Clarivate Plc (CLVT) Earnings Call Transcript & Summary

Thanks for coming to the presentation here. My name is Andrew Nicholas, and I'm the research analyst covering the information services, consulting and HR tech sectors here at William Blair. Before getting started, I am required to inform you that for a complete list of research disclosures or potential conflicts of interest, please visit our website at williamblair.com. With that out of the way, I'm very pleased to welcome Clarivate's CEO, Jonathan Gear, to the 43rd Annual William Blair Growth Stock Conference. Thank you very much for joining us, Jonathan. I'm going to turn it over to Jonathan to make a presentation. And with what time we have left, we'll do some high-level Q&A.

Okay. Great, Andrew. Thanks so much. Thanks, everyone, for attending today. And as Andrew said, I'm going to kick it off -- I know some of you know the Clarivate story well. Some of you are new to the story. So I'm going to kick it off with this very short overview on Clarivate and a couple of kind of key topics, which I think will certainly kind of -- what we've heard from investors the last few weeks. So here's the clicker -- all that kind of stuff. Okay. Just at a very high level, let me describe what Clarivate is. We're a business information company selling across 3 core segments. Those 3 core segments are Academia & Government, which represents a little under half of our revenue; Life Sciences & Healthcare, which is about 30% of our revenue; and the remainder, about 20% in Life Sciences & Healthcare (sic) [ Intellectual Property ]. And within these 3 markets, the common thread which ties it all together is around innovation. We support research and innovation across all 3 of these segments. In Academia & Government, the core is around -- here, we sell into, think of the university library. University of Chicago down the road would be an example of it, top research universities around the world primarily. And we're selling research and analytic tools to help their clients, which tend to be the researchers and professors at universities. We help support content aggregation, all the content that flows into universities, physical books, e-books, digital books, videos. We help support that content aggregation and service. And finally, we support the university systems themselves with true workflow SaaS software systems that run the universities completely. So it's like the SAP or Oracle of a university system, that's what we provide. In Life Sciences & Healthcare, we support the full drug discovery process for our clients. Our clients range from big pharma. That's the bulk of our customers, are big pharma, large biotech, medium biotech. Those are the core of who we serve. And as I said before, we support the full drug discovery process, all the way from the very beginning, the ideation side, when companies are thinking about what are some whitespace we should be entering into, all the way through to once that's approved, to the molecular level; the white suits in the labs, who are developing the solution; through clinical trials; through market access; and post-launch commercialization. And finally, in Intellectual Property, really 2 areas we support here, and we're supporting any company that is intensive around IP, intellectual property, innovation, product, new product launches, and we support it both on patents. We're the largest provider of patent services in the world globally, and we support it around trademarks. So think about customers here, anyone who's very innovation-intensive, could be drug companies, pharma companies, could be high tech, could be automotive companies, very brand-intensive companies like L'Oréal, for example. These are the customers that we serve. And the customer base that we have are fantastic. We are blessed with an incredible set of customers across these 3 segments. We are global in nature. We serve clients in over 150 companies around the world. And what you'll see here are just some examples from those 3 core markets. I talked about how entrenched we are with our customers. Virtually, all of the world's largest research universities in the world are our customers. All of the large pharma companies, drug development companies use our products and our services. And again, virtually all of the large R&D-intensive companies in the world, organizations use us. So we have an incredible set. One of our core assets are our customer relationships, and we serve them around the world through our services. Now this slide kind of shows the types of services and how we go to market. It starts on the very left-hand side with the foundation of what we do at Clarivate, which is highly enriched proprietary data and content. And that's true in all 3 elements of the segments that we serve. In Academia & Government, I will call out our Web of Science as an example of this. We are the world's leading citation database that is used by professors in universities around the world as they do research and they research new content ideas. As they publish into journals, Web of Science is the gold standard that measures the impact of those journals and is critical in the world of publish or perish. In the world of intellectual property, we are the world's largest, again, suppliers of both service around both patents and around trademarks. We have the world's largest curated enriched database on patents. So if you imagine a patent, patents in the raw form are publicly available. They come into a PTO office, a patent and trade office, could be the Alexandria one for the U.S., could be Beijing in China. And we collate all the information, we enrich it, and it becomes critical for an entire patent life cycle process. And the process starts with searching. So if you have an idea and you need to determine, is it an idea that I can patent? Or is there a patent out there that I have to navigate around or an agreement or navigate around? You do an early search. And we tell you what's out there and what's potentially applicable in your use case or product idea. Once you decide this idea that can be patented, we're going to help you register that patent in all the relevant countries around the world. It's a complicated process. Every single country has her own PTO office -- sorry, patent trade office. Everyone has different rules and timings and payment about how those are made. And once those are registered, we maintain, every year as those are renewed, typically -- and every PTO is different, either an annual or every 3 years, we renew their portfolio on behalf of our clients. And our clients here, typically, again, are large innovation-intensive companies or they're large patent law firms. Finally, in Life Sciences & Healthcare, I described previously the full drug development cycle. And we have 4 proprietary databases around competitive information, where drugs are in the development cycle; molecular information, that actually helps the laboratories determine how to bring and go the molecules to address the solution they're trying to create. We help our clients to go through the multistage clinical trail (sic) [ trial ] process. We have data that helps them think about market access as we bring our expertise to help insurance companies and funding agencies around the world help the economics. It will justify them supporting economically new drug being developed and then post launch, where there are opportunities. And these are examples of the core of what we do, which is the enriched data which drives the other elements in here. Once we have the enriched data, we then move up the value chain into analytics and insight. And this is taking our core data. And here, we build using AI tools, large language models and et cetera. We move up the value chain and help unlock some of the insight that's resident in the underlying proprietary data that we have. The next stage, where we provide workflow solutions. And probably the best example we have around this, as I mentioned previously, is our university management systems and library management systems. It's core. If you go into our library customers, people behind the desk look at their -- what they're looking at, those are our systems that they're using to manage the libraries on a day-to-day business. And around all of this, we wrap expert services. That could be services on how to support the annual renewal of your patents. It could be consulting services, where we take the market intelligence that we have and apply it to a unique situation that a client has. And all that allows us to become much, much more sticky with our clients. At the bottom of this page, I won't read them, are examples of the types of underlying core databases that we have. We have multiple dynamics which support the long-term secular growth of these markets. These are fantastic markets. I'll walk through it kind of left to right on the slide here. First, all 3 of the segments that we serve have long-term secular growth trends behind them. It could be the ongoing investment in R&D, which is increasing every year in the clients that we serve; then [ self ] fees, the demand for trademarks, the demand for new patents. It could be the long-term growth in investments in universities that take place and the constant expansion, what you see in publishers, constant demand for new publishing taking place. It could be the ongoing aging of the population, all the new drugs coming out to address therapeutical opportunities to help patients globally. So these trends are taking place across all 3 segments that we serve. Second, these markets are incredibly economically insulated. They're not impacted by a secular up and down or what's happening in the global economy. What we've seen is we went back and we looked at this at Investor Day, we looked at the post dot-com bust, we looked at the great financial crisis, and we looked at the performance of R&D spend, patent filing and university paper publication, all of which substantially increased and overperformed what was happening in the economy. These are markets which basically are largely immune to what's happening up and down in short-term economic cycles. Number three, they are mission-critical solutions that we take to support our clients around drug discovery, of course; [ apps ] in drug development, core to the pharmaceutical industry; research, high-quality research, critical to universities; and innovation, if you think about companies out there that innovate that you can think of, that's come to mind, core to what they do. And finally, looking at us internally for a little bit, we have an incredibly robust business model. It starts with building organic growth rate. And the story of Clarivate in the near term is increasing our organic growth rate. That's where we're very focused on through innovation. As that continues to grow, we have 80% of our revenue is recurring in nature. So a very predictable business model; very high renewal rates, over 90% renewal rates within our subscription business line; a low CapEx model and a kind of flywheel of cash generation. So every year, the cash that comes out of this business compounds, compounds and grows and grows. Quick highlights. We had our Q1 call a few weeks ago now. A couple of things I'd call out, but I won't go through all of it, but we called out a 3% organic subscription growth rate for the business. Free cash flow improving significantly kind of year-on-year. I won't go through all the numbers on the left. I'll maybe talk a little bit about some of the qualitative highlights on the right-hand side. Completed -- I've been -- I should mention, I've been in my seat as CEO since September 1, came in and have restructured the business to focus on agility, innovation, speed of decision-making around these 3 segments, brought in 3 phenomenal leaders to lead those segments, feel really happy with the impact they're having. We continue to deleverage this business entering the year with a little under 4.5x net leverage ratio, been very focused on getting that leverage down to an acceptable level and made great progress around it. Key element here is I talked about the story of Clarivate in the near term is about improving our organic growth rate. There are 3 specific product areas we have to improve to get to our market growth rate of 6%. The first one was around Web of Science in our Academia & Government group. I remember, our flagship products has been relatively flattish the last few years based upon investments that we've made. We saw incredible usage increase last year. Usage in that product increased 78% year-on-year compared to prior years. And that just fed through to a higher renewal rate in Q1, Q1 being our largest renewal quarter for that product, very high renewal rate, increase in net new business. And I think we can put a check by 1 of our 3 products is kind of underway in terms of getting the path down to 6%. We're now focused on the other 2 areas, which is around 1 product in our intellectual product group and a couple of products sitting in the life cycle -- Life Sciences & Healthcare. And the other thing, which I'm going to spend the next couple of minutes talking about because it's become very topical lately, is how we continue to leverage AI and machine learning to improve our products and solutions. So we have used -- I'll focus on Gen AI for a second for all these elements. We've used AI as part of our solutions for years and years, in some cases decades, because frankly, in the world of business information, we cannot exist without AI and all the permutations that come from it. I won't go through all the pieces here, but here are some examples of both machine learning, deep learning and then Gen AI tools and how we've used them today. We've been using it for a long time in our products. Couple that I would call out. So -- and we use machine learning. In Web of Science, we are the benchmark for quality standards in the world of academic publishing. So Web of Science and something we have called the Journal Impact Factor is a measurement used to judge the quality of products. And we use machine learning to continue to fair it out, what's called predatory publishing, kind of unethical behavior, to weed out poor quality publications. It's actually core and critical to what's taking place in academia. We've used large language models and IP to accelerate the interrogation of our proprietary data to provide summaries, again, of the patents that we use. It's critical for us to move faster and move quicker and provide the high-quality proprietary data that we have in IPs. The list can go on and on, but you can feel free to go through this list in the future. Now what I will say with this, when I look at business information tools, in the world of AI, this is kind of how I look at the lens of the opportunity for all of us, including Clarivate. It starts with proprietary data. And we have proprietary data, it's core to what we deliver around all 3 of our segments. I covered a few examples on an earlier slide. The second thing, which is highly relevant to our customers and our use cases, is around analytical transparency. In other words, a black box example, even if it's accurate, will not fit the needs of our academic researchers, certainly will not fit the needs of life science companies and regulators as they go through the life science and clinical trails (sic) [ trials ] process, is having the transparency of the answer all throughout is absolutely critical to our customers and the solutions that they demand. And finally, this view of accurate intelligence. I had a conversation a few weeks ago with a head of patents from one of our companies, a high-tech company. And I asked her, I said, do you -- how are you using Gen AI with your patent attorneys, she had a staff, I think 80 patent attorneys. And she -- and first response is, we would never use Gen AI in our patent process. And then she stepped back a little bit, but she said the importance of getting a patent right is paramount. Close enough doesn't work. If I get a patent word a little bit incorrectly or a little too narrowly, that can cost me hundreds of millions of dollars of protection on this one product. In the world of life sciences and health care, the whole drug discovery process, the regulatory approval process, again, you can't be close enough for the answers. You have to be incredibly precise. And in our markets, these -- those 2 elements are incredibly important. So fundamentally supporting us, and this is where we get the balance of using AI correctly is we're in very high stakes use cases. We sit in incredibly entrenched workflows. And the credentialing, particularly on products like Cortellis in life sciences or around Web of Science in academia with this Journal Impact Factor, are critical to what our customers need. So just -- here's just some examples. Again, I won't go through all of this. And I think we published it, Mark, didn't we, today. So I'll step on it. We have an 8-K on this. You can go look through it. But this lists some examples of both the proprietary data we have across all 3 of the segments; the transparency requirements we have around A&G, Life Sciences & Healthcare; and then how we're taking it to provide very precise, accurate -- 100% accurate answers, which is what our clients need. So we're excited about this as an opportunity. Again, it's core to what we've done, frankly, forever. It's been increasing part of our workflow. Gen AI, we've been using for about 14 months. You would think it [ to the moon ] 2 months ago. It's been a great tool we've been using, and we'll continue to use these technologies going forward. So with that, Andrew, I think I'll wrap up, and we can talk about any questions you might have.

Great. Thank you, Jonathan. Yes, we'll take the remaining 10 minutes or so to walk through some Q&A. And then I think as many of you know, we'll do the breakout in Jenny B once we're through with that. And if you have any questions there, feel free to come along and ask them. So thanks for the presentation there, Jonathan.

I think what I'd like to spend some time on with the group is just kind of walking through the organic growth acceleration that you're expecting over the next couple of years. I think midpoint of guidance this year is in the low 3% range, but the target in '25 is closer to 6%. And as you alluded to in the presentation, there's 3 kind of major areas that you're looking to accelerate. So if we could just kind of walk through each of those, maybe starting with Web of Science, which has some really interesting early signs of improvement here in the first quarter and then -- and walk through the other 2, I think that would be helpful for the group.

Okay. Great. Thanks, Andrew. And I'll break it down. Because in our Investor Day, we provided clarity of exactly how I look at the business. So right now, last year, we grew in kind of the mid-2%s organically. The market rate of the relevant products that we sell into is growing at around 6%. So we had a significant gap. And when we look on the segment by segment, it's not just 1 segment, all 3 segments are underperforming by roughly 200, 300 basis points. However, these segments came down to one specific product area. So in our Academia & Government segment, the relevant market is growing 4%. We have been growing around 2% the last few years. That 2% gap has been entirely Web of Science. It's been a flattish product for us, should be growing at the 4% to 5% range. That's what our competitors grow at, what the market has been growing at. And underlying it, it was such an old dusty product. And in fact, one of our investors use the term dusty, and I've stolen it because it's such a great description of it. The content itself is paramount. It's critical. It's must-have content, but the product was just difficult to use. So we started about 6 quarters ago, investing in the product, beginning to make some incremental improvements, and it's all around the interface and usability of that product. We've made the searching easier, the drill-down easier. We've added some analytical tools to be identified as a search in one particular area to suggest other protected topics that are relevant to that search. We've -- because a huge portion of Web of Science is around the professors and their -- it's kind of their brand, if you will, easy pages where we bring together a profile on the individual users, which they can easily print or send as they do grant applications. So it's kind of moved up from being a pretty dusty search on a database into more of an analytical and workflow tool. Now on the back of that, we saw, as I think I mentioned, usage increase 78% year-on-year in that product, which -- I've lived in this world a long time. That is a massive, massive increase in usage. And on the back of that usage last year in Q1, which again is a heavy renewal quarter for us, we saw our renewal rates go up substantially compared to previous year. We saw our new business go up substantially. So our annual contract value, which is a leading indicator of revenue, increased. So we'll see that revenue continue to roll out over the course of the next 12 months. So when I look at A&G with Web of Science under control, and we're going to continue to make improvements and invest. But I see a barrier to path from 2% where we are today to 4%. That's kind of bucket #1. Bucket #2 is Intellectual Property, which is about 30% of our total revenue. The end market is growing about 5% to 6%. We've been underperforming, again, coincidentally, by about 200 basis points, and it comes down to one product group, and that's Derwent. Derwent is our product, which is the -- I talked about how customers use us, is the upstage providers when they're searching. They have an idea they need to search to see what other relevant patents are out there. And what's happened over the -- if you go back 15 years, companies that we serve had a large internal group that did this. It was an internal service, a patent search service, and they used Derwent. Derwent has been around for decades. The underlying content is viewed as the best -- by far, the best in the industry. And you have these experts, who would drill into Derwent and know how to use it. And then over the -- then starting about 15 -- 10 to 15 years ago, that activity began to be dispersed in the organization. So if you're a product manager, instead of just calling the desk, you do some initial searches yourself. And Derwent really was designed for that. It was designed for that über, überuser. And so we lost share. We lost share, and the core group began to shrink over time. They still exist. It shrunk over time and has been dispersed and that activity that has been dispersed we lost because Derwent was just too complicated a tool to be able to address that source. So we brought in a great product leader in late summer of last year, spent his first few months doing what I love to hear him doing, speaking with the customers, 500 customers, from that, build exactly what we needed on the workflow to improve the interface. We're now investing in that interface right now. We have a clear plan. I expect to begin to rolling out some of the improvements end of this year around that. And similar to Q1, we were able to talk about a Web of Science operational turnaround. My expectation is first half of next year, we'll be doing the same with Derwent. I will say for this year, to hit our guidance for this year, we need a Web of Science turnaround. We don't need that from Derwent. We expect that to impact next year and beyond. And then finally, in -- and I will say, once we get Derwent operating up to market levels, that will lift IP up to the 5% to 6% range, which is what we need to get up to market growth rate. Finally, in Life Sciences & Healthcare, again, about 20% of our business. It actually is funny. It's the smallest part of our business. It is the fastest-growing end market, it's growing at 10%, almost an insatiable demand for high-quality information content and analytics in the drug development cycle and a hugely fragmented marketplace. There, we were -- we have a great set of assets, but we're underperforming in one subsegment of the market around the commercialization, which is the post-market access, post launch part, including Real World Data. Now RWD, Real World Data, it has been an important part of our portfolio, and so it has been growing, but it is a rocket ship in the industry. And historically, we have sold that as data. It's great. It's very important. We sell it to others, and the others build the analytics on top of that and sometimes -- cases, clients, in some cases, third party, and we are leaving value on the table. So the focus we have done there, and we have a fantastic new leader -- segment leader there, Henry Levy, who came from Veeva, is to build out a platform there that we can begin to productize on top of the platform, very similar to a model I saw at my last company. We get that one fixed, and we've lifted that segment up to 10%. So the economic model is we need A&G at 4%. We believe we're a clear path there; IP to grow in the 5% to 6% range. With the execution of Derwent underway, that's a path to get there. And then we need to get the commercialization subsegment growing close to double digit, and that will lift life science.

All right. So we get from 3 to 6 through all those different measures. Once we're kind of in that 5%, 6% range that you're targeting, what does it look like in terms of kind of flow through the bottom line or the type of margin profiles you could expect moving forward once you get to that rate?

So a couple of ways I'd look at it, Andrew. First, on the adjusted EBITDA margin, we're in low 40s right now. That has grown significantly, as you know, significantly the last couple of years as we've enjoyed synergies through cost takeout through the acquisitions that we have done. What we did say this year is for the next 3 years, the market accretion will continue but at a slower pace. So it will be -- we said roughly 150 basis points over the next 3 years at 50 basis points a year. Post that point, we haven't given guidance post that. There is not a natural ceiling at 43%, 44% for this business. I think if you look at our peer groups in this space that you cover and know so well, the ceiling is much higher than that. But we'll come back in a couple of years and say what that EBITDA growth rate looks like coming out of that. Now the second element of this, which often gets forgotten, is cash conversion. So this is a low CapEx business. We have bumped it up in the short term for a couple of years, but we expect it in 2 or 3 years to come back down to industry levels. The cash flow through should be north of 50% [ or ] 60% of EBITDA basis. So this is an extremely cash-generative business.

Absolutely. Maybe only a couple more minutes here. I do want to circle back on the Web of Science acceleration because that seems to be kind of the first proof point here for the plan working. You mentioned with Derwent that there were some market share losses, and that's something that you're trying to turn around. Is that something that happened within Web of Science? Or I believe other point is it's just not capturing maybe new customer use cases for that. Just what was the issue besides the user interface of what -- how did that manifest itself in terms of the flatter growth? Or what were the areas that were most obvious to improve?

Sure. It's a couple of areas. And we'll say, for the universities, there are different buying patterns. In some cases, they're choosing -- and we have one main competitor, Scopus, it's an Elsevier product. In some cases, they're choosing us or them. In some cases, they're choosing both. In some cases, they may have both and drop one for a while. There are budgetary pressures. And the buyer is the librarian in most cases, but the consumer are the professors and the departments. And so there is a relationship between us, the librarian, who is our main buyer, and the users as to how to continue to gain share. And there would be a couple of things that took place we saw that lower growth. First, Elsevier -- I believe Scopus had grown predominantly outside the large 400 top research universities. And there's a long tail of universities, and we had largely ceded that market to them. And the element there was the complexity of our product. It was just not a great product to use. Even though we had the right content underneath it, it wasn't the right easy way for use, particularly for different universities, professors, maybe more part time to use the product. So we had lost share there. The second thing is we had -- every quarter, we would lose a big client. In fact, what was unique about Q1, and we talked about it on the call, it was the first quarter in recorded memory that we had not lost a large client. So that stemming of a -- and large to us, we measure in hundreds of thousands of dollars would be large for us at the university level, particularly to the Web of Science contract. But all those kind of tied together, which was depressing the growth rate again to kind of flattish. The turnarounds we're doing, we think, creates a very clear path to get us back up.

Great. I think that's a good place to wrap up. Again, we'll be moving to Jenny B for the breakout for anyone interested in continuing the conversation. Thank you.

Great. Thanks, Andrew. Appreciate it.