Titans of Data: Leveraging Alternative Data to Enhance the Investment Process with Carrie Lazorchak, Chief Revenue Officer, Similarweb. Rodney Pedersen, Chief Revenue Officer, Visible Alpha. Matt Ober, Managing Director & Chief Data Scientist, Third Point.
Moderated by Tim Harrington, President, BattleFin.
SPEAKERS
Carrie Lazorchak
Chief Revenue Officer
Similarweb
Rodney Pedersen
Chief Revenue Officer
Visible Alpha
Matt Ober
Managing Director & Chief Data Scientist
Third Point
MODERATOR
Tim Harrington
Co-Founder & Chief Executive Officer
BattleFin
TIMESTAMPS
EPISODE TRANSCRIPT
Tim Harrington: (00:06)
Thank you, Rachel and thank you to the SALT team. It's nice to actually be back in person and interacting with people, not having to worry about whether you're on viewed, whether you you've got pants on. So this is live we're all back in person. We have an exciting topic. It's alternative data. I'm Tim Harrington, CEO of BattleFin. Our mission has always been to help source evaluate test and find datasets for the financial and corporate community. We're really excited. SkyBridge is a new investor in BattleFin. So really excited to be working with Anthony, John, Joe, the whole team, and really excited to be sharing alternative data with the audience. So why don't we get started? We'll do a couple of quick intros, try to make it as informative as possible. So Carrie, tell us a little about yourself and SimilarWeb.
Carrie Lazorchak: (01:03)
Okay, great. First of all, I'm very excited to be here. As Tim said, it's nice to be able to interact with people again, I didn't realize how exhausting it is though, I will say, forgot about that. But just as by way of introduction, my name is Carrie Lazorchak and I'm the chief revenue officer of a company called SimilarWeb. First of all, to our clients in the audience, I want to say thank you very much for your business. And for those of you that aren't familiar with SimilarWeb, our mission is pretty simple. We want to help companies win in their market. And the way that we do that is we measure the digital world. We look at the trends across both consumer trends and business trends, across millions of digital properties globally. And we provide that insight and information back to our customers through a very easy to use platform and visualization.
Carrie Lazorchak: (01:56)
Now, Tim was very clear that the big thing people want to know is how and where and what kind of data, et cetera, which obviously some of that's the secret sauce, but I'll try to break it down into a little bit of the art and a little bit of the science. The sciences is, we have a lot of data. We're processing about 10 billion digital signals a day, about two terabytes of data daily that we analyzed. But the art of it is really in how we blend all of the data sources. And those sources are a combination of direct analytics data and anonymize traffic data, partnerships that we have in public data. And we combine that all together with machine learning and unique algorithms, and then deliver that to our clients. Like I said, through a very easy to use visualization platform. And I think that's a key thing we'll talk a little bit about today.
Carrie Lazorchak: (02:49)
There's a lot of data out there. I think the key for this audience is to really understand how to consume that data and how to use that data towards all of your objectives. So really excited to be here and look forward to being part of this panel.
Tim Harrington: (03:02)
Great. And SimilarWeb went public recently, so congratulations.
Carrie Lazorchak: (03:05)
Yeah, thank you. Thank you very much.
Tim Harrington: (03:07)
I've been following you guys for years. I know you've had some of the best Netflix calls I've ever seen [crosstalk 00:03:1] growth. For those of you that follow Netflix, huge subscriber growth story started to fade. You guys called it then international took off, called it again. So kudos on that. Really awesome data set for you guys and the audience to check out. Rodney, tell us a little bit about Visible Alpha.
Rodney Pedersen: (03:35)
Yeah. Thank you, Tim. So Rodney Pedersen, chief revenue officer with Visible Alpha. Visible Alpha came to the market about five years ago to address a pretty significant gap that we saw being consensus estimates, or forecast data for publicly traded companies. All of you have seen this play out, if you've ever read the wall street journal. Company expectations were always made available at a high level, so sales or EPS and never at a granular level, but the investment debate and the investment thesis is always about more granular issues with companies and the sell side analysts that contributed to those revenue and earnings forecasts have always modeled companies at a greater degree of depth. It was just never information that was made available at scale.
Rodney Pedersen: (04:22)
So Visible Alpha came to the market to expose that content and bring value to that content in ways that hadn't been done before. So we source data from full working Excel models, from the sell side. We extract all of the data from those models and align it into a common structure for a publicly traded company. We to process a lot of data, I think on a trailing three month basis, we process about 90,000 models, from the south side it's about 6,000 contributing sell side analysts and ultimately give the buy-side the most comprehensive picture into the market forecasts for any key issue on a company.
Tim Harrington: (04:59)
Great. And I've read a bunch of your work. I think you had an airline piece out recently. I had no idea how many KPIs are actually in the airline industry, key performance indicators. But, if you follow the airlines, check out that report, pretty awesome. And a man who needs no introduction, but we'll let you give one ,Matt over to you.
Matt Ober: (05:20)
Thank you. I'm Matt Ober, I'm the chief data scientist at Third Point. We're about a $20 billion asset manager investing across equity, structured credit and venture investments. And our team looks to take data and technology to provide insights into the different investments we make.
Tim Harrington: (05:39)
Great. And Matt and I actually met years and years ago when he was at WorldQuant, was one of the first people to attend some of the battlefield events in Miami. So it's great to be back on stage with you after whatever, five or seven years. But let's dig right in. I think the space has seen a tremendous amount of growth, email receipt data, geolocation, satellite imagery. Rodney, from your perspective, what's been the real growth driver, what have you guys been seeing from that space?
Rodney Pedersen: (06:11)
I think it starts with a fact which is that the buy-side has to have a differentiated view to outperform and they have to do that on a sustained basis. If anybody sat in on the hedge fund comeback panel yesterday with Steve Cohen and Dmitry Balyasny, that was a key theme that came out of it. And I think that the expansion of data that's been made available in the marketplace over the last 10 years, which Visible Alpha certainly been a part of, has made it possible for the investment manager to get much more specific and much more granular and how they come up with an investment thesis, how they challenged the thesis and ultimately how they monitor that thesis in real time. And I think those that have done the best job at embracing the state of that's come to market have really put themselves in a position to use data in a way that will allow them to outperform. It's been fun to be a part of.
Tim Harrington: (07:07)
And Matt does that jive, are you guys hearing a lot of pull from analysts? Are you guys seeing that from the analyst perspective of I need more data, I need more answers or how does it play out from a buy-side perspective?
Matt Ober: (07:20)
Yeah, I think from our standpoint, all of this data just allows us to go deeper into our research on individual companies. And I think we're able to extract more insights. We have a really strong team. And I think at this point it's becoming part of the playbook that you have to take advantage of working with these great companies and figuring out how to leverage that across all the different investments we make, whether it's earlier in the private stage before they go public or further along. And I think just being able to distill insights from these large data sets is really the difficult part of the investment process. But it's where we find the true value.
Tim Harrington: (07:59)
And Carrie, we had talked a little bit about this. Do you guys feel a lot of pull for this real-time data? Especially given the COVID environment where we're coming out of, is there a really a pull from the buy-side and corporates to now, now, now?
Carrie Lazorchak: (08:14)
Yeah. I think to answer that direct question, the answer is, yes. It's definitely one of the main value propositions of our solution today and whether you want to understand right now at this moment, what are the major keywords that consumers are looking forward to understand where they're going, or you want to observe and understand what are the major purchase decisions that people are making on Amazon marketplace right now, at this minute, we definitely see that as a trend.
Carrie Lazorchak: (08:43)
I'm curious for this audience maybe by a show of hands, how many of you use alternative data today? Yeah. Okay. All right. Yeah. Okay. So my first, I think vis-a-vis back when we started talking about this whole panel on alternative data is, to me alternative data is a very weird name for this space, because I think as these guys just said, it's more necessity data and really what it comes down to now, it's like, how do you use that data? How do you consume all this real-time information? But definitely the acceleration of digital transformation is making the need for understanding of what's happening right now at this moment more important.
Tim Harrington: (09:24)
Yeah. And maybe to Rodney, as a recovering portfolio manager, you mentioned Steve, like I worked at SAC and I remember earning season being one of the most intense things, because you had your models, you were waiting for things to come out, you were kind of you're right or wrong in that instance. And I always thought about consensus was our bogey, so if our model is a lot higher then we'd figure out what the delta is, put a multiple on it and position size it. Trying to think about how to navigate through COVID, I can't even imagine the disparity of analysts. Like what, what did you guys see from the Visible Alpha side? You know, aggregating all of these data sets, these different estimates and where are we now?
Rodney Pedersen: (10:19)
Yeah. It's a great question. It's been really interesting to watch the data as we've gone through COVID. And with forecast data, you're respective of the issue that you're looking at. What you usually see is well ahead of the reporting period, estimates are relatively wide. And then as you approach the reporting period and companies release more information spreads narrow, and there's less uncertainty in the marketplace. But as you look across sectors 18 to 20 months into this environment, there's a lot of uncertainty that we see in forecast data. You mentioned airlines earlier. We were actually looking at airlines travel and leisure companies in the US a couple of weeks ago. And we were comparing dispersion and estimates today, versus what the dispersion estimates look like pre COVID. And today estimates are actually three and a half times wider. There's three and a half times more dispersion and estimates in September of 2021 than there was for a similar forecast horizon pre COVID. So I'm not telling anybody, probably something that you don't intuitively know, which is we're in a more uncertain world, but understanding the magnitude of that uncertainty has been an interesting.
Tim Harrington: (11:29)
And Matt, does that help your analyst, hurt your analysts? What do you guys feel when you see this dispersion of analyst estimates?
Matt Ober: (11:38)
I think volatility presents opportunity. And when there's unknowns, it allows us to have a differentiated view and having all of this information allows our team to do a deeper dive, better understand the company, the KPIs, and really understand what is it that we're seeing in real time? And I think that's become a big trend. Especially during COVID was all the digital transformation we're seeing across all companies and every sector, having information at our fingertips, understanding what's happening when we're all at home, it's beyond important.
Tim Harrington: (12:13)
And Carrie following up on that disparity opportunity. Do you guys tend to get more calls or more interest when things are all over the place, and then you can add value a lot more in those situations? Or what do you think on the disparity like this happening? Does that play well for you guys?
Carrie Lazorchak: (12:34)
I'd say the message we hear is twofold. Both from the companies and from this audience, historical data is not as relevant anymore. So a lot of times people are just studying it to the side and seeing whatever used to be the trend, just assume it's not going to be the trend and start with fresh new data. So we're seeing a lot of people come to us, come to the platform, not spend as much time on the historical data, but really trying to understand what are the more recent trends and then try quarterly those trends to how that may look in the future. So we're definitely seeing that both from companies trying to build strategies and from this audience who are really trying to track performance and understand what's happening.
Tim Harrington: (13:18)
Great. And on some of the calls prior to this, we discussed a couple names just because it's obviously a financial community here. The one that we wanted to take a look at first was Peloton, just giving, so much going on in that name. Rodney, set the stage for us, give us the view on Peloton and what's happening here.
Rodney Pedersen: (13:40)
Yeah. Well, just to the conversation earlier, I think the first question is about revenue, but it's really about much more granular issues. And so we see analysts grappling with a few different issues with Peloton. One is new unit deliveries, which is something that we track invisible office. So how many people are going to buy bikes and treadmills that didn't already purchase them. And there's actually a pretty wide dispersion of estimates for the coming quarters when you look at that. And I think this quarter will be the first quarter where we see results on the lower cost products that Peloton has put out in the marketplace. So pretty big spread in estimates there, a lot of uncertainty. And another key question that we see in the models is churn in their subscription business. So as people contemplate going back to gyms and maybe working out less at home and more at the gym, there's a decent amount of uncertainty on how much churn Peloton is going to see in the quarters to come on their subscription model.
Tim Harrington: (14:37)
And Matt, how do you guys key in on that? Is that, I don't even know if Peloton is a name that you guys look at fairly frequently, but is it also just trying to pick up trends within that space or will you dive right down into the single stock name?
Matt Ober: (14:54)
Yeah, I think for us, we think about even in the fitness industry in general. With Peloton being that first mover in the digital transformation, how are they getting their bikes? What does that supply chain look like? How does the data at the ports look? And then really, how does that look for all the gyms across the country? Not only the large chains, but some of the boutiques. So we think about that as a way to gauge how people are thinking about COVID. And it has a larger impact on just macro trends. So I think we see even individual companies as ways to look at a broader sectors that may not be specifically related, but it helps us just map out our thought process.
Tim Harrington: (15:36)
Great. And Carrie, over to you. What's the data going to tell us here?
Carrie Lazorchak: (15:41)
Well, first of all, I find this a very biased area because I'm a huge Peloton user. So I don't know about you, but when you're tracking investments for the companies you like, you want to root for them. So I'm rooting for Peloton, for sure. I think the one area of our data that's interesting right now is we can see, one of the things that they've been trying to do is really expand the market share, expand the audience of people that can have access to their services and their products. And they introduced this, buy now, pay later model, which is something that's new. It's definitely a new set of data that you have to look at because now you're not getting that immediate view of exactly the people that have purchased the equipment, but the people that are purchasing the equipment and being able to track that, I think that's going to be an interesting insight that we see, we do see positive trends around that as a new consumer opportunity in the new expansion of their market capabilities
Tim Harrington: (16:38)
Yeah. I think this is also why alternative data is so important because you're able to look at what SimilarWeb's saying, you're able to look at how maybe the brand is trending. You're able to see anything from geolocation, are people returning back to those gyms, are they doing different things? Just as we've talked about earlier, being able to combine some of these data sets and get a full picture and leverage the Visible Alpha detail is just so important going forward.
Rodney Pedersen: (17:10)
Yeah. And Tim, I think that also highlights a significant shift from where we were 10 to 15 years ago with data just in the intelligence that you can get intro period as to what's happening with the business. And I don't think that's just limited to people that are trading in the shorter term. Anybody that's looking for insight into a business, you can get a lot of really interesting signals of what's happening in real time. We actually see with our models data, 40% of all the models that we process come from the south side outside of earnings. So if you think about, we process 90,000 models on a trailing three months basis, 40% of every data point that we process is not around earnings. That's a lot of information flow that's happening in real time. Yeah.
Tim Harrington: (17:55)
And let's turn to Zoom. This is obviously one that everyone has probably lived through the past 18 months. We've seen probably one of the greatest success stories of a right time, right place type of company. Rodney was this from zero to a hundred? And set the stage for us with zoom. And then let's talk through it from a data perspective.
Rodney Pedersen: (18:21)
Yeah. The debate that we see in the models on Zoom is your classic software debate, which is what will their new client acquisition look like going forward? How many new customers can they attract that didn't already come onto the Zoom platform? The second question, which is probably more significant for the business, which is how can they expand revenue from their existing client base with some of the new products that they have coming to market? And just like I talked about with Peloton, but any key issue per subscription businesses churn. And so as people are going back to work back to the office, will companies start to pair back on their Zoom subscriptions and Zoom accounts, just like with Peloton? There's a wide dispersion of views on those topics. And actually with the customer count numbers, Zoom had a long history of beating visible office consensus for net new customer additions until last quarter, it was the first time that they had missed. So I think there's a lot of uncertainty that's been introduced there and it'd be fascinating to watch it play out.
Tim Harrington: (19:24)
Yeah. And it seems this highlights some of your data. It seems like the story is changing as well, so you've got what people think about the traditional Zoom subscription. Now they start layering on the telephone offering, which is two or three times the ARPU. So, having the ability to drill down and say, okay, year over year comps are getting tougher and tougher. And I think we talked about it and it wasn't till like...
Rodney Pedersen: (19:54)
Really difficult comps for what they achieved last year. For sure.
Tim Harrington: (19:57)
Yeah. Maybe it's not next year, even the 2023 or wherever it is. How are you going to be able to figure out what the next step is and what's working? What's not? And I can remember as an investor, you never wanted to see decelerating comps at a tech company. So that was always a warning, but now you've got this whole telephone side, high margin, probably lower customer acquisition costs. So it'll be interesting to see how it plays out. Matt, any perspectives on Zoom?
Matt Ober: (20:29)
I think for us, Zoom is a great way to gauge the work from home and the hybrid workforce. And are we going back into the office? Rather than focus on it just as a single company itself, it really gives us a sense of what's going to happen with business travel. Are coming back into the office? are we all moving to this work from home hybrid? So is that the new standard? I think that's been one of the big things on our mind and what a lot of people are watching Zoom for outside of just how Zoom is doing on its own. And I think with these tools that we have now, whether it's Visible Alpha or SimilarWeb like, we have so many more tools at our disposal that it makes us more efficient to be able to look at that quickly and get a good sense of where we're moving.
Tim Harrington: (21:14)
Got you. And Carrie, what's the data telling us?
Carrie Lazorchak: (21:17)
Well, first I think it's a really interesting space to watch right now for two reasons. One, I think one thing that we see with alternative data of Austin, you can watch and industry and you use what you see happening in one industry to correlate to another industry. So that's one thing. Specifically as it relates to Zoom, I think it's interesting the comment you made about the phone and they've been very clear about a strategy to really go after unified communication, broaden the range for which they're providing services to companies. In some way, I think the delays and they get back to the office are going to work to their advantage. It's going to give them more time to condition what is an audience that they have a lot of attention with right now, on the opportunities to continue to use Zoom and to use some of Zoom's new offerings.
Carrie Lazorchak: (22:05)
I know they did an acquisition recently of Five9, which is interesting to watch and see what happens there. So I'd say it's a great space to watch. I think there's other correlating industries to some of the points that were made here, that you can also look at what's happening in those trends, whether it's business travel and some of those things and correlate the speed and rate at which we think people will start to come back to the office and whether that's going to have more impact presumes specifically. But right now I think they have a really good opportunity, because the more people are home and the more people get used to being at on, I think the more businesses are going to accommodate a hybrid structure going forward and that's going to work to their advantage.
Tim Harrington: (22:47)
Yeah. It's interesting. You don't really think about, you're probably not getting rid of your Zoom account. You're always going to have it. It's just a new way of life. But at the same time as with everything it's earnings expectations, are they going to continue to grow, things like that. And now I guess one of the things, we constantly get pinged from different buy-side clients on the bigger themes. So, whereas alternative data can be great very much on a company by company basis. I think it's also incredibly important right now, when you think about some of the larger investment themes, whether its inflation, Matt touched on the work from home trends, unemployment with some of the things happening there. I guess Rodney, as you look to 2022 and see across the different analysts out there, what are some of those themes that you guys are keying in on for next year?
Rodney Pedersen: (23:44)
Yeah. We actually put out a blog post a couple of weeks ago on inflation on our website. And did a little bit of what Matt was talking about, which is looking at company data as an indicator for something broader. And so we looked for companies in our data set that have significant exposure to the lumber industry, which lumber has been a key talking point in the pricing debate and then companies with exposure to use cars. So Weyerhaeuser is one of the larger lumber producers in the world. All the analysts that model that company forecast lumber prices well into the future. Analysts correctly predicted that lumber crisis would peak in Q2 and begin to taper off. But what was interesting to observe is that analysts are actually forecasting by the end of 2022 for lumber prices to remain 80% above pre pandemic levels. And it doesn't feel so transitory and those expectations may play out to be correct.
Rodney Pedersen: (24:47)
They may not play out to be correct, but as all of you work to formulate your own views on inflation, how it impacts your businesses, your investments, there's some interesting signals that you can look for in a company oriented data. Another thing that we looked at was Carvana, which is one of the larger providers or larger sellers of used cars. In the inflation readings that came out this morning, there was a slight deceleration in relation and used car prices had come down. What's interesting in those models is the consensus for used car pricing. Next quarter is 11%. But if you look under the hood, the spread is negative 2%, all the way up to 20% growth year over year on used car prices. Consensus is probably a bad descriptor for that. It's really more of a range of estimates. Into the point that we've been talking about in this panel, I think it highlights uncertainty. And to what Matt said, where there's uncertainty there's opportunity.
Tim Harrington: (25:46)
Yeah. The auto sector in general, to leverage alternative data for trading that in the last 12 to 24 months has been, looking at even the Fords that have had these huge accelerations, stocks performed really well, raised numbers. Next thing you know, you see supply chain issues, you see chip shortages, all of a sudden you're back, nine to 15 to 12. So layering on alternative data, it can be so powerful. Matt, as you looked at 2022, any blind spots? Any things that you're looking for data to help answer these different questions?
Matt Ober: (26:25)
I think it's some of the topics that were just been touching on, it's watching the supply chain, seeing how that's going to be affected around the world. I think the digital transformation we saw accelerated during COVID, I think we think that's going to continue to accelerate and looking at how do we better track that. We have a huge presence at this conference in digital assets, how is digital assets going to affect all of these different sectors, whether it's cryptocurrencies defy the metaverse. So I think for us, it's just being able to look at all these sources and think about it not only in the public markets, but also private companies as we invest earlier.
Tim Harrington: (27:00)
Is there a big disparity in terms of the data sets that you look for, or that you currently work with on the private side versus the public, or they cross over to bowls?
Matt Ober: (27:12)
I think a lot of them cross over to both. I think, SimilarWeb is a great example that they're covering all these companies as they move more and more digitally, and we're able to see them earlier and earlier. So for a company like ours, it helps our analysts know who the potential disruptors are to the public markets. So I would say it's exciting to see a lot of the data providers we've been using for many years, expand the universe that they're covering.
Tim Harrington: (27:37)
Interesting. And what stage do you guys look at, is it an early stage? Is it more series B, C, D? Where do you guys get in-
Matt Ober: (27:47)
Typically series B and further along the line.
Tim Harrington: (27:50)
Okay. And yeah, because I'd imagine the private world is so much different than the public world. Rodney, you guys, I don't think you do any private stuff, correct?
Rodney Pedersen: (27:59)
No, everything that we cover is publicly traded equities. I will say that we work with a relatively small number of private equity firms that look for insight in publicly traded equities for the impact on private markets. But yeah, we cover publicly traded equities.
Tim Harrington: (28:14)
And Carrie, it sounds like from Matt, you've covered both, then is it corporate or is it also kind of the PE and VC firms and...
Carrie Lazorchak: (28:24)
All the above. I think that one of the key reasons people come to SimilarWeb is because you can see consumer trends, you can see broad market trends, consumer behavior trends in real time and it's applicable to all segments. I think Matt said it very well, actually. Yeah.
Tim Harrington: (28:45)
And I know we're running out of time, but kind of speed round closing. We want the audience to walk away smarter, thinking alternative data as the answer. Carrie, if you wanted to have those bullet points, what would they be in the minds of the audience to walk out of here with?
Carrie Lazorchak: (29:06)
I think one of the most interesting things to consider right now is the movement of a lot of legacy brands to D to C. We see very interesting correlations of data when you look at our technographics information and the number of classic indirect companies implementing technologies like Shopify and e-commerce, B2B software, there's a huge trend towards more direct to consumer relationship. We hear it from the customers directly when we talk to them about how they're using our data, because they want to understand what's the demand and what's the trends. And we see a lot of investment there. So I think the B2B software space is a very interesting space to watch. And I think that trend to D to C is going to really create a new dynamic of, and a new area of data that people are going to need to evaluate companies.
Tim Harrington: (29:59)
And one thing, when we started BattleFin, it was very quant driven. So a lot of the quant funds were the first ones to engage cause they could understand the various data sets. And I was just like, give me everything, just throw the data at me. I don't want any insights relative to it. And then we saw an evolution where the fundamental funds and even some of the corporates were coming in and trying to understand it. And I think one thing that you guys seem to have done a good job of was, I don't know, I call it mapping it to tickers, but actually talking about things in terms of companies and public companies. When you guys did that, did you guys start to see more traction? Because it seems like it's a lot easier for us to talk about Peloton and different KPIs than it is to say, okay, here's the algo, here's the machine learning answer. From that perspective, did you guys see a jump in attention and traction once you did that?
Carrie Lazorchak: (31:07)
First of all, I think we're starting to do more of that. I think one area that you'll see from SimilarWeb and I think my solutions head is here. He'll tell you, you'll see more and more information from SimilarWeb that looks at ticker symbol, tickers themselves and aggregates the data for you. But it really depends on the audiences and what you're looking for. But yes, I think we'll do more and more of that. We have more and more demand for that. So you will see that, but obviously because we also play in the private space, there's people that are just coming to look for the trends and understand who's the next big player in any given market. And we provide insights to that as well.
Tim Harrington: (31:47)
Rodney, speed round, minute left, you got, you and Matt, bring us home.
Rodney Pedersen: (31:52)
Yeah. The first thing that I would say is a lot of people think about data and acquiring new data sets as a strategy to come up with better ideas. And that's certainly valid. I would encourage everybody to think about your data strategy also as looking for data that will challenge your views. And I think the more that you can find data that will challenge your own views, ultimately the greater conviction you can have in your ideas and a better probability of differentiating in the long run. That's one really important thing.
Rodney Pedersen: (32:24)
The second thing that I would say is, I think it's very rare that a single data set is going to give you a lot of really great answers. And ultimately where I think people like Matt have created opportunity is by connecting data sets in very meaningful ways. SimilarWeb and Visible Alpha, maybe we should, but we don't really talk. One another we don't create linkages between our data sets. So the managers that invest the time and the energy to create meaningful connections between data sets can uncover insights that others will never see. And I think that's an important part of any data strategy and encourage everybody to think about that.
Tim Harrington: (33:06)
Matt bring us home.
Matt Ober: (33:07)
I just think, in the last 10 years, if we think about where we've come with data and hedge funds, it's become a staple. It's no longer alternative like Carrie said, and working with these strong providers, these are great companies that are out there and we don't have to do everything ourselves makes our team more efficient, allows us to dive deeper into understanding companies and what data can really uncover unknowns. And I think the opportunity is only growing with all of this unique data that's out there.
Tim Harrington: (33:35)
Great. We have 50 of probably the most amazing alternative data providers down on the fourth floor doing one-on-one meetings. So if you have an investment thesis, you want to figure out inflation, you have a company, come down, join us, ask the questions. Thank you guys. Great panels. Look forward to seeing the rest of the conference.
Carrie Lazorchak: (33:54)
Yeah. Thank you.