Ep. 158: Alex Slusky, Vector Capital | Diagnosing Growth Levers and Building a Defensible AI Edge

0:00Alex Slusky: Hey, everybody. Before we get started with today's episode, I want to take an opportunity to tell you about my new book, AI Marketing Blueprint. It just hit number one bestseller status across multiple categories on Amazon, and it walks you through a proven framework that we are taking our clients through here at How to SaaS and how to stay relevant and visible in a world with AI platforms. One of the biggest problems that we have seen across clients and companies is that the traditional channels that they relied on, like paid search or SEO, have declined significantly or are getting more expensive and competitive.

0:33Alex Slusky: The reason for this is that a lot of buyers are starting to self-educate themselves and research on AI platforms. So a lot of that volume that was previously going to those channels is now moving to these new AI platforms. So to stay relevant, the book walks you through seven new rules that companies in all kinds of verticals and industries need to consider so that they can continue growing their pipeline and revenue and ultimately their enterprise value. So if this applies to your business or one of the companies that you've invested in, I definitely recommend that you pick up a copy. It's available on Amazon, on Apple Books, on Barnes and Noble, and even share it with your teams.

1:10Alex Slusky: Grab a bunch of copies so that you can kind of consume the content together and start to apply it to your business. And with that said, let's move on to the episode. Welcome to the Private Equity Value Creation Podcast, where we interview leading investors, operators, bankers, and advisors to help you answer one question. How do we increase the enterprise value of our companies? My name is Shiv Narayanan, and each episode, I will dive deep with a guest to help you become a better value creator and capital allocator. So with that said, let's jump right in and let's get started with today's episode.

1:45Alex Slusky: My guest today is Alex Sluski, and he is the founder and managing director at Vector Capital. And what's really interesting about this episode is that Vector is doing a ton in the world of AI and how they're leveraging it across their portfolio companies, how they're thinking about product in particular, and how they're approaching go-to-market for their portcodes differently. And Alex has been doing this for decades, and there's a ton of experience that he brings to the conversation, along with a lot of great examples in their portfolio in terms of how they're leveraging AI to grow their respective companies.

2:13Alex Slusky: And especially with AI being such a hot button topic and companies, NPE firms and investors and boards trying to figure out how to leverage AI in their product strategy and their go-to-market strategy. I think there's a ton of great takeaways and insights that I'm sure you'll be able to start applying across your investments. So with that said, I'll leave you to it. Enjoy the episode.

2:40Alex Slusky: All right, Alex, welcome to the show. How's it going? Thanks for having me on. Yeah, excited to have you. So why don't we start with your background and Vector, and then let's go from there. Sure. Well, I started my career in technology in the early days of Microsoft in the late 80s. And that led to, with some education, to a venture capital job at New Enterprise Associates, a venture capital firm that's still very much around. and eventually evolved into me joining a family investment office called Zip Brothers Investments. And the way they lured me from NEA was to make me one of those offers you can't refuse, which is come work for us for a couple of years.

3:24And if things work out, we'll help you start your own firm. And I was given that offer in my late 20s, did not refuse it. And things worked out quite well. the Zip family was a key supporter and investor in the early vector funds. And really that decision and my work with them has led to the creation of Vector Capital in the late 90s. So the firm is 28 years old and has been focused on a fairly consistent strategy ever since. We focus on being value investors in technology industry more broadly, but software really has made up about three quarters of our investing over our almost three decades of history.

4:13Alex Slusky: And so, first of all, that's great. That's a great way to set this up and interesting how you got the firm going. Talk about what the focus of Vector is now. What types of companies are you investing in and what stage and what amount of revenue, et cetera? Sure. Well, we tend to acquire companies. over 80 % of our investments are control investments, where Vector is the lead investor, typically the only investor, in partnership primarily with the management team of the company. The vast majority of what we do is focused on software. And the scale is probably$75 million on the low end, about$500 million of revenue on the high end, and enterprise values anywhere from a couple hundred million to a few billion.

5:06That's where we focus. And the firm manages a bit over$5 billion of capital. Most of that is in the private equity strategy I described. We also have a billion-dollar credit business also focused on tech.

5:24Alex Slusky: And so walk us through, like, what percentage of the firm is focused on the debt side versus the investing side? About 80 % of our capital and 80 % of our staff is focused on private equity and the remainder is on technology credit. Got it. Okay. And so on the private equity and the buyout side, like, help us understand what types of companies are you looking for? Like, what are some of the characteristics that really help you feel like, okay, this is one that Vector would want to deploy capital in? Excellent question, Chip. So we're looking for companies that have hit a crossroads and ones that we can make a positive contribution to their future.

6:05So where are those companies found? They're usually in a few buckets. The first one are what we call venture capital silver medalists. These are companies that grew to significant size as venture capital, venture funded software companies. But they're not no longer growing at rates where the venture backers can make the kind kind of IRR on an ongoing basis. Because they're not, you know, they're maybe growing at 10 % or 12%, but they're not growing at 50, which is what you need to continue to deliver venture returns. And these are companies that will certainly make money for their early stage investors, may get the money back for the late stage investors, but don't belong in venture portfolios.

7:06And so we've partnered with some of the most preeminent venture firms in the Valley in acquiring it from them. Occasionally, some of them will roll into our structures, but we're not a late-stage investor. We will be a control investor in those situations. And we will partner with the management teams to manage these companies as private equity-owned assets, not as venture capital-funded assets. And there's a distinct difference between that. That's kind of the first bucket of what we do. and obviously go through a number of examples. The second bucket are smaller public companies that aren't loved by the public market.

7:47We call them kind of fallen angels. Maybe they were hot once, but they were not able to be successful in the public markets. And we will take them private and refocus their business. That's the second bucket. The third bucket, a little more troubled, companies which borrow too much and are now either controlled or owned or about to be owned by their lenders. And we will step in and recapitalize the business and try to fix the capital structure, fix the operations. That's the third bucket. And last but not least, our corporate spin-outs. The typical divisions that are orphaned inside of a larger corporation.

8:32and we will come in and buy them from the corporation. Often the corporation will retain like 19.9 % so they don't have to consolidate. And then we will build up a management team and focus that business on the kind of the needs of this division, not trying to optimize for the larger whole, which is what large corporations are supposed to be doing. So these are the four buckets of companies that we tend to pursue. What's common about them, it's usually companies that are not able to execute crisply, where the management teams are often hamstrung by outside issues that have nothing to do with their market.

9:20And companies that maybe set themselves up for higher growth than they're actually seeing, and they don't know how to recapture it. And we have a number of playbooks across our business of what do you do in each of these situations.

9:36Alex Slusky: And so walk us through that. What do those playbooks look like? Or how are you evaluating which part of the playbook to focus on inside these businesses? Well, you really have to look at what the underlying business is. It's actually great to use a contrast of two deals that are vector deals. both database companies, both purchased from their venture backers. One company is MarkLogic that we purchased a few years ago and sold and then later on proceeded to sell to Progress Software. And one company is SingleStore, which we bought about a year ago from its venture syndicate. Both database companies, both bought by vector, but somewhat different strategies.

10:29So Marklogic was an older database technology, very heavily used in government and financial services. And it was very clear that while its customers were very committed to the product, the product was deeply embedded. As we know, switching costs from databases are very, very high, not something anybody wants to do. And MarkLogic was embedded in healthcare.gov, for instance, in the U.S. counterterrorism center. No one's going to ever rip it out. But what was the opportunity for MarkLogic? It was not the most advanced and most current database technology. It was really going to be a 3 % to 5 % grower, and that's all it could realistically be.

11:10Grow with its current customers, but acquire very few new ones. So the strategy there was to obviously focus on costs. was really to rationalize, to take a company that previously was losing quite a bit of money and turn it into a company that was delivering 30 % to 35 % EBITDA margins. So we took a company with a negative rule of 40 to one that was very close to 40. And obviously that, which we did in about two years, creates a lot of value for all the stakeholders. and once we've cleaned it up and made it a much more focused, better executing business,

11:51we were able to attract progress software. Actually, we had a number of bidders because everybody looked at them and said, you know, we love databases. They're very sticky, but we want databases that make money, not databases that lose money. So that's a very straightforward playbook. We can obviously get into the details of how we did it. Now, take single store. slightly larger than MarkLogic, still growing in the teens and 20s. Maybe not enough to satisfy its venture investors, but actually very much a growth asset in our mind. Now, SingleStore is a database that combines high performance and analytics at the same time.

12:36Many people know it under its old name called MemSQL. Now, combining a high performance database with analytics in one code base is a very hot space. As you think about what you need to do with AI, the thesis for single store has become even stronger than it was a year ago when we purchased it. So the approach to single store is obviously not to optimize profitability. The approach of single storage to be very thoughtful about the use cases where we win, because clearly we cannot take on all open source databases and Oracle and everyone else at the same time. So we have to be very rigorous about the use cases that we have.

13:17And there's about 10 or 12 use cases where we truly thrive. And then put all of our wood behind those arrows. Really laser focus on showing developers and IT departments of why adopting our database ultimately is going to save them money. Now, adopting your database is always a difficult process. and you end up growing with the amount of data and with existing customers more easily than you do winning new ones. But winning new ones is critical to your long-term success. One of the things that's made it a lot easier is some of these very sophisticated, very complex high-performance databases are reasonably complicated syntax and are somewhat more difficult to implement.

14:03Well, guess what? AI riding to the rescue. you. Claude knows how to implement single store. So that's Codex. And so our threshold for being adopted has dropped dramatically. And as a result, the company's growth has even ticked up close to the 30s. Again, very different use case. We have to, in this case, it's a lot more about execution, about working with management team to define those use cases, optimize sales, bring in more rigorous CAC to LTV analysis, which we've done, bring in a new CFO. You know, we are upgrading and improving the business, but in a way where we're trying to increase his growth rate.

14:52And very, very different than the MarkLogic story. So what's important to emphasize is Vector is an expert in software, but we don't run the same playbook on every particular company, because not every situation is the same.

15:06Alex Slusky: Yeah. How do you determine which approach to take for a particular business? Because every company, like you mentioned, especially you're buying companies that there's room for optimization and there's room for improvement. So walk us through diagnosing that business to like, what is a prioritization mechanism to figure out where you actually focus the management team, where you focus your limited resources and and how you actually think about value creation as a as a operational playbook well obviously the vast majority of that thinking not the work has to happen during due diligence underwriting you need to understand what is your tam how competitive are you in your town how quickly is your cam growing you know you know what is the realistically addressable market.

16:07And can I go win in that market, given the research I have? Because something that a$100 million company can do is different than what a billion-dollar company can do or a$10 billion company. Single store may have a fantastic 10 and is growing fast. Now, is it going to go head-on against Databricks? No, that's probably not a war we're going to win. But can we identify specific use cases? Definitely. So you do a lot of that in underwriting. And then you decide, like, how important is growth to my investment thesis? And can I realistically deliver on that growth? Like, is it believable? And you have to look at each other kind of around the table.

16:58and at that table for us it's always the investment team but also the value creation team we have a very capable value creation team led by kieran rao who joined us from vista about just less than a year ago and so we all look at each other and say is can we actually impact growth in this business and if the answer is yes obviously you get paid a lot um as a private equity investor, as a management team member, you know, if you can grow a business, you're going to exit much better. But you need to also be realistic. One of the things we find is that a lot of venture funded businesses try to grow at all costs and the growth is value destructive.

17:41I can show you business after business that we've turned down where the CAC to LTV is actually negative. So you need to be rigorous about what you really expect. And once you've decided on that, then you have to relentlessly execute. Now, that execution, even in growth companies, still means attaining operating efficiencies. Because there's no excuse not to operate as close as possible to the efficiency frontier. Because, like, why not, right? You can either take those dollars into more profit, or you can take those dollars into more R &D and more sales, more feet on the street. But there's no reason to waste money in G &A, in customer support.

18:32Make sure those places are efficient, which really today means AI-enabled as much as possible, and frequently offshore.

18:46And so once you've done that, and you've created in a sense, more dollars to spend, you decide, do I want to spend them on customer acquisition? Which if the market allows it, and your competitive map allows it, absolutely, that's your highest and best use, or drop them to the bottom line. Like an example I gave you with Marklogic, and I can give you many others. You know, just the market, we were not going to grow about three or five percent. So knowing which world you live in is super important. And a lot of executives fool themselves about which world they actually are in.

19:23Alex Slusky: We'll get back to the show in just a moment. But before we do, one of the most common and important value creation levers that we hear about on the show from private equity investors and our own PE partners is go to market. Yet when these same PE partners bring us into their portfolio companies or new target investments that they're exploring, we find that the marketing function is quite immature, underutilized and under optimized. And so that's a huge opportunity that we see inside these companies. And if you have a portfolio company that you feel like it's scaled a lot faster to drive more pipeline and revenue, or you're looking at a new investment where you feel like that could be core to your investment thesis, well, we'd love to explore that with you and figure out how we can partner with you to drive more enterprise value creation on the marketing side, similar to the way that we've done with major PE firms like TA, Updata, HG, SDG, and many more.

20:15Alex Slusky: At this point, we've done hundreds of engagements across hundreds of industries and verticals, and we have a ton of benchmarks and frameworks that we bring to these engagements to help you drive as much enterprise value as quickly as possible. So if that sounds like something that you might be interested in, you can just email me directly at shiv at howtosass.com or go to our website and schedule a demo. And we'd love to speak with you about it further. And now with that said, let's get back to the show. Right. Operationally, how involved are you getting with these companies? And you touched on a little bit, but just help us understand how deep are you getting?

20:52Alex Slusky: How are you partnering with the management teams? Are you focused more on getting the right people in the right seats? or are you bringing your own ops team to actually execute with the teams themselves?

21:07It's a simple question, complex answer.

21:11Alex Slusky: We have time. We do. In the ideal world, we want to give a playbook to the management team and let them execute. That's nirvana for us is we can spend our time on other projects. In reality, most companies that find their way to us have some holes in the management team. Now, if the company is Swiss cheese, and there are many, many holes in the management team, they don't end up in the vector portfolio because we can't rebuild something wholesale. It just becomes very hard. But always there are elements of the management team, maybe a brilliant CEO who needs help with his direct reports, maybe a tremendous chief product officer teamed up with a great VP of engineering.

22:07We always want somebody to build around some core which has been burning the fire of this company and feeding it for a bunch of years. But we understand that the company may have holes. Like we often find weak financial management. You know, we're a private equity firm. We're demanding. So, like we will frequently upgrade the CFO, for instance. So that's nirvana. We give them a playbook and they execute. But what often we find is that there's demand from our management teams for our value creation team to partner with them on discrete tasks. So defining the ideal customer profile, the ICP. We have experts inside Vector who are really, really good at running that analysis and helping educate the chief revenue officer, his team, sales ops, in how to define it and how to focus it.

23:07Because one of the things we find is a lot of companies, particularly when they're venture owned, they spread in all directions. And they try to go after every kind of customer. And you hit customers who are in your sweet spot, and you hit customers that are on periphery. And the ones that are on periphery, even if you win them, they're expensive to win, and they're expensive to keep. Because they're on the periphery, they're not in your main wheelhouse. So, like, defining that often takes an outside perspective. and sometimes you have to kind of slaughter some sacred cows that the business has believed in, but they actually aren't true.

23:44And so that you can focus, we're big believers in focus. And so that project is often done better outside, but then you hand that over and then have the team execute something you develop together. You know, another example would be, let's say a company doesn't know how to offshore, like never had an operation in Eastern Europe or India and doesn't know where to start, then we will bring in, you know, we have operating partners in India or operating partners in the U.S. who know how to do this. We will then kind of bring our expertise to that effort. Lately, we've been bringing a lot of our AI expertise to our portfolio companies Because we use the same consistent set of benchmarking tools, for instance, to determine what percentage of code is AI built.

24:39And so, rather than having each company define its own measures and its own pull request measures, you know, we're going to create one consistent framework across our entire portfolio. So, we can actually show each CEO, this is where you stand. You're number one or you're in the middle of the pack. So there are things that are better done externally than internally. But again, we aren't remotely scaled to run every one of our portfolio companies hands-on. We're not a holding company. So the goal is 12 or 18 months in, once the company's been fully brought up to speed, we've put in the right management team, have that management team run the company, and then have our value creation team do projects here and there.

25:31Alex Slusky: What are some of the areas that you currently see as the biggest value creation opportunities in your portfolio? Well, I've referenced already AI. Getting AI embedded throughout our portfolio is maybe one of the most important things we can do for SaaS companies, kind of going off the name of your podcast. And that really means two things. First, it means having AI permeate the product. This is the harder part, by the way. It's making sure that whatever some young, talented startup that wants to go take our market away by using modern AI tools, that we preempt them. which by the way, our portfolio companies and many software companies more broadly are extremely well positioned to preempt because we understand the use cases.

26:28We already have the customer relationships. We're already there. We're talking to the people at the company. We're in a far better position to execute an AI strategy than some new entrant, but you have to do it. You can't just talk about it.

26:44Alex Slusky: Right. What does that look like? Because we hear this from companies all the time. like putting AI into the product and almost intertwining those two things. It's not like a separate product. It's part of the same product. But I'm curious, like what does that look like in your mind? How have you coached your companies to focus on this? Well, that really means trying to understand how, you know, what the AI threats are and what the AI opportunities are, understanding what the startups are trying to do, and then beginning to think, ask questions like, Like, where is my data store? What, you know, to run AI, you actually need to run AI on something, right?

27:26On some, on data that you're, and information that you're gathering. Like, have I been gathering information? I'll give you a live example. Cybersecurity, obviously, an area that is not perceived as threatened by AI, but has a huge AI opportunity and an AI threat of a different kind. Not that AI is going to replace cybersecurity, but AI attackers, AI-powered attackers are becoming far more virulent. You know, we've all read the stories. And we all know that even if Anthropic and OpenAI succeed in limiting their systems for being jailbroken, some open-weight, open-source LLM won't be. So, let's just assume that the bad guys are going to be fully AI-empowered.

28:13At our portfolio company, WatchGuard, you know, we looked at the situation. We said, well, wait a second. How are firewalls upload their logs to the cloud and have been for a few years? Now, they do this to do some of the EDR and other kind of cybersecurity operations that, you know, we need to do to protect our customers. But what a great database for AI operations. So now we're implementing AI, which can actually monitor all those logs and really process them so much faster. And you almost have like a operation center that's going to be AI powered. Now, big companies have human powered operation centers and increasing AI power operation centers.

29:06But WatchGuard serves SMBs. And SMB doesn't have that, but we're going to give them a cybersecurity CIO in a box powered by AI. But why are we able to do that much faster than you entered? It's because we have millions of devices already deployed, all uploading data to the cloud that AI can help analyze. We're really well positioned. But companies that don't have that need to come up with ways where their data can begin to get pulled so that AI can operate on that data. Very, very important. Now, other companies, like we have a company called Planful, which does budgeting and planning, very successful, growing nicely in the office of the CFO.

29:53You know, clearly their customers aren't going to be comfortable uploading all their data together so that we could begin to give them advice across thousands of different budgets, right? In cybersecurity, people don't mind if information is shared because everybody wants to detect and address threats really quickly. In financial operations, not so much, right? But there, where AI can do is, you know, AI can power chatbots. AI can give tools where we can take budgeting and planning, not just limited to the FP &A department in the corporation, but actually bring our products into the executive suites.

30:34And as you can think about the future, executives can actually sit with our system and put in natural language queries like, show me the budget this way. What happens if I increase the sales force in this geographic region? What are the implications? And we can give those interfaces and executives can run scenarios. much, much more quickly than the software was capable of even as recently as 9 or 12 months ago, but with AI tools. And obviously, the value is not the natural language queries, but all the intelligence and the manipulation that those can translate into using modern tools. So those are – I'll give you two very different examples.

31:20but our portfolio companies and frankly software companies more broadly have to get this right or we're going to get our lunch eaten how do you think about applying ai or similar principles to

31:33Alex Slusky: the go-to-market side because that's the other half of this equation right there's product innovation that has to happen but companies are also struggling to figure out like how do i do sales better or how do i create better content or how do i engage with customers as they're self-educating more. I'm just curious how you go about helping your companies with that. Well, I'm actually glad you asked because we have a portfolio company called Showpad, which is all about AI sales enablement. So Showpad circa a couple of years ago would take your content store, would have ability for someone who's selling complex mechanical equipment, say a caterpillar to for salesperson to understand how all the different features work together you know in a variety of similar tasks but the show bit of the future actually is working to literally have a virtual salesperson not only can we have all the content but ai applying that content can you know customers aren't comfortable with this yet but we're not very far from actually with being able to send an avatar to a sales call.

32:44And powered by all of our data, they can just in real time answer your questions. Now, again, customers aren't comfortable with that yet, but I can envision a world where our avatar is talking to the buying avatar in some not too distant future. And I'm not trying to get too futuristic on you, But enabling sales is critical. Showpad is in that business. But for any software company, just generalizing, if you do something as simple as retain the transcripts of your sales calls, you know, some customers may be uncomfortable with that, but many won't be. You can actually do tremendous analysis and understand, is this prospect real?

33:34Is this prospect far-fetched? Where should they belong in the pipeline? You know, how do I, what do I, what information I can, based on their questions, what information do I need to come back with to address their concern? Imagine a world where every salesperson is as good as your best salesperson because they're, because the tools are so good. I think that's something that actually is being implemented across, certainly our portfolio because that that those tools are available today and if you can buy a product you can absolutely do it yourself and using the clock code this can be done this is not a far-fetched uh and a far-fetched endeavor but also there are increasingly third-party vendor tools that do a lot of this.

34:29So enabling sales is critical because sales has to get more productive, more efficient. As we know, competition is only increasing. And for every software company, because the barrier for writing software has dropped, there'll be more new entrants. There are more new entrants. We have to recognize that. I think existing companies, not just the ones their systems of record because it's been a lot of focus like I'm a systems of record system of record great if your system of record you're in a fantastic position that's why you know there's rumors that Silver Lake wants to buy work there right to put an essential system of record but even if you're not the system of record if you're deeply embedded with customers if you're deeply embedded with use cases and you know the vertical cold you have a big advantage and you have a huge

35:21Alex Slusky: advantage especially with the data that's proprietary in these systems what advice would you have for other private equity firms you know is there thinking about ai and leveraging it across their portfolio like where should they start or where should they focus general private equity firms or technology private technology well uh i'm gonna have to be somewhat edited since there are competitors by definition but uh i think the important thing is to is not to panic. I think it's important to that we all together educate our limited partners that this is not the end of software. It's not even remotely the end of software.

36:06That we are, that as an industry, we have to be very thoughtful about what AI will save money. And so you have to decide, do I pocket those savings? Because I'm not as, back to where we started our conversation, because I'm not as sure about the competitive position in the growth rate of my underlying business. Or can now, can I deploy, if AI saves 50 % of cost in development, do I deploy 2X the developers? All AI powered. So I can build features that much more quickly. And then you need to go through your entire cost structure and then say, where does AI make sense? Where does AI not make sense?

37:02There's been a lot of discussion of customer support. I'm a believer in automating customer support, but realize customer support is like 4 % of revenue, typically four to five. So, yeah, we put AI in. We'll save a point and a half. It's money. It's worth doing. It's not going to change. It's not going to change your life. Adding a lot of AI to R &D is going to save more or either save money or enable you to do a lot more. It's your choice. Adding a lot of AI to sales can make you more effective. I actually don't think ultimately they'll lower sales costs all that much because just expect a more contested cap, you know, competitive map.

37:46You'll have opportunities in GNA. You know, nobody loves payables and receivables. Highly automatable functions with AI. So, like, will software companies look dramatically different in five years? I actually don't think so. But will a lot of functions be done by agents? Yeah, 100%.

38:08Alex Slusky: That's awesome. We're coming up on time here, Alex. But before we close things up and wrap up, if people want to get in touch with you or learn more about Vector, what's the best way for them to do that? Well, obviously our website, vectorcapital.com. But if somebody wants to get in touch with me, I'm pretty easy to reach, alex.vectorcapital.com. Awesome. We'll be sure to include that and the links in the show notes. And with that said, Alex, thanks for coming on and sharing your wisdom. Obviously, you guys have invested capital in a ton of great companies and you've been doing this for so many years.

38:36Alex Slusky: So it was really great to hear your perspective and your wisdom, I'm sure will help a bunch of our listeners and private equity investors that are trying to figure out things with their own firm. So appreciate you doing this. Thank you very much. Thanks for the great questions. Thanks for listening to today's episode. Before we close off, if you haven't already, go grab a copy of my new book, AI Marketing Blueprint. It just hit number one bestseller status on Amazon across multiple categories. and it walks you through a proven framework on how to scale revenue and pipeline in a world with AI platforms where customers are self-educating and learning a lot more off your website and where companies are struggling with declining inbound traffic volumes from paid search, paid social, and even organic and SEO channels.

39:21Alex Slusky: So if that sounds like you or a company that you're invested in, go grab a copy for yourself, your team, or your portfolio company, and I'm sure it's going to help you out on your journey with that business. and with that said thanks for listening today and we'll see you guys next time