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spk04: Greetings and welcome to the SimilarWeb third quarter 2024 earnings call. At this time all participants are in listen only mode. A question and answer session will follow the formal presentation. If anyone should require operator assistance during the conference, please press star zero on your telephone keypad. As a reminder, this conference is being recorded. I would now like to turn the conference over to your host, Rami Meyerson, Vice President of Investor Relations for SimilarWeb. Thank you. You may begin.
spk08: Thank you, operator. Welcome everyone to our third quarter 2024 earnings conference call. Joining me today are our CEO and co-founder, Oral Offer, and our CFO, Jason Schwartz. Yesterday, after market closed, we released our results for the third quarter and published a discussion of our results in a letter to shareholders, as well as an investor presentation with a strategic overview of the business. Please refer to our earnings release and our most recent annual report filed on form 20F for more information on the risk factors that could cause actual results to differ from our forward looking statements. Additionally, certain non-GAAP financial statements are not subject to any further consideration. Reconciliation is the most directly comparable GAAP financial measures are available in the earnings release and the earnings presentation. We will begin with Oral and Jason's highlights of the quarter, and then we will open up the call to questions from sales side analysts. With that, I'll turn the call over to Oral. Oral, please go ahead.
spk03: Thank you, Rami, and welcome everyone joining the call today. I'm extremely proud of the third quarter financial result we reported yesterday. Revenue growth accelerated again to 18% -over-year growth in Q3, driven by an increase in annual customer and improvement retention. Our total customer count grew 21% -over-year, and the net retention, or NRR, increased by 2% point. This is the fourth quarter in a row that we reported accelerating revenue growth and the second quarter of accelerating customer growth. SimilarWeb is one of the only small group of public software companies that have reported accelerating growth over the last year. This growth acceleration and the improvement in our NRR results from a number of initiatives we implemented over the past year. We have improved our marketing capabilities, driving more meetings for our sales team and increasing brand awareness. We built a strong customer success organization that helped turn around our NRR trend over the last three quarters and is now back above 100% again. Susan Dunn, our new CRO, is driving a series of improvements in our -to-market motion, and I'm happy with the progress she's making. It is great to see the success these initiatives are starting to deliver. SimilarWeb's mission is to help companies to be successful in the digital world by providing them with the most accurate, comprehensive, and actionable digital data. So every business can win their market. For more than a decade, we have invested and continue to invest in a series of properties, capabilities that empower us to create our unique digital data. The continued customer growth and improved retention trends are an indication of the confidence our customers place in the quality of our data and their ability to generate value from the data and the solution we provide. The significant investment we have made over the years to build SimilarWeb's unique digital data means that we are in a great position to benefit from the AI revolution. Right now, I see four distinct options for us to capitalize and monetize the generative AI opportunity. The first one is that digital data is a critical and fundamental component of every AI and LLM tech stack, and that is why many of the largest global tech companies are engaging with us to access our digital data to train their LLM and ensure their models are accurate and relevant. Last quarter, we announced our first eight-digit customer, and today I'm pleased to share that during October we secured our second eight-digit customer. This is also a big tech customer who has been with us nearly 10 years and also used our web intelligence, self-intelligence, shopper intelligence through the platform and API integration across many divisions and geographics. It is now also using SimilarWeb digital data to train its LLM, and we continue to engage with several other companies on similar opportunities. The second motion we see opportunity for us in the generative AI is that we believe that the changes that LLMs are already having on the online customer behavior and the evolution of the journey from search to chatbots are more material and present a much more significant opportunity for SimilarWeb. We are engaging with several brands that are keen to understand how the transition from traditional search engines to chatbots for the consumer to find information that leads to transaction will impact their business. The evolution of the customer journey and the risk of omission from the output of the LLM is a growing concern for every brand around the world. SimilarWeb digital data can provide a range of insights that can assist brands in understanding the impact and navigating this new version of the way consumers get their information. I believe that this is a great opportunity that we are uniquely positioned to capitalize as the AI revolution evolves. The third way we are enjoying the AI revolution is of course integrating AI into our own products and solutions, help them increase the usage and speed to insights to our customers. Last year we introduced SimilarAsk, and earlier this year we introduced SAM, ourselves a system agent in our self-intelligent solution. We are deploying and implementing more AI agents per use case across all of our solutions to drive more high customer engagement, accelerating the adoption and use of our solutions. And the fourth area is of course integrating AI into our own internal process and tools, driving more efficiency and reducing costs. We are already seeing improvement in the development cycle around our engineering and reducing our customer support responses time with those tools and implementations. And there is many more to come to drive more cost-saving and improve efficiency all across our organization with AI. I am very bullish on the opportunity ahead of us. We are staffing up our GoToMarket teams to capture the big opportunity that we are seeing on top of our funnel and continue to grow. In Q3 our marketing team generates a record high of more than half a million registrations on our website and created a record high number of meetings this year to our GoToMarket teams. On the brand awareness side, I am super pleased that SimilarWeb has been adopted by leading media outlets and corporate executives as a preferred measure of the digital world. Jeff Bezos and Elon Musk appreciate the critical importance of high quality data. And they, along with many business leaders, reference SimilarWeb when making observations on the digital world. Even this week when Sam Altman, OpenAI CEO, wants to show how big the chatgpt.com website is, he referred SimilarWeb data in his tweet. We appreciate the confidence those leaders express in our data. Our goal is to be the number one partner for digital success. I want to thank the whole team for another quarter of excellent results and great execution during a period of macroeconomic uncertainty and geopolitical challenge. We believe that we are still only starting to realize the potential of our data and the addressable market we serve. And as I like to say, we are just getting started. Thank you everyone on the call for continued support. With that I will turn the call over to Jason.
spk10: Thanks, Orr, and everyone joining us on the call today to discuss our third quarter results. I will provide highlights of our financial performance and then we will open up the call to questions. We generated $64.7 million of revenue in Q3. As Orr mentioned, revenue growth continued to accelerate for the fourth consecutive quarter to 18% year over year in Q3, driven by new customer growth and improving retention. Our remaining performance obligations or RPO totaled $212 million at the end of Q3, up 27% year over year. We expect to recognize approximately 76% of the total RPO as revenue over the next 12 months. In Q3, we achieved an overall net revenue retention rate of 101% and an NRR of 111% for our over $100,000 ARR customer segment, an improvement relative to the second quarter of 2024 for both metrics. We are encouraged by the change of the trajectory over the last two quarters and expect further improvement in the quarters ahead. The increase in multi-year contracts to approximately 45% of our ARR demonstrates the importance and critical nature of our data and we expect will contribute to improve retention rates ahead. Our operational performance in the quarter demonstrates our continued commitment to disciplined execution and we delivered a non-GAAP operating margin of 7%, a fifth consecutive quarter of non-GAAP operating profit. We generated $9 million of free cash flow in the quarter, a fourth consecutive quarter of positive free cash flow. Free cash flow in the quarter was positively impacted by the phasing of customer seats that we had expected to collect in the fourth quarter. We expect to continue to generate positive free cash flow over the coming quarter and in future quarters as well. Following the results that we reported yesterday and that exceeded expectations, we are raising our gardens for revenue and narrowing the guidance range for non-GAAP operating profit for the full year 2024. In Q4-24, we expect total revenue in the range of $64.7 million to $65.7 million, representing approximately 15% growth year over year at the midpoint of the range. For the full year 2024, we expect total revenue in the range of $249 to $250 million, an increase of $2.5 million at the midpoint of the range relative to our previous expectations. Non-GAAP operating profit for the fourth quarter is expected to be in the range of $1.5 to $2.5 million. For the full year, we are narrowing the range and expect our operating profit to be between $14 and $15 million. Our guidance reflects increased operating expenses primarily related to increased head cap. As Orr mentioned earlier, we have decided to accelerate our hiring to capture the opportunities presented by the growing demand for our data and solutions. After delivering four quarters of accelerating revenue growth, non-GAAP operating profit, and positive free cash flow, we remain focused on delivering profitable growth and making further progress towards the Rule of 40 over time, as well as achieving our long-term profit and free cash flow targets. And with that, Orr and I are ready to answer your questions.
spk04: Thank you. At this time, we'll be conducting a question and answer session. If you'd like to ask a question, please press star 1 under telephone keypad. A confirmation tone will indicate your line is in the question queue. You may press star 2 if you'd like to remove your question from the queue. For participants using speaker equipment, it may be necessary to pick up your handset before pressing the star keys. Our first question comes from the line of Ryan McWilliams with Barclays. Please proceed with your question.
spk02: Hey guys, thanks for the question. Orr, great to see new customer growth accelerate. How would you attribute what drove the stronger new customer growth? I'm sure it's a mix, but is it maybe a better macro environment or is it more due to some of the changes the web has made in its market improvements?
spk03: Yeah, thanks Ryan. As I said in the earlier call, our marketing team is doing an excellent job lately driving more brand awareness, more conversions. And a big amount of visitors we have. We're seeing an increase in registration, customer growth, and a very strong top of the fund. So from what I see, a lot of improvement internally. They're
spk02: doing
spk03: a great
spk02: job
spk03: of the team.
spk02: Thanks for that. And then Jason, any early insight into how we should think about our models for next year and revenue growth in 2025? I think things are starting to land sobering here, but how should we think about the key drivers of next year growth?
spk10: Yeah, we'll give full guidance on 2025 at the beginning of the year, but I think that the momentum that you see in the exit rates are good indications to the momentum that we intend to see going forward. So, as we said, we're going to continue to be focused on that profitable growth, continuing to have both operating and cash flow profit on a quarterly basis going forward as well.
spk04: Thank you. Our next question comes from the line of Jason Helstein with Oppenheimer and Company. Please proceed with your question.
spk01: Hi, everybody. Two questions. Or from a product perspective, how has the mix shifted, whether it's versus a year ago, and maybe where are you seeing the most interest? Obviously, you highlighted AI, but it's still super early. But within the other products, what seems to have the most momentum from a business standpoint? Okay. And then second question, Jason, can you unpack the revenue volatility a little bit between the three-queue -over-year and the -queue-god -over-year? Does this have to do with the spike in the billings in two-queue, the way it flows through the accounting, and then kind of what was the catalyst for that? Just maybe unpack why we're kind of seeing a revenue slowdown in the fourth quarter just on an accounting base.
spk03: Hey, Jason. Good to hear you. Thank you for the questions. And from the product perspective, we're seeing two good, I think maybe three products are doing well in the first quarter. We have our core product, the Web Intelligence, that is continuing to do very well. We're seeing more demand on the SEO part. We did a lot of progress there in the past year or two, once we acquired a company called RankRanger two years ago. So we started implementing more deep SEO capabilities, so marketing organization drives more growth around the search channel, and we're seeing great success there. Also, we have a strong quarter on our Sales Intelligence tool. We're seeing high demand. We did a lot of good progress there. We introduced the Sales Assistant, AI agent that helps customers to get better insights, faster leveraging the AI capabilities, so this one is doing very well. We have our Advisory Services organization at the level of demand, a lot of big brands coming with all sophisticated needs and insights about digital activity. So I think those three are really good moments right now.
spk10: And then on the guide, I think by now you guys know we like to give
spk00: guidance
spk10: that we know we can meet, and we're an ARR business, and so a lot of the visibility that you have between RPO and the deferred revenue just flows through the accounting and the AI. That's how the revenue works.
spk01: Okay, so they're just really like, it's not representative of any kind of trend as we're thinking about in tonight's year.
spk10: No, I don't think so.
spk01: Okay, thank you.
spk04: Thank you. Our next question comes from the line of Arun Bhatia with William Blair. Please proceed with your question.
spk11: Perfect, thank you. Congrats guys on the acceleration this quarter. Very nice to see. Or if I can start with you, this is the second big deal that you've announced with a big tech company to use your data to train LLMs. Can you just maybe help us understand what's so special and unique about similar web data that is attracting these companies to license it for LLM training? And how does that fit into that specific LLM training use case? And then maybe you can just touch on something about these contracts, whether we should expect these to be referring and the data to be needed to continually be refreshed over the coming years as these models become a little bit more mature.
spk03: Okay. So I'll tell you just to explain you more. We announced the second customer to be an eight-figure customer, but we do close more than two deals around working with companies who want to train their LLMs. So this is an initiative that we're seeing growing nicely with the AI evolution. And regarding your question to give more visibility about our LLM using our digital data, I will explain to you how I think it works from that perspective. In order to build a really good chatbot, you need to feed the AI also with three data sets. The first data is probably the Internet data, the web data, all the content that he can learn and be smart and read all this knowledge. The second data set you probably need to feed him is what I will call conversation data. That's a chatbot that will learn to speak like a human being. This is probably when they're giving him Reddit data and all kinds of different conversation data. And the third element that the LLM needs is to be up to date with what's happening in the world. He needs to know that Trump won the election or anything that's happening. In order to be up to date, he needs digital data. That's what's happening right now in the world, what people are searching right now, what they're reading, what they're talking about. And this is where the digital data gets very important and something that you need to feed those LLM daily that will be up to track. And they have context. When you talk with the chatbot this morning and talking about the election, he will know what happened. So this is where our data set is feeding the brain. And I hope it answers the question.
spk11: Yep. Yeah, that's very helpful. Thanks, R. And then Jason, if I can just come back to the prior question on the fourth quarter revenue guidance. I think even compared to past guides, it's more conservative from like a sequential perspective when we're comparing Q3 to Q4. And it sounds like some of these new LLM contracts should start to go live in the coming quarters. So is there some extra conservatism in there in the Q4 number or anything else that we should be aware of that might be just starting off timing of RevRect next quarter and beyond?
spk10: Again, I think it's just when these deals come in or go live and how the RevRect flows through in general for us. Once people get activated or start using the data, depending on that, we just recognize the revenue of the subscription term. So there's just the reality of that as well as the Q4 bookings that we hope will come through. The timing of when those come in within the quarter depends on how much of that is going to be recognized in the quarter. So we use the same methodology consistently and we like to give guidance we know we can meet.
spk11: Okay, perfect. Thank you both.
spk04: Thank you. Our next question comes in line of Scott Berg with Needham and Company. Please proceed with your question.
spk05: Hi, everyone. Really, next quarter. Thanks for taking my questions. I have two or in your prescriptive remarks, the second option that you're trying to capitalize on in the Gen. I theme caught my eye, believing that LLMs are changing online customer behavior, consumer data today. I guess how much of that are you seeing in your business today from customers and companies trying to capture and better understand that data? Or is that a trend that you think really impacts the business more going forward versus what you've already seen today?
spk03: Hi, thank you for the questions. So this is early things we start seeing more and more brands start to realize that the consumer change the way they consume information. For example, if I want to plan a trip and vacation to Miami or Hawaii or whatever, most of the changes that I would start to do in the chat box and ask them to show me the top hotel, top restaurants, and I start consuming my information from the chat box other than just due to me used to be searched. So this consumer behavior change is something that the brands will start to really understand now and want to get more visibility about how much time they are being presented as one of the options to the consumer, how it's driving consumer behavior to drive action and the transaction. So we see right now that more and more brands start realizing it and they now seek for market data, digital data to see how they've been perceived, if they are being recommended by the chat box and how and what is the market share, etc. And we are kind of the best company in the world to give this data and help them drive for the right action.
spk05: Got it. Very helpful. And then Jason, you talked about the recovery and net revenue retention. It had a nice increase in the quarter here. You also made the comment that you expected to go higher here, I believe in the short term, not that you are predicting or going to tell us what you think it's going to necessarily be in Q4 and early next year, but how do we think about that trajectory? Can it return to the levels that you saw in maybe 2020, 2021 or 2022? Or do you think you ultimately settle in somewhere in between those levels and where you are today? Thanks.
spk10: Thanks so much. We like the momentum that we're seeing both in the retention and as well as the upsells and cross-sells that we're having with customers. I think what you're hearing are twofold. And there are two things that give us a little bit of confidence over there. One is the fact that 45 percent of our revenue is already locked in on multi-year commitments. And that gives us a lot of confidence and commitment to the retention of the book of business that we have. And then the second thing is you're seeing over and over this large deal that Or talked about earlier is again another indication or another example of how we land, retain and expand those customers, taking them from thousands of dollars to tens of thousands of dollars to hundreds of thousands to millions and now multi-million accounts. That is the motion. We are very encouraged by that and the team that we put in place on the customer success and account management side.
spk05: Excellent. Thanks again for taking the questions. Thanks, quarter.
spk04: Thank you. Our next question comes from the line of Serenda Singh with Jeffries. Please proceed with your question.
spk09: Thank you. In terms of just the two large eight-figure deals that you have at this point, are you able to walk us through a little bit of the journey of how they got there, not necessarily over like the past 10 years, but more in the near term? Is this something where maybe the jump went from an 8 million ARR to a 10 million ARR or how should we think about that with the latest upsells?
spk03: So I think the nice story about those two eight-figure deals, it shows you the amazing long-term relationship with those companies. Those two companies that now have eight-figure engagement with us, they all started very little almost 10 years ago when they started engaging with us around our web intelligence offering, getting more digital visibility. And over the years, each one of them started to buy more of our solution. If it's sales intelligence, shopper intelligence, and more they gain trust with our data and capabilities, we start to go into more events and engagement with them, giving them low market data and basically become the trust advisor for digital market data. And this is how we build over many years those relationships and engagements drive those big things. And I think this will give you the confidence that more and more like those to come down the road. And more and more companies depend on the digital world for driving more revenue and success in the business. We want to be their digital market data provider. So we're very happy with that and hope more to come down the road.
spk09: Thank you. And then in terms of just, if you think about accelerating the hiring within your sales force, can you talk maybe a little bit about the incremental opportunity and where you're focused on at this point? Is that more there's new clients coming on and you see a bigger opportunity there in the near term? Or are we finally kind of seeing the thawing out with existing clients where there's enough demand that we can start to see? I think you mentioned higher NRR, but just a meaningful improvement in the ability to upsell to those clients.
spk03: Thank you for the question. We see two great plays that we can accelerate our -to-market expansion. The first one is to hire more sellers to take over all the meetings and demand we're seeing in the funnel, basically the increase in the inbound demand we see. The second area is basically doing great and repeats around enterprise clients. We
spk11: have
spk03: more than 5,000 customers today. We know exactly in which market and industry customers really need our solution. We want to be actively approaching those customers and educating them about our offerings and drive more success on the enterprise side. Our market is massive. We talk about it a lot of times, but we're focusing on a very big time. We believe that every company that operates online in the digital world and wants to be successful needs our solution to drive more market share and growth. We need to get in front of the right people, present them the capabilities and data and insights we can bring to them and bring them on board. We see a good opportunity there. Especially now that we are a multi-solution company and we can come to a customer and have a web intelligence for the website and an app intelligence for the app activity and shop for the marketplace Amazon strategy. So I can present and come with a lot of great offerings. So we have seen good momentum also on our enterprise play.
spk09: Thank you.
spk04: Thank you. Our next question comes from the line of Patrick Walravens with CitizensJMP. Please proceed with your question.
spk06: Oh, great. Thank you. I have one for each of you. But my first one, or how's your new head of sales, Citizen Dunn, doing? What changes has she made and what is she most focused on?
spk03: Wow, Susan is amazing. I cannot tell you how much I'm lucky that she joined us. A true industry leader, she comes from an amazing background. She was the CEO of Nielsen IQ. It's a $5 billion ARR business. She was leading thousands of people. She grew there since she has been there more than 20 years, living and learning. So she has a lot of industry background, how selling data, insights, very deep knowledge around the CPG ecosystem. And she is a true executive. And she is doing a really great job now, all the right moves, ramp up the -to-market and really set up to success to capture the amazing time we are approaching. And we are very excited about it.
spk06: Awesome. And then Jason, for you, if I look on page 25 of your slide deck at that long-term model where you get to a 25% operating margin, remind us how we think about when or at what level or what size we get to that long-term model.
spk10: Sure. It's between $400 to $450 million. And that long-term model is 85% gross margin, 25% operating margin, and 30% free cash flow, meaning at that level we will be talking about $120 to $135 million of free cash flow. Looking forward to that. Well, congratulations to you guys, and thank you. Thanks so much. Thanks so much,
spk04: Pat. Thank you. As a reminder, if you'd like to join the question queue, please press star 1 on your telephone keypad. Our next question comes from the line of Tyler Radke with Citi. Please proceed with your question.
spk07: Hi. Good morning. Thanks for taking the question. Just going back to the questions around some of the AI use cases and AI deals, can you just remind us exactly the nature of those in terms of how they're structured? And then for deals that sort of involve an AI consumption or API or data access, what are you seeing just in terms of those average deal sizes? How much bigger are they than kind of the traditional similar web deals?
spk03: Okay. So basically, if you're talking about the AI deal, we're talking about two different products. The first one is training LLM and digital data to train their chat bots to be up to date with what's going on in the world. And then basically when you sell, it's different data sets that each one can help the LLMs to be smarter about different things. So it's basically different data streams about what people search, what they read, what's happening right now. And then it's by different regions and platforms. And usually those deals start from six figures and growing. You start small. There's one data set, see if improving the model and then you start adding more models. The second, the brand of the product provided, those brands want to understand how they perceive a consumer using the chat bots. And there it's increased by the number and they want to understand what people ask and the answers. And it's also by region, by platform. So by there it starts with five figures and then it can grow up.
spk10: And Tyler, just to add, those are all subscription, annual recurring revenue. And as Orr was saying before, we do think that these contracts need to be renewed because of the value of the freshness of the data that the LLMs need in order to keep up to date with the data.
spk04: Thank you. Ladies and gentlemen, that concludes our question and answer session. I'll turn the floor back to Mr. Orr for any final comments.
spk03: Thank you. Thank you.
spk04: Thank you. Thank you. This concludes today's conference call. You may disconnect your lines at this time. Thank you for your participation.
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