Unlocking New M&A Strategies: Uniting Venture Capital Insights and Public Equities in M&A

Today's episode of the M and A Science Podcast is brought to you by insight. In today's rapidly evolving business world, staying ahead means embracing change and leveraging technology to not just meet but exceed your strategic goals. That's where Insight comes in. Insight is a comprehensive solutions integrator that helps organizations transform technology, operations and service delivery to future proof the business and innovate the client focused approach to delivery. They combine the power of people and technology to turn the biggest challenges into opportunities. Learn more@insight.com Leave Legacy that's insight.com Leave Legacy hello M and A Friends. This podcast is brought to you by dealroom. M&A deals are more competitive than ever. Your teams need to be collaborative and aligned to act fast and win deals. An M and A lifecycle management platform allows your team to spend less time coordinating and more time executing so you can win more deals. Check out why the best in the industry use dealroom. Go to dealroom.net to learn more. Again, that's dealroom.net I'm Kisam Patel and you're listening to M and A Science where we talk with deal professionals and learn valuable lessons from their experience. This podcast focuses on stories, strategies and what actually happened during M and A deals. Foreign Scientists welcome to the M and A Science Podcast where we learn from the best in M and A to uncover proven techniques for enterprise value creation. If you're interested in learning more about how to optimize your M and A practice, or want to get involved with a community of forward thinking M and a practitioners, visit mascience.com and subscribe to our free weekly newsletter. You want to keep up with us on the go, head over to LinkedIn and follow M&A Science. I'm your host, Kisan Patel, CEO and founder of M and A Science. Joining me today is Thomas Lee, Vice President, Corporate Development at Zip Davis. Zip Davis is a vertically focused digital media and Internet company whose portfolio includes leading brands in technology, shopping, gaming, entertainment, connectivity, health and Wellness, Cybersecurity and MarTech, traded on Nasdaq under ZD. Today we're going to talk about unlocking new M and A strategies and how learnings from VC and public equity can be used in M and A. Thomas, how are you doing today?

I'm doing great. How are you doing?

Kisan, thanks for joining me live. Thanks for taking a break from doing deals and thanks Freshfield for for providing this wonderful office space and WTC3 building in Manhattan.

Thanks for having me. I'm looking forward to today's discussion.

I am as well, can we kick things off with a little bit about your background?

So I'm Thomas Lee. I'm vice President of Corporate Development at Ziff Davis, where I've been now for over five years. Ziff Davis is a publicly traded Internet and digital media company. We own and operate a collection of digital media and software businesses that operate on a largely decentralized basis. My team, corporate development is responsible for driving inorganic growth for the company, namely through M and A. We run a very active program. So in the last five years we've completed approximately 40 transactions representing over a billion dollars in deal value. Before coming to Ziff, I spent a decade in research and investing across public equities and venture capital. Spent seven years in an equity analyst capacity at several investment banks and firms including JP Morgan, which is where I started my career out of college before joining Lazard. Then I spent three years in venture capital. I was an investor at Tenfour holdings, which is an investment firm based in New York focused on early stage and growth stage investments in E commerce and enterprise software.

So I'm really excited about having this conversation because your background's unique. You didn't just take the typical went through banking, private equity and Corp Dev. You had this background of public equities and vc. And before we dive into how those skills have transferred over to M and A, let's break down Ziff Davis a little bit because I think some folks are familiar with old Ziff Davis as the media business, but now it's become a real portfolio. Can you tell me some of the big brands that you have in your portfolio?

Yeah, I think of us as a portfolio company. It's really simply put two sides of the house. There's digital media and software. So within digital media we're in the categories of tech, shopping, entertainment, digital health. And then within software we're in cybersecurity, Martech, connectivity. And so in terms of brands, some of the more popular brands on the digital media side are PC Mag, Mashable, RetailMeNot, IGN. I'm leaving out so many. I feel bad. It's almost like leaving out names for your kids, but those are just a few names. And then on the software side we have Ookla, Speed Test, Fiber Security Group, Moz, you know, SEO, SEM, Asset, and a whole host of others. But you know, forgive me, all the other children.

Yeah, if you want to pick up the rest of those names Thomas didn't mention, just go to Zip Davis website and you'll probably see them all up there. We talked previously about your VC background and how that's shaped some of your views in M and A. Can we talk a little bit more about that?

There's a couple of things that I still stress in my day to day workflows today that really come from my foundation and venture. One is really emphasizing deal sourcing, the other is around investigating product market fit of a target company on deal sourcing first. So in venture you distinguish yourself through differentiated deal flow and differentiated deal flow comes from sourcing. But I'll be blunt. For a lot of people, sourcing is a. It's a painful exercise. You have many conversations, most go nowhere. The process brings about negative emotions because a lot of times the companies that you want to invest in will reject you and a lot of times the companies that want you to invest you probably need to pass on and then you try to do so without sound like a jerk. You add to this kind of a layer of the actual exercise of setting out cold. Outreaches react really en masse in bulk volume, whether that's cold calls or emails. It's viewed as a mundane task and oftentimes viewed as lower value added than say, research diligence or execution. You take all these factors into account, it's no surprise that a lot of corporate development functions prioritize in house resources for diligence and execution and really outsource deal flow generation activities to brokers and bankers. For me, coming from a background in venture, I have a firsthand appreciation for deal sourcing because I've seen it firsthand drive differentiated deal flow, which then drives differentiated investment results. So when I was an early stage investor, my core responsibility was to go find founders and CEOs who were disrupting their respective industries and to invest in, back and support those founders as they scale. But these companies, these management teams and CEOs, they're not easily found. They're not just all neatly sitting in one database ready for you to reach out to. What it will require of me is to really create and cultivate a entrepreneurial spirit and proactive approach to sourcing and really networking. So you need to find a way to network your way into these ecosystems. And taking into account for a lot of these founders, CEOs, when they're raising their first round of institutional capital, they're doing so without a bank or a broker. So there's no formal process. The only way you're even included in the discussion is if you somehow network and source your way into the ecosystem. I've taken this kind of appreciation for sourcing. I've imparted in my team at ziph. So on my team, everyone sources. Regardless of seniority, we take two approaches to sourcing. The first is network driven sourcing. So as the name implies, this is really getting deal flow from people we know, people such as our colleagues, networks, people we've worked with in the past. It could be from people we've done deals with in the past, other investors, other bankers, et cetera. And then the second approach we take is thesis driven sourcing. And so thesis driven sourcing is where we conduct fundamental research on a particular theme or industry, go deep, and if we find the theme particularly attractive for investment, say there's strong secular growth drivers, macro tailwinds, there's an opportunity for us to add value, maybe there's high fragmentation. So right for a potential consolidation play all those factors we take into account and if we deem the sector to be particularly attractive for investment, we'll then create a market map of the entire landscape, create a comprehensive list of all the companies that could be potential acquisition targets, and then stack rank them, stack rank them by criteria that's suitable for us, kind of. In another scenario we would do this where one of our existing portfolio companies or business units identifies a need for a technology product solution, maybe even a management team with a certain expertise. In that same scenario we'd run a buy build partner analysis if it makes sense to buy. Then again we create a market map. We create a full list of all target companies and then reach out to them. That's kind of sourcing. And if I had to characterize the motion for our team, it's very entrepreneurial and very proactive, which I think is very common for a lot of kind of venture capitalists in terms of their sourcing approaches. The second thing I stress today in my workflows that comes from ventures really is investigating a product market fit of a target company. And to do this really as much as I investigate a company's financial performance, in early stage investing, studying the product and the customer are paramount. And it's paramount because at the early stage oftentimes you have very little in terms of KPIs or financial data book really to analyze from series C all the way up to even series A. And so what I do is I'd study a specific market size and then really think about the pain points within the industry and, and really double click into the potential customer and the product that could actually solve those pain points. So with respect to customers, really thinking about who is affected the most by the pain point in the industry, who Are the potential user Personas that would want a solution to this pain point? Who within the enterprise would be advocating to purchase a solution to solve this pain point? Down to the job family with respect to the product. Really thinking about the landscape of the different types of products and solutions, There's a couple categories of companies. There's the incumbent solution providers and oftentimes they're not fully meeting the needs of the customer. Then there's the emerging providers and these companies are doing a better job, but not fully satisfying the needs of the customers. And then there's this new class which is what I call disruptive solution providers. And this is where these companies are driving really a step function improvement in the solution and to fully meet the customer's needs. Ideally, if you're assessing investing or acquiring a company, ideally your company falls into this category. So I would do that assessment, really focus on product market fit, focused on product and the customer specifically, and then overlay that with an assessment on founder market fit, which is essentially asking yourself what is it about this particular CEO, founder and or management team that makes them uniquely qualified to go solve this problem in the industry? And so by adopting this approach, what I've done is for myself personally is I've trained myself to resist the temptation of flipping to the end of an investor presentation where the historical financials are and the three year growth forecast are, and to really delay doing that until I get a full grasp of the industry's problem and then the potential solutions and how that target solution compares to substitute offerings in the marketplace. And this isn't to say that studying financials are important. They obviously are. They're part of every due diligence checklist. But I don't lose sight of the fact that financials are a lagging indicator of a company's performance and health. And it's really customer behavior that's the predictive indicator or leading indicator of a company's performance and health.

Customer behavior. Awesome. That's a lot to unpack here. I want to make sure I got some of the key themes that you talked through. One was your approach around networking into an ecosystem. You talk through building out a market map, doing a buy build partner analysis. And then when you talk through product market fit, this is when you are looking, identifying their customers, really understanding their pain points, mapping it to the user Persona, mapping it to the economic buyer of that solution or who'd want to solve that pain point. And then you're classifying these companies into becoming either the encumbrant merging company or a New class.

That's right. You got it.

How much time you got? This is a lot of good stuff that we can take apart here.

I can go as long as you can go.

So back on the VC experience, because this is really interesting. Our company is like 50 people, 10 million run rate, so I get at least 6, 7 monthly inbound inquiries. Mostly VC, some PE. I know almost all of them though.

That's part of what makes sourcing painful.

Yeah, explain it. Cause I wanna know. Some of it's just if it's just folks you could tell that are calling just to fill up a CRM and stuff like that, I don't have time for em. If it's an inquiry from a customer, I'll take it. Because we got customers that are more PE firms than BC firms. But then it's like, okay, they actually understand a product or they're doing referrals and things like that, or if they've helped build pipeline, I'll take it. There's one investment firm I can think of, they've made some introductions to firms that have converted into accounts. We'll take those calls. But I'm just curious, what's the difference between the cold outreach and your approach when you say you network into an ecosystem?

Not everything I do may be different from what you're thinking, but I did pick up on the fact that you're more receptive to outreach if they're adding some type of value, helping build out your pipeline, et cetera. So there's a couple things that I do that works for me that I'll share. Not sure if it's entirely unique or not, but the first thing I do is I try to meet the founder CEO as early in the company's life cycle as possible.

If we have more time, we can like, sure, I'll talk to you.

No, I have all day. And so stating the obvious, probably for a lot of people, when I meet the founder and CEO for the first time, I am completely attentive. I'm completely engaged. I'm practicing active listening. I've been in countless investor meetings where I've seen other investors try to multitask in this initial meeting. And to me, I think this is a big, big loss of opportunity. It's a loss of opportunity to build a sincere connection with the founder and CEO from the very first touch point. So whenever I meet a founder and CEO, I make it an effort to put my phone on silent. I put my phone face down, I give them my undivided attention, they give me their undivided attention. And what I've seen is this allows us to go much deeper earlier in the relationship and really get a better understanding of what the mission is, what the strategic vision is, what the roadmap is, even what they're looking for out of value added capital partner. And this really is important because when it does come time for them to think about a fundraising activity or an exit opportunity, you've built that good rapport. You're connected with them. Second thing I do, which I think you alluded to a little bit, is actually try to add value. If and however I can, I make it a personal goal. Anytime I meet with founder, CEO, I actually try to leave them some type of value. And it can be anything small. And this is only if I can't add value. But it can be anything from small as just sharing industry research that could be relevant for them. It could be sharing tidbits that I've been hearing about their competitive space. It could be introducing to other capital partners, say if I'm not the right one at this particular time, and it could be referring talent. So you now have spoken to a founder and CEO. You understand their product roadmap, their growth vision. You should have a point of view on where they need to invest in their org chart. So in that case, I'll refer talent. And what I've come to find is when I do this over an extended period of time, and not just days and weeks, but really months, quarters, maybe even years, I build a much stronger relationship with this founder and CEO and one that's built on value exchange. And where this pays off is again, when it gets time for them to raise a round of equity or potentially sell, I'm in the discussion. And for a lot of these companies, in venture, the companies that have great traction aren't actively fundraising. And in M and A, the companies that are highest quality oftentimes are bought, they're not sold. So you have to be top of mind and kind of in the discussion already. Time back to zip. When we look into our CRM on our closed transactions and we trace back to when was the very first touchpoint, the founder, CEO, it could be years before and it's years before in terms of us cultivating and fostering a relationship that culminated in a successful transaction. And I guess one other thing, just quickly I'd point out that I do it's pretty interesting that my team actually does is something we call reverse coverage. So reverse coverage means we don't just wait for bankers to bring us deal flow and teasers. We, we proactively reach out to bankers and really cultivate a relationship. And in doing this, what we're doing is we're staying top of mind. We're keeping them updated on what our M and A priorities are. At the same time, we're able to pick their brains who are experts in their respective spaces, and then also understand what's coming down the pipeline for them. For us. Today, we've cultivated a list of over 200 investment makers around the world. Each member of my team is assigned a subset of that group and we're responsible for really fostering cultivating a relationship with them throughout the years. So in any given year, touch base with them multiple times here through zooms, coffees, lunches, et cetera. What this does is it ensures that anytime there's a sale process that's run in our respective space by these bankers, we're including the conversation. You know, if not we're one of the first calls or first emails.

Private equity firms, do you take a similar approach to them?

Do we also do reverse coverage for private. Yeah, yeah. So exactly right. We do reverse coverage for bankers, which are sources of deal flow, but also with really the owners who are sources of portfolio companies that they'll eventually sell. So actually PE and VC firms will actually do reverse coverage for as well.

This is some good stuff. Okay, so the VC business development experience. I like the fact we mentioned the understanding that the founder CEO's mission is strategic vision. I get that a lot. Where folks fall short on it. Recently had a larger company propose doing a merger and they're just like. You can tell they're not. It's just here's our math on how much value we would create. But there was never. Let me understand where this founder is taking this company or where he's trying to go. They kind of missed the mark on that one. So I see that as being really critical because every founder loves talking about that stuff. This is what's heart to us and what we exist for. So really important. So the mission, strategic vision, and then that point around adding value. I always think of it directly. Again, bring us customers, make some introduction to customers. But you have a really good point about the talent. Hey, where is the company making their next hires? Can you help make some introductions and things like that? These are really good things. I think there are strong elements along the lines. I wanted to ask you understand the customer's mission. You want to create value with the adding value. We'll make some introductions. This is a good approach, but in terms of like Getting in the door. Because even just getting that first conversation going, what does it end up taking you to get?

That you kind of hit it on the head too. On the receiving end, you can very quickly tell if it's an automated email or if it's one that's very shallow versus someone who has been thoughtful, understands the industry and has a more kind of personal touch message. So I try to veer to that second example, which is there's a personal touch to it. The outreach email should be concise, but there should be enough meat in it that shows that you understand what the company is and you actually are seeing. Is there a potential fit where you can help add value? And whenever I craft an email message in that manner, the response rate is much higher than if it's, hey, we're a programmatic acquirer. We compete in your space. Would you be open to talking?

Yes, I get a lot of that. I get a lot of those emails. Let's role play this out. Let's pretend Zip Davis is interested in Deal Room. What would your cold outreach email sound like?

A quick intro on the company. We are a programmatic acquirer, own a collection of dogemedian and software businesses. You know, cite some of our brands that are more relevant to the data room space. We're not in the data room space.

So the security companies probably.

Yeah. Could be interesting.

Hey, we're in security.

Maybe next paragraph would be as we're thinking about expanding our portfolio and your industry is particularly interesting for XYZ reasons. It'd be great for us to connect and start a dialogue. Would be great to get an understanding about your company, your strategic vision, and also just get a temperature check on your openness to M and A. Happy to discuss live. Let me know if you're available.

I like that.

Would you respond to that?

Either the first or second time.

Okay. Or persistence.

Sometimes you ignore the person the first time just to see if they're persistent. There's a little bit of that.

So there's that. And then also if you really kind of study their space, you'll know what conferences they typically attend. And if you're really trying to get smart in this space, then you should attend those conferences too. So now it's okay if I bump into you in the hallway at a conference, it's hey, Kisan, I sent you three emails now and I'm sure you're very busy. You haven't been able to respond. If you have five minutes, we'd love to just give a quick intro and learn a little Bit more about you. There's a certain point where if a founder and CEO is not interested, you just need to respect that.

But I think at a point about that relationship because I never heard of anybody that did a cold outreach and boom slam, close the deal within months. A lot of it was fostering relationship over a variable period of time.

That's right.

I had one on the podcast. Only 20 years. Got to know the person.

Wow.

They've been on the radar and talked to each other. But 20 years later, like right before his retirement, he got the deal done.

Wow. That's incredible. Testament to longevity and investing in a relationship.

Big time. Big time. So I got a little playbook I'm putting together here. We got this cold outreach approach. Got initial message which is thoughtful but sincere and keeping it short and sounding like a real person, not like a cut and paste template. And then getting that initial conversation, if you do it directly, talk through what's interesting to that CEO, founder and then how you can add value to them. So there's that approach and foster relationship. The other methods you mentioned the reverse coverage. Being proactive to reach out to the network of bankers covering your sector. E firms that have portfolios in your sector, venture capital firms, and then also the conferences for the who's who are attending in that sector as well. What else are we missing for deal sourcing?

I think those are the big ones.

We're airing out your whole playbook here on how you guys source deals.

Yeah, this MAA science. We're going to share some of the science on the conferences. Another little trick. Oftentimes you can ask for the attendee list in a conference if there's 200 plus attendees. Even if it's a two day conference, it's impossible to meet all 200 people. So obviously save that list. And then for all the founders or companies that could be interesting to you that you didn't meet during that week, you can send them a follow up email. Something along the lines of attended this conference, saw you on a panel, found this XYZ to be really insightful. I would love to learn more and connect. Here's an intro on myself.

That's a good point. I met a sales guy at a conference before and he told me he goes to this one conference twice a year and it's this whole entire pipeline. He's like, I get that list and I just go down that list till the next conference and then I re up.

There's a lot of kind of science behind conference planning. I'm a big believer in serendipity as well. But with conferences, the more deliberate you can be in terms of These are the 12 people you want to meet in person and then these are the following 12 people that are on the list that if you don't have time to meet, you want to follow up email. Being deliberate actually will produce more results. So I can see how someone can attend a conference and their entire year's pipeline is built if they're very deliberate about it.

Plan, prioritize, execute. Got to have a plan for your conference approach. Anything else are we missing in terms of approaches? There's like the direct, you've got the playbook first coverage and then conferences. The product market fit we talked through, I thought that was pretty interesting. In terms of an analysis, I was wondering is there like an example and you don't have to use one that's like specific to your company, but in terms of how you would approach building out a market map and then starting to go through and like how you would typically run through that type of analysis. And I'm trying to get more of the little steps in between it.

Yeah, sure. So market map, I mean just kind of starting there is market map just means really understanding the landscape and who all the constituents are in a particular ecosystem and the value chain. So just made up, let's say you're looking at a consumer app company, health app company that you want to invest in. So now you want to think about all of the different players in that ecosystem. So there's the kind of B2C consumer app where someone uses that app to do something, maybe to track a fitness activity. But then you want to also think about the market in terms of all of its partners, whether it be where does it get its content from? Maybe it's go to market is partnership with another meal kit company and really kind of map out all the different players that touch that company and then think about which ones will be attractive and a good fit for you to invest or acquire into and then once you identify that company. So in this made up example with a consumer app, to assess product market fit and really take a firsthand point of view and have independent research, what I would do personally is I would download and buy the app. So if you're assuming if you're assessing buying or investing in a company and you're able to use the product, you should use it. So I would buy and download the app. I would go through the entire user onboarding registration system, chronicle everything. So chronicle everything from the friction points in the UX to the trigger points to buying premium features and upgrading. Use the entire product, try out all the features and at the end of it, ask yourself, is this a good product or not? Is it a good product relative to competing products in the space? Is it a good product relative to the cost? And also be open minded that the answer may be no, but it also may not be for you. So you should really kind of open your mind to who the other user Personas and then put yourself in their shoes. Is this product interesting and compelling for them for the price? So you do all that and then you would want to do that for the top four other apps. So now you're looking at the top five apps in the space. Do the exact same exercise, download it, go through the user registration onboarding, try out the product, use all of its features. And then at the end of this exercise you would have now taken a look from firsthand perspective at all top five apps in this particular theme. And then you can create a grid, a grid to really compare and contrast all of the features between these five products. And then you come up with your own point of view of which company has really truly nailed product market fit. And then you can even take an even more granular basis or viewpoint and look at as product market fit on a feature by feature basis. And sometimes what you'll see is for a particular app or company, all the value accrues to one or two features that really have nailed product market fit. And then the rest are just nice to have bells and whistles. So that's one way of really digging into a product and having a firsthand point of view in certain situations. If you're able to use expert networks to really get a lot of insight into surveys or even just firsthand consumers who bought the product and really interview them and really understand what was their path to purchase and then seeing if that path is consistent with your path and your viewpoint. And so you can put all that together and now you see you can get a sense of where the market map of who all the players are, why the consumer app facing part of the business or sector is interesting for investment. And then double click into that to see, okay, this is the app, how is it good or not. And then compare it to the top competitor apps.

That's pretty hands on in the weeds, a lot of work, but that's your first step.

I wouldn't say that's necessarily the first step, but that is a step in the diligence process. When you think about the qualitative piece, of course we're leaving aside the core quantitative assessments, but if you're thinking about just studying a particular product, that's where I would start, which is you've really got to get the product in your hands and start developing a firsthand point of view.

And even if it's maybe not like a consumer product, it's like a B2B, probably sitting through a demo or something like that. Similar approach.

Yeah, yeah. If it's a B2B product and say it's meant for digital marketers, then if you're not a digital marketer, then you'd certainly want to get a subscription or a trial for your digital marketers at your company and have them try it.

Work them and say, hey, let's just review these different products. Okay, so we have the market map. We start honing in on this little segment, and we really start doing our diligence on these different products, doing our own product comparison analysis feature by feature, and getting a sense of strengths and weaknesses between these different products. Then what do we do?

That's where I would stop. In terms of assessing product market fit. And then there's, of course you can do diligence until you're blue in the face. There's just a long list. But in terms of just product market fit, I think that'll give you the 8020 rule, give you kind of the bulk of the value.

I go back to those buckets of like, hey, is this the incumbent versus emerging versus the new class?

Yeah, yeah, that's right.

I want to ask you questions, but I'm trying to keep it relevant to this interview because it's like this. That helps our business out.

Yeah, yeah, no, no, we can go any, any which way direction you want.

Well, you know, I'd say what's fun is like, I, I don't have an operational role in our company anymore. So a lot of this stuff that, when you talk about strategy gets me excited because things that I need to start thinking about. And we're doing some of this stuff right now, like, we're putting together a market map. We're starting to look at the adjacencies around our business and core product. And I, I, I think we haven't done this where it's like, all right, let's like, really get serious about it when we do start identifying it, because I think there's this part of where the product sit, then I think there's like, next part of getting to know people in the company and getting a sense of what the culture is like, because I feel like that's something I've come across where I can tell, like there's certain companies in our arena or adjacencies that we would work really well with and some that we wouldn't. I don't know if you've put that as a factor as you start looking at companies more seriously in terms of.

If you were to acquire a company, how does it relate to, I guess, adjacent companies?

Yeah, it's almost like the culture fit part when you start getting a sense of is that something that comes in later for you or do you start trying to get a sense of that early on?

That's a little bit later on, but it's certainly important in terms of the investment process, which is really thinking about how likely is it that you're able to successfully combine company cultures if one culture of a company is really making up an example leans into R and D and is really big into a lot of experimentation, which inevitably means a lot of failures. And that's culturally embraced at the company. Typically what you see is kind of an earlier stage company, sometimes a little bit higher R and D capex, a lot of more staff on engineering product, which may translate into a lower current margin profile. And then you contrast it with another company that maybe could be later stage. And really everything is around roi. Every decision they make is around roi. Then in that scenario, being very experimental without an ROI to show for it is not as embraced. And then so it comes down to a question of, okay, if you think you're going to combine both companies, which culture will emerge? Or maybe there's a scenario where you keep the culture separate, both people wear their own T shirts or is there kind of meeting in the middle? So those are all things that do come into play. But at the outset, when you're thinking about just the market landscape and then the company that you're interested in and how good that company is, when you view it from a lens of product market fit, I would say the culture fit is later stage in the process.

That makes sense. I think that that makes sense for a more pragmatic approach. And I'm. I'm also like reflecting on my own biases. I think as a founder where it's, hey, let me go meet the other executives to see if they're an asshole or a douchebag, and then we can go do the deep dive diligence.

Yeah, yeah, and that's a good point. Right? So some cultures are also, you know, a no jerks culture. And in some cultures it's if you are extremely High performer will tolerate jerks. So those are all things that you know, you can get a feel for when you meet the other company.

Yeah, I gotta learn from you. I should take more of that pragmatic approach and really mapping the space out and doing the diligence of the product because I think that's actually a better approach. More bottoms up as opposed to top down. Yeah, I'll try your way. We'll compare notes in here in six months.

Yeah, yeah, circle back.

Okay, so think of that same theme of unlocking new M and A strategies. I'm going to just think of our space. Right now it's like all the AI stuff is emerging and we're incorporating AI capabilities. But now all of a sudden we're looking at adjacency of contract analysis tools. Given that it's like a new thing, because really that was always a separate box. But now all of a sudden it seems like there's a opportunity to start converging products and capabilities. Would you just take an idea like that and really take your same thinking? Like we went through, did the market map, we started looking at all these products and we realized, wow, all this stuff out there is like for really big legal firms analyzing at millions of contracts. But there isn't a solution or we see a gap for something smaller. The 1 to 1000 contracts in typical M and A. How would you go about using that to open up a new strategy? And then I guess this would take us to that buy bill versus partner analysis.

Yeah. So I think what I'm hearing the question is you have a solution for contract reviews and it's meant for employees that are a little bit smaller between employees between, you said up to a thousand or so. While a lot of the incumbent solutions are really meant to serve much larger legal firms.

At least I kind of using a real example here. We sell a product, we use it to manage M and A. All this AI capabilities sort of leading to contract analysis. At the end of the day, you're taking unstructured data and you're structuring it and doing all kinds of cool stuff with it. Then when you start looking at that, that's more of the contract analysis space. When you look at that space, it's really servicing pretty high workflows of contract. And then you're saying okay, but there's a kind of a big broad space of folks that just want to do contract reviews for 30 contracts or 50 contracts. But there's no offering that really services that.

That's really interesting. So where I would Start is to really conduct research on that segment of folks that your perception is they don't really have a solution. And so now pick what's critical mass to you. But maybe your goal should be to talk to 10 to 15 people that are in the buyer's seat that are looking for a solution but are not buying because they don't think a solution exists. And then now really understanding, okay, what is it that the incumbent solutions is not satisfying for you and your needs. It might be just as simple as cost, it's just too expensive. But it might be other things. They might say, look, we don't need a Ferrari, just a car works, right? And we were willing to pay for it if it's a quarter of the price. Oh, that's an interesting insight. If you have 12 more interviews and everyone gives you the same consistent message, that can be an idea for a much more toned down, simple, easy to use product at a quarter of the price and you can start building off that. So I would say step one is really conduct the potential customer research and really get to know what their thinking is. One, what is the pain point in terms of the solution offerings currently in the market and then what their price elasticity or what they'd be willing to pay in terms of a product. I think those two would be good insights for you to come back, think about it a little bit more, reflect on it and then go on to the next step.

You really take this venture capital approach when you go through this exercise and it's interesting how you do it and then let it naturally lend to the business case of doing an acquisition in acquisitions.

Oftentimes the companies are a little bit later stage. So the discussion is just completely different versus you're talking to a seed stage company where it's really kind of a conceptual company. If it's a concept, then it's okay. Well, what can gives you conviction in the concept? I've spoken to a hundred customers or potential customers and they're all saying the same thing, that they have this problem and they're willing to pay this much to solve that problem. That's an interesting insight. That could be the kernel to really start a new company. You see how those discussions are less relevant maybe for a later stage company that's doing 50 million in EBITDA. And now you're thinking really about rate of change in terms of financials is really the core discussion.

I like it because it helps you keep an eye on your blind spot in terms of where does this company actually sit. Maybe they are the encumbrant and they are getting disrupted. They know that. But you're looking too close to the company versus looking at that whole market and seeing where things are moving and who are the other players and what they're doing.

Yeah, that's right. It's an interesting point, which is private market fit also is a point in time, so it can be fleeting. You might have product market fit today, but over the next year, if the consumer preferences start shifting, if the marketplace starts shifting where your competitors start more innovating and providing even better products, you actually may lose product market fit. And that may happen first before it actually starts seeping in and is reflected in your financials. So today things are great. You're growing top line, making it up 20% year over year. And then you in real time start losing your product market fit, given just the factors I mentioned. And then you'll start to see revenue in subsequent months start declining.

That's a good point. It's like literally looking long term, near term, forecast out from the product view of where the company's heading as opposed to just those lovely charts that always go up and to the right from financial models.

Always up to the right. They always hit a billion or 100 million revenue in year five.

Absolutely. The bankers. Do you ever use bankers on your deals?

Yeah, yeah, bankers are really helpful. We do source and we prioritize. Proprietary deal bankers are helpful and especially for larger deals. So larger to me means a company doing over 20 million a year in EBITDA. But bankers are helpful there.

On the buy side or on the sell side?

On the sell side in terms of bringing a deal flow. Right. Because nowadays it's unlikely that a company doing 20 million EBITDA will transact without running a formal process to ensure price discovery. But we've conducted such extensive research in all the spaces that we compete in, we oftentimes already have a target list of companies that we want to acquire and kind of mapped out. When we do receive an anonymous teaser from a banker, someone on my team, we can scan in a couple of minutes and we'll know the company is.

That's always fun.

Yeah, it's always fun and it's important because it gives us a speed advantage. Now since we go into the process with the pre research done with the thesis, with the rationale of why the companies make sense to acquire, in the very first meeting with management team, we can dive right into more strategic topics as opposed to spending that first meeting talking about the product or the business model. And so we go into A process with a pre built lead, so to speak. And then as long as we devote the proper resources to that opportunity, we should be able to sustain that lead throughout the process, which increases the odds of us having a successful outcome.

I like that. A good approach and good way to leverage those relationships. On using representation on the buy side though, seems like just if your company doing deals over a billion dollars, then you tend to throw a banker on there as like a CYA type of thing.

I can't speak directly to that because we typically don't use buy side bankers. So we do everything in house. Yeah, I mean, certain special situations, perhaps if it's a little bit more complex, but the typical buyout 100% acquisition that we complete, we're doing it all in house. We'll use, of course, third parties for legal advice or commercial diligence, QV vendors, et cetera. But in terms of an actual buy side banker that's representing us on our behalf in the negotiations, we're doing that in house.

So if I brought you a deal, then it's up to me to go get something on the sell side. There's no buy side search engagement.

That's right.

All right, fair enough. What about the public equity piece? What are some of the things that you've learned from that experience, that use in M and A?

So something that I still utilize heavily today in M and A from my time in public equities is the application of Mosaic theory, which I'll touch on in a second. But before I do, let me point out a big difference between diligence and M and A and public equities is the sheer amount of information that you can get directly from the management team. So if you're in M and A and you're a strategic or a sponsor, you can create a comprehensive list of information requests, due diligence requests, list of questions, even request access to their dashboards, whether it be Google Analytics or HubSpot. You send that list over to the company and in a very short amount of time you get answers to everything. You get written responses, you get call requests to walk through your questions orally. You get a data pack full of Excel files that answers all of your KPI requests. You might even get access to some of the dashboards you requested. And that's. So that's in M. That's obviously not how it works in public equities. In public equities, you're actually quite limited in what you get directly from the management team. You're limited to what they file to the sec, you're limited to what they post to the investor relations section of their website and then you're limited to what they say in public forums, whether that's to the press or to investors. Essentially that spans the qs, the ks, earnings releases, presentations, transcripts, non deal roadshows, investor conferences, and then the occasional interview to CNBC or a particular trade journal. And that's the extent of it. So as a public equity analyst, to become effective at really getting a much more real time sense of the company's health and performance, its competitive positioning, the headwinds, tailwinds that it's experiencing itself, but as well as its peers and the industry at large, you have to be very thoughtful in terms of what other pools of data can you research in order to get that view? Because you're not going to get directly from the company. And so when I was an equity analyst, my approach was really to think about the full value chain of the target company and all the constituents it touches. That meant for me to research and interview a target company's customers, competitors, partners, suppliers, if applicable, and also to look at alternative data sets. So that could be anything from credit card transaction data, say you're looking at a more consumer oriented business to audience data, web traffic from similar web or snlk. Again, if you're looking at a media asset as an analyst, the act of really taking all those disparate pieces of information and then analyzing them and then putting them together like Mosaic, into forming a cogent investment conclusion. The act of doing that is the Mosaic theory. And so that's highly utilized by fundamental equity analysts. But what I've come to find is an M and A is actually quite usable as well in specific situations. And really the main situation that I apply it to is when you're dealing with a larger company, it's an enterprise where they have a customer who's a public company, they have a competitor who's a public company, they may even have an acquirer or potential acquirer that's a public company. If that's the case, then it's a prime example for you to utilize the Mosaic theory. I'll make up an example. Let's say you're assessing investing or acquiring a company, a B2B martech company, and they serve large enterprises. In this case, I would think about three additional categories of companies to really analyze. Outside of what you get direct from the management team, putting aside the data room and the due diligence topics, breakout sessions you have with management team and senior leadership, the three categories I would think about and analyze would be the first would be its customers. So in this made up example, let's say there's a large customer and it's a public company. So here what you can do is you'd pour over the financials, reports, the transcripts and really try to glean anything you can into two questions. One, how likely is it the customer will continue spending on the target company? Solution? That's number one. Number two, what would be the rate of change? Will they spend more, less, hold the same? And what you'll see in certain situations is management will tell you of the target company that everything's rosing great. Top line's growing by 30% year over year and they're going to continue growing because they're going to increase spend with existing customers. Then when you look at the largest customer who's a public company, again this is a made up example, you see they're actually declining in revenue the last several quarters year over year, say 3%. Moreover, the CFO is guiding to margin expansion, so cost takeout and streamlined costs. So now it makes you question how can two things be true at once? You're saying that the target customer is showing that it's declining top line and it's going to cut costs, yet CEO management team of the target company is telling you no, they're going to actually probably increase spending with us by 30% a year. Now that may be possible and may be true, but at a minimum this becomes another point of discussion for you to investigate further with the management team. So that's one category. Second category would be competitors. So here if you have a public company that's a competitor to your target company, you can do a pure benchmarking exercise. And really what this means is you're putting the P and L side by side. Pay particular attention to revenue and margins. So with respect to revenues, what you do is look at the top line growth rate of your target company, do the same for the competitor company and then do the same for the industry at large. The industry cagr. This will tell you a couple of things. It'll tell you who the share gainers and losers are based on the growth rates, right? And then also by looking at the sheer dollar value of revenue capture, you'll get an understanding of where each company is in their customer adoption life cycle. And so that's telling on the revenue side. With respect to margins, we would look at both gross and operating. And the key question here to really think about, is there something structurally different between your company that you're assessing and the competitor that should drive a difference in OLL as a percentage of revenue or OPEX as a percentage of revenue. Say hypothetically they might have different go to markets, one's product led, one's salesforce led. That could be the case. But if that's not the case, then now you can conclude, okay, the operations are actually the same structurally. Then now you can see if your target company is either over earning or under earning relative to the competitor. And if they're under earning, in our case, sometimes we actually would log that as a source of opportunity where we can address in the value creation plan, post closed. And then lastly, the third category company is natural acquirers. So here you're trying to think about your bidding strategy. Trying to think if you are in an auction process, who else are you competing with? And so naturally you could be competing with a larger company that's going to acquire, that's a public company. And you want to think about if they were to compete, what would they offer in terms of price, which gives you an idea of where you need to be to be competitive. So here the first question I would really think through is who's a natural acquirer of their target company? And so the way I think about it is if the target company provides a product or solution that fills an immediate or clear hole in the larger acquirers company's product suite and they've stated publicly they're looking to move in that direction, then I'd classify that company as potentially a natural acquirer. And then from here you can think about and really pour over again the financials, investor days and transcripts to really think about anything. They state about their M and A strategy, Where's M and A fall in their capital allocation priorities? How exquisite has company been in the last several years when they've acquired a company? Is there a type of company that they acquire, is it a certain type of IP or content? There's a certain type of geography, is there a certain type of business model? And once you have that sense down now you can look at valuations. What's the largest deal that they acquired in the past? What's the smallest deal they acquired in the past? Is there a sweet spot where you notice kind of a range of prices that kind of clusters around? And then of course you take all those figures put in the numerator and relate them to KPIs and financials. So now you get multiple on everything from audience, user size, mao daos, depending on business model, and then put those purchase prices over financials to get multiples, over revenue, ebitda, free cash flow. You run all that through the wash. And now you have a sense of okay, here is a natural car that you might be competing with in a bid auction. And if so, here's the range of prices you think they'll pay, which will be informative for your bidding strategy. I know that was long winded, but that in a nutshell is the mosaic theory which is highly commonly used by fundamental equity analysts. But in certain situations I found actually very applicable in MA as well.

We got a few different pillars. It sounds like the customers, competitors, potential buyers. Do you do a lot with suppliers or not that much?

Sometimes, but it really depends on the business model. Right. I think suppliers, if you're creating hard physical goods, I think suppliers is a much more important area topic. But a lot of business that we're looking at are very much capital light. A lot of them are digital media assets and software businesses. So less so important. But there are some edge cases where we would look into that.

All right, so optional on the suppliers, but mainly customers, competitors, potential buyers. I like how you go deep on these areas, but it rolls up into this pretty macro view of this business and the whole ecosystem. I think that kind of lends similar to the way we described that venture capital sort of approach and doing that kind of product fit analysis.

Yeah, yeah. And I don't think it's necessarily either or because to your point, it kind of rolls up into kind of top down picture. And in certain situations I'm sure people can justify starting bottom up first or starting top down first. I think there's merits to both approaches in many ways that it's going to cap it. Yeah, that's approach that works for me.

So customers really understand the customers, their behavior, the spend on this, the competitors. Pure benchmark. Sound like a good approach. That way you get a good understanding of where the different competitors are going and where they sit. And then the potential buyers, obviously you can figure out who the natural buyers would be. Then you can get a sense of how acquisitive they are. And that's where I think it's fun for good public companies like yours. You learn so much about M and A, even going through like S1 filings to even see deals they've done before they went public. Using that information to get a sense of valuation and what others would actually do in the market.

That's right.

What do you think's the hardest part when someone wants to emulate your strategy?

The hardest thing is fusing M and A into the culture of the company. Partly what makes it challenging is it takes an extended period of time. An extended period of time of just repeated reps and sets. Ziff Davis as a company is highly acquisitive. We've completed approximately 40 transactions in the last five years and we have a very highly functioning, well oiled machine in terms of the M and A program and team. So with every closed transaction we increase efficiencies, we gain learnings, we, we reinforce this muscle memory. And by continuously reinforcing this muscle memory, what we've done is we've converted or turned M and A as one growth tool into something that's very natural and almost instinctive for the company as opposed to being a tool that's pulled out of the toolbox every other year and has to be dusted off and relearned. And so that allows us really to move with speed, which in certain situations becomes a big advantage.

It's building your M and A muscle.

Building precisely. Yeah, building it and then also just consistently keeping it in shape or reinforcing it.

That's what's going to make it tough for someone to copy what you guys do.

That would be my take.

I think you're right. I feel like the last few interviews had something along those lines to say. Yeah, when you switched over to M and A, given your background, you didn't come up through banking, you came up through the public equities and venture capital. What was the hardest part of transitioning?

So I've been in M and A for a while now, but I guess when I first joined where I want to hone my craft was really around becoming more deliberate in terms of how I want to compete in a highly competitive bid auction process. So in a highly competitive bid auction process, you're competing on a variety of fronts. You're competing on price, competing on speed, certainty, ease of transacting, and the only way you can ensure victory is if you offer the highest price. Now if you don't want to just completely lean on that lever to compete, then the more clear eyed you are going into a process in terms of how you want to distinguish and differentiate yourself in a process, the more likely you'll have a shot at success and you can back it up here. Before moving to M and A, my job as a researcher and investor, my core responsibility was to generate investment ideas for the firms I worked for. So that meant I spent all my time analyzing companies, interviewing management teams, conducting channel checks, tracking industries and markets, building models, forecasting where a company would be anywhere from one, three, five years out. All that's still very much important in M and A. But in M and A, there's an ad element in certain situations where you're in a competitive bid auction process and you need to be able to compete on those metrics that I mentioned. And I think for our team, over time, we've really leaned into speed and certainty as areas that we really compete and differentiate on. On speed, I don't need to belate a point. We built a system, a machine that works, is repeatable without any hubris. We can move as fast, if not faster, than any other party with respect to certainty. Something that we do a little bit differently from others, I think, is we actually do a lot of work, the initial bid stage. So I know it's common practice for some to almost flippantly throw in an initial bid IOI with a wide range just to get to the next stage and look at the data room.

Right.

That's not our approach. Our approach really is to spend the time doing the work, doing extremely detailed diligence at the initial bid stage given the information set. So that way, when we do put in a bid, it's a highly informed bid given the information set at that stage, speed and certainty has really been something that we've been able to differentiate on and there's been times where we're not the highest bidder and we end up winning the bid for one of those reasons. And then, so, going back to your question, so today I expect myself, but also my team to continue going extremely deep on the purely investment analytical perspective. Critical thinking there. But I also expect myself and my team to run an extremely tight process and ensure seamless execution. That way we continue to really lean into speed and certainty as a differentiator when it comes to auction processes.

That's what it comes down to, if you can build that as your skill, to be able to execute speed, certainty and put an offer on the table.

That's right. We also hear speed and certainty as a combination word, almost as if they're linked, but they're distinct. Speed is how quickly can you complete diligence, get the internal approvals and then wire the funds. Certainty is how likely is it that you can hold your offer through confirmatory and close when you say you're in close. And so those are two things that we think about as discrete items and we try to be very strong in both.

You got to do that. That's what it comes down to. You're actually putting a substantial offer and Committing to it, that's a big thing. There's not a lot of industries that take that big of a bet or cut that big of a check.

Yeah, stating the obvious, but that's given the information set in stage one. In stage two, if there are new learnings that are contrary to our thesis or belief at stage one, then we'll have to accommodate accordingly.

Makes it tough. Yes, everybody wants to get the offer on the table, but then little do they know. For fun, I got some AI related questions here. On a scale of 1 to 10, how excited are you about AI and M and A?

Very excited. On a scale 1 to 10 I'm at a 9. So I think AI will transform all of our workflows in M and A. It'll help us surface more insights, it'll drive better long term decision making. Reason I'm at a 9 and not a 10 is I think we will need to be patient over the next year, maybe a couple as a lot of these tools get experimented on, refined and really become more enterprise grade deployable. I'll give you an example. While certainly possible, I have a hard time seeing that an AI co pilot or agent becoming better than an associate at updating a financial model or say new information uploaded to data room or creating a SIM from scratch or writing an investment member and to do it at a high quality level. So while certainly possible, I think we're at least a year, maybe a couple years out from that.

Are you currently using AI in your practice?

We are experimenting with a variety of tools a lot around increasing efficiencies in our day to day workflows. So everything from recording call notes automatically to summarizing meeting takeaways, next steps, action plans to creating outlines for new memos, and more recently looking at AI powered sourcing tools really to help us better find our next acquisition target. But right now it's really kind of in that trial and experimentation stage. Haven't really fully integrated any particular tool into our data workflows just yet.

There's a lot out there. We're going through a big hype cycle so you have to disseminate between generic AI and stuff that's very industry use case oriented.

Yeah, no, I'd love to pick your brain maybe offline in terms of tools are working well for you.

What tasks would you prioritize to apply.

AI to AI is going to transform the entire stack of M and A activities. Sourcing, diligence, execution, integration. What I'd like to see the most help in the near term is around diligence and specifically within the data room. So I'll give you an example. What I would like to see, what would be very helpful for me is if there's an AI copilot agent that I can deploy into a data room and within two seconds it can summarize all the key findings in the 100 plus files in the data room and it can flag for me all the key risks, classify them as yellow flags, red flags. It can summarize all the key variances between management's forecast and where the company is pacing. It can summarize all the key changes in Trend lines between KPIs and financials and then allow me to interface with the data room really in a natural language manner. So at a minimum, like a chatgpt where it's a chatbot, I can type in questions and it'll answer it instantly based on what knows in the data room and better yet even voice activated. Or if I can just talk to it and ask a question. That would be incredible. Just thinking out loud here, what if the AI can actually be an attendee of your internal meetings? Say it's a more of a passive or ambient attendee where it's on the side of your Google Meet, it's listening to the conversation that's being held and it'll actually offer up insights that builds on people's points. And then taking a step further, if it hears a question that it knows it can answer from information in the data room, it'll instantly answer it in the box inside. How many times have we been in an IC meeting where someone asks are the actuals through April or May? And then there's this pause and you being the one built the model, you're on the shared drive, you download the Excel and then you open Excel and then Excel crashes and now you've lost a minute. Why can't the AI just hear that question and just know from the data room an answer on the spot? That would be incredibly powerful.

I like it. You had a great vision of AI for the future.

It all starts with just thinking about what gives me friction and pain points every day. And now if you can throw an AI at it, then that could be usually helpful. And you think about what separates AI from humans when it comes to in this regard of data rooms is AI has perfect recall and it has perfect extraction. So those are two traits that are incredibly natural to build directly into a data room.

Yeah, I completely agree. I'll just share some thoughts because this is what the notes I picked up that this year I've interviewed about 50 customers around AI use cases. The one we're really focused on is legal diligence, mainly doing extraction of some type. Because if you look at any organization, they all have customers, employees and vendors. There's contracts associated with all of them. It's so much around extracting key information out of those contracts to be able to do analysis. And then right now we're deploying like a comparative. You got two insurance policies. What are the difference between the two? If you have a base template you use for employment agreement and you want to check 50 of them and know which ones are different or have some negotiated clauses that are different, that's probably the main use case that's emerging right now, which has been there. There's been a lot of contract analysis tools we talked about earlier, but it's just going to be simplified. So it's just part of the daily workflow. That's where I brought that up. That's why I was interested in that.

Yeah.

Then there's AI search. Just getting really good at search. And this is where some of the stuff where you want to get information, that's somewhere in the data room. There is some limitations to that now. Like you just can't put all the information through AI and it just magically gives it to you. It just, it just hallucinates and that's. You don't get really good, accurate results. What we're finding is like you take that extraction approach where you take the document, detect what the document is, extract the key information, then it gives you more of like that rag. What does the RAG stand for? I keep forgetting. But you know where they can like dig into information that's more specific to what you're looking for and know what information to pull in there and give you more of an accurate result. That's. There's some work to actually do. That's where we're for us really working closely with customers to understand and build around their specific workflow and use cases to get that kind of result. Otherwise, like out of the box. No, it doesn't matter. Yeah.

In a way, you're kind of crowdsourcing your product. Roadmap what annoys you every day. Okay. Can our engineering team build a product to address that?

Basically the only thing that gets nuanced because every industry has all these variants to it. But we're starting to get some fundamentals that here's some building blocks that you can start with and then you would just start tailoring some of these templates to your firm and their specific approach and they're more yours. And I think that third level, this is probably talking along the lines with the future view, is like platform AI, that now you have something that continuously learns as you're doing more deals. It's got historic information. You want to know how long does it take HR to run through diligence on a type of deal like this? You'll have that information, insight or what the common bottlenecks are going to be in the type of deal you're running. In terms of your predictions on the future of AI and M&A, what are your thoughts there?

AI will transform M&A activities really in three phases. So the first phase is automation. Second phase is insights. Third phase is prediction in automation. As the name implies, this is really how can AI give me tools to automate away my lower value added activities and then give me the tools to increase my efficiency and throughput on higher value added critical thinking type activities. I think you're starting to see some tools emerge on there, but I think there's still a lot of refining and experimenting that needs to be done. And then the second phase is really around prediction. And this is really how can AI lean into its strength, which is ability to digest and analyze data at a much higher level in throughput than humans can. Right. Really just ingest big data, really leverage its tool in terms or its ability to do pattern matching and pattern recognition at a level that humans can and then ultimately to surface us, the practitioners to insights that were either underappreciating or missing altogether. And this kind of goes back to my kind of data room example and sounds like your contract review example, which is there's a corpus of information, it can be structured, unstructured, deploying AI in there for it to organize and really extract out the key insights that help our decision making. And then the third phase is prediction, which I think gets really interesting. And I'm not sure how far away we are from this stage, but this is really where I'd like to be able to just have the AI tell me, is this a good deal or a bad deal? I want the AI to take a step further and say based on everything I know about you and the industry, here are the five companies you should go acquire in the next two years that would be extremely powerful and kind of the use case would be if we're thinking about acquiring a company, I'd love to have a platform where I can type in the name of the company. And now the AI can look at every deal in history that looks and smells like the deal that you're about to do. Same industry, same thesis, same target financials, et cetera. And give me a probability of success score and really on a variety of metrics. So from how likely is it that you'll achieve your pro forma target financials and synergies? How likely is it that you'll be able to retain management for longer than a year? How likely is it that you'll be able to combine culture successfully? We talked about culture earlier. How likely is it that you'll get your deal through regulatory approval and give you a probability score? And then there's the headline score, which is for all these reasons stated is this a good deal or bad deal? And this would be a point of view that's derived from a data driven, empirically evidence backed point of view. So this isn't just Spotify recommending your next song, this is actually really data driven. And then taking a step further, which I think would be really interesting, is what if you can feed the AI everything that you want to know about your company privately, also all public information and then it also takes external data on your competitors, the industry, where the industry's headed in terms of growth forecast. So now it's not only backwards looking but it's taking a forward looking point of view on where the industry's headed and where the puck is going, so to speak. And then it goes back to your stated mission, your stated growth strategy, capital allocation priorities. And it says taking all of these factors in account, these are the five companies you should go acquire the next two years with all the rationale behind it that's data backed. And just having that list going into a strategic planning session is incredibly powerful because even if you don't take any of the recommendations, just the dialogue that would spark would be invaluable. I'm really fascinated by or just excited by the prospect of that coming soon.

If one day I see announcement about you starting an AI company, I'm not going to be surprised.

I've been thinking a lot about the space and how our jobs can be much easier.

This is awesome. We'll have to catch up offline and I'd love to just show you some of the AI stuff and what we've been thinking about. Your background's unique. We covered the venture public equities background and there's a lot of folks that reach out to me that don't come up through banking or private equity and they're looking to break into M and A or just even advice for first time Practitioners in general, give me your best.

Yeah, sure. My advice for first time practitioners would be don't underestimate the value of firsthand and qualitative research. For a lot of people in the industry we can become exclusively focused on financial or quantitative analysis. So building out financial models, forecasting, KPIs running all kinds of sensitivities from on ad spend to return on investor capital, all that's still very important. But when you augment that with firsthand qualitative research, you achieve two things. One, you get a much more complete picture of the investment opportunity, more holistic view. And two, you actually identify more risk upfront which then you can mitigate through a mitigation plan. And so I talked about product market fit earlier. But it's very important where if you're assessing investing or acquiring company where you can actually use the product, it's important for you to actually try buy the product and use it. And that way you develop a firsthand point of view where you actually at the end of trying the product and all the features, you ask yourself is this a good product or not for the money, would you recommend this product to a family member? And again, being open minded, it may not be for you, but you should think about yourself and other potential user process owners. That's important. There's also a lot of information that you can get from social networks. So part of my investment process is anytime I'm looking at a company to assess, I'll go on LinkedIn and I'll read everything I can about that company, especially recently. So look at what the employees are posting about the company. Are they positive leaning? Are they negative leaning? Read the comments. There's actually a lot of insights in the comment section too. Are those comments positive leaning? Are they negative leaning? You can also look at job openings of senior leadership roles. For example, if the company you're looking at has a CTO job opening and it's been longer than a year, that may be indicative that the company's having trouble hiring top talent for a tech position. On the flip of that at how short tenures can be of senior leadership. So if the CMO you notice churns after every year, that could be suggestive of problems at the company in terms of lack of leadership, maybe lack of marketing direction. Those are all kind of telling signs, kind of. In a similar vein, part of my investment process is to go on Glassdoor and read about reviews, read about what the companies are saying about the employees are saying about the management team. And this will tell you a Couple of things, it'll tell you a temperature check in terms of the morale of the company. And then secondly, it also allow you to see if the reviews are consistent with the story that CEO is telling you. So the CEO is telling you, let's say in a made up example, the company's grown like a weed in the first four years, so everything's been great. Then year five they hit a growth wall, they had a right size and it went a riff. And then since then they've been steadily building the company back, recovering. So going into Glassdoor, even before I read the reviews, I should have a hypothesis that if I sort these reviews chronologically, I would think years one through four you'll see great reviews, everything's great, everything's growing. Then year five you'd see a lot of negative reviews, people are upset, there was a rift. And then since then, you would expect a modest rebound and uptick in employee reviews in terms of positivity. But then you go in the Glassdoor and what you've come to find is years one through five as expected. But beyond the rift point, you've noticed reviews have continued to worsen and worsen. That could be indicative, and that can be a kernel of insight where, okay, maybe the company hasn't won back their employee base, maybe the morale hasn't actually turned that corner as the CEO is telling you. So then now at a minimum, this is a discussion point that you need to have further with the management team to really reconcile their story with what employees are saying online. So all that to say is when you augment quantitative research with kind of firsthand point of view, qualitative research, it gives you a much more complete picture of the opportunity, also allows you to walk into any opportunity with eyes wide open in terms of what potential risks or underlying issues are with the company. And if you make this part of your investment process, I think longer term it should drive better decision making.

Golden advice for this whole podcast.

You think so?

I'm glad I think so. I 100% back it up. I know I generally agree with guests on the podcast because it's a nice thing to do, but this one I do believe in. I'm a huge believer in that approach of doing qualitative research, which is why I do these interviews. This is where I'm going to learn. I can read a bunch of M and A books, but I'm not going to learn nearly as much as Talking to active SMEs that are doing deals.

It could be almost, maybe it's not a Spicy take, but it's a mild take because. Or can be pursued as that. Because a lot of folks in the industry almost subscribe to the adage of if you can't quantify it, then it doesn't matter. And this is very much not saying that at all. That actually there's. When you can marry both sets of assessments, you actually become a more holistic investor.

That's a really good view. I gotta get better than the quantitative. I feel like data's lied to me a few times.

Oh, so you already leaned into the qualitative research, which is really important.

Heavily more so than the data. I'm always skeptical because I'm like, I don't trust this data. The chart's always going the same direction. Oh, this is good. What's the craziest thing you've seen in M and A?

I've seen a lot of crazy. I mean, I started my career in the gfc, so a lot of craziness has happened since. The craziest thing in recent memory is the 2021 valuation bubble. And that was a valuation bubble of high growth, unprofitable companies and more speculative areas of the market. So rewinding the clock a bit, 2021, I would describe that market as a year of exuberance. You had markets at all time highs, NASDAQ all time highs, number of SPAC issuance, IPOs, all time highs. And then you also saw really highs in speculative areas of market, from crypto to NFTs to meme stock and you had zero interest rates. So this was a risk on exuberant party for the market. And that risk on exuberance really spilled over into M and a deal making as well. And you saw all types of distortions in the market that year where I remember going through it real time questioning, are we in a bubble because of these really extreme things I was seeing in the marketplace? And so I can recall even getting QV for the company. We would be a one month wait list because all these consultancies had a backlog of projects they need to work through. I can recall deal timelines compress and compress to the point where it wasn't uncommon to receive a book and a process letter saying you have two weeks. No supporting model, no data pack, no access to management. Just tell us if you're interested in bidding in two weeks, which is just crazy. You also saw reps and warranty insurance almost become customary. It was great for that industry because it was a blockbuster year for them. But when you're thinking about Structure proposing a holdback was almost dead on arrival. And if you want to be competitive in the auction process, you had to use reps and warranty insurance. And so those are just crazy kind of things you saw in the marketplace. But I'll share a story that I think sums up the frenetic mood of that year quite well, which is a fellow VC shared with me a story that one of his friends who's a founder CEO surprised himself even at how quickly he was able to raise around a venture. He raised it in three days from meeting the vc, which is crazy. But even crazier than that was throughout the process, the VC never even asked him about the margin profile of his company, just purely invested in him on revenue. His story and his background, which I think just captures that's the type of mood and craziness we were living through in 2021.

That is crazy. What were some of the valuations you were seeing in 2021? You don't have to name any companies, but I'm just curious.

It wasn't uncommon for people to think in double digit revenue.

Asks yeah, I think I had a friend that told me he had a term she had 20x revenue and I was like take it.

Yeah, and hindsight's 20 20. But the justification in that year would be if I'm tripling the business every year, then 20 times revenue is cheap. And then you fast forward and for some companies you now see that okay, there was a huge pull forward in demand during 2021 or the economy has completely changed, et cetera. But yeah, living through it. There's always ways to defend valuations.

Crazy year. Yeah, yeah, this has been great. I appreciate taking the time helping me become a better M and A scientist. Those of you still with us love to hear some feedback. You can Find me on LinkedIn. Always like to hear from those that can listen through the whole entire podcast because you're a true M and A scientist for doing that. Love to hear from you in terms of feedback, suggestive speakers, any other topic ideas? Till next time. Here's to the deal. Thank you for taking the time to explore the world of M and A with our podcast. We love hearing feedback. Tag us on a LinkedIn post. Add a review on Apple Podcasts. We'd love to hear from you. If you need help standing up an M and a function or optimizing one that you already have, we're here to help. And if we can't help you, we probably know someone that can. You can reach out to me by email kisan k I-s o n a science.com or you can text me directly at 312-857-3711. If you just want to keep learning at your own pace, visit mascience.com for a lot more content and resources. That's where you can also subscribe to our newsletter. Again, that's mascience.com here's to the deal. Views and opinions expressed on MNA Science reflect only those individuals and do not reflect the views of any company or entity mentioned or affiliated with any individual. This podcast is purely educational and is not intended to serve as a basis for any investment or financial decisions.