Definitive Healthcare Corp. (DH) Earnings Call Transcript & Summary

Thanks for coming out. I hope you had a good, productive day of meetings.

It's a good day. Thank you for having us.

Fantastic. Thanks.

So Jason, big news from a couple of months back. You're ceding to the incoming CEO.

Yes.

Yes. And are we going to see you at conferences in the future or...

I think you will. You'd be lucky to see my face, not on Zoom. So yes. No, I think the areas that I'll focus a lot of time on are more strategic, get out of the day-to-day, more on M&A, product strategy, spending time with investors, making sure they understand the long-term vision of the company.

Got it. Okay. So I know that you're relatively new IPO on Wall Street. So maybe a brief overview is in order to help people level set the story of Definitive Healthcare, the key investment points and then we can jump into some of the details here.

Sure. So when I started the company 10 years ago -- I'll kind of give the overview of why Definitive Healthcare exists. And first of all, thanks for coming to this prime time that Kash gave us here.

It's the algorithms, AI.

So if you think about health care, it's a big market: $4 trillion spend every year, makes up about $1 out of every $5 that we as Americans spend. But what makes health care particularly unique for a company like Definitive Healthcare is the complexity of the industry. So there's all of these different players in the market. You have physicians, hospitals and health systems, health insurance companies that pay for it all, patients, of course, government regulators. They all want to compete and they all want something out of health care, but they all want something different. So as I was starting Definitive Healthcare, everybody I talked to said, "We want to be in this market. It's big. It's important. There's all this change happening, but we don't understand how to sell and compete within health care." So that's the business problem that we set off to solve. So what we've developed over the next 10 years is a complete view of the entire health care ecosystem. We track data and provide analytics on every single provider of health care. We understand how they're all related and affiliated together. We understand how patients are referred through the networks when they're in network, when they're out of network, the quality of care that these providers provide. And then we package this up into a SaaS solution and sell it to companies that want to compete and sell into the health care ecosystem. So if you think about our primary customers, we think there's about 100,000 companies that we could potentially sell to. We have about 3,000 today, so significant room to grow. The primary markets we sell into are life sciences, the biopharma and medical device companies that want to understand who are the physicians in the hospital is treating the patients that they care about. We sell into health care IT organizations. We sell to health care providers like hospitals and big physician groups who are looking for, "How do I generate referrals and make sure that the patients that are most attractive are coming to my facilities. And how do I keep patients in network over time?" And then we sell to this whole group of diversified companies. So these are companies that sell to many industries but understand health care is big. It's important, it's complex and you need health care-specific intelligence in order to be successful into that. So that's our market overall and who we sell into.

I always like to ask entrepreneurs what was that aha moment that led to the founding of this idea -- conceptualization of the idea and evolution to its current state.

The aha moment, so previously, before Definitive Healthcare, I started a company called Infinata in 2000. That company ended up being a database of every investigational drug globally and tracked data on every pharma and biotech company that was working on these drugs. We sold that to pharma companies for corp dev and then also CROs looking to sell into the pharma ecosystem. So I knew the data business well, and I love health care. Health care is big. It's complex. People will pay a lot of money if you have great data within health care. So I wanted to go into this market. And as I said, I was speaking to a lot of people that's in the market and nobody understood how to sell into this market. And everyone was nervous because EHR systems were taking off. There's this explosion of data. The Accountable Care Act is happening. So there are all these changes that people needed to understand, and that was the moment I said, if you can really help people understand this and help them sell with insights that they can take action on every day, there's a big opportunity there. Obviously, the company has evolved a lot since I originally started, but that was really the thesis.

Congratulations.

Yes. Great. Maybe just taking turns, going back and forth. Rick, maybe a brief encapsulation of the financial model. Many of the aspects of the financial model are fairly intuitive. But maybe dwell upon some of the things that are unique to Definitive Healthcare as far as financial model is concerned?

Yes. Jason has alluded to the tremendous market opportunity in front of us. And of course, it's important that, that tremendous market opportunity be tied to a strong business model. We drive near 90% gross margins. So the business is served very efficiently through our SaaS-based platform. Our customer acquisition costs result in around a 10x LTV to CAC. Our innovation flywheel is very efficient. And so we've been able to drive roughly 30% adjusted EBITDA margins as a public company with a long-term path towards the low to mid-40s. And we combine that with unlevered free cash flow that is roughly equal to and at times greater than our adjusted EBITDA.

Rick, I didn't plan to ask this, but how did you end up in the career track of a CFO? Are you always a numbers person at business school? Or what was your career path?

Always analytical, but I've spent time in -- on the commercial side doing strategy work and customer growth strategy as well as on the financial side. And I'm really attracted to companies like Definitive that have a clearly defined business model aimed at a large growth opportunity, in particular, because for the business to grow, we need to have strong KPIs that allow us to continue to push decisions down. So it's really almost uniquely scalable, and that's one of the really fun things about this model.

Got it. Jason, one of the things that is always a puzzle to buy side is -- and it's not just specific to Definitive, but also to ZoomInfo. We had Henry from ZoomInfo yesterday -- how do you get this data? Is this legit? And what do you do to this data to make it usable, that sort of thing? And when you look at the data that Definitive obtains, it's super valuable. Obviously, that's the key tenet of the value proposition. Can you touch upon where you get this data and how do you process the data and how that technology has changed over time? And how sustainable is this competitive advantage that you have with the data set that you collect?

Sure. I'll go in reverse order. What we've built is highly proprietary and takes many years to recreate, and that's very important. The time element of what we've created over time, how we built on it and iterated and created a solution that just doesn't exist anywhere in the world anymore historically is really important. But if you go back to where we got it from, for the first 10 years of our development until 2019, we didn't buy any third-party data. Everything that we built and collected was done on our own proprietarily through hard work, very smart algorithms and a lot of data science. So the key areas that we get data are, first of all, we get information we gather from about a few hundred thousand different websites. We've built technology to help us gather this data and pull it in every day. We complement that with we make about 700,000 phone calls every single year to get data we can't find anywhere else, confirm data and continue to build out the data set.

700,000...

700,000 phone calls.

A day?

No, a year. That will be a lot.

Got it. So how does that work? I mean that's like mind-boggling scale. So do you call somebody and verify...

So the way that it works, there's a lot of data science behind it, actually. So these are very -- every one of those calls, I think of as super valuable. So how do you make those calls extremely effective? We have algorithms that run every night that tell our callers exactly who to call and what to call for, and that's based on how likely we think it is that data will change essentially. So we don't want to waste a phone call ever. So how valuable is the data, how likely is it that you're going to get an answer that is different than what we have today. So not only do we make that many calls, each one of those calls is infinitely more valuable than just picking up the phone and calling. So we make the phone calls and then we get data from about 20,000 government sources as well. So states and municipalities track data. Centers for Medicare and Medicaid tracks a lot of data. So we pull this all together and what's really important is the data science that does really 3 things. It cleanses the data. So this data comes all in. It's messy. It's different formats. It conflicts often. So we need to determine through data science which data trumps. Second is it links it all together. So we figure out how does this data all come together so that we can start to build a profile of these providers that we track. Third thing that it does is we generate and create new data that doesn't exist anywhere else. So we create new insights that our clients can use to go make decisions on how they want to act and behave every day. I'll give you 2 examples of that. The first is a telemedicine propensity score. When COVID hit a couple of years ago, telemedicine blew up 15,000%, 15,000% between March and May of 2020. All of our clients are saying, "This changes the model. We need to understand..."

[ A lot of sick ] people.

Yes. "We need to understand who is adopting it quickly and who's likely to." So our data science team created with data we already had this telemedicine propensity score that in a single variable can help our clients figure this out. This year, we're rolling out something called Rx decision insight. And what this does is it helps our clients understand not who's prescribing the most of a particular drug but who's actually making the decision of that drug in the first place. And what this allows us to do is our pharmaceutical clients can now say, "I know the number of prescriptions that you all have written in the year, but I want to know who actually drives that decision. And some of you guys just maintain and refill and write those. So if I know who are the most influential prescribers, that's where I want to spend my time." And in a world where access to physicians is going down, making sure that every time that you're spending time with a physician it's the most valuable is becoming even more and more important. So that's the type of things that we do with our data.

Yes. [ Jacob ] and my team says, "Kash, your questions are not that good..."

No, no, no. Not at all, not at all.

Touching more on the financial aspect of things and the second quarter results. I think some investors were a little surprised we saw a sequential decline in leading indicators, I believe: RPO, cRPO. Given health care is typically viewed through the lens of being more resilient in economic downturns coupled with top line performance seen during COVID, right, up 38% that year, and tangential -- kind of I mentioned tangential competitors posting a sequential increase, can you provide more color on what specific verticals led to those declines in those leading indicators and kind of the view you're taking around that for the rest of the year?

Yes. So step one, I would point out that cRPO is a great leading indicator. And it has an element of seasonality because we tend to have more renewals at the end of the year, which results in at the beginning of the year, you've got a full year's cRPO. By the time you get to second quarter, you have only half a year left. So there's an element of seasonality in that. But nonetheless, when we normalize for that, we found that we're seeing the same thing that almost all software companies are seeing, which is heightened scrutiny on the pace of deals going through the pipeline. So clients are interested in the solution. The demand is there, but they've got to jump more hoops to get the final signature on the contract. As a result of that, when we did the deep analysis, I think what you were getting at is we came up about 3 million below where we would have normally expected to be at midyear. So it's not a ton, but it's notable enough that we wanted to call it out in the call. And then you can think through what that would mean if that trend were to continue for the rest of the year in terms of 2023 and other. We have high confidence. We sell to the top line. Everything we do is growth oriented, and you can draw a straight line from that to ROI. So we think these deals will be signed, albeit at a slower pace. And interestingly, we got a ton of questions on our call. But then you've heard a number of other health care software IT companies expressing similar things.

Okay. And I think that's a great segue actually into a more competitive environment, right? Jason just mentioned how a big differentiator is the variety and the quantity of data that you have. But I'm sure there is competition, nonetheless. So can you touch on who Definitive pays attention to? Is there any real threat of someone else coming in and displacing or providing headwinds to landing deals?

Part of what makes this opportunity so compelling is that the way that people try to solve these problems today is really difficult with the existing solution. So you think about an IQVIA, a Clarivate, a DRG. These companies, they've built their view of the world from claims, which it's readily available, third-party claims information, but it's incomplete. When we mapped claims information onto our universe, [ it's ] missing the 45% of the facilities and decision-makers that we track. So it's an incomplete view of the world. And because they're not SaaS natives, they haven't built this up into a SaaS platform which allows you to interoperate, their business model revolves around a combination of providing static data and professional services. So you ask IQVIA a specific question, they send you specific data. Their data scientists will work with it to help you answer your specific question. And if that then generates another question that's suddenly different, you start over again. You contrast that and part of the magic of demoing our platform is in our platform, you go in, you frame your question, you set your variables and then you can iterate on it in real time. So it's faster. It's more accurate. It's less expensive. And so that's really the compelling opportunity. So you've got a set of legacy players like IQVIA, Clarivate, DRG who are competing for the same dollars with their legacy solutions. What we often find is we can coexist with them. So for some things you already have a clearly defined question, you want to use their data set for a particular example, like sales force compensation. It's -- if you're a pharma sales force compensation, they are going to use IQVIA. They're basically locked in because they've got some specific retail pharmacy stuff. So that's a perfect application for it. But people marry that with our unique data and our affiliations in order to work with it.

So I want to -- is that the same question you want to do a follow-up? Okay. Go ahead.

So do you see sitting next to these competitors essentially as headwinds to landing bigger deal sizes with those competitors -- or sorry, with those clients?

No, not at all, not at all. What we provide is fundamentally different. Only we have the proprietary affiliation data and the analytics that you can work with in real time. So if they want to keep using that narrow pharmaceutical sales rep compensation data source from IQVIA, have at it. Most of these customers will have multiple data sources.

And if you look at the trend of our customer base, so just thinking about the larger clients in particular, a couple of years ago, we had no million-dollar clients. Now we've got in the teens, and that's really because we're solving new problems in new unique ways than the existing competitors. So sometimes, we will offer the entire solution on like a mid-stage biotech company. But with large pharma, they have many needs across many therapeutic areas. We're changing the market. So we are solving problems in new ways that are faster and better than anything else.

Jason, I wanted to get your perspective on the role of acquisitions. The depressed valuations, are they causing you to take a more aggressive look at potential opportunities? And also, I wanted to get your perspective on how Analytical Wizards, right, that's more recent relative to Monocl. How is that progressing? And do you see more opportunities for continued distribution leverage, better adoption as the product matures under your distribution?

So Analytical Wizards is a company we bought in February of this year. As we think about acquisitions, we look for 2 key things. Extremely disciplined approach. We want to bring a new capability that we did not have before that we can sell to existing clients or existing commercial team. And then we also want to be able to improve that product by pushing our data, leveraging our data in a new way to make that product better. Analytical Wizards nails both of these. So what Analytical Wizards provides is a technology platform that allows clients within life sciences to do very, very sophisticated commercial analytics, essentially, extremely quickly. It allows them to also pull in data from any source that they want. So the new capability that we got is a whole new set of commercial analytics that we can provide, and now we can combine -- our clients can combine our data with their internal data, third-party data. So a whole new capability set that allows us to get into these bigger clients and grow these relationships far more. So really excited about what we're doing with Analytical Wizards. We actually just launched a product called Passport Express, which takes our data, puts it in the Analytical Wizards' platform and allows brand managers to do really powerful brand analytics right out of the box. The stuff that took 3 to 4 to 5 months before if you work with other companies, you can now essentially turn on immediately with us. So really exciting. In terms of mergers and acquisitions, we want to do 1 to 2 per year. But we're super disciplined. If we want -- if we find 3, we can do 3. If we don't find any in the year, we're okay with that as well. So it must meet those key needs. There's a lot of great companies that we're looking at, focused mostly in life sciences and health care provider end markets. Valuations, I guess I don't have enough data points to say that private's caught up. We're starting to see a little bit, but I think there's room to go still in terms of valuations. But our goal is we find a good strategic fit, typically a tuck-in size, if it's a good company, we'll buy it and grow it over time.

Recently, there was a new sales motion announced, a couple of months ago if I'm not mistaken. Can you kind of touch on how the new sales motion differs from the old and how it plays into what Definitive's near- to medium-term goals maybe from like a top line perspective or anything around that?

Yes, I'm not sure what you were trying to...

Are you thinking of verticalization or...

Yes, the verticalization of...

Okay...

So that's a continuing evolution. Yes. So the way in which we go to market, you can think about our solution as encompassing a shared data set and shared algorithms but surfaced to the customer in ways that match their key concerns. So our sales force is organized to match those key customer concerns across the 4 vertical customer groups that Jason has talked about. You've got life sciences, which encompasses biotechnology as well -- bio and pharma as well as med device. You've got health care IT, you've got providers and then you have our diversified group. All great market opportunities, all growing well. But you've got the sales force, which is a marketing-fed, inside sales force supported by account executives and customer success managers so that the experience of doing business with us is very intimate. The team that's dealing with the provider is very fluent in the issues, concerns and analytical needs of providers, which are subtly different from those of life sciences customers. So that's how we're organized from a sales motion perspective.

We've been on a journey that we verticalized our hunters about 3 years ago. Another year later, it worked so well we verticalized all our account managers, our customer success. Increasingly, we're building front-end workflow on top of our data that is really geared towards those end markets. Analytical Wizards is geared towards life sciences. We'll be rolling out a provider product next year that uses the same data in slightly different ways so that if you are in network development at providers, you turn this on and meet exactly the workflow that you want to think about. And that will allow us to increase logo penetration, right, increase our pricing within those logos as well. So that evolution continues within the company. That verticalization is really important to us.

Jason, I'm curious, what kind of data integration technologies do you use internally to harmonize the data that you're collecting and have it built into metadata models so it can be commonly leveraged across your multiple verticals?

You're assuming I'm smarter than I am, Kash. No, our data science team uses stuff that you would typically think about, like R, Python and things like that are the primary used...

[indiscernible] Those are pretty technical terms.

I can't code it, but I can talk about it.

That's all right. I can't either. I tried coding. I'm a mechanical engineer. I think you guys must have heard -- you must have heard many times that I'd like to code in the [ forefront ]. It did not work. No, not because I didn't know my logic, but because instead of the -- the syntax is in the wrong place, the colons and semicolons. And I said, "I will have nothing to do with software and hardware."

It's frustrating.

But I'm going to get back at it by being a financial guy. Anyway. So with the vertical approach, it's actually a subvertical, vertical upon vertical approach, right?

Yes. Correct. Yes.

You talk about 100,000 potential customers and you have a relatively small share of that market. Does subverticalizing increase the penetration potential? If so, what are you looking for? What are your targets with the subverticalization?

Yes, it's a couple of things. So it allows the people that are focused on those markets to really get into what are the business problems and speak that language. So that's the most important part of what we're trying to accomplish because as we've got more sophisticated, how the clients use the data has diverged more than it did at the beginning where people could just sell into everything. So there's a real advantage to creating subverticals within that. Also, just the way that we bring in clients is a little bit different. So life sciences, bigger clients, more sophisticated needs. They use almost all of our products. You think about like diversified, the needs are a bit more narrow. It's more of a volume game. How do we bring in the next 500, 700 IT clients or diversified clients? So all of that benefits from more folks in the subverticals.

And where are you hiring domain experts? Is it from your target customers yourself that they can go speak the language back and put a software wrapper around the business need?

Yes. So we get -- it varies. We get from lots of different places, but we do hire people directly from industry. So if somebody's been doing commercial analytics at a med device company, for example, we hired somebody similar to that recently. So yes, people that have walked the walk before are ideal.

Not something that I plan to ask, but I'm just curious, what are the good attributes of a successful salesperson that you look to hire and how tight or not tight is the hiring market in New England?

Yes, so the attributes, we don't always need to hire somebody with deep domain expertise within life sciences or providers. It's an advantage when they have that. But our product is highly demo-able. So you can actually show somebody what you're going to get, and our clients quickly understand that's valuable. "I understand how we'd use that day-to-day." So that allows us to -- we still need great people, but we can train them up and we can teach them how to do that versus someone like consulting where that deep subject matter expertise is absolutely essential. The market is tight for salespeople, for sure. I think we're starting to see a little bit of loosening. Lots of companies are starting to announce layoffs, and things like that, has slowed down hiring, particularly companies that haven't made any money. So we're seeing...

One in San Francisco just announced an 11% layoff.

Oh, no kidding? Yes.

[ Exactly ].

So we're seeing it, but it's been tight for the last 1.5 years, for sure.

So on the topic of sales, can we touch on Definitive's approach to using partnerships and if that is something you currently do? Is this something you're looking at? And we'll go from there.

Yes. We are very much a direct sales model, so we don't have much in the way of channel partnerships today. Within life sciences, we build our relationships with companies like ZS and Bain and companies like that, that are working with life sciences companies more from an aspect of we want them to be aware of our data and how to use it and the quality so that when their clients are asking for recommendations, they know to talk about us. But it's all informal relationship building.

Okay. And is it more a direct selling motion because of -- like what is the reasoning for being more direct as opposed to branching out and using partnerships on a more broad basis?

Yes, I think we've determined that we know our product better than everyone else, and we're doing something that is relatively new. So we want to control that sales process as much as possible. We have in the past about a 10x LTV to CAC. So it's a very efficient way for us to go to market as well. So we get to control the end product. We have the efficiency to do it. So it makes the most sense for us.

I'll repeat it. If the LTV to CAC is 10x, why would you not invest more marketing dollars and grow the top line even faster?

It's a great observation, and we actually -- so year-over-year, we grew our sales and marketing 49%. So we're investing, but we're investing in a very measured way. Operationally, you need to make sure that you're finding and attracting the right people, you're getting them onboarded, that you're not overloading them with too many products, et cetera, et cetera. So we've been really pleased to maintain our sales motion in the midst of getting even more focused through the verticalization. And I think we'll continue -- as long as we have such a high LTV to CAC, we'll continue investing in a measured fashion. At the same time, we value profitability as well as growth. We view profit and cash flow efficiency as competitive weapons that enable us to continue to fuel our growth. It's funny. Just 12 months ago when we were going through the IPO process, all of the questions would have been about investing more to grow even faster. And our answer then was we value growth and profitability and here's how we think about it. And now we get a lot of questions about margin expansion, and our answer is we value growth and profitability and here's how we think about it.

It's a balanced model. I mean, as you know, you cannot please everybody all the time. Yes, please go ahead.

Could you just talk about the long-term relationship that you have with your partners? What percentage of -- sorry, with your customers. What percentage of your contracts are long term in nature, what pricing is like, et cetera?

Sure. So to give a few stats that I think would be interesting on this, first of all, not a single customer makes up more than 2% of our revenue, just to give a sense of sort of the diversity of our revenue base. As of the time of IPO, about 61% of our -- which is a year ago, 61% of our contracts were in multiyear deals, 2- to 3-year deals. All of our contracts are at least 1 year. Some get into sort of 4 and 5. Of those multiyear contracts, the vast majority of them have pricing escalators contractually built in that are kind of, I think, mid- to high single digits per annum automatically built into those.

And when did you start the motion focused on multiyear? Is that something like a day 1 exercise that you had?

Not day 1, but not a year ago either. So we've been at it.

Yes, maybe on the customer side, some use cases would be helpful just to talk about the ROI customers achieve, how they're using it, how they're getting benefit. That would be helpful.

[indiscernible]

Sure. Yes. So a classic example would be a couple of folks in my family have had knee replacements over the last few years, so I'm focused on knees.

My family, too.

There you go. So say you're a medical device manufacturer and you have a device or service that improves the readmission, that improves the outcomes for knee replacement surgery. Well, great idea. Early on in the product cycle, you've got to size what that market looks like. So you can use our application to go in and identify how many knee replacements occur in the U.S., what levels of reimbursement are for that, et cetera. So it's good for market sizing, but market sizing isn't very actionable. So then you've got to identify who are the physicians that are driving that volume. You can attack that from a couple of different ways. You can say who are the thought leaders from a KOL perspective, a key opinion leader perspective, who's publishing the interesting papers using our Monocl product, or you can cut straight to assuming that you've already developed your device and you want to commercialize. You can cut straight to who's performing that procedures, who's doing knee replacements all day, every day, high-volume activity. Now you're getting closer to some actionable intelligence, but you're not quite there yet because if there's 5 different physicians practicing, doing knee replacements in any given facility, it's not likely that each of them is choosing on their own what they want to use. There's probably a Chief Medical Officer within that medical system who's driving that decision in order to get on the approved list. And there may be a GPO, which is also involved in the system. So we help you navigate that. So now you know who you need to talk to, but you've got to earn that meeting. So using our platform, you can analyze the set of doctors that are within the purview of that Chief Medical Officer, for example, and you can say, "We know that you do this many knee replacements at this much revenue and oh, by the way, you're missing out on about $2 million of Medicare reimbursement due to excess readmission rates." What you may not know is that peer hospitals that use our solution have readmission rates that are 1/2 yours. And so that $3 million, you could realize a $1.5 million benefit. And I'd like to take 15 minutes of your time to show you the solution and illustrate how it could play out within your specific hospital. So that's how deep we go in terms of mapping this incredibly complex universe. And that's why people sometimes ask us about like, well, why doesn't ZoomInfo just do that? ZoomInfo is obsessed with the massive horizontal opportunity around executive contact information and the technology stack that exists on a global basis. So they even say that anyone who's seriously interested in health care is probably going to be using us. And that's great. It's 20% of the economy. And so a company of any size that has growth aspirations needs to have some folks that are focused on health care. And then you've got to identify the decision maker, earn the meeting and then leave the meeting with a tangible next step. So that's one example of how we do it.

Jason, are you sure Rick is not the Head of Sales?

That's pretty good, right?

[indiscernible] as your CFO. The contextual selling that you just walked through, that's where software is going after, right? Because spraying and praying with e-mail marketing, that's one-way ticket to the spam folder. What you just walked through, that's contextual selling that -- your win rates and close rates have to be really high after you go through all this stuff, right? The physician must be like, "Oh, you nailed it. Where have you been all these days?" Sorry, go ahead with your question.

Can we double-click on the comments you've made that it takes years to build the database? And asking this question in the context of leaps of progress that has been achieved in the data science in the past 5 years. It's anything from like web scraping up to maybe even some heavy end of the data science, like machine learning and NLP capabilities. And I think the question is, I'll be more precise, what is it that it's so defendable?

Yes. I think it's a couple of things. First of all, there's great technology. But in order to make technology work, you really need sort of that subject matter expertise and a real -- a true understanding of the data, and that builds up over time. So what you can do -- what we could do in year 3, we could only do it because of data we collected and analyzed in year 2 and year 1, so on and so forth. So that is -- it's very difficult to do. It's iteration. It's working with customers to understand the nuances of what data is missing and how we might use other data as a proxy. Technology does not figure that out for you. Humans figure that out through iteration and working with the customers to understand these very specific nuances. The other thing that we have is we have the historical data that no one else has. Something super powerful that we provide to clients is, as an example, historical affiliations. So our clients want to understand how physician affiliations change over time. So who's moving or bouncing around, who's loyal, all that type of information. And we have all of that data because we've been tracking that for 10 years. Incredibly powerful, very, very difficult to recreate. Again, it takes time to do all those things.

We've got exactly a minute, half a minute.

Can you talk a little bit about the competitive landscape, especially from the lens of patient to provider to -- sorry, patient to provider to payer and then beyond, right? And who are you sort of competing with what feature set? Because I mean, there's a lot of private companies as well, Komodo and a bunch of them, who are in different pieces of what you do: population health, et cetera. So if you can just maybe talk about from that point of view?

Sure. So within the life sciences market, we primarily compete with IQVIA, Symphony and Clarivate. A little bit with Komodo, although they're much more on sort of clinical analytics and we're more commercial analytics. So that's primarily them. As Rick talked about before, the key difference is the proprietary data that we built, you can't recreate through claims data, which is their approach. So we always have something they don't have, which is really important. On the diversified and health care IT companies, we compete more with ZoomInfo. Generally speaking, if a company is serious about health care in any way, they will either buy our product or they will buy our product and ZoomInfo if they sell to other industries as well. So take a bank. A bank isn't only going to buy Definitive Healthcare, but their health care group will buy Definitive Healthcare. The bank will buy ZoomInfo for their energy practice or automotive, so on and so forth.

[indiscernible]

No, we get some data from EHR, some data exhaust, but we don't intend to be in the EHR business.

We wrap it up here. Do you have a question? No. I see somebody that I used to work with like 25 years back [indiscernible]. We used to be colleagues [indiscernible].

Why are you [indiscernible]

Yes, I've been doing this for a long time. So it's -- I've been at this for 12 years, been building data businesses for 25. This allows me to, frankly, get out -- personally get out of the day-to-day and focus more on areas that I'm super passionate about. So I want to remain super involved with Definitive, help drive the 10-year strategy, help with M&A, help with product stuff, but just do less of the day-to-day.

[indiscernible]

There is not such a thing per se. But I think overall, we're transforming data and analytics into insight for health care. Lot of opportunity to continue to grow in that. Financially, it's all about sustainable long-term profitable growth.

Yes. [indiscernible] Thank you. Thank you very much. I think we'll wrap it up here. Thank you for your time.

Yes. You got it. Thank you, Kash. Appreciate it.

We really appreciate you coming out to join us.

Good to see you. Good to meet you in person.