Netflix, Spotify, Airbnb: how investors might approach the modern breed of companies
When Facebook was in its infancy and only used by a small group of Harvard college students, its value was relatively limited. As it took off, spreading across US campuses and out into the wider world, its usefulness grew exponentially. The more people that created accounts, the more indispensable an account became, leading people to sign up en masse.
This is known as a “network effect”. And everyone wants one.
Indeed, it has become one of the most popular phrases in marketing material and investment reports in recent years. The advantages are clear: self-perpetuating virtues and huge growth potential, allied with powerful barriers to entry. The classical networks from the 19th and 20th centuries (railroads, telecoms, payments) took a great deal of time, capital and effort to build. The results were powerful, so much so that they attracted regulation in every instance.
In the 21st century, network appeal is as great as ever. But cloud and smartphone revolutions have accelerated the building process. Unlike their predecessors, modern network-building platforms are not in most cases inventing new products or even services. Instead, they are aggregating existing resource (cars, labour, houses, food) and in many cases disrupting business models that have been in place for decades (taxi firms, hotels, etc).
This generates tremendous value (who isn’t still at least a little bit impressed when an Uber glides up to your exact location?) for which the platform builder hopes to earn a profit. These “platform fees” vary, but typically average around 30% of consumer spending.
Since most modern platforms are asset light, they are able to grow rapidly and this is a key criterion for success; a hallmark of widespread consumer interest. Many use cloud infrastructure such as Amazon Web Services to begin with, although many take it back in house at a later stage as the economics become more compelling.
As agency businesses, revenues are reported after deducting the biggest share - that of the asset owner (Uber’s drivers, JustEat’s restaurants, Airbnb’s home owners etc). It is tempting therefore to believe that platform profit margins should naturally be high - yet this is not necessarily true.
Applying the analytic tool known as Porter’s Five Forces Framework - which economists use to determine the competitiveness of a business - reveals some similarities across platforms:
- Buyer power (ie the pressure consumers can exert to get businesses to provide higher quality products, better customer service, and lower prices) is low as they are all mass consumer offerings
- Switching costs (the cost of switching to a different brand) for consumers are also low – usually just a matter of re-entering payment details
- Medium threat of new entrants – technically low but elevated by the sheer size of the table stakes (Uber and Netflix lost $6bn last year)
However, the analysis also shows an important difference in supplier power (the pressure suppliers can exert on businesses by raising prices, lowering quality, or reducing product availability), likely a crucial factor in determining gross margin (value add):
|Platform||Service||Switching costs||New entrant threat||Substitutes||Supplier power||Aggregator gross margin|
|Spotify||Music streaming||High||Low||Apple Music||Very high||35%|
|Netflix||Video streaming||Medium||Medium||Hulu, linear, cable||High||35%|
|JustEat (no delivery)||Takeaway food||Low||Medium||Yes||Low||90%|
|Air BnB||House sharing||Low||Medium||Booking.com||Very low||90% (est.)|
|Booking||Hotel booking||Low||High||Expedia, Hotel Direct||Medium||90%|
|Platforms that invented a service/product|
|Apple app store||App hosting||High||Low||Android||Low||90%|
|Google (core)||Search||Low||Low||Limited - Bing?||Low||87%|
|Social media||High||Medium||Low (direct), High, (indirect)||Low||83%|
Source: Schroders, April 2019
Interestingly, most platforms are already duopolistic. The competitors may differ by region and a tail of smaller competitors / new entrants often co-exists; but almost everywhere this is essentially a two horse race.
“You don’t have to outswim the shark. You just have to outswim the guy you’re scuba diving with.” Orrin Bach, Billions, Season 1.
What a race though! While money is cheap and there are market share gains still to be won, platforms will continue an expensive war of sales and marketing. Given low consumer loyalty and switching costs, the medium term game will be less about winning, and more about not losing.
Longer-term, all platforms would like to be the sole monopolistic provider, free to earn the spoils perpetually (or, at least, until they are regulated and the next big thing comes along). In practice, they will most likely settle for a 50% share (a level at which there is no incentive to cut prices) of a lucrative two player market. This should prove a continuing boon for consumers, while frustrating investors seeking short-term profitability as proof of concept.
For those with a longer-time horizon, today’s loss-making platforms could still make a strong investment. It will be a matter of weighing the long-term worth of their equilibrium profits against inevitable short-term losses and dilution. Estimating profits is only half the battle here; profits per share the other.
On a pragmatic note, outside of long-term judgements, monetary policy could have an outsized effect on near-term returns as lofty valuation multiples tend to move both inversely and with greater sensitivity to rising interest rates.
Firstly, each platform should be considered in its own right. The tendency to group stocks into acronyms (FAANG, BAT) is misleading in this regard. Ultimately, these businesses will prove very different propositions.
Broadly, I am more positive on higher gross margin companies. To the casual observer, platforms generally look the same: high revenue growth, no profits. In part, this is because higher gross profits simply enable higher spending on sales and marketing, and game theory dictates the only equilibrium strategy is to spend it. Yet longer term, the fundamental differences should prevail with higher value added companies in stronger positions.
But there are also other factors to bear in mind:
Execution is tough to judge from our distant perspective yet it can be the determinant of success, especially for the lower margin companies. In 2011, Netflix founder Reed Hastings told me there were no barriers to entry to his business, success would simply be a matter of doing it better than everyone else. It was a broad and painful lesson that sometimes that is enough.
Successful pivots and new markets
Many of the truly great technology stocks have been able to develop new products and services that investors cannot imagine (and hence value) at the outset. Clearly, there is no easy way to evaluate this and one must tread a careful line between excessive research & development, and the path to genuine discovery. Clues may exist and at the very least “if you don’t play, you can’t win”. Uber’s willingness to invest in driverless cars, food delivery and freight at least shows it has a chance.
Signs of structural advantage
Along with better execution, this can be difficult to assess during a high growth / high re-investment phase. However, detailed analysis may reveal interesting differences. For example, Uber’s gross margin is 10 percentage points higher than Lyft’s. The biggest constituent of Uber’s Cost of Goods Sold (COGS) is actually insurance premiums. Uber runs an internal insurance division and given a 40% scale advantage in the US (the only market in which it competes), it stands to reason Uber’s costs may be structurally lower given that insurers benefit from larger pools over which to spread risk. One might argue that external insurers have an even bigger pool and while this is true, they also demand a certain profit margin to keep their owners happy.
Uber and Airbnb score highest on the analysis above. Regulation will play a significant role for both and this uncertainty will need to be carefully considered. Valuation matters, too, though for the great compounders, less than most believe.
Unstructured Learning Time
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