Similarweb Ltd. (SMWB) Earnings Call Transcript & Summary

Welcome back to the Jefferies Software Conference. My name is Brent Thill. I'm very excited to have with us the Co-Founder and CEO, Or from Similarweb, as well as Jason Schwartz, CFO, who's on as well. Thank you, gentlemen, for joining the conference. And Or founded the company in 2009, has served as CEO and a Board of Director since that time. We are huge fans of Similarweb's solution. We use it at Jefferies extensively throughout our research process. And as I tell clients, we would be completely blind. It is the flashlight that lets us see what's happening out there in the world and we appreciate the opportunity to use the product and have you guys here today.

Maybe if you think about just as it relates to the recent IPO and maybe talk through the timing and kind of why this was right to come public, ultimately kind of what you're seeing overall in your end markets to kick off would be helpful.

Thank you, Brent. I love the flashlight sentence. I think maybe we should use that in our marketing pitch; Similarweb, the flashlight to show you to navigate digital hectic ecosystem. So yes, so we thought that we are now 4 months running as a public company, and it was a great experience. And we thought going out now is the right time for the company because of few reasons. One, as a business, we've become really mature around our forecasting, about our operation. And we felt there was a good opportunity. The market was good, and we felt that this will be really good to our company perception and brand awareness to be publicly traded in the New York Stock Exchange, and we decided to go out. And 4 months into it, we definitely can say it was the right decision.

Yes, that's great. Jason, I know you've been at the company for quite some time. And maybe if you could also share just a little bit of your perspective on being the CFO and your journey in kind of just your perspective on the story for investors that are still learning story. Sure. Happy to. And again, thanks for having us at the conference today. We are -- as Or said, we are -- we've been at this for a number of years, but have always thought that as more and more transactions and interactions move online, and therefore, digital insights are measurable and easy to get access to business leaders and business operators need to have the ability to see the insights of the competitive market landscape and put what they know about their business in context of that competitive market landscape. And that's really what Similarweb does. Of course, 5 different solutions that Or I'm sure will touch on in a couple of minutes. For us, the -- we've always believe that we operate in a huge TAM and a huge opportunity and that we would be a publicly traded company. So we've been -- since I've been on board planning to be a publicly traded company and have operated like this and see ourselves in a $34 billion TAM and accelerating revenue growth, I think we just reported some great numbers in Q2 of 49% growth with strong net retention and even stronger customer penetration and growth. And we're really excited about the opportunity that we see ahead of us.

Or, many ask us how you do it. Like how do you get this inside. Maybe if you -- we're not asking for you to share the secret sauce, but can you just dive in a little bit deeper in terms of the infrastructure and Jason mentioned these kind of 5 different solution areas, how you're architecting and building this to do what you can do?

Of course. So if I try to summarize what Similarweb do best than anyone else is the technology to predict how the digital world behave, how the traffic moving the Internet. It took us many years. I think I can -- at least 10-plus years of development. What's unique about this technology is how we do -- not I call it secret sauce, but I will take this cooking emotion and continue the ingredients we use and the way we do the cooking. So we have very unique ingredients that we use that a lot of them are proprietary for us. It's basically a combination of 4 different, I would call them, data types, so digital signals that we use. The first one is behavioral data of millions of device. Now they interact with the digital world. This is proprietary data that we own. The second one is data partnership that we go and partner with all the biggest companies that have the data of the Internet, the shifting. They sit on the pipes that's shifting these digital signals like ISPs, DSPs, security companies. And then you have that extraction when you go out and call the big part of the open web like the search engines. And the last one is direct measurement is when we have millions of websites and apps sharing with us the real direct measurement because Similarweb is considered the company with ranking and ratings. So they really care about how we rank them, so they come and verify their data. So this is also a very proprietary data that we own. So we're taking all those ingredients that big part of them are proprietary for us. And with that, we predict how the Internet behaves. This is the traffic that of the Internet. And with this technology, we built 5 business application on top of that. If you understand that Similarweb is the best company to predict the Internet behave, so if you want to do digital research to understand the market share of every player, who's winning, who's losing, and see good visibility for the digital world, you come to Similarweb and you by the digital research solution that we have. If you want to do digital marketing to understand which [indiscernible] work with Similarweb of the best data, so you will come and you get our marketing intelligence solution. If you want to sell to digital companies and you want to find them, qualify them, and you want to get all their data, for example, you want to sell something to e-commerce, you want to find all the e-commerce in specific country and get all the traffic and attribution to qualify them, Similarweb is the best solution. You come for us, and we have amazing sales solution for those companies. If you want to invest in digital companies, private or public, you want to get all those signals. You'll come to Similarweb. We are considered the best alternative data source for that, and we have investor solution. And the last solution is the Shopper Intelligence, if you want to know what people are buying online and where and path to purchase. So we have the best data. And so this is 5 lines of business on top of this very strong technology that we built over the past 10 years.

And if you think about those 5 different engines of growth, can you just maybe characterize where you're seeing the most excitement, maybe what's most mature? How do you characterize the different strengths of those engines?

Yes. So it's a good question. If I look over our 5 lines of business, 5 products, the core product that we start is the research intelligence and marketing those probably a little bit more about 50% of our book of business. They're growing very nicely. And then we have another 3 that are more new that we presented in the past few years; the sales solution, probably between 15% to 20%, growing also very nice in the past few years, really great success. We're a very unique offering now. We have the investor solution we will consider to be one of the top alternative data player. It's only 20-something percent of our business. And then we have the new offering we put into the market, the Shopper Intelligence that we only launched at last quarter and it is seeing amazing results off the gate, so very exciting time for that solution.

And when you think of -- the last one was Shopper Intelligence. Maybe if you can pop the hood and give us a little view of what that looks like on the inside. What -- maybe help go a layer deeper, just describe where you -- of the solution and then ultimately, who's going to end up buying this solution.

So the uniqueness about this solution that the entity you get data inside this solution is brands and what they sell online. So if you look on the other solution that we have, the main entities are all websites or apps or the investors, they look on stocks. And this platform, you come and you look on specific brands. For example, you can come and say, I want to see Red Bull online performance, how many people buying Red Bull online, how much revenue it's making, how many units they've been sold. And then you can go to specific what they call SKU, the different products Red Bull is selling, if they are selling Red Bull diet or Red Bull six pack or Red Bull big bottle, so you can get really understand of what's driving the success and the demand per specific products and specific brand or sub-brands. This is extremely viable information for CPGs, retail, e-commerce marketplaces, a very, very powerful offering.

Big bottles Red Bull, that sounds good. We need one of those to start this off here. And then ultimately, when you think about the monetization of these 5 different areas, can you just describe the economics of each of these categories? Are they similar in terms of you're just paying for -- maybe just describe how customers are licensing these individual solutions. And ultimately, I mean, do you see going forward that you are going to have multiple adoption areas across the same customer? It seems like there's a big attach rate [indiscernible]

So right now, we think that the majority of our customers are buying more than one solution. Historically, most of our customers was always buying the research and the marketing together, and now that we have more offering to give to them. And the interesting thing that each one of those lines of business have different pricing approach according -- this correlates with the value the customer is getting for us. So each one of those 5 products have good, better, best offering that you can buy and get access to different level of features. And then you have a metered approach that, as I said, correlate with the value the customer is getting. So if you think about the shopper as example, the metered approach is the amount of categories you want to analyze, if you want fashion, electronics, food and et cetera. So this is the metered approach. If you think about the investor solution, the metered approaches by stock and sector you want to analyze. And if you look on our sell solution, the metered approach, there is [ six ]. The more sales people are using our platform, the more value they're getting. So -- and on top of that, you always have the add-ons, if you want an API or advisory services. So this is how we're pricing and packaging the different offering.

That's great. We had a question from a client. And again, we encourage you to go to the web -- Wall Street webcasting section. You can ask any question you want, and I'll read it. But ultimately, this is a good question. This is kind of where I was going next is, a lot of clients are talking about the amount of data you're collecting and how you manage this. And so there was a lot of questions about how can the business scale over time as you're collecting more of these signals. And so if you could just talk about the underlying technology stack and how over time you can make this more efficient and profitable for investors?

So you want me to talk about the infrastructure we use to analyze the amount of data we collect like in the tax that we use now?

Yes. I think -- I believe you're on Amazon, you leverage Amazon, but you have your own secret sauce as well on top. But when you think about just ultimately how you get scale and kind of what that [indiscernible] tech stack looks like at a high level?

So the infrastructure now is based on Amazon and then the scaling of the amount of data and storage is very mature, so we're doing it for many years. So we've already been into a really efficient optimized process of collecting those enormous amounts of data and then analyzing without increasing our cost. So we have a fixed cost of the data acquisition that is a big part and then the big part of spend around the infrastructure of the machines analyzing it. And it's kind of really stable. And then you can see that in the really great gross margin numbers that we have, and as a data company you can see how amazing it look when the company is scaling. So you need to spend a lot of money in the early days to build the infrastructure and putting all those data costs that are usually fixed. And as the business scales, become extremely profitable businesses. You can see ZoomInfo as a great example for that.

There's another question around how does mobile and app data compare to PC kind of web data? What's the challenge of getting some of this mobile app data in your system?

It's a good question. So we have app data. It's not fully -- the offer that is not full because we have only androids and we didn't add the iOS yet. I hope that by the end of the year, we will also add the iOS data, then I can say that we have a good app offering. Until we don't have the iOS, it's a big part of the ecosystem, especially in the market that we sell in U.S., U.K., Germany and those markets iOS is a big majority of the devices. And so -- and then when you look on the app insight, at the data, there's area of data when we are doing a good job and there's some data that we didn't present and then maybe it's a gap, and that will maybe give you more context. So -- and we want to analyze the app ecosystem, what's really important, especially to our customers, mostly the usage there. Now there are retention data. This is something and -- download sometimes, this is the data that we have, and we're doing great job now on Android. And then there's all the elements about the in-app revenue that this is something that is very important to the gaming industry and how inventors do. The game -- the in-app revenue, it's data that we don't have. And basically, you need access to a lot of, I would call it, app analytics learning side, something that companies like [ AppValley and Sensato ] are doing a good job. And it's really important to the gaming industry. So this is kind of just to give you a holistic view about how the app ecosystem behave.

There was another question just maybe if you can describe your go-to-market process and ultimately, those coming directly to you versus direct sales. And there was a question maybe for Jason to just talk through sales and marketing productivity, how is it trending?

Yes. So maybe I will start just to give you the view of the go-to-market and then Jason can talk about the efficiency. So we have a big go-to-market organization. I think right now, almost 400 people. And it's divided by the different region. In every region, we have SMB enterprise and strategic and then we split them by the different industries they go after. We have a big part of the demand coming inbound because they have a free website that is very popular. And then we also have outbound machines that going to the relevant customer. Maybe Jason, you want to talk about the efficiency of how it works?

Sure. Thank you, Or. So when you look at our sales and marketing expense, we split it 60-40, 60% goes to acquiring new customers, and 40% is what we invest in our existing customer base for retention and expansion. That 40% of sales and marketing expense correlates to about 23% to 24% of revenue, which means that our recurring revenue base today is generating 13% operating margins today. And the 60% customer acquisition cost is recovered in a 14-month payback period on a gross margin basis. So we think that those are pretty compelling user economics -- unit economics on our go-to-market expenses.

Yes. We're very proud on our go-to-market organization.

There was a question just when you think about the financial framework of top line growth and bottom line and kind of ultimately what do you see the ultimate kind of market growing at a sustainable growth rate for top line? And then ultimately, kind of long term, do you believe -- I think there's some concern, can you hit higher profitability targets over time in the business. I think there's maybe a general overhang of, hey, we're collecting so much day to day, so much infrastructure cost, like, can this really be a super profitable story long term? Can you address those questions?

Maybe, Or, I'll take a first crack at that. It's a great question, Brent, and I think the context of looking back over the last 3 years before we became public. If you look back at 2018, we had a gross margin of 54%, and we've expanded that and increased our gross margin from 54% in 2018 to 71% in 2019 to 77% in 2020, in the first -- first half of this year, we're already at 79%. That shows that high gross margin that -- and leverage on the fixed infrastructure and data costs that Or was talking about before. We think that, that gets into -- in midterm, gets into the 85-plus kind of sustainable gross margins. On the flip side, during that same period, when you look back at 2018, we had a $26 million cash burn. In 2019, we cut that to $11.5 million cash burn. And in 2020, we're already at less than $5 million. And in Q1 of this year, we're already cash flow positive. When you look at the business, the business is effectively a profitable business today. And over the last couple of quarters, we've accelerated that growth from being 30% to 38% to 43% to 49% year-over-year growth in Q2 of this year. We see the acceleration of the business continuing, and we see the retention and net retention numbers growing very, very strongly as well as the number of customers who are expanding from the $10,000, $20,000, $30,000 price point going and increasing to become the hundred and multi-hundred and multi-million-dollar accounts that we were talking about before. Long term, we've put out a long-term guidance that we think is kind of 3 to 5-year guidance. And we've talked about having an 85% plus gross margin with operating profit margins of mid-20s and cash flow margins of 30%.

Sounds pretty exciting.

We're excited about the opportunity ahead of us.

Yes. Or, when you think of on -- many ask, there are different solutions in the market and what is in your opinion kind of the most unique component? I mean, as users of the product, I think we see it. But for those that haven't used it, can you help describe why you're so unique and why others can't really replicate what you're doing?

First, it's very hard to replicate. Maybe somebody will be able to do something similar, but it's very hard because the access to the data and all the know-how to destination. And I think what makes us different is the quality of the data. Even there's other companies, if I give you the example of the sales intelligence ecosystem when we have companies like LinkedIn and they have the best data in the world to do in HR and sales solution, nobody getting closer to them. There are some other players that are trying to provide, but LinkedIn have the best data set. So I think Similarweb is the same story. We have the best data about how the Internet behaves. And this is our uniqueness in each one of those lines of business. On top of that, I think we built a really great product in UI. So the experience of using the platform is delightful and you get great experience. So I think this is what makes us very unique.

Well, there was another client question around retention rates in SMB and enterprise. Can you talk to what you're seeing there?

Yes. So I think that overall, we're seeing a great trend in the retention over time. Very proud of the numbers that we have. I think we report 118% net retention on the big accounts and it was growing nicely over the past quarters, and we're seeing this trend continue. And overall, the business, when you look on the entire book of business from customers who are paying $2,000 and above, we see, mind me Jason, 106%.

Correct. 106%.

106%. And if you look and you break down all the different buckets, enterprise, strategic, SMB, all of the net retention -- gross retention numbers are great, really happy with them. And what you're seeing now is customers that we had a year ago or more than a year. So those one are the one that we did so many improvements from them, so it's cohorts. So the customers we're adding now have better experience, better platform, better services, so...

Last question just as it relates to your guys' time as being a public company, what is the one thing that you think maybe investors aren't hearing as loud as they need to hear? Is there any areas of frustration other than dealing the sell-side analysts like me? Any other areas of -- that you think are important to point out?

I think that the one thing that I always like to -- investors to remember when I give the investor deck presentation is that to understand how big is the TAM that we operate. We have the entire data of the Internet. And I personally believe that every company that operates in the digital world need to have that. I can come and give you all your competitor data. Any reasonable CEO will never say no to it. So it's a massive TAT, a greenfield opportunity, and I think we are positioned extremely strong to capture this opportunity.

Or, Jason, great to see you. Thanks for joining.

Thanks so much, man.

Thank you. Thank you so much.

Thank you.

Have a great day.