NCI: Hunting The Next 10Xers In Tech

Ram Ahluwalia: [00:00:00] In this episode, why is this so cheap? Given the revenue growth and the free cashflow, they have an AI narrative. They're international. They have many embedded real options, many ways to win. 

Mark Mahaney: Maybe three reasons. Those 50 million households that don't have Netflix. Now, some of them just won't be able to afford it if I get that.

But was there something that Netflix hasn't offered you as a consumer that they're going to start offering you now that'll expand their market? If you have a product that's ubiquitous like Google is, and the product gets better, guess what people do? When you see ads for financial products, the tagline always goes, past performance is no indicator of future performance.

I don't think that's true with 

Ram Ahluwalia: companies. Welcome to Non Consensus Investing. I'm Ram Alawalia, your host and CIO at Lumida Wealth, where we specialize in the craft of alternative investments. At Lumida, we help guide clients through the intricacies of managing wealth so they don't have to shoulder the burden alone.

Through this podcast, we draw back the curtain to reveal the strategies employed [00:01:00] by the best in the business for their clients so that you too can invest beyond the ordinary. All right. I'm pleased to have Mark Mahaney join us today. In the next episode of a Lumida non consensus investing, Mark is a senior managing director and heads Evercore's internet research team.

He's covered internet stocks for over 25 years. So he's seen cycles and institutional investors recognize Mark for his research, including 17 years as a top three ranked analyst and five years as a top one ranked analyst. Mark received his MBA from University of Pennsylvania Wharton School, and he was also the former lead bassist for Monkey Funk.

So music and markets coming together, Mark, it's a real treat to have you here. I thoroughly enjoyed your book, Nothing But Net. I have a value approach to investing. I like growth at a reasonable price. I come from the. Peter Lynch School of Thought. [00:02:00] And I thought it was a great way to learn and test a new mental model around growth stock investing.

We'll dig into that in a moment. There's a book for those that are following online. So Mark, if I were to summarize the high level about your framework, you have a key focus on revenue growth, right? If there's one takeaway, it is, can you find a business that has call it six quarters. of 20 percent revenue growth.

And if you find a company that's going to miss that threshold then watch out. Is that a fair summary? 

Mark Mahaney: Ram, one, thanks, Tom, for including me and, or for having me on. Second, thanks for making the comments about positive comments about my book. I really appreciate it. And I tried to distill 25 years of great calls and bad calls.

In the internet sector, which I think is one of the two most dynamic sectors out there along with software over the last 10, 20 years, it's clearly had some phenomenal wealth creation stories [00:03:00] to it. Amazon, Meta, Google, Netflix, there are others, but those are the ones that most come to mind. It's also had some massive blowups, some small companies that probably never should have been in the public markets, maybe Blue Apron.

Companies that created a lot of value and then didn't create any more value after that. Yahoo probably destroyed value. eBay stock price the same as it was 20 years ago. Yeah, I'm exaggerating, but not by much. So I've seen a lot of stories here or there. And what I tried to focus on at the end of the day was my pitch.

to try to get out some one thing out of the book is I try to leave people with the acronym DHQ to invest in tech or growth areas look for DHQs hunt for DHQs and those are dislocated high quality companies and so I talked about four different things that I looked at in high quality companies things like companies that face you Large TAMs have very good at product innovation, have really compelling customer value propositions, and then have great management teams.

And I, my point about the 20 percent revenue growth is usually those four things. There's a [00:04:00] financial tell, which is that those companies that they put that together, they can sustain these premium revenue growth rates, 20 percent revenue growth at scale, by the way, not at, not off a couple of million in revenue.

I'm talking about doing it off a couple of billion in revenue. 10 billion even more impressive. There's three companies in history, I covered two of them, that were able to generate 20 percent revenue growth for 10 straight years after hitting a 25 billion revenue run rate. One was Apple, I didn't cover Apple.

The other one was Amazon, one was Google. And I think those kind of four criteria were there. And maybe even a better numbers way to put it. I didn't put this so much directly in the book, but as I've thought about it time and time again, it's, you can find a company facing a really large TAM, total adjustable market, and having a single digit percent share of said TAM, especially if they're the market leader and you still got an early adoption.

You're early in the S curve of that market, whether that was online retail 20 years ago, maybe it was cloud computing five to 10 years ago. Today, it may well be things like robo taxis, but there's still [00:05:00] other things like delivery, which I think is still modestly penetrated, or even language learning. One of my favorite small cap names is Duolingo, and I like it because it's not a trillion dollar TAM, but it's a decent sized TAM, and they have single digit penetration of that TAM.

So that's the combination I look at. The financial tell of all that are these premium revenue growth rates, and 20 percent revenue growth at scale, that's really impressive. That's four, five, six times faster than GDP growth. In order to do that. You have to have something special about your business. And so that's the tell that I look for.

I try to find those high quality companies. And then as an investor, I do prefer when they get dislocated and there's a lot of ways to describe that, but sometimes it's as simple as a 20 to 30 percent sell off. What I found is that. The best assets that I've ever seen in tech, they all get dislocated from time to time.

They all do. And it's sometimes it's company specific hiccups, and these are all human managers. They make mistakes or there's dealing with intense competition, and they have to figure out a few moves on the chessboard. Or they're just [00:06:00] market rollovers. And of course, they're COVID events and things like that, that just create, give you an NVIDIA, if that's a high quality name.

And I assume it is, I don't directly cover it, but a Microsoft, a Google or an Amazon or a Meta, they give, they get, you get these stocks at a 30 percent discount. You want to buy high quality names on their own discount as opposed. To hunting for low quality names that are super cheap. I'd rather buy high quality names that are somewhat cheap.

Ram Ahluwalia: You want to find the Mercedes when markets are on sale. We saw this with Google back in February when there was a death of search from open AI. Google rallied 60 to 80 percent since then, since pulled back a bit. After MetaSKU on earnings, it dropped something like 15 to 20 percent right on earnings.

That was a great buy. And then more recently, NVIDIA. So dislocated high quality assets makes a lot of sense. Large TAMs, compelling customer value prop, great management teams. And then your summary financial metric that tell is that 20 percent revenue growth [00:07:00] at scale. So what about other factors? For example, you spotted Amazon in the early 2010s.

And that was a great call on your part. Are there other criteria you're looking for? For example, the ability of a company to self finance their own growth and therefore not have to issue shares and low share based compensation? 

Mark Mahaney: Yes. And of course the business model matters too and valuation does matter.

I guess one of the lessons I've learned, so many of these names, Uber is a wonderful example of this and it was a real time example for me in my book and it's been a real time example for the last couple of years. This one, public. I forget now, 2018 or 2019, before COVID, and I think it was in 2018, and the stock went public with, I think, with the largest amount of losses that a public company had ever gone public before, like on a gap basis, they lost 8 billion the year before, and it was really uncertain as to whether something like this could be profitable, the delivery side, Our business is far from profitability, and [00:08:00] I, what I try to do is, this is tough for value investors, but for long term oriented investors, you're, you don't have, you don't have to buy any company that's not profitable, you can wait for them to be profitable, I just, I would ask you to think about their, You get a chance to buy a company earlier stage, just because it's young doesn't mean it's not going to be nicely profitable when it reaches maturity.

So let's not, you want to, so I tried to lay in a couple of exercises to go through to try to figure out whether a big loss generating asset like Uber could one day, generate a lot of profits. It turns out it did. The market was deeply skeptical about that. And I generally found that most businesses can scale their way to profitability.

And Amazon did that. And there was a decade when it was very unclear whether they could generate profits. But if you stuck with a few metrics And you just ask yourself the basic question, are there any comps in the market that are similar to this, where there's proof that the business model can be positive?

That made investing potentially in Snap or Pinterest [00:09:00] or even Twitter, when they went public, easy. Because there was this asset called Facebook that was dramatically positive at scale. So there's no reason these couldn't be. There's no structural problem with these business models, or you could look at part of the business that was profitable.

And I think you could do that with, I think Netflix, maybe early on, you could see part of the business was profitable or better yet with Uber. There, there were markets that gave you enough disclosure to realize in some markets where they had enough presence, enough scale. They were profitable, so the action question wasn't could they be profitable, the action question was can they scale enough than the other markets, and if you believe that they could, then you could see a way to significant amount of profitability.

Sorry, Rom, I think I went off on a little bit of a tangent, but that's the kind of stuff I look for and it's even easier, like if you can catch a model that isn't profitable, but You can have reasonable conviction, can be profitable long term. There's a lot of value creation between not being profitable and being profitable, and then from being profitable to very profitable.

There's value creation along the way. 

Ram Ahluwalia: Got it. So if you can catch that kink in the curve when the firm is going from not [00:10:00] profitable to profitable, and if you can use a comp that helps, as in the case of Snap, Hey there, hope you are enjoying this episode. Make sure you never miss out by subscribing and following Lumida Wealth on your favorite social media, Instagram, TikTok, YouTube, and X.

Links are in description or just look up Lumida Wealth on any of these channels for more. Your support helps us bring the latest non consensus thinking from experts so that you too Can invest beyond the ordinary. Now, Uber is quite challenging. They're the category leader. They're building a category with Lyft.

There was no comp there other than valuation metrics like price to sales, because they're not profitable. So are you building out a financial model and then running a classic? DCF at that point, are you looking at a multiple and saying, this is fairly priced? How did you approach that scenario? 

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