How I Predicted Spotify's "Turnaround."
Update
Edited by Brian Birnbaum and an update of my original Amazon, Hims, Spotify and Uber deep dives.
The mental model that has made me millions of dollars and I expect will make me hundreds of millions of $ going forward.
As you can see in the graph below, Spotify’s free cash flow per share continues to grow exponentially. As a result, the stock is now up over 500% since I initiated a significant position. For many, this is a shocking development because just a few years ago the consensus was that Spotify was a bad business. However, the mental model that I used to see ahead for Spotify is widely applicable and I believe will enable me to spot many other success stories before the market does.
In the rest of this write up I’ll break down this model for you, so that you can use it too.
The economy is evolving into a collection of networks.
The first component of this mental model is understanding what’s happening in the broader economy. The economy is evolving into a collection of networks in which the winners are total. Meta has captured the world’s social fabric; Amazon has captured the world’s commerce; and Netflix has taken over the world’s entertainment industry. In relative terms, all they’ve done is aggregate previously existing resources into a single network.
To win, you need to have the biggest network.
Owning the biggest network unleashes network effects, which yield much more rapid growth than previous business formats ever could’ve. Indeed, these companies aggregate as many network participants as they can because scale decreases the cost per additional network participant–a virtuous cycle. More capital amassed well reinvested makes the flywheel spin faster.
It thus follows that in the network-defined economy, scale is far more important than profits specifically because scale dramatically increases profits in the future. We’ve seen the market complain repeatedly when Amazon posts “low profits”--only for Amazon to then post record-breaking numbers yet again. We’re seeing this happen with Spotify now, and going forward, this sort dynamic will only become more prevalent as networks come to dominate additional industries.
When it comes to networks, value lights up the income statement only in later stages.
Networks create value differently than traditional vehicles. Since the most important thing is achieving leading scale, for decades it may look like the company in question is not creating any value. But the network, by solving acute problems, is constantly attracting new users.
Scaled economies shared represent the most powerful moat in the modern economy.
The world’s leading networks tend to share economies of scale with customers. As they get bigger, they reinvest more capital to deliver more value to network participants at lower prices. If you study Amazon closely, you will see that they constantly reinvest capital to bring down prices, increase selection breadth, and deliver ever-higher levels of convenience for customers.
In the short term, this reduces profits. Over the long term, this yields a massive network of highly loyal customers that do not even contemplate buying from alternative companies. Per the way networks are built, this creates a near insurmountable moat. Disruption requires a new network to come along that provides meaningfully more value to customers at a lower cost–and without a fundamental technology shift, the odds of this happening tend to zero.
For instance, for Amazon to be disrupted either it has to kill itself or we need to see new tech emerge that rewrites the rules of the game. Which we should always be wary of, but also realistic about.
Rapid user growth tends to be the result of extraordinary organizational properties or process power.
World-class networks tend to emerge from extraordinary organizations. In a world of free information flow, initially there’s no reason for users to join a network unless it happens to delight them. To get there, companies often have to be highly customer-centric and unreasonably prone to experiment and fail relentlessly in order to attract more users than competing networks. In essence, these organizations have to be finely tuned machines that convert market signals into value more efficiently than competitors.
The first step is a highly qualitative exercise. But winners betray themselves, performing one impossible feat after another, such that the odds of overcoming all of them are near zero. When a company defies odds in that manner, sustainably and over time, it’s usually indicative of extraordinary organizational properties. In turn, this greatly increases the odds of the network in question succeeding over time.
For example, Hims has built a vertically integrated infrastructure to bring on-demand personalized medicine at scale while operating outside the traditional insurance-based healthcare system. The odds of this were essentially zero, yet they succeeded. I term this process power–a company with unwavering focus, determination, and talent.
Additionally, over the long term a marginal advantage in adoption yields exponential advantages in terms of the resulting user bases. We’ve seen this with Spotify–the user experience has subtly led that offered by Apple or Amazon Music.
Extraordinary process power tends to equate to higher average revenue per user, until .
Networks must solve a specific problem to gain traction. For example, Amazon started selling books and Uber with black cabs in San Francisco. However, the same organizational properties that have enabled these companies to scale their network also allow them to successfully enhance their scope. This is generally true for other extraordinary organizations.
Over time, both Amazon and Uber have notably increased the breadth of their offerings. This is because the infrastructure required to sell additional products and services resembles the original. Marginal investments tend to open up new and infinite lines of business, that suddenly make the value of the network show in the income and cash flow statement.
Spotify streaming music led to adding podcasts, audiobooks, and an ever growing list of additional verticals. They are even pushing into video now and are on their way to competing with Youtube. Because they haven’t had to rebuild the entire company to do this, together with some newly-acquired focus on cost efficiencies, they’ve yielded tremendous operating leverage, which has sent the stock flying in a short period of time.
Networks are about to enter their golden age thanks to proprietary data.
While there are meaningful odds of blockchain disrupting centralized networks at some point in the future, leading networks are about to get way bigger. Their unmatched scale and engagement gives way to proprietary datasets that are now enabling these companies to train AI models that no one else can. As these AI models come online, I expect two things will happen:
Exponentially more value will be delivered to network participants at a marginal cost.
The moat’s of these platforms will get stronger as the AI models yield more engagement and stronger datasets, which will in turn make the models smarter and thus spinning the flywheel over time.
Five years from now, I believe that these networks will be seen as boot loaders of AI models that the world will come to rely on to solve various problems. For instance, I believe that while there are above-zero odds that Tesla disrupts Uber, I think it’s more likely that Uber evolves to be the AI model that manages the world’s fleet of autonomous vehicles. I also believe that Amazon’s personal shopping assistant, Rufus, will create more value over the next decade than the entire ecommerce operation has created for the past two decades.
Thus, I believe these networks’ best days are ahead of them. The rest of the economy is going to follow suit. Networks will take over the most remote corners of the global economy over time, which should yield plenty of attractive investment opportunities based on this mental model going forward.
Don’t be fooled by the income statement.
All the above is to say, don’t be fooled by the income statement. Quantitatively, value takes a long time to appear in a way that can be identified by classically trained analysts. Further, companies of this sort tend to engineer their income statement in order to minimise paper profits and thus taxes.
Spotify is a great example of this–for years they’ve “lost money”--while their cash flow has been rather healthy and created a strong balance sheet over time. In Spotify’s case, focusing on the cash flows versus the income statement has made me a lot of money. This goes especially for successful networks.
I teach this mental model in depth in my Tech Stock Goldmine course. My students love that, in under 2 hours, they get access to what it took me ten thousand hours to learn.
I’ve put tremendous effort into synthesizing this powerful and elegant mental framework that enables you to absorb all my knowledge with a fraction of the effort it has taken me to acquire it.
Having seen over 400 students go through it successfully now, I can tell you that it works and you can obtain lifetime access for just $350. Don’t miss out.
Until next time!
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Great information as always Antonio, you’re doing really cool analysis on the leading edge of investing.
No one can predict the future. Luck is not predicting.