Elastic N.V. (ESTC) Q2 2026 Earnings Call Transcript
Access earnings results, analyst expectations, report, slides, earnings call, and transcript.
Overview
The earnings call reveals strong financial performance with raised revenue guidance and significant shareholder returns. The Q&A section addresses concerns about seasonality and government shutdown impacts, but emphasizes strong commitments and consumption. The company's focus on AI capabilities and market expansion is promising, despite some renewal delays. The positive sentiment is reinforced by a robust shareholder return plan and optimistic guidance, suggesting a positive stock price movement over the next two weeks.
Key Financial Performance
Revenue Total revenue for the second quarter was $423 million, representing growth of 16% as reported and 15% on a constant currency basis. This growth was driven by strong consumption, deal momentum, and traction with customers spending over $100,000 annually.
Sales-led Subscription Revenue Sales-led subscription revenue in the second quarter was $349 million, growing 18% as reported and 17% on a constant currency basis. This reflects the strategic advantages of the Elastic search AI platform in addressing critical consolidation and generative AI use cases.
Current Remaining Performance Obligation (CRPO) CRPO was approximately $971 million at the end of Q2, growing 17% as reported and 15% in constant currency over Q2 of the prior year. This growth was supported by strong deal momentum and healthy consumption trends.
Operating Margin Non-GAAP operating margin was 16.5% for the second quarter. This was achieved through disciplined cost management and increasing revenue.
Free Cash Flow Adjusted free cash flow was approximately $26 million in Q2, representing a margin of 6%. This quarter is typically a seasonally low free cash flow margin period for the company.
Customer Growth The number of customers spending over $100,000 annually grew approximately 13% year-over-year, with 180 net new customers added over the past 4 quarters. Quarter-over-quarter, approximately 50 net new customers were added.
Large Deals Over 30 commitments greater than $1 million in annual contract value were closed in Q2, with 5 of them representing greater than $10 million in total contract value and 2 of those greater than $20 million in total contract value. This was driven by platform consolidation and Gen AI use cases.
Share Repurchase Program Approximately $114 million in cash was returned to shareholders during Q2, representing purchases of approximately 1.4 million shares at an average price per share of $84.45.
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Operating Highlights
Elastic Security: Chosen by a major chemical manufacturer for its XDR platform, delivering advanced threat protection and a 35% increase in operational efficiency. Also selected by CISA for a $26 million commitment to secure U.S. federal civilian agencies with a unified SIEM as-a-service offering.
Agent Builder: Introduced as a new product to simplify the operational lifecycle of AI agents, enabling users to interact with data in Elastic search and build AI agents with robust workflow capabilities.
Streams: Launched as an agentic AI solution to simplify working with logs, helping SRE teams rapidly understand issues for faster resolution.
DiskBBQ: Released as a new disk-friendly vector similarity search algorithm for more efficient vector search at scale.
Generative AI (GenAI) Adoption: Strong demand for Elastic's platform for semantic search and Agentic applications. Over 2,450 customers on Elastic Cloud use it for GenAI use cases, with 370 spending over $100,000 annually. Signed 4 GenAI deals exceeding $1 million in annual contract value.
Large Deals: Secured over 30 commitments valued at over $1 million, including 5 deals exceeding $10 million and 2 surpassing $20 million in total contract value.
Sales Execution: Fifth consecutive quarter of disciplined sales execution, focusing on high-value opportunities and achieving strong subscription revenue growth of 18%.
AutoOps: Made available to self-managed customers, simplifying cluster management through real-time issue detection and resolution.
Acquisition of Jina AI: Acquired Jina AI to enhance multilingual and multimodal embedding and reranker models, accelerating Elastic's strategy in AI and vector search.
Share Repurchase Program: Initiated a $500 million share repurchase program, with $114 million already returned to shareholders in Q2.
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Risk or Challenges
Market Conditions: The company faces competitive pressures in the AI and security markets, as evidenced by the need to outperform competitors in securing large deals, such as the 8-figure deal with a chemical manufacturer and the $26 million commitment with CISA.
Regulatory Hurdles: The company operates in sectors like security and public infrastructure, which are subject to stringent regulatory requirements, as seen in the deal with CISA for securing U.S. federal civilian agencies.
Economic Uncertainties: Despite strong performance, the company acknowledges risks and uncertainties that could impact future results, as highlighted in their forward-looking statements disclaimer.
Strategic Execution Risks: The company’s reliance on large deals and strategic realignment of the sales team to focus on high-value opportunities could pose risks if these strategies do not yield consistent results.
Supply Chain Disruptions: No explicit mention of supply chain disruptions was made in the transcript.
Technological Challenges: The company’s success in AI and GenAI applications depends on continuous innovation and maintaining technological leadership, which could be challenging in a rapidly evolving market.
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Guidance & Outlook
Revenue Expectations: For Q3 FY2026, total revenue is expected to range between $437 million and $439 million, representing 15% growth at the midpoint. For FY2026, total revenue is projected to range between $1.715 billion and $1.721 billion, representing approximately 16% growth at the midpoint.
Sales-Led Subscription Revenue: For Q3 FY2026, sales-led subscription revenue is expected to range between $364 million and $366 million, representing 17% growth at the midpoint. For FY2026, sales-led subscription revenue is projected to range between $1.417 billion and $1.423 billion, representing 18% growth at the midpoint.
Non-GAAP Operating Margin: For Q3 FY2026, the non-GAAP operating margin is expected to be approximately 17.5%. For FY2026, the non-GAAP operating margin is projected to be approximately 16.25%.
Non-GAAP Diluted Earnings Per Share: For Q3 FY2026, non-GAAP diluted EPS is expected to range between $0.63 and $0.65. For FY2026, non-GAAP diluted EPS is projected to range between $2.40 and $2.46.
Capital Allocation: The company has initiated a $500 million share repurchase program, with more than 50% of the authorized amount expected to be used in FY2026.
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Shareholder Return Plan
Share Repurchase Program: In October, during the Analyst Day, Elastic announced a $500 million share repurchase program as part of its capital allocation framework. The program is already underway, and during Q2, the company returned approximately $114 million in cash to shareholders. This represents purchases of approximately 1.4 million shares at an average price per share of $84.45. Elastic expects to use more than 50% of the $500 million authorized amount in fiscal 2026.
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Key Q&A
Q:Are non-AI native customers seeing an increase or acceleration in consumption due to an increased AI focus?
A:Yes, there is strong consumption across the board, including traditional businesses, observability, and security. The company secured large commitments, including five deals over $10 million in total contract value, all cloud-based.
Q:Why did billings lag other growth metrics like CRPO and RPO?
A:The lag was due to seasonality and an atypical revenue distribution last year. Additionally, a government shutdown caused some renewals to slip from Q2 to Q3. However, commitments and consumption remain strong, and the company raised its guidance for the year.
Q:What is the composition of the newly introduced sales-led subscription revenue guidance?
A:The guidance includes commitments driven by the sales team for both cloud and self-managed subscriptions, excluding monthly cloud self-serve business, which is expected to remain flat. The company raised its full-year guidance due to strong Q2 performance.
Q:Why did sales-led subscription revenue growth decline from 22% in Q1 to 18% in Q2?
A:The decline is attributed to seasonality and renewal slips due to a government shutdown. Management emphasized that focusing on pricing in isolation is incorrect and highlighted strong overall consumption and commitments.
Q:How is the company addressing challenges with RAG (Retrieval-Augmented Generation) and monetizing AI search capabilities?
A:The company specializes in relevance and messy unstructured data, simplifying complex tasks with tools like Agent Builder. Agent Builder uses vector databases and embedding models to connect private data with large language models, enabling monetization through AI search capabilities.
Q:Why was the revenue beat in Q2 lower than historical levels?
A:The company provided closer-to-the-pin guidance during Financial Analyst Day, reflecting expected variability and seasonality. Despite this, the company raised its full-year guidance significantly.
Q:What is driving the momentum in the sales team’s productivity and capacity?
A:Changes made six quarters ago are yielding results, with strong sales execution and commitments. The company continues to invest in go-to-market capacity and AI capabilities, which are driving differentiation and deal wins.
Q:What is the company’s perspective on recent acquisitions by competitors in observability and security?
A:The company views these acquisitions as validation of its strategy. Elastic believes its data platform and AI capabilities are more advanced, enabling it to win deals and expand its market presence.
Q:How are AI workloads impacting the company’s business?
A:AI workloads are more compute-intensive and growing faster than other cohorts. The company is seeing broad adoption across industries, with production use cases driving stickiness and revenue growth.
Q:What is the impact of product optimizations like logs DB on cloud revenue?
A:Product optimizations make the platform more efficient, enabling customers to manage growing data volumes and bring new workloads onto the platform. Commitments are driving consumption and revenue growth.
Q:How does the company view the mix of cloud versus self-managed revenue?
A:The company does not differentiate between cloud and self-managed revenue internally. Both are important, and the sales team is incentivized to meet customers where they are.
Q:What was the impact of the government shutdown on Q2 results?
A:The shutdown caused some renewals to slip from Q2 to Q3. However, these customers continue to use the software, and the renewals are expected to close in Q3.
Q:How is the company performing in the federal sector?
A:The U.S. public sector performed well despite the government shutdown. The CISA deal, a $20+ million security win, highlights the strength of the company’s platform and AI capabilities.
Q:What is the company’s approach to large deals and renewals?
A:Large deals include a mix of new logos and expansions. For example, one of the largest deals was a new logo worth over $20 million. Renewals that slipped due to the government shutdown are expected to close in Q3.
Q:Review of Unclear Management Responses
A:Management avoided directly addressing the specific breakdown of cloud versus self-managed revenue in the sales-led subscription guidance. They emphasized that the sales team is not given separate targets for cloud and self-managed, making it difficult to assess internal performance against these categories. Additionally, they did not provide a detailed breakdown of the $30 million large deals into renewals versus new customers.
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Earnings Word Cloud
The most frequently occurring keywords in this quarter's earning call
AI agent
Agent Builder
AutoOps
CISA
Cloud self
Discovery
DiskBBQ
Elastic Security
GenAI
LLM
Observability
SIEM
Search
Streams
adoption platform
agency
application
architecture ability
capability
challenge
context engineering
customer
deployment
detection
feature
figure
inference service
issue
log
observability
solution
threat
use case
use search
vector database
vector search
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