Similarweb Ltd (SMWB) 2025 Q4 法說會逐字稿

Greetings. Welcome to Similarweb fourth-quarter fiscal 2025 earnings call. (Operator Instructions) Please note, this conference is being recorded.

I will now turn the conference over to Rami Myerson, Vice President, Investor Relations. Thank you. You may begin.

Thank you, operator. Welcome, everyone, to our fourth-quarter 2025 earnings conference call. Joining me today are our CEO and Co-Founder, Or Offer; our Chief Financial Officer, Ran Vered, who started with us in late December 2025; and Maoz Lakovski, our Chief Business Officer, who is joining us as well.

Yesterday, after market close, we released our results for the fourth-quarter and published a discussion of our results in a letter to shareholders on our Investor Relations website at ir.similarweb.com. Today's webcast will be accompanied by an earnings presentation, which is new and underscores our commitment to Investor Relations and transparent communication.

The webcast can also be accessed from our Investor Relations website. Certain statements made on the call today constitute forward-looking statements, which reflect management's best judgment based on the currently available information. These statements involve risks and uncertainties that may cause actual results to differ from our expectations.

Please refer to our earnings release and our most recent annual report filed on Form 20-F for more information on the risk factors that could cause actual results to differ from our forward-looking statements. Additionally, certain non-GAAP financial measures will be discussed on the call today. Reconciliations to the most directly comparable GAAP financial measures are available in the earnings release and the earnings presentation.

Today, Or and Ran will walk through the highlights of the quarter and the full year, review the progress we are making on our profitable growth strategy and provide our initial outlook for 2026. Following our prepared remarks, we will open up the call to questions from sell-side analysts.

With that, I'll turn the call over to Or. Or, please go ahead.

Thank you, Rami. Welcome, everyone, joining the call today, and a special welcome to Ran, who joined us as our new CFO in December 2025. I will begin with our Q4 and full year 2025 highlights, then cover our strategy and the progress we made in 2025, rolling out our innovative solution and conclude with our 2026 priorities and goals. Now let's look at our Q4 2025 performance on slide 5. Revenue grew 11% year-over-year to $72.8 million.

This was below our guidance, mostly due to the timing of two large LLM data training contracts that did not close yet, but remain active in our pipeline. Given the size and complexity of those AI contracts, sales cycles can take longer to complete. That said, once closed, we expect them to represent a very big multiyear revenue opportunities with strong expansion potential.

We are working hard to close those deals. In addition, and despite the delay of those deals, we slightly exceeded the midpoint of our non-GAAP operating profit targets for the quarter through disciplined cost management. Despite the low topline performance, we delivered our ninth consecutive quarter of positive free cash flow and achieved our second consecutive year of positive operating profit.

We generated approximately $13 million in free cash flow for the year, reinforcing our commitment to profitable and durable growth. Net revenue retention for all clients was 98% and 103% for clients above $100,000. We are focused on driving improvement in these metrics in 2026 by executing our customer expansion playbook.

Later on, I will expand on the drivers behind that optimism and the action we are taking. Finally, customer demand for our AI offering continued to expand. AI-related revenue reached 11% of sales in the fourth-quarter, up from 8% at the end of the second-quarter of 2025, driven by our portfolio of innovative AI solution, which we also will cover later in the presentation.

Turning to slide 6 and our key messages. First, 2025 was a build year. We built the platform to win in the AI era, while the market was dynamic, we leaned into the opportunity forming around AI. We accelerated product innovation and launched new offerings such as App Intelligence, which was the fastest-growing product we had in 2025.

We introduced Ad Intelligence, Gen AI Intelligence, AI Agent and MCP integrations, which is a new industry standard for AI systems to access our data. Most recently, we launched the AI Studio, which is an AI-powered chatbot interface that make it easier for more users to access our data and actionable insights and recommendations.

These are commercial products already gaining traction. As said, in Q4, 11% of our revenue came from AI-related use case. We see AI as a significant monetization tailwind going forward. Second, we demonstrated the strength and durability of our model. We grew AI revenue three times year-over-year and achieved our second consecutive year of positive operating profit and free cash flow.

One important highlight is that 60% of ARR is now multiyear, up from 49% a year ago. This is an important metric as it reflects deeper customer relationship, stronger alignment with our value proposition and greater revenue visibility. Most importantly, it shows that our customers are choosing to commit to our data and products for a longer period of time, which is a strong vote of confidence in the value we deliver.

In addition, 63% of ARR comes from customers generating over $100,000 annually, reinforcing how embedded we are in mission-critical use cases in the Enterprise segment. Third, our data moat matters more than ever. AI models and systems are only as strong as the data behind them. Our proprietary digital data now powers enterprises, LLM and AI agents.

The quality of our data has been validated by both third parties and customers. For example, we expanded our integration within the Bloomberg terminal. This positions Similarweb as a premium alternative data provider for institutional investors and provide another proof point of the quality of the data we provide. And finally, 2026 is transformation year.

We are moving from building to scaling, as AI become embedded into workflow and trusted digital data become a strategic asset. We believe Similarweb is well positioned to power the next generation of digital intelligence. Let me walk you through how we are executing our strategy to build an AI-driven data powerhouse on slide 7.

Our strategy is built on three pillars: strengthening our data moat, deepening enterprise relationships; and third, scaling AI-first integrated solution. So let's start with the first one, durable data moat. We are a leader in the digital market data. For more than a decade, we invest hundreds of millions of dollars in developing and building our data moat, building deep expertise in collecting and estimating digital behavior at global scale.

We continue to invest in R&D to enhance the quality, accuracy and the breadth of the data sets that power our digital intelligence. We continue to expand coverage, accuracy and freshness across web, app, search, ads and now chat-based channels, staying at the forefront wherever digital traffic is shifting. This is a hard-to-replace asset with compounding advantage and significant long-term commercial potential.

AI depends on it. It does not replacing it. Second, we are powering leading enterprise with our trusted digital data. Many of the world's largest and most sophisticated companies are already our customers. We see significant opportunity to scale those relationships by applying our proven expansion playbooks, increasing multiproduct adoption over time and driving higher NRR.

We already have two large tech customers generating over $10 million in ARR. Those are broad multi-use case relationship across multiple teams and functions. Both have expanded into a data agreement that power their LLMs, positioning Similarweb as a critical building block within their AI stack. Enterprise expansion will be a key focus area for us in 2026 and beyond.

Third, we are doubling down on AI-first integrated solution. And we will continue to expand our AI portfolio to establish ourselves as a winner in the AI transformation. Our data sets are uniquely positioned to power both enterprise users and AI systems, a dual strategy built for people and for agents. Through ecosystem partnerships like Manus, our data is embedded directly into AI-native workflows, especially for research-driven use case.

Just as financial data become essential for research platforms, chatbots, we believe that digital market data can play a similar role across all platforms. We expect it become a meaningful commercial growth driver. As we execute on our three pillars, we remain fully committed to operational excellence to drive durable, profitable and cash-generative growth.

As you can see on slide 8, we made significant steps forward on our strategy in 2025, as we build Similarweb for the next stage in our journey. Starting with the data moat. In 2025, we launched multiple new data sets to further extend our 360-degree visibility across the digital world and establish our leadership in digital data.

We significantly expanded our coverage across ad data, ad spend data, chatbot activity data and Gen AI visibility. These data sets are very unique, and we believe we are uniquely positioned to provide a comprehensive view across web, app, search, e-commerce, advertising and emerging AI-driven channels and covering the full digital journey across touch points. Moving to the enterprise pillar.

We delivered a solid performance in 2025. Our $100,000 customers grew 12% year-over-year and now represent 63% of ARR. Revenue from multiyear contracts increased significantly to 60% of ARR from 49% in 2024. Lastly, on our AI-first solution, we launched our innovative offering, AI Studio, AI agent embedded across our business solution to accelerate time to insight, Gen AI Intelligence model, which help brands measure their visibility and sentiment across generative AI platforms and a new chatbot MCP integration, including partnerships like Manus, which opened an exciting new distribution and monetization channel.

Our partnership with Manus extends our data sets into agent-driven workflow, where autonomous AI agents capable of performing complex text activities, execute marketing analysis, competitive assessment and strategic planning. Manus, which was recently acquired by Meta, is one of the fastest scaling start-up in history, and this collaboration offer us revenue opportunities to scale with it.

Furthermore, Manus provides access to a much broader set of potential end users beyond our core subscriber base, expanding our TAM by empowering millions of users with our data. This milestone partnership reinforced our value proposition as essential data layer for the next generation of agentic tools and serves as a strategic blueprint for more integration to come.

Those are some of the steps we took to strengthen our data moat, deepen enterprise relationship and position Similarweb to win in the AI era. slide 9 captures our AI data and product strategy, how we power the ecosystem, build AI-first solution and expand distribution at scale. First, we are powering LLM and AI agents. We are seeing strong traction, licensing our data directly to leading LLM companies for both pre- and post-training use case.

This is a strategic priority for us, and we expect it to become increasingly strong revenue stream for us over time. At the same time, autonomous agents require trusted structured digital intelligence to operate efficiently, that's exactly what we provide. Our data is built for both human and agent, and we see accelerating demand from both.

Second, we are building our own AI native solution. With Gen AI Intelligence, we are helping brands to improve their Gen AI visibility and sentiment. We are seeing strong market validation on this front, including the recognition of our leadership by G2 Crowd, and we have recently launched it in a self-serve with adoption from hundreds of customers.

We believe our data provides an important competitive advantage in this new market, and we are on a journey to become a market leader in this category as well. We are also transforming our traditional software into an agent-first model, launching workflow-specific AI agents across marketing and sales use case. This moved customers from insights to action with a faster time to value and stronger ROI.

This effort is helping us to get to many more users, grow adoption and TAM. We are very excited about the potential of our own agentic strategy. Third, we are expanding distribution at scale. Through partnership with leading LLM and agent platform such as Manus and through MCP integration, we're embedding Similarweb directly into AI ecosystems. Our MCP is already available in Cloud and will soon be integrated into ChatGPT.

Enabling AI systems to seamlessly access our data, so users can consume Similarweb insights directly within their workflows. Those ecosystems partnership unlock new customers, expand our TAM and position our digital data as a critical ingredient for AI-driven research and decision-making. We believe we are well positioned to be an AI winner with multiple commercial opportunities across data, products and partnership, and we are excited about the potential.

I would like to spend a moment on the AI Studio on slide 10, because this is more than just a new product launch. AI Studio represents a huge shift in how users interact with Similarweb data. Historically, our platform delivered a powerful data-driven insight, but often required technical expertise to extract value. AI Studio changed that.

With an AI-powered interface, user can ask a business question in a plain language and in all languages and instantly receive actionable insight, what used to take time, and specialized skills can now happen quickly and easily. This is a major step in democratizing access to our data across teams and workflows. AI Studio expands the number of users who can leverage Similarweb, increases engagement, enable faster and more seamless insight generation and unlock new monetization opportunities.

The early feedback, both from better customers and since launch has been amazing. We see AI Studio as a core part of our product strategy and an important driver of future growth. I encourage you to watch the demo video after the call via the link on the slide to see it in action. Let me close by reflecting back on 2025 and how we set up for 2026 on slide 11. 2026 was a pivotal year. We made real progress.

As I said, AI revenue grew three and now represent 11% of Q4 revenue. That is a meaningful traction and clear validation that AI is already contributing to the business. We also strengthened our durability of the model. $100,000 customer grew 12% and 60% of ARR is now multiyear, up from 49% a year ago. They give us better visibility and reinforce the depth of our enterprise relationship.

At the same time, we acknowledge that 2025 was not within challenge. Overall NRR stabilized at 98%, and we are not satisfied with that level. While NRR for our $100,000 customers was at 103%, we know we can execute better across the broader base. We have taken action we are sharpening our go-to-market strategy, upgrading talent, refining processes and building scalable playbook to drive cross-sell and expansion.

We see a clear opportunity to convert onetime AI evaluation deals into recurring revenues and to accelerate the adoption of our newer solution across the installed base. That's why we have a strong conviction in 2026. We are well positioned to capture long-term AI spend. Our AI-first portfolio is scaling, ecosystem partners team are expanding, and we are targeting high-growth segments like LLM companies, large big tech players and the OEM with our own dedicated go-to-market team and focus.

With Ran joining as a CFO, we will also strengthen our financial discipline and public market execution. So 2025 set the stage. 2026 is about disciplined execution and acceleration.

With that, I will hand it over to Ran.

Thanks, Or. It's a pleasure to be here with you. I'll provide highlights of our financial performance and guidance for the first-quarter and the full year of 2026. But before I do, let me first provide a short overview of my background, why I joined Similarweb and what are my priorities as our CFO. I'm on slide 13. I'm very excited to join Similarweb at this juncture in our journey.

Or and the team have built a digital data powerhouse. And as we have discussed today, this unique asset is poised to take advantage of emerging opportunities in the AI generative era. Similarweb is my first role as a tech company CFO over 2 decades. Previously, I was CFO of two US listed tech companies, and I most recently joined from Lusha, a B2B sales intelligence unicorn.

I look forward to leveraging my experience and financial discipline to help execute our clear strategy to accelerate revenue growth to the next level, while doubling down on our commitment to expand profitability and deliver durable free cash flow. This is what I am committed to doing all while ensuring we remain disciplined capital allocators.

I look forward to meeting you over the coming weeks and months. Turning to slide 14 and our quarterly results. We generated $72.8 million of revenue, an 11% increase relative to the fourth-quarter of 2024. Revenue were lower than expected due to delayed closing of two major LLM-related agreements that were anticipated in the fourth-quarter.

As (technical difficulty) noted, we remain in active discussions. Non-GAAP operating profit for the quarter was $3.4 million, reflecting a 5% margin compared to $2.6 million and a 4% margin in 2024. This was within our guidance range, thanks to disciplined cost control. Turning to the full year financials on slide 15. I will not review each metric, but we highlight that despite lower revenue, operating profit came in ahead of our expectations at the beginning of the year due to our sustained focus on disciplined execution. 2025 was our second consecutive year of positive non-GAAP operating profit and free cash flow.

We are committed to generating profitable growth going forward. Good cash generation and strong balance sheet are critical for a business in any stage of the cycle and become even more important in periods of volatility. On slide 16, you can see that we ended the year with $72 million of cash and cash equivalents and no debt. We also have an available line of credit of $75 million.

After nine consecutive quarters of positive free cash flow, the business has a solid core and the financial flexibility to weather market headwinds, while staying focused on our long-term goals to maximize shareholder value. Our capital allocation priorities over the coming years will be: first, to continue to invest in R&D at around 20% of revenues to improve our digital data and deepen our competitive moat.

Second is to invest in M&A only when it meets our rigorous financial returns criteria and advances our strategic goals to improve our data asset and product portfolio. Over the last two-years, we completed several bolt-on acquisitions, including 42matters, which boosted our app intelligence capabilities and Admetricks, which enhanced ad intelligence. The current market volatility is enriching the M&A pipeline.

We remain committed to a strong balance sheet that provides us with financial and operational flexibility. Turning to our outlook for 2026 on slide 17. For the full year 2026, we expect total revenue in the range of $305 million to $315 million, representing 10% year-over-year growth at the midpoint of the range. In Q1 2026, we expect total revenue in the range of $72 million to $74 million, representing 9% year-over-year growth at the midpoint.

For the full year, we expect our non-GAAP operating profit to be between $16 million and $90 million. Non-GAAP operating profit for the first-quarter of 2026 is expected to be in the range of $0.5 million to $2.5 million. As I provide guidance for the first time at Similarweb, we are taking a deliberately prudent approach. We are assuming pockets of end market weakness persists, and we are grounding the initial outlook in the high visibility of our core business drivers, while we are encouraged by the strong demand in the pipeline for larger AI deals.

After delivering the second year of solid revenue growth, non-GAAP operating profit and positive free cash flow, we remain committed to building a more durable franchise in Similarweb. With that, Or and I are ready to answer your questions. Following Q&A, Or will share some closing remarks.

Operator, please open the line for questions.

(Operator Instructions) Raimo Lenschow, Barclays.

I had like two questions. And Ran, welcome to the team and all the best. One for Or. If you think about the large LLM contracts that you're signing there, but then you also look at the large customer NRR actually just came down a little bit. Is there -- do we need to think about that as an addition or somewhat as a replacement that people that -- people using more LLMs going forward, that means they need to use less of their own and that kind of impacts the NRR numbers then?

Or are they not correlated? Could you speak to that dynamic going on there? And then I had one follow-up for Ran.

Yes. I think that there's no correlation between the core business when we sell our regular software when brands buying the Web Intelligence, App Intelligence to drive growth traffic online versus our motion of selling data for LLM use case. That is -- it's a different use case, especially to train LLM to be smarter, better about the world. So it's a different -- I don't think it's come on each other.

Yes. Okay. Perfect. Okay. Makes sense. And then the one for you, like the -- obviously, with these larger contracts coming through, it kind of as a CFO and as a new CFO, it's kind of difficult to guide. How do you think about your guidance philosophy in terms of going forward, kind of if those big deals in the pipeline, is it worth maybe taking them out and they become like upside when they come through? Like how do you think about that dynamic?

Thanks for the question. First of all, I'm really happy to be on this call. So when we look on the guidance, we took a reasonable approach. And this is one of the reasons we widened the range. In prior years, the range we guide to the Street was around $3 million. And now because of that LLM deals and the big deals, we widened the range to $10 million just because we know -- we see these deals in the pipeline, but the timing of them to land is not that clear.

As we say in the prepared remarks, this is one of the main reasons we lost Q4. So when I look on it, some of it with percentage is baked already into the guidelines. But when we're going to land them, of course, this will -- we'll see how we adjust the guidance going forward.

Arjun Bhatia, William Blair.

Yes. Perfect. Or can we maybe just go back to the first question. I understand the 2 demand kind of drivers between LLMs and the core business are not correlated. But I think if I exclude your AI revenue, it seems like the core business is slowing quite a bit. And so I'm curious if you could just help us understand what's happening there, excluding your AI revenue?

Is the core NRR obviously is down. What are the challenges there going forward? And how do you sort of remediate that to get that core business back to stronger growth?

Yes. Thank you, Arjun, for the question. First of all, I think this quarter numbers, you can see that the core business is not falling. It's still growing. You can see because you basically saw an example of a quarter when the big data deals didn't claim, they slipped for another quarter, and you still see a growth in the revenue.

So we do see growth in the core business even without the data for LLM. But the data for LLMs are very big deals and they are significant. We think that in the regular business, we're selling a deal between $20,000, $30,000 at land and then expansion can be $50,000 to $60,000. Those data for LLM is significant. It's 7-figure deal sometimes and then they behave very, very different.

And how to predict and forecast, as you can understand. And so I think I hope this give you some visibility. I know maybe Maoz, our Chief Strategy Officer, maybe you have anything on that topic as well on your mind.

Yes, happy to help, and thanks for the question. We're seeing GRR and renewal rates in a very good traction. So when we have 60% of the book of business, which the majority of it is still non-AI under multiyear. So we're seeing a good durability of our core book of business. We need to work on the expansion path in order to increase NRR.

We are now in the -- we are very optimistic about NRR going forward. We think that some of the LLM onetime deals push have affected the NRR. But going forward, we are working hard to improve it, mostly focusing on the expansion. We have great product portfolio from App Intelligence, which is a very fast-growing product for us.

Ad Intelligence, the GEO, Gen AI Intelligence that we are launching, and we're seeing good success with our clients. So overall, the core business of us is still growing, and we are very bullish. Renewal rates are solid. Multiyear is there, great client feedback, and we are laser-focused on expanding it and increasing the NRR.

Okay. Understood. And then one for Ran. Can you -- just going back to the guidance range, I appreciate, and I think it's helpful that at least it's a wider range given some of the uncertainty around the customers and how lumpy they can be. But can you just touch on what you're expecting? What would have to materialize to hit the high end of the range versus the low end? Like what are the different scenarios that are contemplated in that wider guidance range?

Arjun, thanks for the question. So I think we need to land the big LLM deals. So probably this is what can drive the difference between the low end and the high end of the range. And because those deals are really big, seven figures, as Or also mentioned, and we see them in the pipeline, and we see also the engagement with the customers. I was -- actually when I joined and I was -- I'm here talking with the people; I see the pipeline.

I'm really encouraged by the pipeline and by the fact that we're delivering these deals to the larger LLM. But again, I think it's mainly in terms of timing, when they will end and what will be eventually the size of them. I think this is why the range is in the $10 million range.

Ken Wong, Oppenheimer & Company.

I just wanted to check as far as the miss in the quarter, was that $4 million fully from the large AI LLM deals? And then how much of that is baked into the 1Q guide?

Yes. So first of all, thank you for the question. So yes, the majority of the miss is because of those two deals that were very, very big and been in the pipeline for a long time. And we thought and we hope to get them to the finish line. And looking now in the Q1 guidance, we're taking more cautious steps. As I said, it's very hard to forecast them.

One deal will probably become later in the year. And the other one was split into more small amounts and one of them already came. So we have confidence that some of that will come at Q1. I think I hope this will answer the question.

Got it. And so then when I think about the growth rate, assuming some of it is in Q1 that kind of perhaps puts your core business or your organic growth at high single digits. Is that the right way to think about it until you guys get the go-to-market motions and the product sorted out for '26?

These big deals are taking a lot from our go-to-market as well, seeing that even when you have sales force salespeople and some of them know that there is those opportunity of very big deals, a lot of efforts are going into those directions. So it's part of the organic growth and taking attention from other stuff, but they are a big opportunity.

What we did this year in order to be more disciplined around it, we built a dedicated team to go and be focused only on those opportunities to have a better forecast and execution and also try to leverage even more upside as we have only single-digit customer right now in this LLM motion, but there's probably much more customers we can approach and onboard. So I hope this dedicated team will give us a better forecast and execution on that.

Okay. Fantastic.

[Scott Berg], Needham & Company.

Lucas (technical difficulty) on for Scott Berg. First, you guys made some strong sales investments heading into fiscal 2025. We understand some sales cycles have elongated. But in general, I guess, could you guys just talk about the productivity kind of throughout the year of the new investments? And then what type of additional sales investments does your fiscal 2026 guidance imply?

Yes. First of all, thank you for the question, and I think it's a good question. So we were not very happy with the performance and the investments we did, we were hoping to get better yield from the investments that we did at the beginning of the year to try to accelerate growth. And we did see the yield of the sales getting better every quarter. But the good news is that we will not need to do any investment going into this year.

We took some steps to optimize the go-to-market motion once we saw that we're not getting the outcome we were looking for and reduce layers of management and remove some low performance and starting the year with a fully ramped team and with no more investment needed in order to drive the results we're looking into this year.

Got it. That's helpful. And then just one other question here, kind of surrounding the net revenue retention compression. Would you say is that primarily driven by lapping the larger AI contracts from late 2024? Or just any other kind of underlying changes in gross retention or expansion trends that we should be thinking about?

Yes, I think it's an excellent question. And the answer is yes, you're right, because some of those big deals left and this year, it's impacting, of course, the NRR. But also if you think about last year and all this new data for LLM that is including sometimes onetime deal, they are not being reflected in the NRR because those are onetime and NRR is only carrying revenue.

And this is why it looks like the NRR of the big accounts are dropping. But in reality, we had much more revenue because of the onetime last year. So we expect the NRR metrics to get better going forward. And also as more of those onetime trials of data for LLMs are maturing into ARR, of course, contribute and get better results over time.

Patrick Walravens, Citizens Bank.

Great. This is Kincaid on for Patrick. Or I just wanted to know if you could give us a little breakdown of that 11% of revenue coming from AI solutions. What are the components that drive that as well as I understand that 2 of these LLM deals slipped from this quarter. Can you give us any info on how many did close this quarter?

Yes. So the data for LLMs and deals, there was, I think, one, I need to look or two last quarter that was not as big as the one we expected that did close, but much more smaller with new players. But overall, the AI revenue is a bucket that includes few offering, not only the data for LLMs, you have the Gen AI model that we sell to brands that's including there.

We have AI chatbot partnership like the one in Manus that it's the revenue of setting up the partnership and then there is like a usage-based component on top of that. So there's a few channels inside this 11%, not only the data for LLMs. It's a few streams that are kind of new for us that are starting in the past couple of years because of the AI revolution, and we see those offering as a tailwind going into this year.

Luke Horton, Northland Securities.

Just wanted to touch on some of the -- what you guys call commercial execution shortfalls. I guess, could you be a little bit more specific of this -- was this around the hiring ramp or pricing in the sales cycle? Or I guess, what kind of changes have you made to the go-to-market organization to improve these win rates and pipeline conversion in 2026?

So in 2025, we increased our sellers all across the board trying to accelerate the revenue growth. And there was a lot of noise adding a lot of people in a short time. It took a lot of long time to ramp them up. And we didn't see the yield we were hoping also on the enterprise side and the talent and the expansion. So we had to optimize it and tweak it over the year.

And I think, as I said before, we -- going into this year, we have the right talent in place. I don't know, maybe, Maoz, anything that you have to say around that as well?

I think the key for us is doubling down on growth opportunities. Or mentioned the team and the go-to-market investments we are making around AI, LLMs, OEM, where we see a lot of growth potential. So we're doubling down there. We are refining our go-to-market strategies. We are seeing increasing yields overall, but we're also aware of the market dynamics and the uncertainty in the market.

So we think we are well set for 2026. We're confident in our ability to hit our guidance throughout the year. We're seeing strong pipeline. We are optimistic about the pipeline, some large meaningful deals. We have the onetime we need to convert into recurring deals, and we are on it. So overall, we think we are in a good position.

Got it. And then lastly, I just want to go back to the AI Studio as this is a pretty significant product for you guys. But I guess, could you give some clarity around the monetization of this, if this is sort of seat-based or consumption-based or like premium tier pricing? Just any sort of information around that would be great.

Maoz, you're in charge of pricing, you can take it.

Yes. We're actually super excited about the AI Studio. Reason being is that we see this product as a mean to get to many more users within the organization. It can help us cross the chasm and make the data and insights much more available. So we are super bullish about this, and we're seeing great demand and initial traction.

In terms of monetization, so at this point, we are baking some of it within the enterprise plans. But the model is twofold. It's data access and then data consumption, which means that essentially you need to have access to the specific data you want to have queries on. It could be a country, it could be a data set, but we align it to the customer needs. The second is the consumption.

So we give some level of consumption within the package and then the clients could grow. We see it as a very strategic role for us, again, because we see us getting to many more users. With that, in terms of our AI strategy, worth mentioning also the Manus partnership, which we are extremely, extremely optimistic about. We see this as a huge opportunity for us to get to nontypical users of Similarweb and monetize it.

We're seeing a potential huge distribution and to unlock a lot of TAM for us. So between the AI Studio, which is a mean to grow TAM within our client base to the Manus example with unlocking distribution for noncore users, we are very happy that we are able to monetize and they can get to many more users. I hope it helps you understand.

I will add on top of that, that some of our big enterprise customers, they have unlimited users' package. So we've never been about seat-based approach. We've been about most data access and not for consumption. And we hope that, for example, this AI Studio in those enterprises that really have a big amount of users, we can increase adoption because as we said, you can talk to the AI Studio in any language.

So you move the language barrier, you don't need to be experts on our platform and where every one of the data set is signed. And so everybody can easily go ask the business (technical difficulty) business questions and get immediately the data you need and then the based on consumption. So it's very similar to concept based for business outcome. So you have a question and you get answer and you pay for that. So we hope this will drive a good adoption and success into this year.

Awesome. That was super helpful.

(Operator Instructions) Adam Hotchkiss, Goldman Sachs.

Ran, nice to meet you in this forum. I wanted to just dig in on the sales cycle comments, or what is it specifically about the sales cycles that have maybe been then elongated to the extent you can share? I guess I'm just trying to understand what I think needs to be done from your side to get those over the finish line.

Yes. I think that the lesson learned that we try to add many salespeople in onetime. So it was taking the instruction of the managers and then sort of increasing the sales cycle. We're trying to build an outbound motion for enterprise that was a very long sales cycle, much longer than what we used to. We are very inbound-based business.

Every year, we're getting more than 100 million people visiting our website and hundreds of thousands of people who register to try our solution every month. But it's a big volume. This is usually is what's feeding the salespeople. And they used to a specific sales cycle. And once we try to do more outbound or enterprise, it was tougher and does not fit with the -- what the model that we used to.

So -- and during the year, we shift everything more to land and expand and decided to back off of this outbound enterprise approach because most of the enterprise has already been familiar or using us or used in the past. And this is much more efficient and much more profitable for us to land through the inbound and then the expansion -- the enterprise expansion play on the current book of business.

So all of those together is kind of a little bit changed the sales cycle during last year, all those testing that we were trying to do acceleration. So it's a little bit hurt the sales cycle and hurting the sales yield in a few quarters. But as we change and adapt it, it's got better and better by the end of the year.

Okay. Great. And then I just want to touch on the, I guess, the broader competitive landscape and customer budget landscape. I think there's a lot been made of the GEO/AIO market, and it feels like there's a lot of funding going into that space. It feels like incumbents are spending there. Is that where you're seeing most of customer attention and budgets go given what's happening on the LLM side? And I guess, number one, is that true? And number two, how do you feel you're positioned in that space?

Yes. I think it's a great question, and let me help and maybe also Maoz have some thoughts as driving strategy. But the GEO, AEO, still there's no straight name for this market is a new market. And of course, it's a red ocean. There's a lot of small players there. I'm happy to say that we launched a really amazing offering in that space that is doing well.

We've already been recognized by G2, one of the companies like Forrester for software that met the market as a leader, especially for the enterprise. And it's a new motion. Some of the budgets go -- a lot of attention go there for sure. I don't know if this market is big. I think it's still small and developing. I think what's more interesting is that basically, a lot of attention go there because a lot of brands are losing traffic now because search is declining.

So everybody is trying to understand what's going on, if it's going on to ChatGPT, if I need to invest there. But in reality, there's much bigger movement happening. Search is declining. So brands trying to close this gap by investing more on paid channels, then paid goes up. And then they need to bring some of the traffic that went to the ChatGPT.

And I think that in this environment, you need a much more holistic solution to help you manage all channels, okay? Because one channel is going down, the AI chatbot that is a new channel going up, and then you have the ad spend that is going out of control. And you need to control all of them as the CMO or the head of digital running businesses trying to win back your traffic.

And I think Similarweb is the only solution right now that can give you full visibility and optimization and insights across all channels. And I think with that, our Gen AI offering is great. It's really good. But I would say that you do more than only Gen AI solution. You need the ad intelligence solution, you need the AEO solution and you need the benchmarking and competitive research solution.

I think all of them together, this is what Similarweb is offering. And I don't know, Maoz, maybe you have any interesting stuff to say here.

Yes. I'm fully aligned, and that's what we're hearing from the market. And I think the critical part here is we have the right to win. We are helping leaders to navigate between web and Gen AI. Every CMO, it's even a CEO discussion, (technical difficulty), e-commerce, whatever business model, everyone has this question, what should they be doing?

How should they be balancing between the traditional kind of web and the new Gen AI. So this is where we come in. So this is one thing that we are unique from any other player in this market, and we think we're going to win. Second, we are a data company. We have a meaningful data moat. Also when it comes to Gen AI visibility, and we are monetizing this.

We are selling it directly through our dedicated product, and it's picking up super nicely. And second, we are also feeding the ecosystem. We also have an OEM play here, and we are bullish about this as well, and it's working very nicely for us. Last, we have the clients. So we have the CMOs. We have the head of digital marketing. They speak with us. It seems like GEO, AEO is more than the traditional SEO. It gets more interest because users are spending much more of their time within these engines.

And they are coming to us. And honestly, there's a lot of market education and thought leadership. We are playing in this game, and we are very optimistic on our ability to become a very meaningful player. And the G2 recent recognition is just kind of another one that shows that we are in the right direction.

This does conclude our question-and-answer session. I would like to turn the conference back over to Or for closing remarks.

Before we conclude, I would like to highlight four key takeaways on slide 19. First, 2025 was a build year. We deepened our data moat and positioned the company for the AI area. Second, we delivered solid growth. AI revenue grew three times year-over-year, multiyear ARR increased, and we extend our track record of profitability and free cash flow.

Third, our leadership in digital data become even more valuable as AI adoption accelerates. And fourth, 2026 is about disciplined execution and scaling what we build, and we have strong belief in the opportunity ahead. AI is a meaningful tailwind for data companies like us. And as I like to say, we are just getting started. Thank you, everyone, on the call for your continued support. We look forward to speaking to you again over the coming weeks.

Thank you. This does conclude our conference. You may disconnect at this time, and thank you for your participation.