Growth Accelerates, Target Price Raised to $300

Overview

This report reviews Snowflake's fiscal year 2027 first quarter earnings. The report argues that Snowflake achieved accelerated growth thanks to the monetization of AI capabilities (especially Cortex Code) and strong performance in its core data platform business. Q1 product revenue grew 34% YoY, beating market expectations, and management provided more optimistic full-year guidance. Based on this, Morgan Stanley maintains its 'Overweight' rating on Snowflake and significantly raised the target price from $245 to $300, believing it has joined the ranks of a few successful AI software winners.

Core views

Strong earnings rebound, with AI becoming the core driver. Snowflake's Q1 product revenue reached $1.33 billion, growing 34% YoY, further accelerating from 30% in the previous quarter, and exceeded market consensus estimates by 5.2%. Unlike previous growth driven by one-time migration large orders, this acceleration is primarily due to increased consumption from AI features and steady growth in core data platform business. Management pointed out on the earnings call that since Cortex Code became fully commercialized in February, it has had a significant pull effect on customer demand. Guidance significantly raised, validating AI monetization logic. Given the strong Q1 performance and early success of AI products, management raised the full-year FY27 product revenue growth guidance from the previous 27% to 31%. Specifically, Q2 guidance is for 30% YoY growth, which is far higher than the 26% expected by the market. This guidance upgrade explicitly includes the contribution of Cortex Code to customer consumption trends, marking that AI monetization has entered a substantive phase. Focus on operational efficiency improvement and customer expansion. AI not only drove revenue growth but also improved internal efficiency. Data shows that the use of Cortex Code doubled engineering productivity, each sales representative won 86% more use cases YoY, while the company only net added 17 employees excluding acquisition impact. In terms of market expansion, the Snowflake brand effect emerged, new customers increased 38% YoY in Q1, and the overall customer base grew 22% YoY, showing that its AI and data strategies resonated strongly in the market. Valuation re-shaping and long-term vision. Morgan Stanley believes Snowflake is aiming to become an enterprise-level 'Agent Control Plane', leveraging its advantages in customer data, context engine, and security governance to orchestrate agent workflows. Although expanding audience groups to business users and modern developers requires new marketing efforts, its core competitive advantage remains solid. Based on the sustainability of growth and the establishment of AI leadership, the institution upgraded valuation multiples and the target price.

Analysis framework

The report adopts a typical 'Performance Verification + Valuation Reassessment' analysis framework. First, by breaking down quarterly revenue components, distinguishing between 'one-time factors' and 'structural drivers', confirm growth quality (pointing out this acceleration stems from AI consumption rather than simply large order migration). Second, combine changes in management guidance with the timing of new product (Cortex Code) launch to verify the authenticity and continuity of AI monetization. Finally, use Discounted Cash Flow (DCF) combined with Relative Valuation (EV/FCF Multiple), based on upgraded long-term Free Cash Flow forecasts, recalculate the target price, and conduct a horizontal comparison with peers (such as Datadog) to verify valuation rationality.

Methodology notes

• Valuation MethodDCF Cash Flow Discounting

  DCF Cash Flow Discount Model

  The report uses the DCF model to calculate the target price, discounting projected future free cash flows (FCF) to present value using the weighted average cost of capital (WACC 11.1%). This is the core method for assessing the intrinsic value of high-growth tech companies.

• Valuation MethodEV/EBITDA valuation

  EV/FCF Multiple Valuation

  The report uses the Enterprise Value to Free Cash Flow ratio (EV/FCF) as the valuation anchor. By applying a multiple of 39x to the forecasted 2030 free cash flow and adjusting for growth rate (similar to PEG concept), a reasonable enterprise value is derived.

• Industry Analysis FrameworkVolume-price decomposition

  Consumption Volume and Unit Price Analysis

  In the SaaS and Data Cloud sectors, revenue growth can be decomposed into customer count (volume) and per-customer consumption/retention (price/volume). The report analyzes new customer growth and increased consumption by existing customers due to AI to explain the revenue acceleration.

• Competition and Strategy FrameworkMoat / competitive advantage

  Data Network Effects and Switching Costs

  The report emphasizes Snowflake's advantage as a 'Context Engine' and possessing knowledge of customer data, which constitutes the competitive moat (barrier to entry) in enterprise AI agent workflows, enabling it to win market share.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• Snowflake Inc. (SNOW.US)

  Direct beneficiary, AI product monetization acceleration drives dual growth in revenue and profit

  Strengths

  Core data platform business strong, Cortex Code drives consumption increase, rapid new customer growth, improved operational efficiency

  Weaknesses

  Expansion to business users and developers requires new marketing strategies, faces competition from public cloud vendors

  Comparison

  Compared to Datadog (DDOG), Snowflake's valuation multiple (14.4x FY27E revenue) is slightly lower or flat, but growth prospects are more attractive due to AI monetization

  Risks

  Intensified competition leading to pricing pressure, difficulty expanding into adjacent data management areas (such as OLTP)

Key data

• Q1 Product Revenue$1.33 BillionUp 34% YoY, exceeding consensus estimates by 5.2%
• FY27 Product Revenue Growth Guidance31%Raised from previous 27%, showing growth acceleration
• Q2 Product Revenue Growth Guidance30%Far higher than market consensus estimate of 26%
• New Customer Growth38%Year-over-year increase in number of new customers in Q1
• Target Price$300Raised from $245, implying approx. 71% upside potential
• Forecasted Free Cash Flow for 2030$4.2 BillionBase case assumption, corresponding to 39x EV/FCF multiple

Impact & implications

The report believes that Snowflake's performance proves that the data platform value in the era of large models has not been weakened, but rather found a new growth curve through AI functions. This is of great significance to alleviate market concerns about its unclear positioning in AI competition previously. The upgraded target price and rating indicate that institutional investors begin to reassess Snowflake's premium ability as an 'AI Infrastructure Winner'. For the industry, it means the combination of data cloud platforms and AI application layers has entered the harvest period, and companies with strong data governance and consumption models will receive valuation re-rating.

Risks

• Pressure from competitive vendors may affect pricing, thereby dragging down growth and margins
• Difficulty proving expansion into adjacent data management use cases (such as online transaction processing OLTP)
• Public cloud competition creates weight pressure on growth

What to watch

• Subsequent monetization progress and customer adoption of Cortex Code and other AI products
• Trend changes in Net Revenue Retention (NRR)
• Growth in the number of annual contract value over $1 million customers
• Execution effectiveness of market expansion to business users and modern developer groups