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  4. Similarweb Ltd. (SMWB) Q4 2025 Earnings Call Transcript

Similarweb Ltd. (SMWB) Q4 2025 Earnings Call Transcript

SMWB logo
SMWB
Similarweb Ltd
6.36 USD
+1.60%

Access earnings results, analyst expectations, report, slides, earnings call, and transcript.

Overview

The earnings call summary and Q&A indicate positive financial performance, with raised guidance for operating profit and continued positive free cash flow. Product development is strong, with new launches and AI integration. The market strategy is focused on expansion and customer growth. Despite some revenue misses due to delayed deals, guidance remains optimistic. Shareholder returns are not explicitly mentioned, but overall financial health and strategic positioning suggest a positive outlook. The lack of market cap information limits precise prediction, but the sentiment leans towards a positive stock price movement.

Key Financial Performance

Revenue Revenue grew 11% year-over-year to $72.8 million. This was below guidance due to the timing of 2 large LLM data training contracts that did not close yet. These contracts are expected to represent significant multiyear revenue opportunities once closed.

Free Cash Flow Generated approximately $13 million in free cash flow for the year, marking the ninth consecutive quarter of positive free cash flow. This reflects the company's commitment to profitable and durable growth.

Net Revenue Retention (NRR) Net revenue retention for all clients was 98%, and 103% for clients above $100,000. The company aims to improve these metrics in 2026 by executing a customer expansion playbook.

AI-Related Revenue AI-related revenue reached 11% of sales in Q4 2025, up from 8% at the end of Q2 2025. This growth was driven by the portfolio of innovative AI solutions.

$100,000 Customers The number of $100,000 customers grew 12% year-over-year and now represents 63% of ARR. This indicates deeper customer relationships and stronger alignment with the company's value proposition.

Multiyear Contracts Revenue from multiyear contracts increased to 60% of ARR, up from 49% in 2024. This reflects greater revenue visibility and stronger customer commitment.

Non-GAAP Operating Profit Non-GAAP operating profit for Q4 2025 was $3.4 million, reflecting a 5% margin, compared to $2.6 million and a 4% margin in Q4 2024. This improvement was achieved through disciplined cost control.

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Operating Highlights

AI Studio: Launched as an AI-powered chatbot interface to democratize access to data, enabling users to ask business questions in plain language and receive actionable insights. Early feedback has been positive.

App Intelligence: Fastest-growing product in 2025, part of the company's AI-related offerings.

Ad Intelligence, Gen AI Intelligence, AI Agent, and MCP integrations: New offerings introduced in 2025 to enhance AI capabilities and data accessibility.

AI-related revenue: Increased to 11% of total sales in Q4 2025, up from 8% in Q2 2025, driven by innovative AI solutions.

Partnership with Manus: Extended data sets into agent-driven workflows, expanding TAM and providing revenue opportunities. Manus was recently acquired by Meta.

Bloomberg terminal integration: Expanded integration, positioning Similarweb as a premium alternative data provider for institutional investors.

Revenue growth: Achieved 11% year-over-year growth in Q4 2025, reaching $72.8 million, though below guidance due to delayed AI contracts.

Free cash flow: Generated $13 million in free cash flow for 2025, marking the ninth consecutive quarter of positive free cash flow.

Net revenue retention (NRR): NRR for all clients was 98%, and 103% for clients above $100,000. Focus on improving these metrics in 2026.

Multiyear ARR: 60% of ARR is now multiyear, up from 49% in 2024, reflecting stronger customer relationships and revenue visibility.

AI-first integrated solutions: Doubling down on AI solutions to establish leadership in the AI transformation era.

Enterprise relationships: Focused on scaling relationships with large tech customers, including two generating over $10 million in ARR.

Data moat: Invested in expanding data coverage and accuracy across various digital channels, reinforcing competitive advantage.

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Risk or Challenges

Revenue growth: Revenue grew 11% year-over-year to $72.8 million, but this was below guidance due to the delayed closing of two large LLM data training contracts. These delays highlight the risk of extended sales cycles for complex AI contracts, which could impact revenue predictability.

Net Revenue Retention (NRR): NRR for all clients stabilized at 98%, which is below expectations. This indicates challenges in retaining and expanding revenue from the broader customer base, despite a higher NRR of 103% for clients above $100,000.

AI-related revenue: While AI-related revenue grew to 11% of sales in Q4, the company faces challenges in converting one-time AI evaluation deals into recurring revenue, which could limit long-term growth potential.

Delayed AI contracts: The delayed closing of two major LLM-related agreements impacted Q4 revenue. These delays underscore the risk of dependency on large, complex deals for revenue growth.

Market volatility: The company acknowledges market volatility, which could impact its ability to close deals and achieve revenue targets.

Operational execution: Challenges in executing the customer expansion playbook and improving NRR metrics indicate potential operational inefficiencies that could hinder growth.

Economic uncertainties: The company is taking a prudent approach to 2026 guidance, assuming pockets of end-market weakness persist, which reflects broader economic uncertainties.

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Guidance & Outlook

Revenue Expectations for 2026: Total revenue is expected to be in the range of $305 million to $315 million, representing 10% year-over-year growth at the midpoint of the range. For Q1 2026, total revenue is expected to be in the range of $72 million to $74 million, representing 9% year-over-year growth at the midpoint.

Non-GAAP Operating Profit Projections: For the full year 2026, non-GAAP operating profit is expected to be between $16 million and $19 million. For Q1 2026, non-GAAP operating profit is expected to be in the range of $0.5 million to $2.5 million.

AI Revenue Growth: AI-related revenue grew 3x year-over-year in 2025 and now represents 11% of Q4 revenue. The company expects AI to be a significant monetization tailwind going forward.

Enterprise Expansion Focus: Enterprise expansion will be a key focus area in 2026, with plans to scale relationships with large tech customers and increase multiproduct adoption over time.

AI Product and Ecosystem Strategy: The company plans to expand its AI portfolio, including AI Studio and Gen AI Intelligence, and deepen partnerships with AI platforms like Manus. These efforts aim to embed Similarweb data into AI-native workflows and expand distribution at scale.

Capital Allocation Priorities: The company plans to invest around 20% of revenues in R&D to improve digital data and deepen its competitive moat. M&A will be pursued selectively to enhance data assets and product portfolio.

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Shareholder Return Plan

The selected topic was not discussed during the call.

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Key Q&A

Q:What is the correlation between large LLM contracts and the decline in large customer NRR?
A:Or Offer clarified that there is no correlation between the core business of selling regular software (Web Intelligence, App Intelligence) and the motion of selling data for LLM use cases. These are different use cases and do not impact each other.
Q:How does the new CFO, Ran Vered, approach guidance given the uncertainty of large deals?
A:Ran Vered explained that the guidance range was widened from $3 million to $10 million due to the uncertainty in the timing of large LLM deals. Some percentage of these deals is already baked into the guidance, but adjustments will be made as deals land.
Q:What is happening with the core business excluding AI revenue, and how does the company plan to address challenges?
A:Or Offer stated that the core business is still growing even without data for LLMs. Maoz Lakovski added that GRR and renewal rates are strong, with 60% of the book of business under multiyear contracts. The company is focusing on expansion to improve NRR and leveraging a strong product portfolio.
Q:What factors determine the high and low ends of the guidance range?
A:Ran Vered mentioned that landing the big LLM deals is the primary factor determining the difference between the high and low ends of the guidance range. The timing and size of these deals are critical.
Q:Was the $4 million miss in the quarter fully due to large AI LLM deals, and how much of this is included in the Q1 guidance?
A:Or Offer confirmed that the majority of the miss was due to two large AI LLM deals that slipped. One deal will likely close later in the year, while the other was split into smaller amounts, with some already included in Q1 guidance.
Q:What is the expected growth rate for the core business, and how do large deals impact this?
A:Or Offer explained that large deals take significant attention from the go-to-market team, impacting organic growth. A dedicated team has been created to focus on these opportunities, aiming for better forecast and execution.
Q:How productive were the sales investments in fiscal 2025, and what changes are planned for fiscal 2026?
A:Or Offer admitted that the sales investments in fiscal 2025 did not yield the expected results. The company optimized its go-to-market motion, reduced management layers, and removed low performers. No additional investments are planned for fiscal 2026.
Q:What caused the net revenue retention (NRR) compression, and how does the company plan to improve it?
A:Or Offer attributed the NRR compression to the lapping of large AI contracts and the inclusion of one-time deals that are not reflected in NRR. The company expects NRR to improve as more one-time deals mature into ARR.
Q:What are the components of the 11% revenue from AI solutions, and how many LLM deals closed this quarter?
A:Or Offer explained that the 11% AI revenue includes data for LLMs, Gen AI models, and AI chatbot partnerships. One or two smaller LLM deals closed this quarter, but they were not as significant as the expected ones.
Q:What changes have been made to the go-to-market organization to improve win rates and pipeline conversion?
A:Or Offer stated that the company shifted from an outbound enterprise approach to a more efficient inbound and expansion model. This change improved sales cycles and yields by the end of the year.
Q:How is the AI Studio monetized, and what is its strategic importance?
A:Maoz Lakovski explained that AI Studio is monetized through data access and consumption. It is strategically important for increasing user adoption and expanding TAM within the client base.
Q:What is the competitive landscape for GEO/AEO, and how is the company positioned?
A:Or Offer and Maoz Lakovski highlighted that Similarweb offers a holistic solution for managing all channels, including GEO/AEO, ad intelligence, and competitive research. The company is recognized as a leader in this space and is optimistic about its position.
Q:What caused the elongation of sales cycles, and how has the company addressed this?
A:Or Offer attributed the elongation to the addition of many salespeople and a shift to an outbound enterprise approach. The company has since reverted to an inbound and expansion model, improving efficiency and profitability.
Q:How does the company view the broader competitive and customer budget landscape?
A:Or Offer and Maoz Lakovski noted that while GEO/AEO is gaining attention, Similarweb's holistic approach to managing all channels positions it uniquely. The company is leveraging its data moat and client relationships to navigate market dynamics.
Q:Review of Unclear Management Responses
A:Management avoided providing specific details on the exact number of LLM deals closed this quarter and the precise breakdown of the $4 million miss in the quarter. Additionally, while they discussed the broader competitive landscape and customer budget dynamics, their responses lacked detailed numerical evidence or specific examples.
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Earnings Word Cloud

The most frequently occurring keywords in this quarter's earning call
AI Studio
AI agent
AI era
AI portfolio
AI solution
AI system
AI workflow
Enterprise
LLM
MCP integration
Slide
Studio AI
TAM
Today
action
adoption
advantage
app search
demand AI
distribution scale
driver
durability model
ecosystem
enterprise relationship
generation
journey
moat
monetization
pillar
platform
playbook
potential
progress
quality
research
set
step
traction
user insight

SMWB Transcript

Similarweb Ltd. (SMWB) Q1 2026 Earnings Call Transcript
Positive5-13

The earnings call shows positive financial performance with a 10% revenue increase, improved gross margin, reduced net loss, and positive free cash flow. Despite forward-looking risks, the overall financial health appears strong. The absence of strategic and operational updates limits the overall positivity, but the financial metrics suggest a positive stock movement.

Similarweb Ltd. (SMWB) Q4 2025 Earnings Call Transcript
Positive2-18

The earnings call summary and Q&A indicate positive financial performance, with raised guidance for operating profit and continued positive free cash flow. Product development is strong, with new launches and AI integration. The market strategy is focused on expansion and customer growth. Despite some revenue misses due to delayed deals, guidance remains optimistic. Shareholder returns are not explicitly mentioned, but overall financial health and strategic positioning suggest a positive outlook. The lack of market cap information limits precise prediction, but the sentiment leans towards a positive stock price movement.

Similarweb Ltd. (SMWB) Q3 2025 Earnings Call Transcript
Unknown11-12

The earnings call provided mixed signals. Financial performance and guidance are stable, with positive free cash flow and disciplined cost management. However, the lack of a revenue beat and raise, unclear management responses, and a wider than usual Q4 guidance range introduce uncertainty. The Q&A reveals some execution challenges and vague responses, but also highlights potential growth in LLM data deals. Overall, the sentiment is balanced, with neither strong positive nor negative factors dominating, leading to a neutral prediction for stock price movement.

Similarweb Ltd. (SMWB) Q2 2025 Earnings Call Transcript
Positive8-13

The earnings call summary and Q&A reveal strong revenue growth, increased customer base, and improved operating margins. The introduction of new products, especially in AI, and a significant increase in multiyear contracts enhance revenue durability. While there were some unclear management responses, the overall sentiment from analysts was positive, particularly due to the robust pipeline and profitability improvements. The full-year guidance and strong free cash flow further support a positive outlook, likely leading to a stock price increase in the short term.

SMWB Report

SIMILARWEB LTD. 6-K
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Frequently Asked Questions

Where does this earnings call transcript come from?

All transcripts are sourced directly from the official live webcast or the company’s official investor relations website. We use the exact words spoken during the call with no paraphrasing of the core discussion.

How soon is the transcript available after the earnings call ends?

Full verbatim transcripts are typically published within 4–12 hours after the call ends. Same-day availability is guaranteed for all S&P 500 and most mid-cap companies.

Is the transcript edited or altered in any way?

No material content is ever changed or summarized in the “Full Transcript” section. We only correct obvious spoken typos (e.g., “um”, “ah”, repeated 10 times”, or clear misspoken ticker symbols) and add speaker names/titles for readability. Every substantive sentence remains 100% as spoken.

Why do some answers appear as “Unclear” or “Inaudible”?

When audio quality is poor or multiple speakers talk over each other, we mark the section instead of guessing. This ensures complete accuracy rather than introducing potential errors.

Who creates the AI Summary and Key Q&A highlights shown above the transcript?

They are generated by a specialized financial-language model trained exclusively on 15+ years of earnings transcripts. The model extracts financial figures, guidance, and tone with 97%+ accuracy and is regularly validated against human analysts. The full raw transcript always remains available for verification.

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