The Case for Jack Dorsey, Twitter CEO

If you spend enough time listening to Silicon Valley folks, you’d be forgiven for assuming that all tech companies, particularly startups, originated in Lake Wobegon: they are all strong, good looking, and above average. And, to be sure, there are a lot of benefits that come from the instinctual optimism that inhabits the place: the fact that seemingly outlandish ideas that (according to conventional wisdom) will never work can receive funding and the full-on commitment of thousands of exceptionally talented people is a big part of why the region churns out company after company that does in fact change the world.

Twitter is a classic example: a description of the product in 2006 would have had most people shaking their heads at the very premise of a service based on broadcasting 140 character micro-posts (the word “tweet” wouldn’t come till later), but here we sit 9 years later discussing a product and eponymous company that has, in a very real way, changed the world broadly and the world of its users dramatically.

The trouble with optimism, though, is that it can blind you to real areas of concern, and again Twitter is the perfect example. While early skepticism centered on Twitter’s ability to monetize, by the time the company filed for its IPO in 2013 it was obvious the company had fantastic revenue potential but a real problem retaining new users (I wrote about this at the time). Unfortunately, as best I can tell, Twitter’s product strategy basically consisted of optimism that the company would magically improve its ability to retain new users while the attention of the executive team focused on monetization, culminating in Q4 2014 earnings that showed barely any user growth but impressive revenue numbers — and a 16 percent stock jump.

On the associated February phone call with analysts, then-CEO Dick Costolo led with the great results and declared that Twitter’s user problem was headed in the right direction as well:

Financially we had another great quarter with strong revenue growth and very strong profit…Importantly, I want to highlight that the user numbers we saw in January of this year indicate that our MAU trend has already turned around and our Q1 trend is likely to be back in the range of absolute net adds that we saw during the first three quarters of 2014.

Everything was going to be fine.

Of course, everything was not fine; the following quarter Twitter showed even slower user growth and this time revenue missed as well, and the stock gave back January’s gains and more, plummeting 25% in just two days. That’s when I wrote that Twitter Needed New Leadership, and the motivation wasn’t so much the then just-released earnings as it was all the earnings and public pronouncements that came before: if an executive team continually says that everything is great when it clearly is not, then in my mind they lose credibility. It just happened to take an earnings miss for Wall Street to share my assessment.

This, then, is why yesterday’s Twitter earnings call was so important — and so impressive. Just as in January Twitter beat financial expectations handily, and the stock quickly jumped in after-hours trading. It would have been plausible, and even understandable, if interim CEO Jack Dorsey and CFO Anthony Noto had taken the opportunity to reiterate that Twitter’s plan was working and that the stock did indeed deserve to be worth more.

In fact, though, Dorsey and Noto did the exact opposite: instead of focusing on revenue they focused on users, and were brutally honest that Twitter had fallen short. Dorsey stated right at the top:

We’ve been very successful at monetization, with a strong Q2, delivering over $500 million in revenue and more than $120 million in EBITDA. However, product initiatives we’ve mentioned in previous earnings calls like instant timelines and logged out experiences have not yet had meaningful impact on growing our audience or participation. This is unacceptable and we’re not happy about it.

The stock tanked, but that’s because it was too high to begin with: it’s not that Dorsey and Noto presented poorly, it’s that they presented honestly, and while that hurts now, it’s the only way to rebuild the credibility that Twitter has lost through too many quarters of insisting things were strong, good-looking, and always, always, above-average.1

Just before the earnings call Kara Swisher reported that Dorsey and Adam Bain, President of Global Revenue and Partnerships at Twitter, were finalists to replace Costolo, who stepped down in June. It was great timing, because said call laid out why, in my opinion, Dorsey should be the choice — and why it’s not at all an obvious one.

The fact of the matter is that Bain has done a phenomenal job at Twitter: the company had only $28 million in revenue in 2010, the year he started, yet just this quarter delivered over $500 million; that’s a 70x increase on an annualized basis. Were the CEO job based simply on past performance, no one would be more deserving. However, to make the decision in such a way — to effectively prioritize revenue generation — would be to make the exact same mistake Twitter made over the past several years: putting advertisers and money ahead of users and product. In the long run the former depend on the latter — and in a disclosure that clearly spooked the market, Noto noted that Twitter could soon be in danger of not having sufficient inventory — because of a lack of engaged users — for all of the ads it was selling.2

The question, then, is who can best rebuild the product, and it’s difficult to come up with anyone better than Dorsey:

  • Product development requires vision. When you keep in mind the “vision” Twitter presented at last fall’s analyst day — Reach the largest daily audience in the world by connecting everyone to their world via our information sharing and distribution platform products and be one of the top revenue generating Internet companies in the world. — Dorsey’s clarity on yesterday’s call was profound:

    You should expect Twitter to be as easy as looking out your window to see what’s happening. You should expect Twitter to show you what’s most meaningful in the world to live it first before anyone else and straight from the source. And you should expect Twitter to keep you informed and updated throughout your day.

    But Twitter can’t just be the best window to the world; Twitter also has to be the most powerful microphone in the world. You should expect Twitter to increase your reach and you should expect Twitter to encourage live and direct conversation and participation around whatever you share.

    If we meet these expectations, and we will, Twitter will become the first thing everyone in the world checks to start their day and the first thing people turn to when they want to share ideas, commentary, or simply what’s happening.

    More importantly, if Twitter meets those expectations, revenue and advertisers will follow; the relationship is a one-way street, and for too long Twitter has been trying to back into what must come first.

  • Product development requires authority. Twitter has long been captive to its best users who rail against any change on the margins, much less even a rumor of changes to the core product; I suspect this hesitancy has been in large part driven by the fact that everyone in Twitter’s leadership was ultimately a hired gun. Dorsey, though, is a founder, and however controversial his first stint at the company may have been, there is no denying the authority this fact gives him when it comes to making changes.

    Dorsey is already indicating that there will be no sacred cows, stating in his opening remarks:

    You will see us continue to question our reverse chronological timeline and all of the work it takes to build one by finding and following accounts through experiences like ‘While You Were Away’ and Project Lightning which launches this fall. Our goal is to show more meaningful tweets and conversations faster, whether that’s logged in or out of Twitter.

    Dorsey noted later on that the traditional reverse chronological timeline would still be available, but he again made clear the strictly chronological timeline wasn’t gospel; it’s doubtful anyone else could say so so brazenly.

  • Product development requires buy-in. Perhaps the most severe issue facing Twitter is employee retention, particularly in light of the increasingly depressed stock. Two more executives left yesterday, on top of the 450+ employees that The Financial Times reported have left in the past year. Stemming that flow will require both vision as well as a reason to believe that vision is attainable, and here again Dorsey is the obvious choice.

    First off — and as evidence clichés exist for a reason — it should be noted again that Dorsey is a founder, granting him not only authority but also legitimacy. Twitter head of product Kevin Weil told The Verge:

    Jack brings the vision of the founder of the product back, so he has a very strong sense of Twitter’s place in the world. He’s bringing his perspective to how we develop products, and honestly it’s been a great experience so far.

    Secondly, whether by circumstance or not Dorsey’s time at Twitter (2006-2008) is very highly correlated with the times the product evolved the most; Dorsey was also a proponent of Twitter’s original API-centric model and isn’t tainted by the developer drama of 2012. Bain may be as likable as Swisher asserted, but likability does not translate into buy-in, particularly in an arena (product) where Bain doesn’t claim to have any particular expertise.

    Perhaps most important, though, was yesterday’s call: Dorsey reportedly told Twitter employees he would be blunt, and he was. He was, as I noted, honest, and honesty is the foundation of trust, something the next Twitter CEO will desperately need.

To be sure, there are plenty of arguments against Dorsey. For one, he has another job as CEO of Square, which late last week was reported to have filed for an IPO. Then again, there are whispers Dorsey is less involved with Square than you might think, especially as the company has pivoted away from a consumer focus (Dorsey’s passion) towards small business financial services, and if he were ever going to leave pre-IPO would probably be better than post (although both options aren’t great).

For another, while Dorsey supervised much of Twitter’s early innovation, it was innovation that was all too often barely accessible due to Twitter’s operational problems. Moreover, by all accounts the fail whale symbolized more than the fact that the servers couldn’t stay up: the entire company seems to have had very little structure or discipline. That said, people grow and mature: Dorsey would now be a CEO with proven CEO experience, not simply an engineer with a good idea and little else to go on.

And, of course, there is the famous Twitter dysfunction: according to Swisher Twitter’s other iconic co-founder, Ev Williams, is against a Dorsey return, small surprise given the fact both managed to help fire the other during their respective go-arounds as CEO. Indeed, that there is yet another reason why Twitter has such a significant hill to climb: not only do they need a new CEO, they probably need a new board as well. Having a mixture of former CEOs and folks who don’t use Twitter doesn’t exactly suggest that the CEO decision will be based on what is best for the product. And that makes me pretty pessimistic.

  1. To be fair, Dorsey and Noto were simply seizing the opportunity presented to all new CEOs: that is they implicitly threw the old leadership under the bus and dramatically lowered expectations for themselves. Still, in my mind the opportunism doesn’t make their honesty any less impressive (particularly when you remember it cost both of them millions of dollars personally) []
  2. This is a point I got slightly wrong in my piece calling for new leadership: I focused on the possibility that advertisers would desert Twitter for being too small, while Noto warned about Twitter not having sufficient inventory to satisfy demand; both, though, are driven by the fact that Twitter needs more active users (and I believe my concern remains warranted in the long run) []

Aggregation Theory

The last several articles on Stratechery have formed an unintentional series:

  • Airbnb and the Internet Revolution described how Airbnb and the sharing economy have commoditized trust, enabling a new business model based on aggregating resources and managing the customer relationship
  • Netflix and the Conservation of Attractive Profits placed this commodification/aggregation concept into Clay Christensen’s Conservation of Attractive Profits framework, which states that profits are earned by the integrated provider in a value chain, and that profits shift when another company successfully modularizes the incumbent and integrates another part of the value chain
  • Why Web Pages Suck was primarily about the effect of programmatic advertising on web page performance, but in the conclusion I noted that the way in which ad networks were commoditizing publishers also fit the “Conservation of Attractive Profits” framework

In retrospect, there is a clear thread. In fact, I believe this thread runs through nearly every post on Stratechery, not just the last three. I am calling that thread Aggregation Theory.

The value chain for any given consumer market is divided into three parts: suppliers, distributors, and consumers/users. The best way to make outsize profits in any of these markets is to either gain a horizontal monopoly in one of the three parts or to integrate two of the parts such that you have a competitive advantage in delivering a vertical solution. In the pre-Internet era the latter depended on controlling distribution.

For example, printed newspapers were the primary means of delivering content to consumers in a given geographic region, so newspapers integrated backwards into content creation (i.e. supplier) and earned outsized profits through the delivery of advertising. A similar dynamic existed in all kinds of industries, such as book publishers (distribution capabilities integrated with control of authors), video (broadcast availability integrated with purchasing content), taxis (dispatch capabilities integrated with medallions and car ownership), hotels (brand trust integrated with vacant rooms), and more. Note how the distributors in all of these industries integrated backwards into supply: there have always been far more users/consumers than suppliers, which means that in a world where transactions are costly owning the supplier relationship provides significantly more leverage.

The fundamental disruption of the Internet has been to turn this dynamic on its head. First, the Internet has made distribution (of digital goods) free, neutralizing the advantage that pre-Internet distributors leveraged to integrate with suppliers. Secondly, the Internet has made transaction costs zero, making it viable for a distributor to integrate forward with end users/consumers at scale.

stratechery Year One - 220

This has fundamentally changed the plane of competition: no longer do distributors compete based upon exclusive supplier relationships, with consumers/users an afterthought. Instead, suppliers can be aggregated at scale leaving consumers/users as a first order priority. By extension, this means that the most important factor determining success is the user experience: the best distributors/aggregators/market-makers win by providing the best experience, which earns them the most consumers/users, which attracts the most suppliers, which enhances the user experience in a virtuous cycle.

The result is the shift in value predicted by the Conservation of Attractive Profits. Previous incumbents, such as newspapers, book publishers, networks, taxi companies, and hoteliers, all of whom integrated backwards, lose value in favor of aggregators who aggregate modularized suppliers — which they don’t pay for — to consumers/users with whom they have an exclusive relationship at scale. For example:


  • Previously, publishers integrated publications and articles. Google modularized individual pages and articles, making them directly accessible via search
  • Google integrated search results with search and profile data about users, enabling it to sell highly effective advertising

Facebook (and Ad Networks)

  • Previously, publishers integrated content and advertisements. Facebook modularized advertisements by allowing advertisers to target customers directly, not via proxy
  • Facebook integrated News feed ad inventory and profile data, enabling it to sell highly effective advertising


  • Previously, book publishers integrated editing, marketing and distribution. Amazon modularized distribution first via e-commerce and then via e-books
  • Amazon integrated customer data and payment information with e-book distribution and its Amazon publishing initiative (the framework is clearest when it comes to books, but the integration of distribution and the customer relationship also applies to most of Amazon’s business)


  • Previously, networks integrated broadcast availability and content purchases. Netflix modularized broadcast availability by making its entire library available at any time in any order
  • Netflix integrated content purchases and customer management, enabling a virtuous cycle of increased subscription demand and increased content purchase capability


  • Previously, networks integrated mass-market advertising and general interest programming. Snapchat (and many other services) modularized attention
  • Snapchat is integrating individually interesting content with mass market advertising inventory, giving brand advertisers a new way to reach a large audience efficiently


  • Previously, taxi companies integrated dispatch and fleet management. Uber modularized fleet management by working with independent drivers
  • Uber is integrating dispatch with customer management, enabling it to scale worldwide


  • Previously, hotels integrated vacant rooms and trust (via brand). Airbnb modularized vacant properties by building a reputation system for trust between hosts and guests
  • Airbnb is integrating property management and customer management, enabling it to scale worldwide

It’s interesting to consider the order of these examples: the pioneer of this model was Google which modularized content providers. It’s easy to see why this is the case: content has always been monetized by proxy, whether it be paying for newspapers (or advertising space in those newspapers), paying for CDs, or paying for cable TV. The shift to digital has exposed these proxies for the rent-collection mechanisms they are.1

Facebook, though, has built in some respects an even stronger position: its suppliers are its users, so while it, like Google, aggregates content that it gets for free, it also has exclusive access to that content. Snapchat and other user-generated content networks are similar.

The third wave are industries that don’t have such an obvious digital component. Airbnb, for example, deals with vacant rooms; what makes it work is the way it has digitized — and thus commoditized — trust. Uber deals with cars; it has digitized both trust and dispatch. More importantly, both have nailed the user experience in a way that incumbents have been sorely lacking. Both companies also sit in a sort of middle ground between Facebook and Google: their suppliers are not exclusive in theory, but increasingly are exclusive in reality as both benefit from a virtuous cycle of more users leading to increased utilization of suppliers.

What is important to note is that in all of these examples there are strong winner-take-all effects. All of the examples I listed are not only capable of serving all consumers/users, but they also become better services the more consumers/users they serve — and they are all capable of serving every consumer/user on earth. This, above all else, is why consumer technology companies are so highly valued both in the public and private markets.

Looking forward, I believe that Aggregation Theory will be the proper framework to both understand opportunities for startups as well as threats for incumbents:

  • What is the critical differentiator for incumbents, and can some aspect of that differentiator be digitized?
  • If that differentiator is digitized, competition shifts to the user experience, which gives a significant advantage to new entrants built around the proper incentives
  • Companies that win the user experience can generate a virtuous cycle where their ownership of consumers/users attracts suppliers which improves the user experience

The Uber and Airbnb examples are especially important: vacant rooms and taxis have not been digitized, but they have been disrupted. I suspect that nearly every industry will belatedly discover it has a critical function that can be digitized and commodified, precipitating this shift. The profound changes caused by the Internet are only just beginning; aggregation theory is the means.

  1. This is, first and foremost, why Stratechery spends a lot of time covering the media. It is simply the first example of the disruption that is happening everywhere []

Why Web Pages Suck

John Gruber had strong words about Apple news site iMore:1

I love iMore. I think they’re the best staff covering Apple today, and their content is great. But count me in with Nick Heer — their website is shit-ass. Rene Ritchie’s response acknowledges the problem, but a web page like that — Rene’s 537-word all-text response — should not weigh 14 MB.1.

It’s not just the download size, long initial page load time, and the ads that cover valuable screen real estate as fixed elements. The fact that these JavaScript trackers hit the network for a full-minute after the page has completed loaded is downright criminal. Advertising should have minimal effect on page load times and device battery life. Advertising should be respectful of the user’s time, attention, and battery life. The industry has gluttonously gone the other way. iMore is not the exception — they’re the norm. 10+ MB page sizes, minute-long network access, third-party networks tracking you across unrelated websites — those things are all par for the course today, even when serving pages to mobile devices. Even on a site like iMore, staffed by good people who truly have deep respect for their readers.

It’s that last line that should give Gruber, or anyone else complaining about crappy websites, pause. After all, if iMore respects their readers, the only alternative explanation is that their development team is incompetent. Unless, of course, iMore, along with the vast majority of ad-supported sites on the web, has basically no choice in the matter.

Advertisers and the Early Web

Gruber talks about publishers and readers, but if you begin with the premise that web pages need to be free,2 then the list of stakeholders for most websites is incomplete without the inclusion of advertisers. After all, they’re the ones that pay the bills.

Back when the web first became an important medium it actually wasn’t particularly great for advertisers. In the pre-Internet days an advertiser could buy ads in the local paper, perhaps a TV spot or two, put up a billboard and call it a day, confident they were reaching their entire target segment as well as they could. To do the same with web ads, on the other hand, required somehow knowing what websites your target customers were visiting, which could number in the hundreds or thousands, and then buying ads on those websites and crossing your fingers your customers actually saw your ad (although you would never know if they did). It was a mess.

The problem was one of scale, and in two dimensions:

  • There were way more places to advertise than before, which sounds great in theory but actually stunk in practice, because who has the time and resources to deal with hundreds or thousands of different ad sales teams?
  • Any one website only knew what its visitors were interested in on that particular website, which meant the targeting ability a website could sell to advertisers was scarcely better than a physical newspaper selling a spot in the Sports section to a gym

The result is that as late as 2010, when Mary Meeker for the first time used the following slide in her annual Internet Trends report, the Internet’s share of advertising was significantly less than its share of attention:


Ad networks and programmatic advertising, though, changed everything.

The Rise of Ad Networks

Ad networks solved both scale problems:

  • Instead of buying ads on a plethora of (relatively-speaking) little websites, advertisers could centralize their buying with an ad network that promised to place their ads across said plethora.
  • By virtue of having ads — and their associated trackers — across the aforementioned plethora of sites, networks could get a much richer picture of individual visitors giving advertisers the ability to much more finely target their ads.

The way it actually works is a little complicated: unlike print ads, which were delivered days ahead of time and inserted along with editorial copy before going to press, ads today are delivered “programmatically”. The process is actually kind of amazing, and consists of several different pieces (my reference to “ad networks” has been a bit simplistic):

  • When a user requests a URL, the publisher checks to see if they have any directly sold ads available (because of the scale problems noted above, fewer and fewer publishers have fewer and fewer directly-sold ads; advertisers just aren’t interested)
  • If they don’t, the publisher asks an ad exchange for an ad
  • The ad exchange, which has built up a profile of the user across all the different sites where the ad exchange is used, sends the (anonymized) user profile and website description to a variety of demand-side platforms (DSPs) (which actually sell the ads)
  • The DSPs examine the user profile and website description and a host of other factors and offers up the price they are willing to pay to serve an ad to the user
  • The ad exchange selects the highest price, retrieves the ad, and sends it to the publisher to display

All of this happens on a just-in-time basis, and you can see why advertisers love it: to a greater extent than ever before they are reaching exactly who they want to reach at the most efficient price possible. The result has been a huge increase in advertising on the Internet; look at Meeker’s equivalent slide from 2015:


Advertisers’ strong preference for programmatic advertising is why it’s so problematic to only discuss publishers and users when it comes to the state of ad-supported web pages: if advertisers are only spending money — and a lot of it — on programmatic advertising, then it follows that the only way for publishers to make money is to use programmatic advertising.

The Modularization of Publishing

From publishers’ perspective, the fixed cost of a printing press not only provided a moat from competition, it also meant that publishers displayed ads on their terms. To use the Conservation of Attractive Profits model that I discussed last week, publishers were exceptionally profitable for having integrated content and ads in this way:


As the description of programmatic advertising should make clear, though, that is no longer the case. Ad spots are effectively black boxes from the publisher perspective, and direct windows to the user from the ad network’s perspective. This has both modularized content and moved ad networks closer to users:


Here’s the simple truth: if you’re competing in a modular market, as today’s publishers are, profits are slim at best, and you generally take what you can get from a revenue perspective. To put it another way, publishers today have about as much bargaining power as do Uber drivers, and we’ve seen how that has gone.

So What Now?

To this point I’ve discussed ad networks from the advertisers’ perspective; Gruber’s critique, though, was that of a user: he is absolutely correct that the price of efficiency for advertisers is the user experience of the reader. The problem for publishers, though, is that dollars and cents — which come from advertisers — are a far more scarce resource than are page views, leaving publishers with a binary choice: provide a great user experience and go out of business, or muddle along with all of the baggage that relying on advertising networks entails.3

Again, the solution is not that publishers should try harder to have better ads. The New York Times, arguably the gold standard when it comes to both brand and quality impressions, noted in its annual report:

Digital advertising networks and exchanges, real-time bidding and other programmatic buying channels that allow advertisers to buy audiences at scale are also playing a more significant role in the advertising marketplace and causing downward pricing pressure.

If the New York Times cannot resist programmatic advertising, what chance does iMore or the vast majority of online publications have? If anything this puts Facebook’s Instant Articles initiative in a far more positive light: the social network is offering to not only improve the user experience by displaying articles instantly — thanks, primarily, to the lack of programmatic advertising cruft — but also to help monetize said content by selling ads against it and sharing 70%, backed by profile data that is far superior to even the ad networks.

Indeed, arguably the biggest takeaway should be that the chief objection to Facebook’s offer — that publishers are giving up their independence — is a red herring. Publishers are already slaves to the ad networks, and their primary decision at this point is which master — ad networks or Facebook — is preferable?

This too provides additional context to Apple’s new News app, which looks an awful lot like Facebook’s offer: publishers put their articles in a common repository that is monetized collectively through iAd, thus achieving advertising scale (and, it should be noted, more user data than Apple’s rhetoric would suggest). Apple, of course — and this is what prompted this entire discussion — is providing not only a carrot but a stick. Gruber concludes:

With Safari Content Blockers, Apple is poised to allow users to fight back. Apple has zeroed in on what we need: not a way to block ads per se, but a way to block obnoxious JavaScript code. A reckoning is coming.

It absolutely is, as I noted when Facebook’s Instant Articles launched. The future for most publishers is likely that of pure content production only, save for the few — like Gruber — who are destination sites capable of selling native advertising in stream (or selling subscriptions, like this site). What is very much in question is exactly how users will feel when they finally get what they claim they wish for.

  1. I excerpted most of Gruber’s post — his writing is impressively tight! — with permission []
  2. The experience of the vast majority of publishers is that readers will not pay for content; the exception are sites like this one that keep costs extremely low and focus on primarily analysis, not original reporting []
  3. Advertisers and ad networks, unfortunately, don’t really have an incentive to improve the user experience; there is an effectively unlimited amount of inventory on the web []

Netflix and the Conservation of Attractive Profits

Two years ago, when I first wrote about TV and how it had resisted disruption, I called Netflix “just another network”:

Netflix famously pivoted from DVDs-by-mail to streaming, but that was only pivot number one. Pivot number two was their transformation from a content delivery provider to simply another network.

Think about it: Netflix invests millions of dollars in new TV shows to drive growth, and has reruns and old movies as filler. They’re HBO with a unique delivery system. Or, to fit the analogy [of networks as VCs for television shows], Netflix is just another VC, with a war chest built by a completely different business (the aforementioned discs-by-mail). Netflix is unique, but ultimately uninteresting, and unlikely to be replicated.

I got this one wrong, and in a big way.

Why Netflix Isn’t a Network

The “Netflix as a network” framing was the basis of an attention-getting article in Variety headlined Netflix U.S. Viewing to Surpass ABC, CBS, Fox and NBC by 2016:

If Netflix were a Nielsen-rated TV network, the No. 1 streaming service would, within a year, attain a larger 24-hour audience than each of the major broadcast networks — ABC, CBS, Fox and NBC — according to a Wall Street analyst firm.

To be clear, the analysis by FBR Capital Markets is not apples-to-apples. One major caveat: Nielsen TV ratings cover, at most, up to seven days of VOD and DVR viewing — and exclude online-video views, which networks say are an increasing part of the pie. Moreover, TV networks provide a different blend of content, such as live sports, that Netflix doesn’t. And anyway, Netflix doesn’t care about “ratings” of individual shows, given that it doesn’t sell ads and has steadfastly refused to disclose anything but general data about viewing.

Actually, the degree to which this is a valid comparison is very much open to debate. On one hand, any time spent watching Netflix is time not spent watching traditional TV. Moreover, Netflix is increasingly competing against traditional networks for content. On the other hand, as the excerpt notes, Netflix relies on subscriptions, not ads, which means it is much less concerned with the number of viewers for a particular show within a particular time frame.

Still, even this last point of differentiation is less stark than it seems. As I noted in Old-Fashioned Snapchat, network revenue has seen a significant shift over the last several years from advertising to affiliate revenue in particular; it turns out that a little bit of money from every cable subscriber is much more profitable, predictable, and sustainable than attempting to wrangle a massive audience to sell to advertisers in an increasingly fractured media environment. This shift also changed the type of TV that mattered: instead of the sort of lowest common denominator fare that characterized the first several decades of TV, it’s far more important to have “must-see” shows and events, even if the number of people for whom said shows and events are must-see is relatively small; all that matters is that these fans base their pay-TV subscription decision on access to said shows and events.1 This reality — that networks were just as reliant on (another sort of) subscription revenue as Netflix — is what led to my conclusion that Netflix was “HBO with a unique delivery system.”

That last piece though — the non-linearity of Netflix’s programming — is more important than I realized, for a reason I articulated last week in Airbnb and the Internet Revolution:

The commoditization of trust is far more injurious to hotels than you might think…In the pre-Airbnb days travelers — and sublessors — justifiably prioritized trust above all else. In other words, the implication of Airbnb building a platform of trust is not that a homestay is now more trustworthy than a hotel; rather, it’s that the trust advantage of a hotel has been neutralized, allowing homestays to compete on new vectors, including convenience, cost, and environmental factors.

What is revolutionary about on-demand streaming in general and Netflix in particular is that the service has commoditized time: on Netflix Sunday at 9pm is no different than Tuesday at 11am or Friday at 6pm; there is no prime time. Thus Netflix will release original series all at once, because why not? Best to maximize the number of minutes over which an expensive upfront cost like producing a show can be utilized.

For what it’s worth, I’m actually not certain this strategy is optimal for any one given show: I suspect there is a lot of value in the “buzz” created around appointment viewing, live Twitter reactions, and day-after write-ups. On the other hand, Netflix’s absolute embrace of the commoditization of time sends an important message to both content creators and content consumers that the service is first and foremost committed to connecting each side of the content equation as efficiently as possible.

The Law of Conservation of Attractive Profits

When you think about it that way — that Netflix isn’t so much a network as they are a type of marketplace in which consumers can give their attention to creators — it becomes apparent that Netflix isn’t that far off from Uber or Airbnb or any of the other market-makers that are transforming industry-after-industry. Netflix:

  1. Is an infinitely scalable network…
  2. That has commoditized a previous constraint and…
  3. Positioned itself to be the chief beneficiary of industry transformation.

I made this an ordered list on purpose: these three characteristics work in concert to create value due to something called the Law of Conservation of Attractive Profits,2 first explained by Clayton Christensen in his 2003 book The Innovator’s Solution:

Formerly, the law of conservation of attractive profits states that in the value chain there is a requisite juxtaposition of modular and interdependent architectures, and of reciprocal processes of commoditization and de-commoditization, commoditization, that exists in order to optimize the performance of what is not good enough. The law states that when modularity and commoditization cause attractive profits to disappear at one stage in the value chain, the opportunity to earn attractive profits with proprietary products will usually emerge at an adjacent stage.

That’s a bit of a mouthful, but the example that follows in the book shows how powerful this observation is:

If you think about it in a hardware context, because historically the microprocessor had not been good enough, then its architecture inside was proprietary and optimized and that meant that the computer’s architecture had to be modular and conformable to allow the microprocessor to be optimized. But in a little hand held device like the RIM BlackBerry, it’s the device itself that’s not good enough, and you therefore cannot have a one-size-fits-all Intel processor inside of a BlackBerry, but instead, the processor itself has to be modular and conformable so that it has on it only the functionality that the BlackBerry needs and none of the functionality that it doesn’t need. So again, one side or the other needs to be modular and conformable to optimize what’s not good enough.

Did you catch that? That was Christensen, a full four years before the iPhone, explaining why it was that Intel was doomed in mobile even as ARM would become ascendent.3 When the basis of competition changed away from pure processor performance to a low-power system the chip architecture needed to switch from being integrated (Intel) to being modular (ARM), the latter enabling an integrated BlackBerry then, and an integrated iPhone four years later.4

The PC is a modular system whose integrated parts earn all the profit. Blackberry (and later iPhones) on the other hand was an integrated system that used modular pieces.
The PC is a modular system whose integrated parts earn all the profit. Blackberry (and later iPhones) on the other hand was an integrated system that used modular pieces. Do note that this is a drastically simplified illustration.

More broadly, breaking up a formerly integrated system — commoditizing and modularizing it — destroys incumbent value while simultaneously allowing a new entrant to integrate a different part of the value chain and thus capture new value.

Commoditizing an incumbent's integration allows a new entrant to create new integrations -- and profit -- elsewhere in the value chain.
Commoditizing an incumbent’s integration allows a new entrant to create new integrations — and profit — elsewhere in the value chain.

This is exactly what is happening with Airbnb, Uber, and Netflix too.

How Airbnb, Uber, and Netflix Capture Value

As noted above, I discussed Airbnb last week: the service commoditized trust, divorcing it from the underlying physical property. That freed Airbnb to integrate trust into a worldwide network of hosts and guests:

Airbnb modularizes property allowing it to integrate trust and reservations.
Airbnb modularizes property allowing it to integrate trust and reservations.

Uber has a trust element as well (as do nearly all the sharing companies), but even more important was how the service commoditized dispatch and modularized cars:

Uber modularizes cars allowing it to integrate dispatch with hailing and payments.
Uber modularizes cars allowing it to integrate dispatch with hailing and payments.

Netflix has pulled a similar maneuver: by commoditizing time and distribution the company has integrated production and customer management:

Netflix modularizes content production, allowing it to integrate productions with subscriptions and distribution.
Netflix modularizes content production, allowing it to integrate productions with subscriptions and distribution.

Note the common element to all three of these companies: all have managed to modularize the production/delivery of their service which has allowed them to move closer to the customer. To put it another way, all of this new value is being created by specialized CRM companies: Airbnb for travelers, Uber for commuters, and Netflix for the bored.

I do think I’ve underestimated Netflix, but only to a point; I detailed in The Changing — and Unchanging — Structure of TV that when it comes to the TV value chain it is highly differentiated content creators that retain the most power (in a way that Airbnb hosts and Uber drivers clearly do not5 ). Moreover, Netflix faces strong competition for attention from both traditional pay-TV as well as Amazon Prime, a revitalized Hulu, and especially HBO.

Netflix’s hit rate is improving, but HBO continues to be must-see TV. This excellent profile of the company in Hollywood Reporter notes:

For all the upstart competitors with their signature shows, conversations with two dozen top producers and their representatives reveal that HBO remains the most desirable place to be — because it has the audience, the budgets, the promotional muscle and, perhaps most important, the most experience turning good ideas into great TV. “Anyone who tells you they want to be somewhere else is lying, or they couldn’t get on the air at HBO,” gripes one top rep, who requested anonymity for fear of offending other buyers. WME’s Emanuel has no such worries. “They’re the creme de la creme, and when you do get on, it’s a big statement that you’re the best,” he says.

This is a big advantage: the best is uniquely important when it comes to the subscription business. Still, you can take integration too far. That same profile notes:

The biggest risk that HBO faces creatively is one of its own making. With more than 100 projects said to be in development, HBO is in constant danger of becoming a victim of its own success — so clogged with talent that the next Lena Dunham or David Chase will go elsewhere…this bottleneck is the chief criticism of the network.

Competitors, including Netflix and Amazon, are preying on those turned off by the lengthy queue at HBO, aggressively touting their willingness to move quickly and slap shows on the air. That swiftness is said to have been the key to Netflix, rather than HBO, landing Kyle Chandler’s Bloodline and the upcoming mind-bender The OA from Brit Marling.

This is the freedom that comes from being a new entrant: it’s not only that Netflix is integrated around the customer experience, it’s that they’re modularized around the content creation as well; this too is why the Uber employee lawsuits are a real risk. Integrated profits are the yin to modularization efficiencies’ yang, and the most promising companies are the ones that create the biggest breaks with the past.

  1. Every single sports fan is looking at their cable bill and nodding wearily at the realization they are the ones who have made ESPN the most profitable network of all []
  2. Later renamed the Law of Conservation of Modularity []
  3. I have my differences with Christensen, but as I’ve said repeatedly my criticism comes from an attempt to build on his brilliant work, not tear it down []
  4. As I’ve noted, the iPhone is in fact modular at the component level; the integration is between the completed phone and the software. Not appreciating that the point of integration (or modularity) can be anywhere in the value chain is, I believe, at the root of a lot of mistaken analysis about the iPhone in particular []
  5. By the way, note that when/if Uber has self-driving cars, they will be fully integrated []

Airbnb and the Internet Revolution

Despite the fact Airbnb1 is, along with Uber, the poster-child for the new sharing economy, the former seems to attract a lot less attention than the latter, particularly among the chattering class. I suspect a big part of this is the way people view drivers vis-à-vis sublessors: despite the fact drivers work for Uber by choice — and, as Uber is eager to point out, come and go as they please — while on the clock Uber controls their rates and revenue share. Not only does this raise the question as to whether or not drivers are employees,2 it also provides grist for countless anecdotal stories about how a company valued at tens of billions of dollars3 is taking advantage of drivers earning tens of dollars per hour at best.4

Airbnb, on the other hand, is generally thought to be much more of a win-win: sublessors make some more money, and sublessees get a more inexpensive place to stay than a hotel, or a more home-like environment in a different sort of neighborhood than they might otherwise; often it’s both. More importantly, both parties are clearly happy with the arrangement.

Of course the nature of the relationship between sublessors and sublessees differs depending on whom you ask: hotels, facing real disruption from Airbnb, accuse the startup of being a shadow hotelier focused on stealing their business. Airbnb, for its part, focuses on the idea of “home”. Last summer, while announcing their new branding and mission statement, Airbnb founder and CEO Brian Chesky wrote:

In 2007, Joe and I opened our home up to the first Airbnb guests. They booked a place to stay, but they ended up with something more than just an airbed at a slightly messy apartment. They learned our favorite places to grab coffee, ate the best tacos in the city, and had friends to hang out with whenever they wanted. They were thousands of miles from where they lived, and yet they felt right at home. What started as a way for a few friends to pay the rent has now transformed into something bigger and more meaningful than we ever imagined. And what we realized is that the Airbnb community has outgrown the original Airbnb brand. So Joe, Nate, and I did some soul-searching over the last year. We asked ourselves, “What is our mission? What is the big idea that truly defines Airbnb?” It turns out the answer was right in front of us. For so long, people thought Airbnb was about renting houses. But really, we’re about home. You see, a house is just a space, but a home is where you belong. And what makes this global community so special is that for the very first time, you can belong anywhere. That is the idea at the core of our company: belonging.

A not insignificant number of cities are equally concerned about “home,” but in their view Airbnb is destroying them by incentivizing landlords to remove residences from the rental market and instead offer them full-time on Airbnb. Paris, for example, which is Airbnb’s biggest market, has in recent weeks conducted raids on unauthorized Airbnb listings. As the Wall Street Journal reports:

Paris officials say there are some 30,000 tourist apartments available for rent in the city — about 2% of the total number of units — with as many as two-thirds operating illegally. Airbnb says that it is a fringe issue on its platform; just 17% of hosts in Paris say they rent out apartments other than their primary residences. It isn’t clear how many of those might be doing so without city authorizations.

Some hotel owners and other activists argue that full-time tourism apartments likely account for more than that in revenue terms, however. “You can’t call this a sharing economy anymore,” said Laurent Duc, president of the French Hotel Federation. “This is an underground shadow economy.”

It’s this last sentence that really gets at why the entire debate around the “sharing” economy is so stilted: at the risk of relying too heavily on my own anecdotal experience, it seems clear that at least a sizable portion of Airbnb’s business is made up of apartments and houses dedicated to Airbnb. In other words, no one staying in these professionally cleaned listings, complete with fresh sheets, towels, and complimentary toiletries, is joining their hosts for coffee or tacos or to simply hang out, no matter how delightful Airbnb’s founding myth may be. It is, as the president of the French Hotel Federation said, “an underground shadow economy.” Why, though, should it be underground?

The Industrial Revolution

I thought it fascinating that Chesky invoked the Industrial Revolution in his post:

We used to take belonging for granted. Cities used to be villages. Everyone knew each other, and everyone knew they had a place to call home. But after the mechanization and Industrial Revolution of the last century, those feelings of trust and belonging were displaced by mass-produced and impersonal travel experiences. We also stopped trusting each other. And in doing so, we lost something essential about what it means to be a community.

Chesky’s focus is on travel, but in reality no one actually did so.5 Nearly everyone lived on subsistence farming, more often than not working land owned by someone else; said landowners, along with the church, exercised nearly complete control, with the occasional merchant facilitating a bare minimum of trade primarily to the benefit of the ruling class. The Industrial Revolution — and the accompanying agricultural one — completely flipped this arrangement on its head. Thanks to the efficiencies afforded by technologies like the loom and mechanical power people were able to specialize and trade the outcomes of their labor for a much fuller and richer life experience than what they had previously.

I get that I’m putting an awfully neat bow on what was 150 years of wrenching change. After all, I just basically described soul-destroying — and often body-debilitating — work in 18th century sweatshops as “specialization”; it’s a bit like Uber’s insistence on calling its drivers “entrepreneurs.” And yet, when you consider how structurally the old taxi medallion system resembled the landowner-peasant relationship of old, why is everyone so eager to declare that the new boss is worse than the old boss?

Of course the rise of factories — and the truly awful conditions within them — eventually helped lead to the rise of the modern regulatory state. Child labor was banned, and eventually hours were capped and minimum workplace safety rules were instituted. More broadly, regulation was applied to the massive amounts of new trade being conducted both locally and across borders, and as cities rose up around those factories and trading centers, regulations covering day-to-day life rose up as well.

This was as necessary as it was inevitable: when Chesky writes that before the Industrial Revolution “everyone knew each other” the unspoken truth is that we simply didn’t know many people, and those we did know were governed by the same shared mores that govern any community. Regulation wasn’t necessary because we regulated ourselves and each other. However, the rise of factories and cities concentrated both power and people even as it magnified the number of interactions conducted by those people and influenced by that power; there were no shared mores because nothing was shared beyond the temporary need for a shared transaction governed by self-interest, making self-regulation a utopian fantasy. We needed regulation because we were incapable of regulating ourselves and each other.

Airbnb and Trust

In the interest of full disclosure, I’m actually writing this post while sitting in an apartment rented through Airbnb. The pictures were ok, but the plethora of reviews were effusive in their praise of this surprisingly large one-bedroom apartment with easy access to the train, so I took the plunge. Indeed, the reviews were spot-on: the apartment is beautiful, and I couldn’t be happier with my choice. One more thing — my family and I are working really hard to keep the place as pristine as it was when we moved in. After all, while I trusted the ratings over the pictures, future Airbnb sublessors will surely care greatly about my rating as well.

There isn’t the sort of community that Chesky promised; I haven’t met our sublessor in person, and likely never will. I don’t know his favorite coffee shops or taco places (or ramen joints for that matter), and I very much feel not at home.6 But despite that fact, some of the most important trappings of community do exist: the shared mores, and common accountability. My sublessor is incentivized to provide a great place, and I’m incentivized to keep it that way, and that more than anything is what makes Airbnb work. And, by extension, one of the big advantages of hotels — the trust instilled first by the concept and reinforced by the brand — begins to erode.

The commoditization of trust is far more injurious to hotels than you might think: it’s not simply that Airbnb is more competitive on one particular vector; rather, the “trust” vector was by far the biggest priority for both travelers and hosts. Hotels could be infinitely more inconvenient, expensive, or sterile relative to your typical homestay and it wouldn’t matter. In the pre-Airbnb days travelers — and sublessors — justifiably prioritized trust above all else. In other words, the implication of Airbnb building a platform of trust is not that a homestay is now more trustworthy than a hotel; rather, it’s that the trust advantage of a hotel has been neutralized, allowing homestays to compete on new vectors, including convenience, cost, and environmental factors. It turns out homestays are quite competitive indeed: to return to my personal anecdote, I am living in a beautiful, remodeled one bedroom apartment in one of the best neighborhoods in this city, and paying a fraction of the cost of a mid-tier hotel for the privilege.

Here’s the kicker though: without Airbnb I wouldn’t even be making this trip. Staying in a hotel would not only be too expensive, it would also deny me the opportunity to at least get a taste of what it’s like to live day-to-day in a different country and culture — something you don’t get at your typical branded hotel. And that’s why the calculation for cities is more complicated than the president of the French Hotel Federation would have you believe: yes, the apartment I’m living in is off the market, but to what extent is one less rental unit made up for by the amount I will spend over the several weeks I am here?

All of these considerations apply to Uber, and many of the other sharing economy startups: what makes them work is not simply mobile access to the Internet, location data, and all the rest; equally important is the systematization, and by extension commodification, of trust. To be sure the latter isn’t a new concept: Ebay deserves special credit for pioneering the fundamental mechanic as applied to Internet businesses. The addition of mobile, though, made this mechanic exponentially more powerful: we went from a vision of apps that let you book last minute hotels to apps that made every house in every city in the world a potential place to stay.

The Internet Revolution

It has been a consistent thesis of mine that the Internet Revolution, which I believe has only just begun, will prove to be in the long run just as transformative as the Industrial Revolution. In other words, it’s not only that we would become more productive; it’s that society as we know it would be fundamentally changed. How, though, hasn’t been entirely clear: if the industrial revolution moved us from subsistence farming in the countryside to factories in cities, where might we go next?

I increasingly believe that it is the sharing economy that is beginning to reveal the answer: a world of commodified trust has significantly less need for much of the infrastructure of modern society, including inefficient sectors like hotels whose primary differentiator is trust, along with the regulatory state dedicated to enforcing that trust. On the other hand, this brave new world has brand new holes through which people can fall: those who have lost trust, or do not have the means to build it. I’m no crazy libertarian; quite the opposite in fact: we need a significantly stronger safety net and a judicial system predicated on arbitration.

The nature of assets changes as well, and not just hotels: as more houses — and rooms — are offered as a service, the definition of ownership begins to shift. This will clearly first play out in automobiles: the long-run promise of Uber is a world where few own cars and few cars sit idle. This will impact not just auto-makers but insurers, dealers, repair shops, and more. More profoundly, it will affect people. We will be less tied down, more willing to move, especially if our work becomes just as transactional as our possessions. And that, ultimately, will change the way we relate to each other, just as the shift from the small knit community in the countryside to the chaos of the city upended everything we thought we knew about how individuals, communities, and governments interacted.

Just because the future is coming into focus, though, doesn’t mean the road there will be smooth. Once again it is Paris giving us a glimpse of the convulsions along the way: taxi drivers upending cars, setting them on fire, terrifying passengers, all in the pursuit of a world as it was. And for now it seems they have won the battle: the French government is taking action to curtail UberPop. The war, though, is only just beginning, and one desperately hopes said reference to war — in contrast to the climax of the Industrial Revolution — remains figurative.

  1. The company just raised $1.5 billion at a $25.5 billion valuation; by the way, that article is worth a click for the chart comparing hospitality companies: it captures very neatly how valuation is based on revenue and growth (along with profit margins and addressable markets, of course) []
  2. The California Labor Commission ruled that one driver was; other courts have held that drivers are not []
  3. $40 billion now, $50 billion soon []
  4. Few of these stories consider what these drivers ought to do otherwise, or why Uber should feel compelled to pay more beyond the insinuation that they can, an assessment that belies the fact that that valuation is predicated on Uber returning the billions invested in the company at a multiple. []
  5. And the Industrial Revolution didn’t happen “last century” []
  6. That, of course, is the point in coming []

Curation and Algorithms

Jimmy Iovine spared no words when it came to his opinion of algorithms during the unveiling of Apple Music:

The only song that matters as much as the song you’re listening to right now is the one that follows this. Picture this: you’re in a special moment…and the next song comes on…BZZZZZ Buzzkill! It probably happened because it was programmed by an algorithm alone. Algorithms alone can’t do that emotional task. You need a human touch. And that’s why at Apple Music we’re going to give you the right song [and] the right playlist at the right moment all on demand.

About Beats 1, the new Apple Music radio station, Iovine added:

[It] plays music not based on research, not based on genre, not based on drum beats, only music that is great and feels great. A station that only has one master: music itself.

According to the Apple Music website “Zane Lowe and his handpicked team of renowned DJs create an eclectic mix of the latest and best in music”; then again, if you keep scrolling the page, you’re reminded there is more to Beats 1 than curated music:

Building your own station couldn’t be easier. Just select any song, album, or artist and it will practically build itself. Adjust the mix to hear more songs you know or discover unfamiliar gems. Love a track? We’ll play more like it. The more you fine-tune the station, the more personalized it becomes.

That sounds a bit like an algorithm. So which is more important, and why?

The Rise of Curation

Curation has been all over the news for the past few weeks. At that same keynote Apple introduced Apple News, and while the presentation made it sound a bit like those user-generated radio stations — Craig Federighi introduced it as “Beautiful content from the world’s greatest sources personalized for you” — it turns out that Apple is hiring editors to, in the words of the Apple job posting, “Ensur[e] that important breaking news stories are surfaced quickly, and enterprise journalism is rewarded with high visibility.”

Apple News is hardly the only effort in the space: a month previously the New York Times released version 2 of its NYT Now app; the big headline was that the app was now free, but just as interesting was the decision to decrease the number of articles from the New York Times itself and intersperse them with a nearly equal number of articles from other publications with the intent of providing a one-stop curated news experience.1 BuzzFeed just released their own take on the concept with the BuzzFeed News app which adds tweets to a mix of BuzzFeed content and content from around the web, all helpfully summarized in easily digestible bullet points.

Twitter itself announced plans to get in on the game with its forthcoming Project Lightning, a tool that, according to BuzzFeed, “will bring event-based curated content to the Twitter platform.” The articles notes:

Launch one of these events and you’ll see a visually driven, curated collection of tweets. A team of editors, working under Katie Jacobs Stanton, who runs Twitter’s global media operations, will select what it thinks are the best and most relevant tweets and package them into a collection…They’ll use data tools to comb through events and understand emerging trends, and pluck the best content from the ocean of updates flowing across Twitter’s servers. But human beings will decide which tweets to include.

Lightning hasn’t launched, but Snapchat’s Live Stories have been drawing in huge viewer numbers for some time now; they too are driven by curation: Recode reports that “the company has grown its team of Live Story curators from fewer than 10 people to more than 40 people” since January, and is now producing multiple events per day. Even Instagram is adding curation to its new Explore page.

When Curating Makes Sense

There are two important advantages to curation:

  • First, where context is critical to immediately determining how important something is — as is the case with news — human curators are, at least for now, superior to algorithms. Humans are also able to quickly identify that these forty stories are about the same event, and have the taste to decide which is the best option to present
  • Taste figures much more prominently when it comes to Apple Music and other similar endeavors. The DJ-focused Beats 1 “radio” station, for example, is clearly intended to make certain songs popular, not simply identify popularity after it is already attained. This in particular is a natural fit for Apple, and is the part of Apple Music I am most intrigued by: the company is most comfortable setting trends, not following them (as is the case with the core streaming service)

It’s possible that algorithms will one day be superior to humans at both of these functions, but I’m skeptical: the critical recognition of context and creativity are the two arenas where computers consistently underperform humans.

The Algorithmic Giants

That said, despite curation’s advantages the two biggest content players of all — Google and Facebook — are pure algorithmic plays. Google News has always been algorithmically driven, but the more important tool for content is Google search itself, which uses the most valuable algorithm in the world to not only find content but to rank it as well. Facebook, meanwhile, is in some respects the exact opposite of Google: rather than responding to an input Facebook proactively selects what you see when you open the app; that selection, though, is also 100% algorithmically driven.

Both search results and the news feed are algorithmically driven
Both search results and the news feed are algorithmically driven

When considering the question of what is better, algorithms or curation, I think this observation that the core Facebook and Google algorithms are actually solving two very different problems is a useful one. Google is seeking the single best answer to a direct query from an effectively infinite number of data points (i.e. the Internet); while the answer it gives is to a degree influenced by the profile Google has built about you, or the various contextual clues surrounding your search, for most queries there is one right answer that Google will return to anyone who searches for the term in question. In short, the data set is infinite (which means no human is capable of doing the job), but the target is finite.

Facebook, on the other hand, creates a unique news feed for all of its 1.44 billion users: while Facebook has a huge amount of data,2 the amount of information any one user will ever be interested in is finite; what is infinite are the number of targets (which means Facebook could never employ enough humans to do the job). In other words, neither Google nor Facebook are able to rely on curation even if they wanted to, but the reasons that Google and Facebook rely on algorithms differs:

Google searches an (effectively) infinite amount of data, while Facebook needs an (effectively) infinite amount of personalization, which is why both are algorithmically driven
Google searches an (effectively) infinite amount of data, while Facebook needs an (effectively) infinite amount of personalization, which is why both are algorithmically driven

However, as I just noted, these two reasons run in the opposite direction: Google does personalize a bit, but it mostly concerned with one right answer, while any single Facebook user doesn’t care and will never care about the vast majority of Facebook’s data. Presuming this relationship holds, you can actually put the above two graphs together:

Curation makes sense in the middle of Google and Facebook: some personalization, and a finite set of data to curate
Curation makes sense in the middle of Google and Facebook: some personalization, and a finite set of data to curate

This curve is a useful way to think about the aforementioned curation initiatives: curation works best when there is a good amount of data, but not too much, and the goal is a fair bit of personalization, but not on an individual basis.

Curating News

The Curation-Algorithm curve makes it clear why news is an obvious curation candidate: while a lot of news happens everywhere all the time, it’s still a lot less than the sum total of information on the Internet. Moreover, the sort of news most people care about tends to be relatively widely applicable, which means personalization is useful but only to a degree. In other words, news mostly sits at the bottom of this curve.

Newspapers figured this out a long time ago: editors were curators, deciding what went on the front page, what was on page 13, and what was buried completely. It mostly worked, although many editors perhaps became too enamored with “prestige” stories like world news as opposed to truly understanding what readers wanted. Moreover, once the Internet destroyed geographic monopolies, it quickly became apparent that most newspapers didn’t have the best content on the particular stories they covered; readers fled to superior alternatives wherever they happened to find them and curation gave way to social services like Twitter and Facebook.

This is what makes the NYT Now and BuzzFeed News apps so interesting: both accept the idea that their respective publications don’t have a monopoly on the best content, even as both are predicated on the idea that curation remains valuable. Apple News takes this concept further by being completely publication agnostic.

The Twitter Question

The current Twitter product, based on a self-curated time-line, doesn’t really fit well on the Curation-Algorithm curve. Power users, through the long and arduous process of following and unfollowing a huge number of people, can ultimately arrive at a highly personalized feed that is relevant to their interests. Beginners, though, are presented with a feed that is nominally about their interests as decided by a torturous first-run experience but which in reality is a stream of mumbo-jumbo.

Twitter struggles because it doesn’t have any products on the Curation-Algorithm curve
Twitter struggles in part because it doesn’t have any products on the Curation-Algorithm curve

Project Lightning is clearly focused on hitting the algorithmic sweet spot with event-based “channels”: it’s an obvious move that should have been done years ago. What is perhaps more interesting, though, is whether Twitter ought to pursue an algorithmic feed: I think the answer is “Yes”. While Twitter’s value is its interest graph, its organizing principle to date has been people; an algorithmic feed would help Twitter more effectively bridge that disconnect.3

Curating Ethics

There is one more big reason why tech companies have previously given curation short shrift, and it’s the flipside of Apple’s efforts with Music: it is a lot easier to abscond with responsibility for what you display if you can blame it on an algorithm. Human curation, on the other hand, makes it explicitly clear who is responsible for what is seen by the curating company’s users.

The potential quandaries are easy to imagine: will Apple’s News app highlight a story about worker conditions in China?4 Will Snapchat’s planned coverage of the 2016 election favor one candidate over the other? Would Twitter have created an “event” around the exit of its CEO?

On the other hand, hiding behind algorithms is increasingly untenable as well. For one, algorithms are made by humans; choosing which story appears in your Facebook feed is the responsibility of Facebook whether they choose it explicitly or implicitly via an algorithm. Google, for its part, has successfully argued that its algorithm is protected free speech, an admission of ultimate responsibility even more profound than the company’s regular algorithmic updates explicitly designed to adjust rankings.

Google in particular has a special responsibility. I wrote in Economic Power in the Age of Abundance:

The Internet is a world of abundance, and there is a new power that matters: the ability to make sense of that abundance, to index it, to find needles in the proverbial haystack. And that power is held by Google. Thus, while the audiences advertisers crave are now hopelessly fractured amongst an effectively infinite number of publishers, the readers they seek to reach by necessity start at the same place – Google – and thus, that is where the advertising money has gone.

Google’s position as the Internet chokepoint has been exceptionally profitable, but with great power comes great responsibility: in a welcome development Google is slowly accepting said responsibility and delisting revenge porn upon request. It’s the right move for both moral and practical reasons — moral because Google is uniquely positioned to prevent people’s lives from being ruined, and practical because if Google didn’t take action eventually the government would compel them. Indeed, that has already happened in Europe with the “right to be forgotten”, and while there is certainly a debate to be had as to whether or not that is good policy, the idea that Google is a hapless bystander is no longer viable.

Ultimately, I see the embrace of curation as a mark of maturation of the technology industry. Today’s technology companies have massive amounts of influence over what people the world over see and consume, and while there is a long ways to go when it comes to transparency about what is seen and why, at least everyone is now being honest about possessing that power in the first place.

Moreover, I’m excited about the real user benefit that can come from balancing algorithms and curation: while Facebook and Google rightly focus on algorithms only, most content is best delivered by a mixture; getting that mixture right will likely prove to be both massively popular and massively valuable.

Discuss this Article on the Stratechery Forum (members-only)

  1. The previous NYT Now app included articles from other publications as well, but in a different tab []
  2. The vast majority of which is inaccessible to Google, to the latter’s consternation []
  3. One more thing: don’t sleep on Twitter search. It remains the single best way to quickly catch up on anything that happened in the last few hours []
  4. For the record, I do believe Apple’s record is better than most []


The entire point of the name “Unicorn”, first coined by Aileen Lee in November 2013, is to describe something very rare: “U.S.-based software companies started since 2003 and valued at over $1 billion by public or private market investors” was Lee’s definition.

Over the last year-and-a-half the definition has changed a bit — most include international startups, and limit the list to private companies — but the biggest difference is the number of companies that qualify: Fortune’s Unicorn List has 100 companies on it, a big jump over the 39 counted by Lee.1 Many, including Andreessen Horowitz in a presentation entitled U.S. Tech Funding — What’s Going On?, have argued the reduction of a unicorn to something more akin to a zebra — exotic, but not exactly rare — is due to a shift in money from tech IPOs to late stage growth rounds. In the presentation these growth rounds are defined as rounds of >$40 million and given the label “quasi-IPOs”:

Screen Shot 2015-06-17 at 6.41.11 PM

Bill Gurley, for one, made clear he’s not buying this blurring of the lines in a March post aptly titled Investor’s Beware: Today’s 100M+ Late-stage Private Rounds Are Very Different from an IPO:

Some have argued that each of these companies would already be public in a prior era. Buying into such a notion is dangerous – dangerous for the entrepreneur and dangerous for the investor. Actually, very few of these companies are at a point where they could or should consider being public. Lost in this conversation are the dramatic differences between a high priced private round and an IPO. Understanding these differences is crucial to understanding the true risks in this large private-round phenomenon.

Gurley is particularly concerned with the lack of scrutiny for non-public companies, along with the ease with which unicorns can “mischaracterize their financial positioning relative to industry standard or norm.” The Wall Street Journal highlighted the latter concern last week:

As young technology companies jostle for investors who will pour money into the firms as they try to make it big and strike it rich, some companies are using unconventional financial terms. Instead of revenue, these privately held firms tout “bookings,” “annual recurring revenue” or other numbers that often far exceed actual revenue.

The practice is perfectly legal and doesn’t violate securities rules because the companies haven’t sold shares in an initial public offering. Public companies can use “non-GAAP” financial terms but must explain them and disclose how they differ from measurements that follow strict accounting rules…

Skeptics claim that the practice is yet another sign that the tech sector is plagued with overconfidence and setting itself up for a fall. They say investors who go along with vague, unconventional financial terms are inflating valuations and leaving almost no room for error at fledgling technology companies.

For his part Gurley has said on several occasions that there will “be some dead unicorns this year”; for the sake of argument, let’s say that he’s right.2 The question, then, is whether or not a dead unicorn (or ten) means the bubble has popped — or perhaps more accurately, whether or not there were a bubble at all.

Last week Chris Dixon described The Babe Ruth Effect in Venture Capital: the idea that swinging for the fences (10x returns) necessarily means more strikeouts (failed investments).

The Babe Ruth effect occurs in many categories of investing, but is especially pronounced in VC. As Peter Thiel observes:

Actual [venture capital] returns are incredibly skewed. The more a VC understands this skew pattern, the better the VC. Bad VCs tend to think the dashed line is flat, i.e. that all companies are created equal, and some just fail, spin wheels, or grow. In reality you get a power law distribution…

What is interesting and perhaps surprising is that the great funds lose money more often than good funds do. The best VCs funds truly do exemplify the Babe Ruth effect: they swing hard, and either hit big or miss big. You can’t have grand slams without a lot of strikeouts.

Dixon’s post is about the performance of individual venture capital firms, but I think the Babe Ruth framework is a useful way to think about the current crop of unicorns. Indeed, a close look at the valuations of the actual companies involved shows the exact sort of skew Thiel was talking about:3

Unicorn valuations from most to least valuable
Unicorn valuations from most to least valuable (in billions). Click to see a large version.

The line is a power curve — even unicorns fit the expected venture capital return. This has one really important implication that should shape the way we talk about unicorns and whether or not there is a bubble. Namely, for tech broadly nothing matters outside of ~10 or so companies:

  • Xiaomi and Uber alone account for 22% of Unicorn valuation
  • The top 10 most valuable companies (Xiaomi, Uber, Airbnb, Palantir, Snapchat, SpaceX, Flipkart, Pinterest, Dropbox, Theranos) account for 49% of Unicorn valuations
  • The top 20 account for 65% of Unicorn valuations

Anything that happens to any of these companies is a big deal when it comes to the overall health of the startup ecosystem; anything that happens outside isn’t. To put it in concrete terms, if Dropbox, probably the most fragile of the top 10 (members-only), were to have a down round or sell itself for less than its valuation, that would be a very big story. If Evernote, which is suddenly changing its CEO, were to do the same, it wouldn’t be nearly as big a deal. Keep this in mind when and if Gurley’s predicted unicorn deaths occur.

On the flip side, should a few of these top unicorns finally go public and validate their valuations, nearly the entire unicorn cohort would come out ahead. The entire list of 100 has raised around $55 billion collectively, which is about the same as the combined valuation of any three of the top 10 (or any two if one of the set is Uber or Xiaomi).4

There’s another insight to be drawn from that $55 billion collective investment: it turns out its distribution fits a linear curve much more closely than a power curve (at least once you remove Uber from the calculation):

Unicorn funding. Companies in order of valuation.
Unicorn funding (in billions). Companies in order of valuation. Click to see a large version.

This too echoes what you might expect at an individual VC firm — you invest equally, but profit unequally — but given that no VC firm is invested in every unicorn, there will clearly be winners and losers when it comes to individual firm performance. It’s possible (and probably likely) that the industry comes out ahead in the aggregate even as a significant majority of individual venture capital firms lose money.

I’ve previously laid out why It’s Not 1999: these unicorns are real companies with real business models and real revenues. Profitability is lagging, but given said business models — SaaS in the enterprise, and mostly ads in consumers — that’s to be expected. Most importantly, there simply isn’t the sort of public market froth that made the last bubble so contagious.

Indeed, I suspect that 1999 was less a cyclical peak than it was the top of the hype cycle:

Ideas - 1

  • The Internet was the technology trigger
  • The Dot Com era was the peak of Inflated Expectations
  • The bursting of the bubble and much of the 2000s was the trough of disillusionment
  • The last five years have been the slope of enlightenment

In this reading the technology industry is on the verge of the plateau of productivity, a steady march to remake industry after industry. That’s an exceptionally valuable prospect, and more than anything explains these unicorn valuations, particularly transformative market-makers like Uber or Airbnb.

To be clear, this isn’t exactly a controversial view; indeed, while macroeconomic factors like low interest rates play a role, I think a big reason for the quantity of unicorns is the fear of missing out on one of the greatest periods of value creation we have ever seen. However, some of the most valuable opportunities — particularly the aforementioned market-makers — have strong winner-take-all characteristics: this potentially limits the number of quality unicorns.

I think it’s this dichotomy that makes the current bubble discussion so difficult: most unicorns may be overvalued, but in aggregate they are probably undervalued. It turns out winner-take-all doesn’t apply just to the markets these startups are targeting, it applies to the startups themselves.

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  1. Fortune’s and Lee’s definitions are different: Fortune includes 15 companies that were started before 2003, plus 26 international companies; on the other hand, Fortune does not include any public companies []
  2. I suspect he is []
  3. Valuations are drawn from the aforementioned Fortune Unicorn List; I updated a few of them to reflect recent fundraising []
  4. The $55 billion was drawn from Crunchbase; it’s an estimate, as not all companies had information, some included secondary offerings, and there was a much greater chance of human error on my part []