Similarweb SMWB Q2 2025 Earnings Call

Thank you, Ramy, and welcome everyone joining the call today. I'm extremely proud of the second quarter financial results that were reported yesterday. Revenue increased by 17% year-over-year to $71 million, ahead of our expectation. Our customer base grew 18% year-over-year to almost 6,000 ARR customers at quarter end. We reported a seventh quarter of positive free cash flow and returned to positive operating profit in the quarter. We are also reiterating guidance for 2025 revenues and raising our profit guidance for the year. Customer interest in our GenAI data and solution is amazing, and the revenues from our GenAI data and new solution were approximately 8% of second quarter revenues and are growing. We are focused on three high-impact opportunities where Similarweb is uniquely positioned to lead. The first one is our Similarweb GI Intelligence. In April, we launched AI Traffic to show how much website traffic comes from GenAI sources as well as the prompts and landing pages driving traffic. In June, we expanded our product line with AI Brand Visibility, giving companies daily insight into how often they are cited in AI chatbot platforms across key topics. The second one is our AI Agent. We are rolling out AI agents to help our customers maximize the value they can extract from our data in the shortest time. We're receiving great feedback from our customers and usage is growing by 60% month-over-month since launch. And the third one is our generative AI and LLM data. We are supplying our unique and fresh digital data to companies that are building their own LLM and generative AI applications. Last year in Q2, we signed a seven-figure ARR contract with one of our big tech customers to use our data to train and improve its LLM. This customer was already using four of our solutions across multiple business units and countries. After signing this contract, they became Similarweb's first eight-figure ARR customer. In June this year, this customer renewed and expanded the contract for GenAI application and LLM data with a multi-million dollar ARR and a multi-year upsell. Contracts like this one demonstrate the durability of those AI transactions as recurring revenue streams and provide me with the confidence in our ability to convert additional customers and expand our AI revenue streams. We continue to invest in our technology and expand and enhance our data to deliver the most comprehensive view of the digital world. In Q2, we expanded our product offering to empower customers with deeper insights across the digital landscape. We launched Similarweb Ad Intelligence, giving businesses a clearer and more complete view of the digital ad spend and paid marketing universe, leveraging the capabilities of Ad Metrics that we acquired in 2024. We also introduced additional modules to our mobile app intelligence and shopper intelligence, providing our customers with more tools and data to succeed and win their markets online. The investment in go-to-market that we started in the fourth quarter of 2024 is ramping as planned and we are starting to see additional results. One of the KPIs we track for sales force productivity is the number of salespeople booking deals. And I'm super happy that the number of salespeople booking deals increased by 50% year-over-year in the second quarter. I'm also super proud we continue to operate efficiently and returned to profitability in the second quarter as well as reporting our seventh quarter of positive free cash flow. And as I like to say, we are just getting started. Thank you to everyone on the call for your continued support. And with that, I will turn the call over to Jason.

Yes, thank you for the question. Usually when we engage with companies who want to train their LLM models, the process is that you deliver them a one-time bulk of data and that they can test and validate that the data is improving their model and make it more accurate. They pay a one-time fee for this data for the testing, and after they test and validate that the data improves, we engage with them with a long-term commitment, usually multi-year contracts.

A lot of them can benefit, and also the multiple whole data sets that they can buy and use for multiple use cases on improving the LLMs. So the opportunity is in both fronts: more customers buying once it's proved that it can improve the LLMs, and the second one that they can get more data to improve other areas of those models.

It's just the sales cycle. You engage, you get the data, they need to test, they need to validate. We feel very strong around that. We position as the number one digital data company in the world right now and the number one of web data. Those LLMs do their learning and training on web data. So we feel very confident that we can build a very good pipeline and convert it down the road.

So definitely the GenAI has a lot of traction. I think it's the fastest growing product we have currently in our product portfolio and we're seeing a lot of demand for that and a very strong pipeline going forward. I think almost every one of our customers when we present them are trying and evaluating them. That's the solution.

Great. Thank you. And regarding the go-to-market productivity, we also see a nice improvement. We also shared it in the investor letter and we talked about it that we had a record high of salespeople closing deals. So you see that they start ramping up and we're looking forward for them to closing more deals in Q3 and Q4.

So those are very big data deals also not only by dollar but also amount of data. So they start with usually seven-figure deals and there is a lot of room for expansion and as I talked a little bit before because there's many different data sets that can be used on training those LLMs from web data, firmographic data, consumer behavior data, etc. So each data set is priced differently.

So there's a strong pipeline for those offerings. But it's not only the data for LLMs, it's also the GenAI module that helps track brand visibility on chatbots and the traffic websites get from GenAI. And of course the AI Agent. So we have three different offerings around AI that we are now bringing into the markets and it looks strong and we're seeing great demand all across those three offerings.

Yes. So it's a combined strategy. Basically you take each one of the product offerings we have today and you add agents to it in order that the stickiness will go up. How that customer exceeding from those solutions will go up. So those agents are integrated inside of our solutions.

Yeah, thank you for the question. So I don't think all those engagements are supposed to be one-time deals. The process is that you pay one time to go into the evaluation of the data when you need to shift your infrastructure big amount of data. So they pay one time for that. Once the data is landed on their servers, they try to start evaluating and once they go through this process and see the uplift and the improvement in their models, then they come and engage for the long term. And basically you see that we are engaging with those companies for a long time. As Jason said before, we already renewed one of those customers for multi-year engagement. So we are very confident that the pipeline we have going forward is not only strong but also has big opportunity outside of that.

Yeah, I think one of our biggest lessons is to do a much better job on communication. I think our strategy and our commitment to show and deliver what we say is on track for the past four and a half years that we're a public company and I think that's just being much better in communication we can contribute a lot for that going forward.

And so, thank you everyone for joining our call, especially our shareholders for the support. We look forward to speaking to you again over the coming days. Have a great week everyone. Thank you.