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Wednesday, April 29, 2026 at 8:30 a.m. ET
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Micha Kaufman: Thank you, Emily. Good morning, everyone, and thank you for joining us. Let me start with the headline. Q1 was a solid quarter of execution with both revenue and adjusted EBITDA coming in at the high end of our guidance range. Esti will walk through the details shortly, but the underlying message is this, we are focused on executing the strategic transformation while being methodical in managing the existing business across both top and bottom lines. Maintaining financial discipline and transparency throughout this transformation is critical, and we are committed to doing that consistently and credibly.
Let me now turn to the transformation or as we mentioned last quarter, we are in the early stages of a multiyear journey to reposition Fiverr from a transaction-oriented marketplace into a trusted work platform for complex high-value outcomes. This is not a cosmetic shift. It is a fundamental evolution of how work is matched, delivered and orchestrated on our platform. Our North Star is clear: to become the most trusted platform for completing high-value, high-trust work. This means enabling businesses and talent and increasingly AI-driven workflows to collaborate effectively on complex outcomes. Two months into the transformation, the early signals across all pillars of this transformation are consistent with our plan.
First, we are strengthening the high-end talent flywheel and expanding into more complex, higher-value projects. Projects over $1,000 continue to grow at a strong double-digit rate with clients completing $1,000-plus projects, up 18% year-over-year. We are also seeing increasing participation from talent delivering these engagements. What's important here is not just the growth. It's the nature of the work. We are seeing businesses come to Fiverr not for isolated tasks, but for multiphase mission-critical projects. For example, one, a global health care company is working with talent on Fiverr to produce over 30 multilingual animated assets for a product launch with ongoing spend across multiple engagements.
Two, a C2C sports platform in New Zealand built a full mobile application through multiple development phases on Fiverr. Three, a European entrepreneur is building an AI-enabled invoicing SaaS platform to comply with regional regulatory standards. These are not one-off gigs. They are sustained high-value engagements that require coordination, iteration and trust. This is exactly the segment we are targeting and exactly where the market is moving towards more strategic outcome-based engagements. Second, we are investing heavily in matching infrastructure and experience. This is our main differentiator and the key to driving trust and quality, which are the core primitives of the market. Our research and internal data confirm this. The primary differentiator in hiring platforms is not price.
It is talent, quality and trust. Historically, Fiverr has won on ease of use and speed. Winning upmarket means extending that advantage into quality and trust, and that is exactly what our infrastructure investments are designed to deliver. That is why we are rebuilding our matching infrastructure from the ground up. We are moving from keyword-based matching to context-aware, outcome-driven matching powered by a knowledge graph that captures not just who the talent is, but what they have delivered in what context and with what results. At the same time, we are shifting ranking from optimizing for conversion to optimizing for expected project success and buyer satisfaction. The data is already moving.
Recent tests in Fiverr Pro show mismatch rates down nearly 10%, and we are consistently seeing higher value engagements, leading to stronger repeat behavior. These are the early proof points of a durable trust mode. Third, we are evolving Fiverr into a comprehensive work platform. Today, most high-value projects on Fiverr run on infrastructure built for a different era of the platform. We are addressing this by building an end-to-end fulfillment layer that includes visibility into project progress, early detection of risk, structured feedback loops and active orchestration by Fiverr. This is a fundamental shift in responsibility and perception of responsibility. We are becoming an active partner for our clients and talent, not just a passive connector.
Over time, this infrastructure will also allow Fiverr to integrate seamlessly into agentic workflows, where AI handles coordination and humans provide judgment and accountability. Fourth, we are expanding our go-to-market capabilities to scale more aggressively into high-value work. We are now building 3 new growth engines. First, talent-led growth engine, driving high-quality demand directly to high-performing freelancers. Second, industry-led growth engine, building tailored experiences for specific industries such as e-commerce and early-stage start-up companies. And third, partner-led distribution, embedding Fiverr directly into workflows and platforms where high-value demand already exists. These initiatives expand beyond traditional performance marketing and are designed to create scalable, durable growth engines aligned with our upmarket strategy. Finally, we are improving execution across the organization.
We are optimizing production workflows through better telemetry, identifying bottlenecks and increasing discipline in delivery. At the same time, we are rebuilding how work is executed with AI agents at the center and human judgment where it matters most. This approach enables faster decision-making, reduces handoffs, improves product quality and drives efficiency across the organization. Mastering this as a company will also allow us to generate a reusable blueprint for our customers and talent to replicate and enjoy. Stepping back, the fundamental dynamics of this market are moving in our direction. AI is increasing, not reducing, the complexity of matching the right talent to the right work. The demand for trusted outcome-based platforms is not a future possibility.
It is already showing up in our data, in our customer examples and in the infrastructure we are building. Fiverr has a differentiated model, a compounding data advantage built on real transaction outcomes and an end-to-end platform that no point solution can easily replicate. We are executing with urgency and discipline, and we are confident in where this leads. With that, I'll turn it over to Esti for the financial details.
Esti Dadon: Thank you, Micha, and good morning, everyone. We delivered a strong first quarter with both top and bottom lines exceeding the midpoint of our guidance. Revenue was $105.5 million, down 1.6% year-over-year, reflecting continued growth in high-value work, offset by headwinds in low-value transactional activity on the marketplace alongside a continued growth of service revenue. Adjusted EBITDA was $22.6 million, up 16.3% year-over-year and representing an adjusted EBITDA margin of 21%. This is an improvement of 330 basis points from a year earlier as we continue to execute with strong financial discipline. Turning to our revenue segments. Q1 marketplace revenue was $67.1 million, driven by 2.9 million active buyers, $356 in spend per buyer and a 27.7% marketplace take rate.
The continued momentum in our upmarket strategy and shift towards more complex engagement is clearly showing in our cohort behavior with spend per buyer growth of 15% year-over-year. Projects over $1,000 grew at a strong double-digit rate, driven by 18% growth in clients completing these engagements. This growth is coming from both new adoption and repeat behavior as buyer expand into larger use cases, along with increased usage of dynamic matching and managed services. Looking ahead, macro conditions remain largely unchanged. Based on current trends, we expect marketplace growth for the remainder of the year and on a full year basis to track broadly in line with Q1 performance.
Service revenue in Q1 was $38.4 million, up 30% year-over-year and accounted for 36% of total revenue. Services revenue came in slightly higher than expected as AutoDS ran a successful campaign at the start of the year, pulling certain user sign-ups and revenue forward from Q2 to Q1. Overall, our expectation for services revenue for this year remain largely unchanged with growth moderation in Q2 and continuing into the second half of the year. As Micha mentioned, 2026 is a transformational year for us as we make critical foundational investments to strengthen our high-end talent flywheel. Our decisions are centered on improving marketplace quality and trust, prioritizing high-value work and driving more focused execution with strong financial discipline.
On capital allocation, we continue to take a disciplined and balanced approach. Our strong balance sheet allows us to invest in growth, returning capital to shareholders and remain opportunistic on M&A. We generated $21 million in free cash flow in Q1, and we expect to continue executing our buyback program in a thoughtful manner. As of March 31, 2026, we had $59.5 million remaining under the current authorization. Now on to guidance. For the full year 2026, we expect revenue to be in the range of $380 million to $420 million, representing a year-over-year growth of negative 12% to negative 3%.
We are raising our full year adjusted EBITDA guidance and now expect it to be in the range of $64 million to $80 million, representing an adjusted EBITDA margin of 18% at the midpoint. For the second quarter of 2026, revenue is expected to be between $95 million to $103 million, representing year-over-year growth of negative 13% to negative 5%. Adjusted EBITDA is expected to be between $16 million to $20 million, representing an adjusted EBITDA margin of 18% at the midpoint. Our revenue outlook reflects solid execution in Q1 and the continued uncertainty in the market conditions.
Our adjusted EBITDA guidance reflects the strength of our core marketplace profitability and our continued commitment in maintaining disciplined margin profile while investing in the transformation. As we look at the rest of the year, we are staying focused on our core priorities, driving progress in higher-value work, improving trust and quality and building scalable growth engine. We believe these are the right indicators to evaluate the business as we transition to the next phase. With that, we will now turn the call over to the operator for questions.
Operator: [Operator Instructions] We have the first question from the line of Eric Sheridan from Goldman Sachs.
Eric Sheridan: Maybe 2, if I could. One, just coming back to the transformation strategy. I want to know a little bit more about the duration of sort of completion of what you call sort of the infrastructure layer and putting the pieces in place, and how we should be thinking about when you exit that phase of the transformation and some of the execution shifts more predominantly to go-to-market or what the mix is of building blocks relative to execution on the transformation strategy, that would be one. And then the second one would just be, you talked a little bit about partners and evolving the go-to-market strategy.
I want to know if you could go a little bit deeper in terms of what those types of partners might look like and what market opportunity they might open up that maybe you're under-indexed to today?
Micha Kaufman: Essentially, the transformation is an ongoing process, and since we just started it mid last quarter, we are anticipating to see results over the remainder of the year with more emphasis, because it takes time between the things that we develop and release until they show up in the numbers, to see this more in the second half of the year and definitely towards the end of the year. And as we said, we will continue to be transparent on what we're seeing and the progress there.
As the transformation, my belief is that the entire market is in a transformational moment where every business needs to adapt to a new reality where AI plays a critical game, not in just making products better and more efficient, but also being able to connect with agentic realities where agents are actually using the platform. This is not limited to this year, I think that this is going to be a transformation that every business out there will have to implement in the coming years. It's very similar in my mind to the digital transformation when businesses went from the offline to the online and now are seeing a new reality.
Now we are already seeing some initial signals that we called out in the opening remarks of areas where that transformation has started, and we started rolling out experiments and new products and how they influence a higher quality matching and focuses on better conversion and better retention around high-end talent and larger scopes. So over the next few quarters, we will continue to report on what we're seeing. The progress, and obviously, the more history we have in doing this, the results should accumulate. And as we said, this is going to be a turnaround year where the next years are going to be years of growth. In terms of the other question regarding partners and go-to-market strategy.
Again, we very much focus on this idea of human-in-the-loop partners where the requirement for a skilled talent network to make judgment calls on AI's work and on calibrating models and checking integrity and ensuring accuracy is paramount, and I think that this is an area where Fiverr can play a major role. That together with agents that we're developing to automate some of this work to make sure that the experts are actually focusing only on things that humans need to focus is a very important and critical role in what we're doing. It is still early, there's a lot of AI automation use cases.
We're running successful pilots with some initial customers, and we see that there's a lot of demand for Fiverr to become a fulfillment partner for SMBs to adopt automation. So again, early in the process, but we will have more things to call out in future quarters.
Operator: We have the next question from the line of Jason Helfstein from Oppenheimer.
Jason Helfstein: Kind of like a 2-part question, but on the same theme, so obviously, you've had a front row seat to this whole evolution of how agents are evolving the business. As you're seeing kind of even these more cutting-edge frontier models coming out, how is that further evolving your view on kind of how both you will leverage this technology, how your companies -- how your customers will leverage it? And then there's also been discussion among investors that AI agents are like lowering the barriers to new business creation. There's like more -- new domains coming online, I think a record number of apps being submitted to the app stores.
I guess like how do you think about that, like is that a positive for Fiverr or a negative for Fiverr? Can you leverage that? Just kind of broadly all bring those topics together.
Micha Kaufman: So essentially, the way we're thinking about how agents are becoming a part of what we're doing, essentially, agents are very much learning from human -- skilled people on how to run workflows much, much faster, much more efficient, 24/7. But at the same time, a lot of what agents are doing require ongoing judgment. And it's much like everything else with AI. Everybody has the access to the same AI which means that also everybody has access to the same agents that are available out there. Just having access to this technology doesn't give you a competitive edge, it just flattens everything and it -- maybe it elevates the floor.
But on top of what agents are doing and how you create skills for agents, how you create workflows that combine multiple skills, multiple agents, that is an art. And that is what a lot of companies are actually focusing in and providing their employees, their expert skills onto agents. Now in the case of businesses, not all businesses have the talent to actually train an agent and oversee what the agent is doing and providing judgment and calibration and fine-tuning. We see this on Fiverr. The implementation of agents across our system internally require tremendous amount of calibration to overcome hallucinations, inaccuracies or just moderate execution.
So definitely, the role of an expert, of an employee, of a freelancer is changing, but it is highlighting the uniqueness of what they can build, bring to the table to provide an advantage. Now, when we think about lowering the barriers, or agents lowering the barriers for business creation, this is amazing news for us. I've seen lately staggering numbers on the launches of new products in recent months. I believe April was the highest month with over 19,000 new announcements on product and company releases. On the one hand, the signal to noise is extremely complex because it makes everybody a builder, but building something gives you nothing.
It's all about the deployment, it's all about taking you to the market. It's getting noticed, it's validating and then it's scaling. These tasks are largely unresolved yet by AI. Can AI help in this? Yes. But generically speaking, because it provides the same help for everybody else, again, flattening everything. What gives you that competitive edge when you create something or you almost create something and you want to improve it and then you want to deploy it and then you want to scale it, this is where experts come in. Now the reason why I believe that this is not still showing up in the numbers is this is a transformative period.
I remember the digital transformation from 2000. It took time for businesses to understand that if you don't have a website, you're going to be out of business over time. The same goes with AI, and the same goes with experts that need to come with AI to make your AI or your execution better than your competitors. And I think that we're in the early innings. It's going to take some time. But all in all, I actually think that this is really a great upside for us. And when I look at the marketplace, we see AI consulting, business formation, all grow really strong double digit.
So this, to me, I think it's an early sign of what would come. Also AI-related categories continue to be super strong. AI development up 118% year-over-year. Marketing automation, also growing really strong double digits, and I can go into -- my answer is really long, so I'll stop here, but I can give more color around this.
Jason Helfstein: I guess it hasn't automated us doing this earnings process yet, but maybe someday.
Operator: We have the next question from the line of Ron Josey from Citi.
Ronald Josey: Automation is the future, right? Can't wait. I wanted to ask a little bit more -- 2 questions. First is on just attracting the talent to the marketplace as we go to more upmarket projects -- upmarket and towards these multiphase projects. We're clearly seeing continued strength on spend per buyer. We're seeing that growth reaccelerate. So talk to us just about the talent on the marketplace as we go more upmarket and these multiphase projects. And then one of the things that struck me, matching is a key part of the marketplace. And I think I heard the team talk about mismatch rates being down 10%.
So during this transformation era, talk to us just about the ability to continue to execute on some of the key tenets of the marketplace like dynamic matching and the results that you're seeing.
Micha Kaufman: On the first question, talent is super important. As we know from research, quality is core and the ability to match quality, drive quality perception is super critical, and this is very much in the center of this transformation for us. Now getting access or getting talent to the platform has never been an issue. Actually, we always had, I would say, an abundance of talent. What we're more adamant right now is really understanding on the meta skill level, what does it mean to be a talent and for what type of customer and what type of an outcome, and creating this skill graph is super critical.
In other words, what this means is, a, we're more picky about talent. But two, by improving the algorithm, improving the matching, we can create -- we can anticipate better outcomes, better happiness, and as a result, we also anticipate better retention in our customers. Those are the key things. So when we call out the reduction in mismatch, this is key because this actually means -- and it's like hiring for any job, right? Some people that you hire turn out to be amazing, some you later on figure out that there is something that you missed or they missed, which makes the match not optimal. We don't want to tolerate this.
And we actually think that if there's one huge advantage based on data that we've accumulated over 16 years, billions of interactions, tens of millions of transactions, is being able to take that data and actually make matching like anything that was done before by anyone. And this is a reason to win, this is a reason to exist. So we're putting a lot of pressure there and seeing numbers, seeing the amount of actual matches that were mismatched in hindsight, getting down is a very positive signal, and we're far from that. We're just starting right now. And obviously, over time, as we accumulate more signals, deeper signals, we will continue sharing it with you guys.
Operator: We have the next question from the line of Bernie McTernan from Needham.
Stefanos Crist: This is Stefanos Crist calling in for Bernie. I wanted to follow up on Ron's question on the matching, could you maybe give us any more details on what a baseline mismatch rate is or maybe what the revenue impact is of that 10% reduction? And then I also wanted to ask on the AutoDS pull forward, could you talk about what went right with that campaign? And is the pull forward just a dynamic of annual subscriptions? Or is there anything else?
Micha Kaufman: In terms of matching, we haven't publicly shared any specific numbers, but with this transformation, we're really focusing on trust and quality as core primitives, so to us, mismatch is really about making sure that we have this deep understanding of what are the things that will drive a perfect match between a customer with their specific circumstances and needs and the very specific skill and validated experience of a talent to do this task, okay? And again, as we move forward to do this restructure and refocus, we are going to be able to provide more color, more specific color as we really focus on those KPIs. And this nuanced understanding is super important.
It's not just driving revenue today, but it is driving the flywheel and driving the repeat rate. Now on the AutoDS, essentially, we had a very strong influencer campaign that we found great timing to do. In Q1 -- essentially, we were kind of focusing this on Q2, but we were able to actually execute this slightly earlier, not something that we plan to replicate, but -- which is baked into the numbers, which that has drove strong sign-ups at the beginning of the year, okay? So we called it out because this was a great opportunity for us to move something from Q2 to Q1 and do it earlier.
Operator: We have the next question from the line of Doug Anmuth from JPMorgan.
Douglas Anmuth: I have 2. Micha, can you just talk about where you are in terms of hiring AI native personnel within your own company and how you're thinking about that? And then Esti, can you just help us bridge the EBITDA margins from the 21% in 1Q to the 18% or so for the full year?
Micha Kaufman: In terms of hiring AI native, we're on track. We continue to do this, and it's -- obviously, the -- I think the competition over talent is pretty brutal, but we've added incredible people into the team. And what's interesting is that if you really can find, identify and attract the right people, it's really different than it used to be before in terms of the amount of people that you need to do this because essentially, those are really AI natives are very much what I found in common, and I actually wrote about this. It is really this idea that they have this founder mentality, this entrepreneur mentality. And what's really common around them is that they're 10xers.
Essentially, there are people that can do 10x, and a lot of what they do is really put up these systems, these agents, these workflows and be able to connect them for the rest of the company and continue evolving this, tweaking, calibrating, validating. It's incredible. And this is really, I think, also points to future corporates being leaner, smaller, but having people that can actually multiply the work. And talent strategy is important, not just for us, but for all companies, top of mind, in my opinion. I'll let Esti address the EBITDA question.
Esti Dadon: So as for the 18% full year margin guide, so that actually reflects the hiring and the investment that we're doing in the transformation, and that picks up over time during the year, so it's consistent with our expectation at the beginning of the year. As you know, overall, we're very committed to execute the transformation and -- but that is with a strong financial discipline, so we are planning to execute that together with higher profitability and to continue to generate healthy cash flow.
Operator: We have the next question from the line of Brad Erickson from RBC Capital Markets.
Bradley Erickson: I guess all this transformation talk, larger buyers, et cetera, I wonder, do you think about adjusting the economics or take rates or pricing or how you merchandise your services at all to kind of serve that type of customer? And then along those same lines, what would you say you want to kind of be signaling here this morning on overall marketing intensity as you pursue, again, this kind of maybe different customer profile than you have historically?
Micha Kaufman: As for the first question, there's nothing to call out at the moment. The -- what we see from the dynamics is as expected. I don't want to speculate on future models. Obviously, it's a very dynamic company. We look at it all the time, but I don't have anything to call out at the moment. In terms of similar to the market with the customer profile and marketing, so we gave some example of use cases in the prepared remarks, and these types of examples are rising. That portion of the business is growing. It is taking a larger size of our overall activity, and as it continues to grow, it will drive the business for growth.
Now as we create more efficient, higher trust, higher quality solutions with everything I've outlined, again, I'm happy to go through it, but I was pretty long in my opening remarks about what we're doing with the transformation. What we're doing with acquiring customers, with creating the flywheel will become more efficient, allowing us to also invest more aggressively in marketing to feed this flywheel as it grows. That's the plan. This is why we said at the beginning of the year, and I'm reiterating this, we're building ourselves for growth in the next couple of years.
And this is really important and the foundational work that we're doing is not -- are not buzzwords, it is really the essence of the business.
Operator: We have the next question from the line of Matt Condon from Citizens Bank.
Matthew Condon: My first question is just on as we look at the green shoots that you're seeing in success moving into more complex projects, can you just talk about what you're seeing today as far as the product launches or go-to-market that's really driving that success in the transactions of $1,000-plus growing, clients purchasing projects $1,000-plus growing? And then my second question is just you talked in the letter a lot about this comprehensive work platform, can you just talk about the specific products that you are really focused on today is really enabling that end-to-end platform, as you called it?
Micha Kaufman: The truth is we're only 2 months into the transformation, so what we've progressed so far is not big product launch yet. What we're doing is really dealing with the fundamentals of the business, the infrastructure of the business, the data infrastructure, the matching algorithm, the quality improvements, all of these. It's not really about new product launches, but it is very much about how we enhance everything we do. In some cases, we completely rewrite those solutions. Now we -- I called out job post as an example, dynamic matching, managed services, and they're driving large engagements on Fiverr.
And we highlighted a few examples in the prepared remarks, but more broadly, we're seeing a clear shift in how customers use the platform. These products are fundamentally changing Fiverr from a place to complete isolated task into a platform to execute multiphase high-value projects. So again, 2 months into it, it's not about shiny, new launches and creating promises. It's about going back to the basics and making sure that we provide a level of service, a quality of service that is unmatched. That is the focus, and this is where we're starting to see the numbers provide signals.
Operator: Does that answer your question, Matt?
Matthew Condon: Yes, that's great. I just had another question just on the comprehensive work platform, just the end-to-end platform that you're launching, like what are the capabilities that you really need to launch to enable this end-to-end service?
Micha Kaufman: Sorry for skipping this. So on the product front, we talked about investing in an end-to-end fulfilling layer, which we think is key to identifying and increasing the value of Fiverr as an active partner in ensuring that the customers and the talent is engaging efficiently, and if there's anything in the process that we need to identify to course correct, we're there. This is really important because as you go to more bespoke, more complex types of projects, being there and being a part of that transaction and making sure that you understand the scope, you understand the progress, you can create transparency.
You identify early on if things are on track or are deviating from track is super important. And this is a whole new layer that we are creating, and it's important as we think about changing the perception of Fiverr as a high-end solution for high-end scope and talent. And as we -- I can talk about those core pillars. I just don't want to reiterate the -- my opening comments, but it's all about the matching and the brain behind things. It's about the product itself.
It's about the go-to-market and how we entertain, how we engage with customers, and it's all about this idea of operational excellence where we're creating this extremely high execution capability, which we want to also provide for our customers. The learnings that we have as a team on how to be more efficient, where do you need to have a human-in-the-loop and where can Fiverr help with both providing you with the right tech, but also with the human-in-the-loop is critical. And all of these learnings are transforming from our internal execution into the tools that we are and we will provide for our customers and for talent.
Operator: We have a last question from the line of Josh Chan from UBS.
Joshua Chan: I guess with your move upmarket, what's the profile of the customer that you're ultimately targeting? You mentioned projects above $1,000, so is that the benchmark of what you're targeting? And then secondly, on free cash flow, could you talk about whether the Q1 level of free cash flow is roughly sustainable for the rest of the year and then your willingness to more aggressively buy back the stock at these levels?
Micha Kaufman: So in terms of focus, it's still largely focused on SMBs, probably larger than the micro businesses, but still SMBs. There's a lot of untapped demand, both into larger customers and larger use cases. If every business and definitely midsized businesses and up are building their own new tech stack that includes agents, APIs, MCPs, all of these use cases require a tremendous amount of validation to check accuracy, integrity, compliance, security, all these things require the mix of both technology and human-in-the-loop to continue calibrating, validating, in some cases, building, fixing. Those are areas that Fiverr is a perfect fit. And so we'll see those -- more of these use cases as we continue exploring this.
But largely speaking, it's SMBs. And the projects of $1,000 and more is a proxy, it's a way to identify the spend capacity and willingness on digital services, and so that has provided us with a good point. Now it's $1,000 and above, and within our marketplace, we have everything in ranges of hundreds to tens and sometimes hundreds of thousands of dollars on transactions. But that's kind of a reference point to help us identify the seriousness and willingness to invest in your business.
Esti Dadon: As for cash flow, we generated $21 million free cash flow in Q1, and we plan to continue to generate strong cash flow and to be consistent and disciplined on capital allocation. Obviously, our capital allocation priorities remain the same. First and foremost, we are investing in the business, and we will continue to invest in the transformation and generating cash flow. Now as for buyback, we have authorization of $59.5 million, and we will use it and act on that thoughtfully over time.
Operator: This concludes our question-and-answer session. I would like to turn the conference back to the management for any closing remarks.
Micha Kaufman: Thank you, Marin, for moderating the call today. And for everyone joining, wishing you a great day and looking forward to speaking soon.
Operator: Thank you. The conference has now concluded. Thank you for attending today's presentation. You may now disconnect.
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Fiverr (FVRR) Q1 2026 Earnings Transcript was originally published by The Motley Fool