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  • New Defaults

    One of the most well-known papers in behavioral economics is The Power of Suggestion: Inertia in 401(k) Participation and Savings Behavior by Brigitte C. Madrian and Dennis F. Shea. From the introduction:

    In this paper we analyze the 401(k) savings behavior of employees in a large U. S. corporation before and after an interesting change in the company 401(k) plan. Before the plan change, employees who enrolled in the 401(k) plan were required to affirmatively elect participation. After the plan change, employees were automatically enrolled in the 401(k) plan immediately upon hire unless they made a negative election to opt out of the plan. Although none of the economic features of the plan changed, this switch to automatic and immediate enrollment dramatically changed the savings behavior of employees.

    I would certainly call a shift from 37 percent participation to 86 percent participation a dramatic shift! However, as Madrian and Shea note, there was a downside:

    For the NEW cohort, 80 percent of 401(k) contributions are allocated to the money market fund, while only 16 percent of contributions go into stock funds. In contrast, the other cohorts allocate roughly 70 percent of their 401(k) contributions to stock funds, with less than 10 percent earmarked for the money market fund

    The issue is that the money market fund was the default choice, which meant that while the new program helped people save more, it also led folks who would have chosen better-performing funds to earn far less than they would have. Defaults are powerful!

    Just ask Facebook, which is conducting a (probably futile) public relations campaign against Apple over iOS 14’s impending “App Tracking Transparency” requirement. Apple told Bloomberg:

    Apple defended its iOS updates, saying it was “standing up” for people who use its devices. “Users should know when their data is being collected and shared across other apps and websites — and they should have the choice to allow that or not,” an Apple spokeswoman said in a statement. “App Tracking Transparency in iOS 14 does not require Facebook to change its approach to tracking users and creating targeted advertising, it simply requires they give users a choice.”

    In fact, users have had a choice for several years; Apple has given customers the ability to switch off their device’s “Identifier for Advertisers” (IDFA) since 2012. What makes iOS 14 different is the change in defaults: instead of users needing to turn IDFA off, every app has to explicitly ask for it to be turned on, and given the arguably misleading way that this tracking is presented by the media generally and Apple specifically, both Facebook and Apple expect customers to say no (Facebook launched its campaign at the same time it added the prompt).1 Changing the defaults can change the course of a multi-billion dollar company.

    China, Control, and Quarantine

    One year ago, on January 5, 2020, Wuhan, Hubei province’s largest city, was set to host the 3rd Session of the 13th Hubei Provincial People’s Congress and the 3rd Session of the 12th Hubei Provincial Committee of the Chinese People’s Political Consultative Conference, the two most important political gatherings of the year. Perhaps that is why the city reported no new cases of a mysterious respiratory illness that had started appearing the previous November for the following 11 days. Three weeks later, the entire city was locked down in a drastic attempt to contain the virus we now know as SARS-CoV-2.

    Last week, meanwhile, came a lockdown of another sort; from the New York Times:

    A Chinese court on Monday sentenced a citizen journalist who documented the early days of the coronavirus outbreak to four years in prison, sending a stark warning to those challenging the government’s official narrative of the pandemic. Zhang Zhan, the 37-year-old citizen journalist, was the first known person to face trial for chronicling China’s outbreak. Ms. Zhang, a former lawyer, had traveled to Wuhan from her home in Shanghai in February, at the height of China’s outbreak, to see the toll from the virus in the city where it first emerged. For several months she shared videos that showed crowded hospitals and residents worrying about their incomes…

    Ms. Zhang’s trial, at the Shanghai Pudong New District People’s Court on Monday, lasted less than three hours. The official charge on which she was convicted was “picking quarrels and provoking trouble,” a vague charge commonly used against critics of the government. Prosecutors had initially recommended a sentence between four and five years.

    For all of the consternation in China about the the initial cover-up, Zhang’s case is a reminder that controlling information for political purposes is China’s default approach. It is worth noting, though, that the willingness to exert control can be useful, particularly during a pandemic. While Wuhan’s lockdown drew the most attention, and some degree of emulation, that wasn’t what actually stopped the virus’ spread. The Wall Street Journal explained in March:

    The cordon sanitaire that began around Wuhan and two nearby cities on Jan. 23 helped slow the virus’s transmission to other parts of China, but didn’t really stop it in Wuhan itself, these experts say. Instead, the virus kept spreading among family members in homes, in large part because hospitals were too overwhelmed to handle all the patients, according to doctors and patients there.

    What really turned the tide in Wuhan was a shift after Feb. 2 to a more aggressive and systematic quarantine regime whereby suspected or mild cases — and even healthy close contacts of confirmed cases — were sent to makeshift hospitals and temporary quarantine centers. The tactics required turning hundreds of hotels, schools and other places into quarantine centers, as well as building two new hospitals and creating 14 temporary ones in public buildings.

    These centralized quarantines were not optional, and they were effective: China had the coronavirus largely under control by late spring, and the economy has unsurprisingly bounced back; China is expected to be the only Group of 20 country to record positive growth for the year.

    The West’s Haphazard Approach

    The United States (along with Europe, it should be noted), has not done so well. Actually, that’s being generous: by pursuing selective lockdowns and completely eschewing centralized quarantine, the West has managed to hurt its economies and kill its small businesses, without actually stopping the spread of the coronavirus. At the same time, as Tyler Cowen argued in Bloomberg last May, centralized quarantines were never really a serious option:

    There has been surprisingly little debate in America about one strategy often cited as crucial for preventing and controlling the spread of Covid-19: coercive isolation and quarantine, even for mild cases. China, Singapore and South Korea separate people from their families if they test positive, typically sending them to dorms, makeshift hospitals or hotels. Vietnam and Hong Kong have gone further, sometimes isolating the close contacts of patients.

    I am here to tell you that those practices are wrong, at least for the U.S. They are a form of detainment without due process, contrary to the spirit of the Constitution and, more important, to American notions of individual rights. Yes, those who test positive should have greater options for self-isolation than they currently do. But if a family wishes to stick together and care for each other, it is not the province of the government to tell them otherwise.

    Cowen’s first paragraph makes clear that the views in the second are widely held: no politician that I know of, in the U.S. or Europe, seriously argued for centralized quarantine, even though it was likely the only way to contain SARS-CoV-2. The very idea of governments locking up innocent civilians is counter to our default assumption that individual freedom is inviolate.

    That, though, is why it is strange that so many have acquiesced to ever-tightening restrictions on information. It seems that over the last year to have a pro-free speech position has become the exception; the default is to push for censorship, if not by the government — thanks to that pesky First Amendment — then instead by private corporations. And meanwhile, said private corporations, eager to protect their money-making monopolies (in the political sense if not the legal one), are happy to comply; YouTube led the way, declaring in April that it would ban any coronavirus content that contradicted the same World Health Organization that tweeted on January 14th that there was no human-to-human transmission, but most tech companies have since fallen in line.

    To be perfectly clear, I am in no way denying the presence of huge amounts of misinformation, which, by the way, continue to circulate widely despite tech companies’ best efforts. What concerns me is that this sort of dime store authoritarianism is resulting in the worst possible outcome:

    Being half authoritarian and half free has been the worst outcome in terms of the pandemic

    China’s control of information is not ideal — the Wuhan coverup is about as compelling an example as you will ever see of the downsides of information control — but at the same time, it would be dishonest to not recognize that authoritarianism can be effective in actually controlling a pandemic. The West, though, will neither do what it takes to contain the coronavirus, even as we flirt with information suppression at scale. What makes this nefarious is that the cost of the latter is often unseen — it is the ideas never broached, and the risks never taken. But how do you measure opportunity cost?

    Vaccines and Defaults

    Here the coronavirus again provides a compelling example, this time in the form of Moderna’s RNA vaccines. David Wallace-Wells wrote in New York Magazine in December:

    You may be surprised to learn that of the trio of long-awaited coronavirus vaccines, the most promising, Moderna’s mRNA-1273, which reported a 94.5 percent efficacy rate on November 16, had been designed by January 13. This was just two days after the genetic sequence had been made public in an act of scientific and humanitarian generosity that resulted in China’s Yong-Zhen Zhang’s being temporarily forced out of his lab. In Massachusetts, the Moderna vaccine design took all of one weekend. It was completed before China had even acknowledged that the disease could be transmitted from human to human, more than a week before the first confirmed coronavirus case in the United States. By the time the first American death was announced a month later, the vaccine had already been manufactured and shipped to the National Institutes of Health for the beginning of its Phase I clinical trial. This is — as the country and the world are rightly celebrating — the fastest timeline of development in the history of vaccines. It also means that for the entire span of the pandemic in this country, which has already killed more than 250,000 Americans, we had the tools we needed to prevent it.

    As Wallace-Wells notes, this does not mean that the Moderna vaccine should have — or could have — been rolled out in January. It does, though, provide a powerful thought experiment about opportunity cost.

    Opportunity cost is distinct from the costs normally calculated in a cost-benefit analysis: those costs are real costs, in that they are actually incurred. For example, if I want to buy a new sweater, it will cost me money. Opportunity cost, on the other hand, is the choice not made. To return to the sweater example, whatever funds I use to buy a sweater cannot be used to buy slacks — the slacks are the opportunity cost.

    In the case of the vaccine, the opportunity costs of not deploying it the moment it was developed are enormous: hundreds of thousands of lives saved in the U.S. alone, millions around the world, and untold economic destruction avoided. Again, to be clear, I’m not saying this choice was available to us, and you can easily concoct another thought experiment where the vaccine goes horribly wrong. What makes this thought experiment worthwhile, though, is that it is such a powerful example of opportunity costs, and it is opportunity costs — the thing not learned — that are the biggest casualty of defaulting towards information control instead of free speech.

    This isn’t the only mistaken default. Another topic that received minimal discussion was the concept of human challenge trials, where individuals could volunteer — and be richly compensated — to be exposed to the virus to more quickly test the vaccination’s efficacy. When I broached the idea on Twitter, plenty of folks were quick to cite the very real ethical concerns with the concept, but few seemed willing to acknowledge the opportunity costs incurred by waiting a single day longer than necessary, which ought to present ethical concerns of their own. There was also no discussion of making the vaccine broadly available in conjunction with Phase III trials, despite the fact that RNA-based vaccines are inherently safer than traditional vaccines based on weakened or inactivated viruses. Similarly, when I expressed bafflement that people weren’t outraged by the FDA’s delay in approving the vaccines, the response of many was to insist the agency was rightly prioritizing safety. What, though, about the safety of those suffering from a pandemic that was accelerating? At every step the default was a bias towards the status quo of no vaccine, no matter how great the opportunity cost may have been.

    What is most dispiriting, though, is this chart from Bloomberg:

    A map of how many vaccines have been distributed in the U.S.

    As of this morning only 30% of distributed vaccines have been administered; that’s not quite as bad as it seems given the U.S. policy to hold back the second shot in reserve (itself a conservative decision that seems driven by the status quo default), but that still means millions of shots are unused and risk expiration. A major hold-up has been strict prioritization protocols, which prioritize equitable distribution over speed. It’s another misplaced default.

    Technology and Opportunity

    At this point many of you are surly muttering that this was the fastest vaccine development program in history, and that the U.S., for all of its struggles, has already vaccinated 1.42% of its population, the 3rd most in the world. Both are true, and worth celebrating.

    At the same time, the timeline in that New York Magazine article is worth keeping in mind: the single most important reason these vaccines were developed so quickly was because of technological progress. This brilliant article explains how mRNA vaccinations work in computer programming terms, but the entire concept is built on years of work. The Harvard Health Blog noted:

    Like every breakthrough, the science behind the mRNA vaccine builds on many previous breakthroughs, including:

    • Understanding the structure of DNA and mRNA, and how they work to produce a protein.
    • Inventing technology to determine the genetic sequence of a virus.
    • Inventing technology to build an mRNA that would make a particular protein.
    • Overcoming all of the obstacles that could keep mRNA injected into the muscle of a person’s arm from finding its way to immune system cells deep within the body, and coaxing those cells to make the critical protein.
    • Information technology to transmit knowledge around the world at light-speed.

    Every one of these past discoveries depended on the willingness of scientists to persist in pursuing their longshot dreams — often despite enormous skepticism and even ridicule — and the willingness of society to invest in their research.

    Longshot dreams, enormous skepticism, and even ridicule certainly sound familiar to anyone associated with Silicon Valley, and there is an analogy to be made between how technology accelerated vaccine development, even in the face of conservative defaults, and how the technology industry broadly has driven U.S. economic growth for decades now, even in the face of stagnation elsewhere.

    What makes software so compelling to anyone ambitious is that (1) the potential applications are limitless and (2) the limitations on creation are your own imagination, not external regulations. This certainly has its downsides, as anyone trying to get a software release out the door understands; you can add new features and fix bugs forever, because after all, it’s just software. At the same time, you can build anything you want, without asking for permission, and what could be more exciting than that?

    I’m reminded of this old Steve Jobs interview:

    Jobs was talking about life in general, but the potential he articulates is much more easily grasped in software; what is notable is that it was the software-driven companies that performed the best throughout the pandemic. Perhaps the assumption that any problem is solvable is a muscle that can be developed in software and applied to the real world? Amazon is a striking example in this regard: the so-called “tech” company hired over 400,000 new people in 2020, as it brought its massive logistics network to bear in the face of overwhelming demand; no wonder many have been joking on Twitter that the company should be in charge of the vaccination rollout.

    Or, better yet, we ought to figure out how to export the Amazon mindset beyond the world of technology, but to do that we need new defaults.

    New Defaults

    Start with these three:

    • First, it should be the default that free speech is a good thing, that more information is better than less information, and that the solution to misinformation is improving our ability to tell the difference, not futilely trying to be China-lite without any of the upside.
    • Second, it should be the default that the status quo is a bad thing; instead of justifying why something should be done, the burden of proof should rest on those who believe things should remain the same. This sounds radical, but given the fact that the world is undergoing profound changes driven by the Internet, it is the attempt to preserve the unsustainable that is radical.
    • Third, it should be the default to move fast, and value experimentation over perfection. The other opportunity cost of decisions not made is lessons not learned; given the speed with which information is disseminated, this cost is higher than ever.

    The urgency of this reset should come from where all of this started: China. Dan Wang wrote in his 2020 letter:

    This year made me believe that China is the country with the most can-do spirit in the world. Every segment of society mobilized to contain the pandemic. One manufacturer expressed astonishment to me at how slowly western counterparts moved. US companies had to ask whether making masks aligned with the company’s core competence. Chinese companies simply decided that making money is their core competence, and therefore they should be making masks. The State Council reported that between March and May, China exported 70 billion masks and nearly 100,000 ventilators. Some of these masks had problems early on, but the manufacturers learned and fixed them or were culled by regulatory action, and China’s exports were able to grow when no one else could restart production. Soon enough, exports of masks were big enough to be seen in the export data.

    This, to be clear, was not the result of authoritarianism, but despite it; Taiwan exhibited the exact same sort can-do attitude alongside a free press, elections, and pig intestines in the legislature. China, meanwhile, is increasing control of the private sector; the latest example is Alibaba and Jack Ma, who was last seen in October criticizing the country’s regulators; China proceeded to kill Ant Group’s IPO, in a signal to any other billionaires with big ideas about who was boss, and Ma’s whereabouts are unknown. The U.S. can absolutely compete with this approach, not by imitating it, but by doing the exact opposite.

    Intentions Versus Outcomes

    A few years after Madrian and Shea’s landmark study, Richard Thaler, the Nobel-prize winning economist at the University of Chicago, devised a new approach for 401(k) enrollments that sought to overcome the downside of default choices (while preserving their upside). What I wanted to highlight, though, was this bit from the introduction of Save More Tomorrow: Using Behavioral Economics to Increase Employee Saving:

    Economic theory generally assumes that people solve important problems as economists would. The life cycle theory of saving is a good example. Households are assumed to want to smooth consumption over the life cycle and are expected to solve the relevant optimization problem in each period before deciding how much to consume and how much to save. Actual household behavior might differ from this optimal plan for at least two reasons. First, the problem is a hard one, even for an economist, so households might fail to compute the correct savings rate. Second, even if the correct savings rate were known, households might lack the self-control to reduce current consumption in favor of future consumption…

    For whatever reason, some employees at firms that offer only defined-contribution plans contribute little or nothing to the plan. In this paper, we take seriously the possibility that some of these low-saving workers are making a mistake. By calling their low-saving behavior a mistake, we mean that they might characterize the action the same way, just as someone who is 100 pounds overweight might agree that he or she weighs too much. We then use principles from psychology and behavioral economics to devise a program to help people save more.

    I suspect a similar story can be told about our slide to defaulting that free speech is bad, that the status quo should be the priority, and that perfect is preferable to good. These are mistakes, even as they are understandable. After all, misinformation is a bad thing, change is uncertain, and no one wants to be the one that screwed up. Everyone has good intentions; the mistake is in valuing intentions over outcomes.

    To that end, the point of this article was not really to discuss the coronavirus or vaccinations: with regards to the latter, there is more to praise than to criticize, and I freely admit I am not an expert about either. And yet, that isn’t a reason to settle, or to not examine our defaults: why can’t we accomplish other big projects in a year? What else can we build with so much broad benefit so quickly? And critically, what can we change about our psychology and behavior to make that happen? New defaults are the best place to start.

    1. This previously stated that “Indeed, Facebook won’t even bother asking“, which is no longer true ↩

  • The 2020 Stratechery Year in Review

    From the beginning of Stratechery I have posited that writing about tech is a way to write about everything, given the way in which the Internet is affecting every part of society. The pandemic of 2020 has put this thesis on steroids: the lasting impact of COVID will be not entirely new ways of living, but rather the dramatic acceleration of trends that were already in place, particularly those enabled by technology. This includes real world issues like working-from-home, and new digital questions raised by the sheer quantity of information, much of it wrong, but some very right.

    A drawing of The Implication of More Information

    Stratechery explored all of these issues this year, in both 44 Weekly Articles and 141 Daily Updates (including 18 Daily Update Interviews).

    This was also an exciting year for new product launches: in February Stratechery launched The Stratechery Podcast which lets you consume Stratechery in your favorite podcast player. Then, in May, I launched Dithering, a thrice-weekly 15 minute podcast, with Daring Fireball‘s John Gruber.

    iTunes is only a directory

    Today, as per tradition, I summarize the most popular and most important posts of the year on Stratechery.

    You can find previous years here: 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013

    Here is the 2020 list.

    The Five Most-Viewed Articles

    The five most-viewed articles on Stratechery according to page views:

    1. The TikTok War — How TikTok exposed Facebook’s blindspot, thanks to its Chinese roots, and why those Chinese roots make TikTok a genuine concern. See also this Daily Update comparing TikTok to Quibi, and this Daily Update about how the TikTok ban went wrong.
    2. The End of OS X — OS X is retired, but fortunately, its legacy appears to live on in macOS 11.0.
    3. The Anti-Amazon Alliance — Google Shopping is changing its model, suggesting Google is joining the Anti-Amazon Alliance; 3rd-party merchants should do the same.
    4. India, Jio, and the Four Internets — There are four Internets: China versus the U.S., and the E.U. and India. India’s potential new model rests on Jio. See also this Daily Update about how Jio’s success shows why Facebook Free Basics was the wrong approach.
    5. The Slack Social Network — Slack lost to Microsoft head-to-head, but has shifted to a horizontal strategy that the vertically-oriented Microsoft can’t match. See also this Daily Update about Salesforce’s acquisition of Slack.

    A drawing of The Four Internets

    Coronavirus and Information

    The dominant story of 2020 was obviously COVID, but what was particularly interesting from a tech perspective were the debates about surfacing new information while battling misinformation. Notably, the first four articles were a sort of miniseries published in March; the final article discussed the same issues in the context of the election.

    • Zero Trust Information — Zero Trust Networking is security with Internet assumptions; there is tremendous value if we apply the same approach to information.
    • Defining Information — In a follow-up to Zero Trust Information, exploring the four types of information and how their value changes with time.
    • Compaq and Coronavirus — Compaq’s descent from a company of action to a brand is a frightening parable for the the West’s focus on talk over action.
    • Unmasking Twitter — Twitter has a new policy to listen to experts about what content to limit; what happens, though, when experts are wrong?
    • Twitter, Responsibility, and Accountability — Twitter went too far last week for reasons that go back to 2016 and the unfair blaming of tech for media’s mistakes.

    A drawing of Utility Versus Interest on Social Media

    The Big Picture

    These are the articles where writing about tech means writing about the world broadly; this has never been more true than in 2020, particularly given that we are at The End of the Beginning.

    • The End of the Beginning — The beginning of technology was about the shift from batched computing in one place to continuous computing everywhere. That era of paradigm changes may be over, which means the real changes are only beginning. See also this Daily Update which discussed The End of the Beginning in the context of Carlota Perez’s Technological Revolutions and Financial Capital.
    • Coronavirus Clarity — The coronavirus crisis is making clear just how powerful tech companies are; hopefully this leads to a much more productive conversation about how that power should be utilized or regulated. See also How Tech Can Build, about Marc Andreessen’s seminal essay.
    • Chips and Geopolitics — TSMC showed the power of modularization, and now they are core to the U.S. national security strategy. See also this Daily Update about TSMC, Intel, and U.S. national security.
    • Dust in the Light — The Internet ends gatekeepers and increases transparency, which has world-altering effects — both good and bad.
    • Social Networking 2.0 — Facebook and Twitter represent the v1 of Social Networking; it’s a bad copy of the analog world, whereas v2 is something unique to digital, and a lot more promising. See also this Daily Update about how Facebook failed to build a social media platform.

    A drawing of The Evolution of Computing

    Niches and Direct-to-Consumer

    While Stratechery frequently discusses Aggregation Theory, a major focus in 2020 were companies and platforms that go direct-to-consumer by focusing on niches.

    • Email Addresses and Razor Blades — The fate of Harry’s and other DTC companies, particularly relative to companies like Credit Karma, highlight how the Internet elevates the importance of demand over supply.
    • Platforms in an Aggregator World — Facebook Shops are good for Shopify merchants, but bad for Shopify; the answer is to push more into the real world. See also the afore-linked The Anti-Amazon Alliance.
    • Never-Ending Niches — The Internet changed how media competes to focus and quality, but quality is defined by your niche.
    • Disney and Integrators Versus Aggregators — Disney’s reorganization reinforces their integrated strategy; there is a lot to learn for anyone competing with Aggregators.
    • The Idea Adoption Curve — Mapping the technology adoption curve to ideas gives insights as to which business models work on which parts of the addressable market.

    A drawing of Every Niche Competes on its Own Terms

    Antitrust, Regulation, and the App Store

    One month after writing Aggregation Theory I noted that regulation was inevitable; that inevitable moment arrived in a big way in 2020, with Congressional hearings, reports, and multiple antitrust lawsuits. Apple also received unprecedented attention for its control of the App Store; both were big topics on Stratechery:

    A drawing of Apple's Leverage of Control of Payment Processing

    Five Companies

    Stratechery had its usual focus on specific companies and the evolution of their strategies in 2020. In addition to the afore-linked India, Jio, and the Four Internets:

    • Visa, Plaid, Networks, and Jobs — The history of credit cards helps explain why Plaid is valuable to Visa, and how Visa can make it significantly better. See also this Daily Update about the Justice Department’s lawsuit to block the Visa-Plaid acquisition.
    • Apple, ARM, and Intel explained how Apple ended up replacing Intel chips with their own ARM chips, which is a core part of Apple’s Shifting Differentiation to superior hardware integrated with exclusive software. See also this Daily Update about Intel’s ongoing struggles.
    • Nvidia’s Integration Dreams — Nvidia’s acquisition of ARM only makes sense from a financial perspective, unless you buy Jensen Huang’s datacenter dreams.
    • 2020 Bundles — The state of bundles in 2020: Netflix, Disney, Amazon, Microsoft, and Apple. Plus, Microsoft’s purchase of ZeniMax. See also this Daily Update with more about Microsoft’s ZeniMax purchase, and this Daily Update that explains how Microsoft’s Xbox strategy is dramatically different from Sony’s PS5 strategy.
    • Stripe: Platform of Platforms — Stripe’s announcement of Treasury — banking-as-a-service — manifests the breadth of the company’s ambition.

    A drawing of The Visa Network

    Stratechery Interviews

    Thanks to the launch of the Stratechery Daily Update Podcast I devoted more Daily Updates this year to interviews, including:

    A drawing of Platform of Platforms

    The Year in Daily Updates

    Fifteen of my favorite Daily Updates:

    A drawing of Ben's Communities

    I am so grateful to the Stratechery (and Dithering!) subscribers that make it possible for me to do this as a job. I wish all of you a Merry Christmas and Happy New Year, and I’m looking forward to a great 2021!

  • Social Networking 2.0

    It’s a rather motley crew. One is a nurse, another a lawyer, a third an investment adviser. There are three programmers, a soldier, and a data scientist. An entrepreneur, a consultant, and, I just found out today, a nuclear engineer. The ring leaders are a hotel clerk and a person we have known for years, yet no one knows his name, and then there is me.

    We talk about all kinds of things: video games and COVID, family frustrations and bad bosses, and whether Aaron Rodgers is better than Patrick Mahomes (if only Rodgers had had Andy Reid). And, of course, the Milwaukee Bucks. That’s the reason we are in the same group, after all, which is another way of noting that all of us — except the Kansas City Chiefs fan — are originally from Wisconsin. And yet many of us had never met each other until a couple of years ago, when we attended a Bucks game together; the physical world was a trailing indicator.

    Home on the Internet

    While my Twitter bio has changed over the years, the last sentence has, as far as I can remember, stayed the same:

    Ben's Twitter profile

    The proximate cause for that sentence was the fact I lived in Asia, even as my Twitter-personae was firmly rooted in the United States, whether that be because of my longstanding interest in technology, or enthusiastic support of Wisconsin sports teams. And yet, when I moved back to the United States, my interest and relationship to Taiwan remained, and Twitter specifically and the Internet broadly were a way to stay connected; the bio still fit.

    For a time that bio described Twitter as well: for a particular type of person, someone who thrived on information — the more the better! — Twitter was a place to not simply learn but to find people like yourself. That is how the “Fiefdom”, the name the aforementioned motley crew gave ourselves, found each other. We all loved the Bucks — or, perhaps more accurately, loved to complain about the Bucks — but while Twitter helped us find each other, over the past few years the medium has grown too noisy, performative, and combative to be a place to simply hang out; we have a group DM, which, frankly, sucks, but at least it is our own place.

    That’s not my only online community: while the writing of Stratechery is a solo affair, building new features like the Daily Update Podcast or simply dealing with ongoing administrative affairs requires a team that is scattered around the world; we hang out in Slack. Another group of tech enthusiast friends is in another Slack, and a third, primarily folks from Silicon Valley, is in WhatsApp. Meanwhile, I have friends and family centered in Wisconsin (we use iMessage), and, of course Taiwan (LINE for family, WhatsApp for friends). The end result is something I am proud of:

    Ben's communities

    The pride arises from a piece of advice I received when I announced I was moving back to Taiwan seven years ago: a mentor was worried about how I would find the support and friendship everyone needs if I were living halfway around the world; he told me that while it wouldn’t be ideal, perhaps I could piece together friendships in different spaces as a way to make do. In fact, not only have I managed to do exactly that, I firmly believe the outcome is a superior one, and reason for optimism in a tech landscape sorely in need of it.

    Social Networking 1.0

    Earlier this year in The TikTok War I explained why the first version of products on the Internet were usually a bit of a dud:

    It is always tricky to look at the analog world if you are trying to understand the digital one. When it comes to designing products, a pattern you see repeatedly is copying what came before, poorly, and only later creating something native to the medium.

    Consider text: given that newspapers monetized by placing advertisements next to news stories, the first websites tried to monetize by — you guessed it — placing advertisements next to news stories. This worked, but not particularly well; publishers talked about print dollars and digital dimes, and later mobile pennies. Sure, the Internet drew attention, but it just didn’t monetize well.

    What changed was the feed, something uniquely enabled by digital. Whereas a newspaper had to be defined up-front, such that it could be printed and distributed at scale, a feed is tailored to the individual in real-time — and so are the advertisements. Suddenly it was print that was worth pennies, while the Internet generally and mobile especially were worth more than newspapers ever were.

    The most famous feed in technology is the Facebook feed, which through its algorithmic magic made the lives of your friends and family seem far more tantalizing than they probably were in reality. The result was a social network that the FTC, in a lawsuit filed last week, claimed was a monopoly:

    Facebook holds monopoly power in the market for personal social networking services (“personal social networking” or “personal social networking services”) in the United States, which it enjoys primarily through its control of the largest and most profitable social network in the world, known internally at Facebook as “Facebook Blue,” and to much of the world simply as “Facebook.”

    The FTC focused on “friends and family”:

    As Facebook has long recognized, its personal social networking monopoly is protected by high barriers to entry, including strong network effects. In particular, because a personal social network is generally more valuable to a user when more of that user’s friends and family are already members, a new entrant faces significant difficulties in attracting a sufficient user base to compete with Facebook.

    I certainly felt this way previously; in 2016 I wrote in How Facebook Squashed Twitter:

    Facebook always had an inherent advantage over Twitter in that its network, at least in the beginning, was based on networks that already existed in the offline world, namely, people you already knew. That made the service immediately approachable and useful for basically everyone. Twitter, on the other hand, was more about following people you didn’t know based on your interests. This theoretically applied to everyone as well, but uncovering those interests and building an appropriate list of people to follow had to be done from scratch.

    I increasingly wonder, though, how much of my previous Facebook analysis was wrong not because I misunderstood Facebook, but because I overestimated Twitter. I noted last week while writing about the FTC’s lawsuit in the Daily Update:

    I would prefer a world where the [Instagram] deal didn’t happen. As I have noted I believe that absent a deal there would be more competition in the advertising space, and more consumer-focused startups.

    At the same time, I do have serious rule-of-law reservations about undoing a deal eight years on, particularly given the fact that it appears that the advertising-supported space is doing better than I thought a few years ago: Snapchat in particular is building a great business, LinkedIn is doing much better, and TikTok is obviously on its way. Honestly, I wonder to what extent Twitter’s endemic poor management made the advertising space seem worse than it actually was?

    I would go further: Twitter’s incompetence didn’t simply make Facebook’s advertising business look more dominant than it should have; it led all of us — including the FTC — to miss the point that friends and family was Social Networking 1.0: something imported from the analog world that, as time goes on, will be viewed as inferior to the far richer universe that is Social Networking 2.0.

    Twitter Incompetence and Identities

    Go back to the Fiefdom that I started with, and the terrible experience that are Twitter group direct messages. It’s impossible to keep your place, so if you follow a link or answer another message, you are dropped to the bottom of the thread. Of course there is no searching, and no third-party API so that someone else could do a better job. The thread also frequently fails to update in real-time, meaning you sometimes reply to questions that have already been answered, which is unfortunate because there is no way to respond to individual messages. It’s honestly awful.

    And yet, we use it anyway, because that is where our friendship group formed around our shared interest in the Bucks, and it is the interest graph where Twitter has always had the potential to differentiate itself; in 2015, when it was already clear that the company had missed its opportunity to be great, I wrote in Twitter and What Might Have Been:

    What makes Twitter the company valuable is not Twitter the app or 140 characters or @names or anything else having to do with the product: rather, it’s the interest graph that is nearly priceless. More specifically, it is Twitter identities and the understanding that can be gleaned from how those identities are used and how they interact that matters.

    Identities — plural — referred to the many users of Twitter, but a second thing that is interesting about my Twitter group is that @benthompson is not a member; my alter-ego, @notechben is. I created that account — which, I will tell you right now, is pretty annoying to follow — so that I could tweet freely during basketball games without losing followers from my primary Twitter account. After all, just because you like my takes on tech, it does not necessarily follow that you like my takes on sports.

    What I increasingly realize, though, is that separating my identities on Twitter does not mean a lesser experience, but a far superior one; social interaction in any medium is always a balance between self-expression and the accommodation of others, which means that in the analog world it is a constant struggle to strike a balance between being myself and annoying everyone around me at some point or another. The magic of the Internet, though, is that you can be whatever you want to be:

    On the Internet, nobody knows you're a dog
    Image from The New Yorker cartoon by Peter Steiner, 1993

    There are clear downsides to this property of the Internet, particularly on public forums like Twitter, where trolls can attack anyone, bots can astroturf any subject, and even nation-states can seek to incite civil unrest. That’s the thing, though: public broadcast mediums are Social Networking 1.0 as well.

    From v1 to v2

    Remember that the key characteristic of v1 digital products is that they simply copy what already exists offline. For Facebook that meant digitizing connections between friends and family, and for Twitter it meant broadcasting conversations as if you were sitting at a bar. Such literal translations, though, have limits: Facebook soon found it necessary to augment content from friends and family with professionally produced content from publishers, while public Twitter conversation has disappeared in the face of performative putdowns and political proclamations. The problem is that digital makes analog goods worse: a lot of what your friends and family believe is boring or objectionable, and conversations constrained by the geography of a bar simply don’t translate to a worldwide audience.

    What truly makes a category is v2: products that are only possible because of the unique properties of digital. That, for example, is why TikTok is such a threat to Facebook’s hold on attention; again from The TikTok War:

    While it is easy for users to create text updates, and, with the rise of smartphones, even easier to create pictures, producing video is difficult. Until recently, phone cameras were even worse at video than they were photos, but more importantly, compelling video takes some degree of planning and skill. The chances of your typical Facebook user having a network full of accomplished videographers is slim, and remember, when it comes to showing user-generated content, Facebook is constrained by who your friends are…

    ByteDance’s 2016 launch of Douyin — the Chinese version of TikTok — revealed another, even more important benefit to relying purely on the algorithm: by expanding the library of available video from those made by your network to any video made by anyone on the service, Douyin/TikTok leverages the sheer scale of user-generated content to generate far more compelling content than professionals could ever generate, and relies on its algorithms to ensure that users are only seeing the cream of the crop.

    TikTok’s “network”, such that it is, is the entire world, which means its content is better than Facebook’s could ever be, which means it is a far better attention sink than Facebook could ever be.

    Meanwhile, on the other extreme, public broadcasting by default — whether that broadcasting be to the entire world, as on Twitter, or to all of your friends and family, as on Facebook — actually constrains your ability to communicate, because you run into the conflict I described earlier: your “whole self”, versus others’ only somewhat overlapping interests.

    This is where messaging is a much more natural fit, and, as far as the depth of your network is concerned, messaging services are just as much a threat to v1 social networks connectivity as TikTok is to Facebook’s hold on attention: I can simultaneously be a Bucks fan with the Fiefdom, be a tech enthusiast with my Slack group, explore ideas with my WhatsApp group, and talk politics with my trusted friends. The fact that I am not my whole self in any of these groups is a feature, not a bug, and one that is uniquely made possible by digital.

    Social Media Optimism

    Facebook, despite its immense success, has been far more attuned to the inadequacies of its social networking model than Twitter has, and has been pushing aggressively to adapt its products to a v2 world. That includes its shift to emphasizing Groups in 2017, and its focus on messaging, including the spin-out of Messenger, the acquisition of WhatsApp, and its attempts to unify the messaging experience across its platforms.

    Even that, though, suggests that the company can’t entirely escape its roots: having one identity is a core principle for Facebook, which is great for advertising if nothing else, but at odds with the desire of many to be different parts of themselves to different people in different contexts. Twitter, meanwhile, is unlikely to ever recover from its missed opportunity to dominate the interest graph.

    Instead, the role for both products will be as a bridge between attention-focused products on one side, and private interest-defined trusted groups on the other.

    v1 vs v2 Social Networks

    Their networks still have value, but primarily as a tool for distribution and reach of content that will increasingly be created in one place, and discussed in another.1

    This, needless to say, doesn’t seem like much of a monopoly, certainly not one worth reaching back in time to retroactively change the rules of the game. What is encouraging, though, is that this view also gives hope for the seemingly hopeless climate that has been fostered by v1 social networks. The problem with forcing everyone to be their “whole selves” for the world, whether they want to or not, is that it becomes strikingly difficult to find common ground. After all, there is always something about everyone that is annoying or off-putting.

    On the flipside, to the extent that v2 social networking allows people to be themselves in all the different ways they wish to be, the more likely it is they become close to people who see other parts of the world in ways that differ from their own. Critically, though, unlike Facebook or Twitter, that exposure happens in an environment of trust that encourages understanding, not posturing.

    This has been the case for me: I am in private groups with plenty of folks that I disagree with about a whole host of things, but because we share a common interest, and are ok being trusted friends on that vector, I have learned a lot about why they believe what they believe about a bunch of issues. I think it helps my analysis, and I think it makes me a better citizen. That certainly isn’t our expectation of social media today, but that is because we are stuck on v1.

    I wrote a follow-up to this article in this Daily Update.

    1. Instagram and Snapchat, in my estimation, are fully self-contained networks that encapsulate content generation, distribution, and discussion; they are the integrated version of this model ↩

  • Privacy Labels and Lookalike Audiences

    In 1990, Congress passed the Nutrition Labeling and Education Act, which required nutrition labels for nearly all packaged food products; the label includes a standard serving measurement, calories per serving, and the “% Daily Value” for nutrients like fat, cholesterol, sodium, carbohydrates, protein, and a number of vitamins and minerals. For many consumers, though, labels were like road signs: they provided tactical assistance while grocery shopping, but you still needed a map for how to eat.

    Enter the food pyramid, which was introduced by the U.S. Department of Agriculture in 1992:

    The USDA Food Pyramid

    The concept is a simple one: according to the USDA, consumers should eat a lot of carbohydrates, some vegetables and fruit, a small amount of dairy and proteins, and as little fat as possible. It was also completely wrong. Scientific American noted in 2006:

    Even when the pyramid was being developed, though, nutritionists had long known that some types of fat are essential to health and can reduce the risk of cardiovascular disease. Furthermore, scientists had found little evidence that a high intake of carbohydrates is beneficial. After 1992 more and more research showed that the USDA pyramid was grossly flawed. By promoting the consumption of all complex carbohydrates and eschewing all fats and oils, the pyramid provided misleading guidance. In short, not all fats are bad for you, and by no means are all complex carbohydrates good for you.

    Road signs are well and good, but if they get you to a place you may not want to be going, they may not be as valuable as they seem. To that end, let me be clear about my goals for this Article, which is going to be both more critical of Apple and more gracious to Facebook than the conventional wisdom about privacy on the Internet: you don’t have to agree with my conclusions, but I will feel I have accomplished my job if you can at least see that everything in this space comes with tradeoffs.

    Privacy Nutrition Labels

    Starting today Apple will require all new apps and app updates submitted to the App Store to include detailed information about their data collection practices; these submissions will manifest to customers in the form of “Privacy Nutrition Labels”, which Apple introduced at WWDC in June:

    There is, as you might expect from an Apple marketing presentation, nothing that seems objectionable, and a whole lot that is worth celebrating: of course consumers should want information that…well, what is this information used for? Apple, in a recent advertisement, provided the food pyramid to their nutrition labels:

    This is truly scandalous, but not for the reason Apple wants you to think it is: the way in which this ad depicts how your information is used — literally broadcasting your web browsing and searches and private conversations to those around you — is so misleading that it is hard to call it anything but misinformation.

    And yet, I can understand why some celebrated the ad, because the fact of the matter is that all of the information depicted in the commercial (except, in more and more cases, private chats, which are increasingly encrypted), are collected, particularly by Facebook.

    Lookalike Audiences

    Let’s grant, for the sake of this article, that Facebook is collecting vast quantities of information about you, whether that be through activity on Facebook properties, activity in apps that have embedded Facebook’s SDK, or activity on websites with Facebook pixels embedded. Let’s further assume that Facebook has taken that data and combined it with information from Facebook advertisers and other publicly available data sources in what I have previously called a Data Factory:

    Facebook quite clearly isn’t an industrial site (although it operates multiple data centers with lots of buildings and machinery), but it most certainly processes data from its raw form to something uniquely valuable both to Facebook’s products (and by extension its users and content suppliers) and also advertisers (and again, all of this analysis applies to Google as well).

    I prefer the term “Data Factory” to “Data Refinery”, because processed data isn’t really a fungible good: while oil from one refinery is no different than oil from another, and priced identically, Facebook data is valuable only to the extent that it is usable on Facebook, which primarily means an advertising approach called “lookalike audiences.” From the Facebook Business Help Center:

    When you create a Lookalike Audience, you choose a source audience (a Custom Audience created with information pulled from your pixel, mobile app, or fans of your Page). We identify the common qualities of the people in it (for example, demographic information or interests). Then, we deliver your ad to an audience of people who are similar to (or “look like”) them.

    You can choose the size of a Lookalike Audience during the creation process. Smaller audiences more closely match your source audience. Creating a larger audience increases your potential reach, but reduces the level of similarity between the Lookalike Audience and source audience. We generally recommend a source audience with between 1,000 to 50,000 people. Source quality matters too. For example, if a source audience is made up of your best customers rather than all your customers, that could lead to better results.

    This is actually a rather fair representation of how lookalike audiences work, but of course the scary details are hidden between the lines; let me try and make them explicit:

    • As noted above, Facebook really is tracking you everywhere, both on Facebook and off, with the eager cooperation of both publishers and app developers (you will understand why shortly).1 All of this data builds a far more in-depth behavior profile than Facebook’s anodyne “demographic information or interests” language suggests.
    • A third-party, meanwhile, has a list of profitable customers. For a game maker, this might be a list of Identifier for Advertisers (IDFAs) of users that made a considerable number of in-app purchases; for an e-commerce site, this might be a list of email addresses. Naturally, said third-party would like to find more gamers who will make in-app purchases, or customers who will buy products.
    • Lookalike audiences accomplish exactly that: the third-party can upload their list of profitable customers2 and set the maximum price they are willing to pay to acquire those customers. Facebook will then find other Facebook users that “look like” them, using its data factory, and show ads to those users, with the price based on an instantaneous auction between all of the different advertisers seeking to reach those particular customers.

    I get why this sounds creepy; it would be pretty disturbing if a salesperson showed up at my door to inform me that someone who visits the same websites I do just bought this really neat grilling implement, which means I might be interested in said grilling implement as well. The fact that said salesperson is probably right — I do love my grilling implements! — makes it even creepier. This, though, is by-and-large what is happening when you see that scarily accurate Instagram advertisement.

    Except that this isn’t what is happening at all.

    Tradeoffs and Computer Scale

    What makes that Apple advertisement so misleading is the level of individuality it implies in terms of data collection and application. Individuality is a real problem when it comes to data collection; in 2019’s Privacy Fundamentalism I included a photo of the East German Stasi Archives from Wired and noted:

    The Stasi's files
    Image from Wired.

    That the files are paper makes them terrifying, because anyone can read them individually; that they are paper, though, also limits their reach. Contrast this to Google or Facebook: that they are digital means they reach everywhere; that, though, means they are read in aggregate, and stored in a way that is only decipherable by machines.

    To be sure, a Stasi compare and contrast is hardly doing Google or Facebook any favors in this debate: the popular imagination about the danger this data collection poses, though, too often seems derived from the former, instead of the fundamentally different assumptions of the latter. This, by extension, leads to privacy demands that exacerbate some of the Internet’s worst problems.

    • Facebook’s crackdown on API access after Cambridge Analytica has severely hampered research into the effects of social media, the spread of disinformation, etc.
    • Privacy legislation like GDPR has strengthened incumbents like Facebook and Google, and made it more difficult for challengers to succeed.
    • Criminal networks from terrorism to child abuse can flourish on social networks, but while content can be stamped out, private companies — particularly domestically — are often limited as to how proactively they can go to law enforcement; this is exacerbated once encryption enters the picture.

    That last point provides the most trenchant example of how privacy rules that don’t consider trade-offs can go wrong; from the New York Times late last week:

    Privacy concerns in Europe have led to some of the world’s toughest restrictions on companies like Facebook and Google and the ways they monitor people online. The crackdown has been widely popular, but the regulatory push is now entangled in the global fight against child exploitation, setting off a fierce debate about how far internet companies should be allowed to go when collecting evidence on their platforms of possible crimes against minors.

    A rule scheduled to take effect on Dec. 20 would inhibit the monitoring of email, messaging apps and other digital services in the European Union. It would also restrict the use of software that scans for child sexual abuse imagery and so-called grooming by online predators. The practice would be banned without a court order.

    Those European rules comes from a perception of online privacy that looks a lot like that Apple advertisement: companies clicking through your email and social network accounts, carefully charting everything you do, just so they can show an ad. Why would you not want to stop such creepy behavior?

    The reality, though, is that nearly all of the child pornography reported to authorities is found by automatically scanning images and comparing them to a repository of known illegal images housed by the National Center for Missing and Exploited Children; there are no humans involved, and not only because it is a crime to even view these horrific images: it is completely impossible to do this work at human scale, but automated scanning, computation, and comparisons, are precisely the sort of work that computers are good at.

    The Analog Advertising Era

    The stakes for online advertising are, of course, massively lower; the reason for the previous section — beyond raising awareness about the massive downside of this new E.U. rule — is not to infer any sort of comparison in either importance or trade-offs. The relevant point, rather, is the last one: computer scale is so different from human scale that analogizing from one to the other is like using a map of Australia to navigate America.

    Consider, for example, this letter from Apple’s Senior Director of Global Privacy Jane Horvath assuaging concerns that Apple had lost its nerve in terms of implementing its App Tracking Transparency (ATT) feature, which disables the aforementioned IDFA unless customers opt-in (Apple delayed the implementation to next year):

    Advertising that respects privacy is not only possible, it was the standard until the growth of the Internet. Some companies that would prefer ATT is never implemented have said that this policy uniquely burdens small businesses by restricting advertising options, but in fact, the current data arms race primarily benefits big businesses with big data sets. Privacy-focused ad networks were the universal standard in advertising before the practice of unfettered data collection began over the last decade or so. Our hope is that increasing user demands for privacy and security, as well as changes like ATT, will make these privacy-forward advertising standards robust once more.

    The fact that pre-Internet advertisers were limited to mediums like TV had profound implications that went far beyond privacy; as I explained in 2016’s TV Advertising’s Surprising Strength — And Inevitable Fall, the entire post-World War II economic order was built around the opportunities and limitations offered by analog advertising.

    • Content companies, from TV stations to radio stations to newspapers, were incentivized to produce broadly appealing content that applied to the maximum number of people, in order to both maximize the number of consumers for advertisers and also to avoid any uncomfortable antitrust questions about their control of scarce mediums.
    • Consumer packaged goods companies of all types, from household products to food companies to clothing brands, were similarly incentivized to produce lowest-common-denominator products that would appeal to the most people possible, and advertise them on those mass market media channels.
    • Retailers increasingly consolidated and increased in size, culminating in massive outlets with even larger parking lots, the better to both house all of those CPG products — who bid against each other for scarce shelf space — and also to capture an increasingly suburban clientele that preferred a big house with a TV room over a smaller residence in a big city.

    There were certainly advantages to this state of affairs, particularly when viewed through the rose-tinted glasses of nostalgia: a limited number of ways to get middle-of-the-road content, for example, offered a shared source of truth that made it easier to find common political ground;3 large and predictable markets worked to the benefit of large and profitable conglomerates that provided millions of middle class jobs; and, of course, the fundamental limitations of the analog world — which operates at human scale — meant that “advertising that respects privacy…was the standard.”

    The Internet has profoundly upset every aspect of this order, for both better and for worse. Information is no longer scarce, but abundant, which means access to much more valuable information much more quickly, as well as a torrent of misinformation, which means people have to learn to navigate information for themselves. It has had a similar effect on products, both digital and physical: traditional CPG companies are overhauling their strategies in the face of Internet-native challengers, while companies like Shopify create an explosion of new shopping destinations that are not limited by geography, but instead serve the entire world.

    All of these changes, in fact, are about exceeding human scale via technology and the Internet, and is it any surprise that advertising has gone through the exact same transformation? When I write a post on Stratechery, I am not driving to your door and reading these words aloud to you; in fact, I don’t have any idea who you are. Computers take care of moving these bits from my computer to yours. It’s the same thing with an app developer creating in-app purchases, or an e-commerce site selling grilling implements: the entire reason their businesses are possible is precisely because they don’t know who I am, and have no need to. And yet they can sell me exactly what I want just the same.

    Growing Internet GDP

    I am, by virtue of temperament, experience, and self-interest, an Internet optimist. The fact that you can access information anywhere meant I could learn anywhere, whether that be small-town Wisconsin or big-city Asia. And, once I had leavened that learning with enough education and work experience to be dangerous, I could create a business that has the entire globe as its addressable market. Of course I didn’t do this alone: the Stratechery stack is dependent on a host of services like Stripe, which I wrote about last week: thanks to the ability to collect credit card payments from anyone I have helped “increase the GDP of the Internet”, to quote the platform company’s mission statement.

    Increasing the GDP of the Internet is important precisely because of all of the upheaval I just described: just because the way in which our economy was organized in an analog world is being upset by the Internet, it does not necessarily follow that what comes next will be better. It is possible to imagine, though, what “better” looks like: individuals and small companies leveraging the Internet to deliver individuals and small groups exactly what they want.

    This is the paradox of the Internet: computer scale unlocks human level opportunities, in contrast to the analog world where human scale gave the edge to large companies. You might imagine a graph that looks something like this:

    The Internet Size Paradox

    This is not to scale (pun very much intended): the biggest platforms, from Shopify to Stripe, are off the chart, given the fact they connect everyone on the planet, whereas even the biggest multinationals are limited by geography, shelf space, and distribution costs. That’s ok, though: they are also limited in where they can advertise, as well.

    Niche products and publications, on the other hand, can build sustainable businesses with customers across the entire world who have nothing in common except a shared interest in the product or publication in question; or, to put it another way, customers who “lookalike”. That’s the thing about Facebook and other digital advertising companies: they are just as essential a part of growing the GDP of the Internet as are Stripe and Shopify and other companies with universal approval ratings. It is no good to be capable of serving anyone anywhere if they can’t find you.

    The Internet’s Choice

    This is the beginning of the defense of Facebook’s approach to advertising, but not the end; after all, no matter what Apple’s Senior Director of Global Privacy may argue, we are not returning to a world defined by TV advertising from large CPG companies that gave middle class employees jobs for life. The Internet offers two clear alternatives: either a million blooming flowers, or all-encompassing behemoths that succeed by controlling access to customers. In the case of information, that alternative is Google, and in the case of products, it is Amazon.

    What is notable about both is how relatively untouched they are by Apple’s privacy campaign. Yes, Google has app SDKs, but they also have an even larger presence on the web than Facebook, have somewhat less need for data given the directed nature of search advertising, and oh yeah, are the default search engine on Apple devices, which makes it that much easier to ensure that information flows via Google’s channels (like AMP pages, which get around Apple’s recent cookie-crackdowns by being served from Google’s own URLs). And, of course, there is Android and Chrome, which gives Google far deeper access to all of the information it could ever want than Facebook could even dream of.

    Amazon, meanwhile, is increasingly where shopping searches start, particularly for Prime customers, and the company’s ad business is exploding. Needless to say, Amazon doesn’t need to request special permission for IDFAs or to share emails with 3rd parties to finely target its ads: everything is self-contained, and to the extent the company advertises on platforms like Google, it can still keep information about customer interests and conversions to itself. That means that in the long run, independent merchants who wish to actually find their customers will have no choice but to be an Amazon third-party merchant instead of setting up an independent shop on a platform like Shopify.

    This decision, to be clear, will not be because Amazon was acting anticompetitively; the biggest driver — which, by the way, will also benefit Facebook’s on-platform commerce efforts — will be Apple, which, in the pursuit of privacy, is systematically destroying the ability of platform-driven small businesses to compete with the Internet giants.

    Facebook Fats

    Apple’s means are, I should note, anticompetitive in spirit, if not in law; the company’s policies are predicated on control of the App Store, and a demonstrated willingness to use its power to get its way. That is how the company can not only disable access to the IDFA programmatically, but also demand that apps disclose what information they send to their own servers using open Internet protocols.

    Leaving aside legality, though, it is notable that Apple is quite obviously swimming against the prevailing current. That current, I would argue, is not greedy companies pushing the limits just because they can, but rather the fundamental nature of computers and the Internet. Computers emit data as a matter of course, and the Internet makes the transfer of that data free. To strive for a world without the generation or capture of data is to fight against the very nature of technology.

    This is not, to be very clear, to excuse the worst abuses of this capability (which, notably, are third-party advertising networks that, unlike social media companies, actually do sell your data), but simply to acknowledge its reality; this acceptance is crucial, because it shows why Apple’s map is wrong: the company is less protecting customers from Facebook than it is protecting Google and Amazon and other centralized consumer services from independent competition. Just think about it: small companies can only compete against the big guys if they can work together, whether that means collectively using services like Stripe and Shopify, or advertising — with their shared data, via lookalike audiences — on platforms like Facebook.

    I get that this is not a particularly popular position, and Facebook sure doesn’t make it easy to hold to. I remain very concerned about the company’s power and impact on everything from information dissemination to radicalization to yes, privacy. At the same time, the USDA was not necessarily wrong to say that some fats could be dangerous; rather, the mistake was in operating in broad generalizations, leading normal folks simply doing their best to adopt carbohydrate-heavy diets that were even worse. While transparency for customers is definitely a good thing, Apple’s simultaneous appeals to analog analogies and simplistic presentation of privacy trade-offs risks a similar path when it comes to the GDP of the Internet and to what extent power is disbursed versus centralized.

    Everything in moderation.

    1. For the record, Stratechery does not have the Facebook pixel — the share button below is pure HTML — and does not use lookalike audiences; in fact, as noted in Stratechery’s Privacy Policy, I do not share any user data with any third parties. ↩

    2. A source audience has to have at least 100 people from a single country, both for effectiveness and to prevent privacy violations ↩

    3. At least for those whom the media bothered to pay attention to  ↩

  • Stripe: Platform of Platforms

    Today Stripe is announcing Stripe Treasury; from the company’s press release:

    Stripe, the technology company building economic infrastructure for the Internet, today announced that it is launching Stripe Treasury. This gives Stripe’s platform users powerful APIs to embed financial services, enabling their customers to easily send, receive and store funds…

    Stripe Treasury…enabl[es] platforms like Shopify to easily offer its merchants access to critical financial products to manage their businesses’ finances. With Stripe Treasury, platforms can offer their users interest-earning accounts eligible for FDIC insurance in minutes, enabled by Evolve Bank & Trust. Platform business customers can have near-instant access to revenue earned through Stripe, spend this directly from their balance with a dedicated card, transfer it via ACH or wire transfer, pay bills, and more.

    Stripe Treasury, as its website notes, is banking-as-a-service, but, critically, Stripe is not a bank; look carefully at the product’s press image:

    The promotional image for Stripe Treasury

    That is an API call creating a bank account at Goldman Sachs for a pilot on the Rocket Rides platform. Notably, Goldman Sachs is not the only big bank on board; again from the press release:

    Stripe is enabling standardized access to global banking capabilities via APIs by developing its bank partner network to include Goldman Sachs Bank USA and Evolve Bank & Trust as US partners, and Citibank N.A. and Barclays as global expansion partners. Stripe will fulfill compliance and regulatory requirements in partnership with its US banking partners to make it easy for platform customers using Stripe Treasury to embed banking experiences into their products. And through Stripe, these banks are able to extend their reach to millions of businesses.

    This is a textbook example of the power of platforms; consider an operating system like Windows: any number of applications can run on any number of computers thanks to there being an abstraction layer in the middle:

    A drawing of The Concept of an Operating System

    This is analogous to the layer for banking that Stripe is offering with Treasury:

    Stripe's position as a platform

    This explains that API call above: a Rocket Rides pilot doesn’t have the wherewithal to open a business bank account at Goldman Sachs, and Goldman Sachs doesn’t have the flexibility to offer a banking account to individual entrepreneurs. This, though, is the exact sort of problem platforms solve: they provide an abstraction layer that connects different sides of a market, even if those different sides have dramatically different needs and capabilities.

    Stripe and Shopify

    It is Stripe’s partnership with Shopify, though, that is particularly compelling, and emblematic of both how powerful Treasury can be, and how extensive Stripe’s platform ambitions are. Again from the press release:

    For businesses today, accessing financial services can typically involve a series of bureaucratic hoops and a lengthy application process. According to recent Stripe research, setting up an account takes 5 and a half days on average (and 7 days on average for online businesses), around one in four (23%) businesses have to send a fax to open an account, and over half of businesses (55%) are required to visit a branch in person to open a bank account. Financial services simply weren’t designed for the modern internet, and this is a pain point for businesses today: nearly half (46%) of companies report that their banking experience has hindered their company growth.

    This is a pain point I know quite well; Stratechery is incorporated in the U.S., and I had to fly back to the U.S. for the express purpose of opening a business bank account!

    This kind of off-line banking experience is increasingly incongruous in a world where 76% of businesses (e.g. retailers) use an industry-specific software platform to manage their business, a figure that increases to 92% for businesses with more than 500 employees. The feedback from Stripe’s users is that they want a digital solution for financial services available directly within the software platform that powers their operations. On the flipside, Stripe’s platform customers are increasingly looking to embed financial services into their own product, but oftentimes face barriers to doing so.

    Now with Treasury, someone starting up a new Internet business can simply start selling goods, services, or yes, subscriptions, and have their banking needs met by the same software which is powering their business. Stripe co-founder and President John Collison explained in an interview:

    Which seems more ergonomic for a business? That they decide they’re going to start an online store and the very first thing they do is go down to a bank, and maybe in person, and they’re going through that process, they’re setting up their accounts, then they come back and do some white boarding. And they’re like, “Hmm, what should our business be?” That’s not how it works.

    How it works is they have this cool idea and they try it out and they open a Shopify store for it and they have this money coming in. So we need a way to access those funds, now they will be able to, with Shopify Balance, manage their funds directly within Shopify. That latter thing sounds like a much more natural and ergonomic way to handle the cash flows of their business.

    What is notable about Shopify is that it too is a platform, and a very powerful one at that. This is how I described the company’s then-new logistics offering in 2019’s Shopify and the Power of Platforms:

    What Shopify is doing is what platforms do best: act as an interface between two modularized pieces of a value chain.

    A drawing of The Shopify Ecosystem
    Every referral partner, developer, theme designer, and now 3PL provider are simultaneously incentivized to compete with each other narrowly and ensure that Shopify succeeds broadly, because that means the pie is bigger for everyone.

    On one side are all of Shopify’s hundreds of thousands of merchants: interfacing with all of them on an individual basis is not scalable for those 3PL companies; now, though, they only need to interface with Shopify.

    Thus the title of this Article: Stripe isn’t simply a platform, it is a platform for platforms.

    Stripe Capital

    This broader understanding of Stripe’s ambition became clear to me earlier this week with another announcement, Capital for platforms. Stripe Capital itself is not new; launched in 2019 the service lends money to businesses that use Stripe’s payments processor; as Bloomberg noted at the time:

    As the industry has become more digital, PayPal Holdings Inc., Square and even Amazon have introduced small business lending programs, as have a slew of startups including SoftBank Group Corp.-backed Kabbage Inc. and public company OnDeck Capital Inc. Though lending poses risks, Stripe, much like other payment services, says the extra data it has on customers will give it a better idea of whether borrowers can repay loans. The company believes that edge will protect it from significant losses during an economic downturn.

    Stripe Capital seemed both obvious and, as the article notes, rather unoriginal; this week’s expansion — which was announced with a 29-word blog post — makes clear it is much more. Carefully read this tweet from founder and CEO Patrick Collison:

    Note the word Patrick Collison emphasized: *your*. Capital for platforms is not for Stripe’s customers, but rather the customer of Stripe’s customers, which is to say, Stripe is asserting itself as the platform of platforms; go back to the news that Shopify Balance will be powered by Treasury:

    Stripe as a platform for platforms

    Stripe does not have a customer relationship with all of the Shops on Shopify; that is exactly what Shopify is good at, so why would they? Instead, Stripe is focusing on what it is good at: providing that API layer to banks that will never have the capability to serve Shopify Shops, and exposing said layer to Shopify to incorporate into their product.

    Notably, Treasury skipped the intervening step that Capital started with: Stripe isn’t exposing banking-as-a-service to customers directly on Stripe, but rather making an API available to those customers to offer to their customers. John Collison explained to me:

    We have a lot of conviction about this idea that the financial services that a plumber needs will be different from financial services that an e-commerce company needs will be different than financial services that a gym or a yoga studio needs, and they will be provisioned by different companies. Given that we have lots and lots of exposure to those kinds of businesses with our platform partners, this is a great way to get started with that.

    This means the above illustration, fully realized, looks a bit like this:

    Platform of platforms

    Stripe’s Ambition

    Here I think Stripe’s goal — building the economic infrastructure for the Internet — is instructive. Consider the Internet itself: you are reading this Article on the Internet via a connection provided by an Internet Service Provider, which is a relatively local affair that is designed for a particular geography. It is Internet Service Providers that connect to a grand network of cables that is known as the Internet backbone; this map from Telegeography, for example, shows the world’s submarine cables:

    The Internet's submarine backbone

    This image is incomplete — major portions of the Internet backbone obviously run overland — but is sufficient for the analogy: Stripe isn’t necessarily competing with other fintech providers — ISPs in this analogy — but instead is seeking to be the backbone for all of them, as well as an entirely new universe of platforms that can offer their unique customers financial services that are perfectly tuned to their needs.

    Stripe is ten years old now, but the ambition implied by these announcements explain why the founders claim they are just getting started. John Collison noted:

    We are still very early in developing the set of Stripe products beyond the core payments engine, things like Treasury. We’re building a global payments and treasury network, and we are in November of 2020 launching the Treasury part of it, and so we are just now filling out all the acronyms in our product suite, and that’s the version one of the product. And from a growth point of view, our business is growing really rapidly in APAC and EMEA, and so we’re just early in the business trajectory with all the helter-skelter-ness that comes from that.

    Speaking as an analyst, I would like nothing more than to see an S-1 from Stripe, but it sounds like it’s not coming anytime soon (and I can state with a high degree of confidence that Stripe will not be doing a SPAC with any of its rumored suitors); the company is reportedly raising more money, but is increasingly spending the money it raises on acquisitions and investments (one would certainly assume that the core payments business is not only profitable but also has a very attractive cash conversion cycle).

    Instead the company is busy building, well, exactly what it has said it was building all along: economic infrastructure. And, I will freely admit, until this week I didn’t completely appreciate just how mammoth an undertaking that was.

    Stratechery subscribers can read the full interview with John Collison here; it is also available for subscribers via podcast.

  • Five Lessons From Dave Chappelle

    While there are not huge differences between Stratechery Weekly Articles and subscriber-only Daily Updates, I do spend more time on the Weekly Articles trying to craft an overarching narrative; Weekly Articles, by virtue of being free, are better suited to sharing, and humans like stories, not just analysis.

    However, the first lesson from Dave Chappelle’s latest release on Instagram, Unforgiven, is that one best not compete with Chappelle when it comes to story-telling; the way in which the comedian weaves together multiple stories from his childhood on up to the present to make his argument about why he should be paid for the rights to stream Chappelle’s Show is truly extraordinary.

    To that end, I thought a more prosaic approach might be in order: Chappelle’s 18-minute special, which I highly suggest you watch in full, is chock-full of insights about how the Internet has transformed the entertainment industry specifically, and business broadly; my goal is to, in my own clumsy way, highlight and expand on those insights. That I ought to make a simple list and not compete on story-telling is one lesson down; four to go.

    Lesson Two: Talent in an Analog World

    This lesson is exposed in two parts; first, Chappelle on his precociousness as a child comedian:

    A few minutes later, though, Chappelle admits that fourteen years after he started as a standup comedian he signed a deal to make Chappelle’s Show under some amount of financial duress:

    Chappelle may have been preternaturally gifted, but that wasn’t enough to avoid being broke in the early 2000s when he signed that contract with Comedy Central. Granted, Chappelle was almost certainly scratching out a living doing standup, but to truly make it big meant signing up with a network (or, in the case of music, a label), because they controlled distribution at scale.

    That’s the big difference between stand-up and something like Chappelle’s Show: when it comes to the former your income is directly tied to your output; if you do a live show, you get paid, and if you don’t, you don’t. A TV show or record, on the other hand, only needs to be made once, at which point it can not only be shown across the country or across the world, but can also be shown again and again.

    It’s the latter that is the key to getting rich as a creator, but in the analog world there were two big obstacles facing creators: first, the cost of creating a show or record was very high, and second, it was impossible to get said show or record distributed even if you managed to get it made. The networks and labels were the ones that had actual access to customers, whether that be via theaters, cable TV, record stores, or whatever physical channel existed.

    Over the last two decades, though, technology has demolished both obstacles: anyone with access to a computer has access to the tools necessary to create compelling content, and, more importantly, the Internet has made distribution free. Of course the Internet did exist when Chappelle signed that contract, but there are two further differences: first, the advent of broadband, which makes far richer content accessible, and second, social networks, which provide far more reach than traditional channels, for free. Today it is far more viable for talent to not only create content and distribute it, but also promote it in a way that has tangible economic benefits.

    Lesson Three: The House Wins

    What is noteworthy about Chappelle’s argument is that he is quite ready to admit that everyone involved is acting legally:

    From the perspective of 2020, and Chappelle’s overall point about how he feels his content was taken from him, this seems blatantly unfair. At the same time, from a network’s perspective, Chappelle’s success pays for all of the other shows that failed. It’s the same idea as the music industry: yes, record companies claim rights to your recordings forever, but for the vast majority of artists those rights are worthless. In fact, for that vast majority of artists, they represent a loss, because the money the network or label spent on making the show or record, promoting it, and distributing it, is gone forever.

    There is an analogy to venture capital here, which I made five years ago in the context of Tidal:

    This is why, by the way, I’m generally quite unsympathetic to artists belly-aching about how unfair their labels are. Is it unfair that all of the artists who don’t break through are not compelled to repay the labels the money that was invested in them? No one begrudges venture capitalists for profiting when a startup IPOs, because that return pays for all the other startups in the portfolio that failed.

    It’s not a perfect analogy, in part because the output is very different: a founder will typically only ever have one company, so of course they retain a much more meaningful ownership stake from the beginning; an artist, on the other hand, will hopefully produce new art, which they will be in a much stronger position to monetize if their initial efforts are successful. Chappelle, for example, earns around $20 million per stand-up special on Netflix; Taylor Swift, another artist embroiled in an ongoing controversy around rights to her original work, fully owns the rights for her two most recent records.

    The lesson to be learned, though, is that for many years venture capitalists, networks, and record labels could ensure that the expected value of their bets was firmly in their favor. There were more entrepreneurs that wanted to start companies, more comedians that wanted to make TV shows, and more musicians that wanted to make records than there was money to fund them, which meant the house always came out ahead: sure, money was lost on companies, comedians, and musicians that failed, but the upside earned by those that succeeded more than made up for it.

    Over the last two decades venture has been flooded with new sources of capital, resulting in far more founder-friendly terms than before; comedy, meanwhile, has been a particularly notable beneficiary of the podcast boom, as more and more artists create shows that are inexpensive to produce yet extremely lucrative for the artist. Music has seen its own independent artists emerge, although the labels, thanks in part to the power of their back catalogs, have retained their power longer than many expected. Still, the inevitable outcome of Lesson Two is that Lesson Three is shakier than ever.

    Lesson Four: Aggregators and the Individual

    The one company that comes out looking great is Netflix:

    Technically speaking, Netflix did exist when Chappelle negotiated that contract with Comedy Central, but the company was a DVD-by-mail service; the streaming iteration that Chappelle is referring to wasn’t viable back then. Indeed, the entire premise of the streaming company is that it takes advantage of the changes wrought by the Internet to achieve distribution that is not simply equivalent to a TV network, but actually superior, both in terms of reaching the entire world and also in digitizing time. On Netflix, everything is available at anytime anywhere, because of the Internet.

    Netflix’s integration of distribution and production also means that they are incentivized to care more about the perspective of an individual artist than a network; that is the optimal point of modularity for the streaming company. At the same time, it is worth noting that Netflix is actually claiming even more rights for their original content than networks ever did, in exchange for larger up-front payments. This makes sense given Netflix’s model, which is even more deeply predicated on leveraging fixed cost investments in content than networks ever were, not simply to retain users but also to decrease the cost of acquiring new ones.

    At the same time, Aggregators (even weak ones like Netflix), are inherently a better bet for the individual creator than middlemen like the networks ever were. On Netflix, every show is equally accessible relative to every other show; there is no fighting for prime time slots or seasons. It’s the same dynamic on Google or Facebook: all content is treated the same, which is absolutely a problem for companies that used to rule the roost when physical distribution mattered, and nothing but upside for individual creators that only exist because of the Internet.

    And, by extension, a company like Netflix is far more sensitive to the needs of the creators that its audience actually care about. The fact the company has twice extended Chappelle’s stand-up special deal is all of the evidence you need that that $20/million per show is money well spent, not because Netflix made people watch, but because people sought it out, and the reality of Aggregators is that they win by making users happy in a world where competition is only a click away, not by denying them choice by virtue of controlling physical distribution.

    Lesson Five: The Real Boss

    Chappelle made this point explicitly in his call to action:

    This is the most important lesson of the Internet: the consumer is the ultimate boss. In markets without any sort of additional friction, like website or social media, this means that power accrues almost completely to Aggregators, with creators able to connect with consumers as secondary beneficiaries. Look no further than the fact that this special was posted on Instagram: Chappelle has the platform to appeal directly to his fans that his predecessors, all of whom despised the networks and labels and their contracts just as much if not more than he does, lacked. That Chappelle’s Instagram post is no different in format from one posted by you or me is a feature, not a bug.

    Of course not everything is as clear cut as the open web, or user-generated content. In other markets, with legacy friction from analog business models, or legal friction like copyright, power is more disbursed, which is why it is not certain that Chappelle’s power play will succeed; the fact of the matter is that he did sign a contract, which absolutely gives Comedy Central the rights to stream Chappelle’s Show on HBO Max, CBS All Access, and anywhere else they please, and customers may very well choose to ignore Chappelle’s plea. After all, they are the boss.

    What is just as clear, though, is that networks and anyone else dependent on physical distribution are on the retreat. Contracts and copyright may secure their place for longer than seems earned, but there is a reason this fight is about content made twenty years ago, while Chappelle is very content with the status of content made today. The Internet favors creators and Aggregators, while everyone in the middle of the smiling curve — where power used to be centered — is increasingly of little value.

  • The Idea Adoption Curve

    Matthew Yglesias, in his new book One Billion Americans, admits:

    The One Billion Americans agenda — tripling the American population — is a radical suggestion that lies well outside the boundaries of conventional political arguments.

    Ezra Klein, in his new book Why We’re Polarized, promises:

    What I am trying to develop here isn’t so much an answer for the problems of American politics as a framework for understanding them. If I’ve done my job well, this book will offer a model that helps make sense of an era in American politics that can seem senseless.

    Klein’s promise is very similar to the brand promise of Vox, the digital media site he co-founded with Yglesias and Melissa Bell: “Explain the news”. Yglesias, on the other hand, seems more invested in creating the news that future Vox might one day explain. I think the distinction is meaningful even with the news that both Yglesias and Klein are leaving the company they founded: in fact, I think the distinction explains their destinations.

    Crossing the Chasm

    In the introduction of his classic tech marketing book, Crossing the Chasm, Geoffrey A. Moore writes:

    This book is unabashedly about and written specifically for marketing within high-tech enterprises. But high tech can be viewed as a microcosm of larger industrial sectors. In this context, the relationship between an early market and a mainstream market is not unlike the relationship between a fad and a trend. Marketing has long known how to exploit fads and how to develop trends. The problem, since these techniques are antithetical to each other, is that you need to decide which one—fad or trend—you are dealing with before you start. It would be much better if you could start with a fad, exploit it for all it was worth, and then turn it into a trend.

    That may seem like a miracle, but that is in essence what high-tech marketing is all about. Every truly innovative high-tech product starts out as a fad—something with no known market value or purpose but with “great properties” that generate a lot of enthusiasm within an “in crowd” of early adopters. That’s the early market. Then comes a period during which the rest of the world watches to see if anything can be made of this; that is the chasm. If in fact something does come out of it—if a value proposition is discovered that can be predictably delivered to a targetable set of customers at a reasonable price—then a new mainstream market segment forms, typically with a rapidity that allows its initial leaders to become very, very successful.

    The key in all this is crossing the chasm—performing the acts that allow the first shoots of that mainstream market to emerge. This is a do-or-die proposition for high-tech enterprises; hence it is logical that they be the crucible in which “chasm theory” is formed. But the principles can be generalized to other forms of marketing, so for the general reader who can bear with all the high-tech examples in this book, useful lessons may be learned.

    Moore divided tech markets into five parts, that I summarized in 2015’s The End of Trickle-Down Technology:

    The Technology Adoption Curve

    • Technology Enthusiasts love tech first and foremost, and are always looking to be on the cutting edge; they are the first to try a new product
    • Visionaries love new products as well, but they also have an eye on how those new products or technologies can be applied. They are the most price-insensitive part of the market
    • Pragmatists are a much larger segment of the market; they are open to new products, but they need evidence they will work and be worth the trouble, and they are much more price conscious
    • Conservatives are much more hesitant to accept change; they are inherently suspicious of any new technology and often only adopt new products when doing so is the only way to keep up. Because they don’t highly value technology, they aren’t willing to pay a lot
    • Skeptics are not just hesitant but actively hostile to technology

    Allow me to take Moore at his word, and apply this model to something rather different than tech B2B marketing: ideas. It seems to me that Yglesias and Klein are focused on different parts of this adoption cycle. Yglesias is somewhere between an enthusiast and a visionary; the core concept of his book is closer to the former, and the policy prescriptions closer to the latter. Klein, meanwhile, is focused more on pragmatism, or even conservatism: explaining, instead of creating.

    This is, to be sure, a crude simplification of two writers with nearly 40 years of material between them, but I don’t think it is an accident that Yglesias has set out on his own on Substack, whereas Klein is joining the New York Times.

    The Idea Adoption Curve

    I wrote last month about the New York Times‘s traditional role in setting the national news agenda; headlines in the New York Times in the morning were lead stories on national newscasts in the evening, and headlines in regional papers the following day. If you map this dynamic to Moore’s model, it might look like this:

    The Idea Adoption Curve

    Where, though, did the New York Times get its ideas? Obviously a lot of stories came from its own reporting, or that of its peers, but the “enthusiast” part of the curve was mostly centered in academia. Visionaries, meanwhile, were a collection of think tanks, journals, and speciality magazines that operated at a loss, which was fine because making money was never the point: getting ideas into publications like the New York Times was.

    Idea generation in the analog age

    What happened in the 2000s, when Yglesias and Klein first burst on the scene as part of the original generation of political bloggers, was the development of a new genre of “enthusiasts” who were creating and debating new ideas mostly for free. Sure, most of these bloggers found work with publications like American Prospect (Yglesias) or Washington Monthly (Klein), but those publications were political projects, not economic ones, with the goal of influencing the mass market, not monetizing it.

    Vox, on the other hand, has been something much different, both in terms of mission statement and business model. “Explaining the news” is, from a certain perspective, about crossing the chasm on the idea curve; enthusiasts have created new ideas, and visionaries have refined them, and now the challenge is to spread those ideas to the population generally. Vox’s business model, meanwhile, is firmly on the right hand side of the curve. Advertising is all about scale, and the vast majority of the market falls to the right of the chasm.

    The problem with this approach, though, is that publications simply aren’t as good at advertising as Facebook and Google. I wrote five years ago in Popping the Publishing Bubble:

    Publishers and ad networks are locked in a dysfunctional relationship that doesn’t serve readers or advertisers, and it’s only a matter of time until advertisers — which again, care only about reaching potential customers, wherever they may be — desert the whole mess entirely for new, more efficient and effective advertising options that put them directly in front of the people they care about. That, first and foremost, is Facebook, but other social networks like Twitter, Snapchat, Instagram, Pinterest, and others will benefit as well:

    A drawing of Facebook As a More Efficient Advertising Option

    I don’t know the specifics of how Vox’s business is doing, although it is notable that the site’s previous ad inventory is now mostly filled with requests for donations; meanwhile, there is no confusion about the business models of either Substack or the New York Times.

    Visionaries and Substack

    Start with Yglesias, and Substack; this is obviously a business model near-and-dear to my heart, given that Stratechery was perhaps the first site built around the idea of a one-person publication supported by subscriptions at scale.1 I don’t have any illusions about reaching the mass market; Stratechery is very much predicated on capturing the “Visionary” part of the curve. Read again the explanation I excerpted above:

    Visionaries love new products as well, but they also have an eye on how those new products or technologies can be applied. They are the most price-insensitive part of the market

    The “price-insensitive” part is key: Stratechery and Substack publications like Slow Boring may not be that expensive, but they are, relative to text on the Internet, shockingly pricey. Subscribers, though, don’t mind, as long as what they are getting is consistently unique and provocative; look no further than One Billion Americans, or Yglesias’s Twitter account, to see why he ended up on Substack.

    What is neat about this model is that it is far more sustainable and accessible than the old model of corporations and donors subsidizing think tanks, journals, and specialty magazines, and far more ideologically diverse than academia. It is important, though, to be honest about the model’s limitations: while I remain very bullish about the potential of subscription-based local news entities, it is difficult to envision a future where most people pay for news or analysis directly.

    One way to understand why is to map the Idea Adoption Curve against a “Willingness-to-Pay Curve”; I suspect it looks something like this:

    Willingness-to-pay on the Idea Adoption Curve

    Enthusiasts — now on Twitter, for the most part — generate and debate ideas for free, while the real money, at least from an average revenue per user perspective, is with the visionaries. This is where the Substack model makes the most sense. What is notable, though, is that the chasm of ideas is also a chasm of monetization.

    Push Versus Pull

    How do ideas cross the chasm into popular acceptance and public policy? Vox tried to pull them over, with, I think, limited success; the New York Times, on the other hand, has been positioned to cross the chasm for decades. What has changed is that while the New York Times used to be mostly supported by advertising, which incentivized it to remain planted on the right side of the divide, pulling ideas from the fringes into the mainstream, its shift to subscriptions has pushed it to the left part of the curve, incentivizing the newspaper of record to more actively generate and push new ideas.

    This has, as I noted in Never-Ending Niches, changed the New York Times:

    To the extent that the New York Times has been successful online — and the company has been very successful indeed! — it follows that the company is well-placed in terms of both focus and quality, and in that order.

    In this view, the fact that deeply reported articles about Chinese disinformation on Twitter are held as being low quality by the Chinese government is immaterial; what matters is that the New York Times‘ audience, which is mostly in the United States, finds it of high quality (I certainly do).

    That’s an easy example, but there are ones that hit closer to home; for example, I thought this 2018 story that claimed that Facebook Gave Data Access to Chinese Firm Flagged by U.S. Intelligence was, as I wrote at the time, “deeply flawed at best, and willfully mendacious at worst.” It turns out, though, that I am not particularly interested in the “Everything tech does is bad” niche; that story was very high quality for much of the New York Times’s audience.

    These two stories were in the News section, not Opinion, but the point is that the distinction matters less than ever before; the pursuit of subscription revenue pushes the New York Times to the left side of the chasm, which means that to the extent it still fulfills it role of conveying ideas across the chasm it is more focused on pushing particular points of view into the broader public, as opposed to pulling ideas the broader public may favor. This certainly makes the New York Times an attractive landing place for Klein, who, for all of his focus on “explaining the news”, has never been shy about his political preferences and desire to influence policy. Now he can do so from a platform that has long been defined by its ability to cross the chasm.

    BuzzFeed Versus the New York Times

    Yglesias and Klein’s departures from Vox weren’t the only media news of the week; BuzzFeed acquired HuffPost (and some cash from Verizon). In an interview on Recode Media, BuzzFeed CEO and founder — of both BuzzFeed and HuffPost! — Jonah Peretti took aim at the New York Times’ shift; from Recode:

    The Times, Peretti allowed, has since refined a very good subscription business model, which has allowed it to make better journalism by hiring more and better talent. This is not a controversial opinion. But the next part may be: The New York Times, Peretti argued, can’t really be called “the paper of record” anymore — because of that same subscription model.

    “A subscription business model leads towards being a paper for a particular group and a particular audience and not for the broadest public,” Peretti said. He’s alluding, in part, to the theory that the Times’s subscriber base wants to read a certain kind of news and opinion — middle/left of center, critical of Donald Trump, etc. — and that straying from that can cost it subscribers. But he’s also simply arguing that the act of requiring readers to pay to read cuts the Times off from a big audience.

    Peretti’s solution to that problem, it turns out, sounds a whole lot like a combined BuzzFeed/HuffPost — publications that are widely distributed, supported by advertising, and free:

    “Will a subscription newspaper that is read by a subset of society have as big an impact as it could on voters, on the broad public, on young people, on the more diverse rising generation of millennials and Gen Z?” he argued. “I think there’s a huge opportunity to serve those consumers. And not all of them are going to be subscribers to any publication.”

    BuzzFeed is firmly planted on the right side of the Idea Adoption Curve; most of the publication’s content is about anything other than news or ideas, and its primary distribution network is Facebook (Twitter is for the left side of the curve, and Facebook the right). It also has an advertising kitchen sink business model, with a combination of premium advertising, programmatic advertising, affiliate marketing, e-commerce, etc., all of which only make sense at scale.

    The Implications of Abundance

    At the same time, it is worth noting that the New York Times has, contrary to Peretti’s implication, never been a newspaper for the masses. Sure, its subscription model is by default exclusionary, but only being available in printed form, mostly in New York, was far more exclusionary. The point about subscriptions driving a particular point of view is a valid one, but then again, it is not as if BuzzFeed has been shy about its political preferences either. The reality is that the implication of the Internet is that ideas are in abundance, and people will seek out what they already agree with, as opposed to accepting what is delivered to them.

    This explains the newly prominent role of the right side of the Idea Adoption Curve; I noted while summarizing the Technology Adoption Curve:

    Skeptics are not just hesitant but actively hostile to technology

    This, translated to ideas, explains the prominence of conspiracy theories and misinformation. These strains of belief have always existed, in America in particular, but one implication of the Internet leveling the information playing field is that these alternative views of reality can both spread further than ever before, even as they are far more visible to everyone else. This is both reason for alarm, and for skepticism about said alarm: yes, the misinformation problem is worse than before, but much of our fear is rooted in newfound awareness of an old problem, and there is a strong case to be made that the emergence of valuable information makes up for the propagation of misinformation that mostly feeds confirmation biases.

    What is indisputable, though, is that the nature of information and its spread has been fundamentally altered in a way unseen since the printing press. It affects Yglesias and Substack, Klein and the New York Times, and, one increasingly suspects, the very fabric of society and the foundation of our political institutions and organizing principles. And, if this is right, we are only now at the end of the beginning.

    1. Yes, subscription-based newsletters existed long before Stratechery, particularly on Wall Street, but at much higher price points ↩

  • Playing on Hard Mode

    One way to understand how the Internet is different is to not only examine what business models work, but also the history of how those business models came to be. Start with text and images, long the province of newspapers: the first attempts at website monetization placed ads alongside article text; after all, that is how advertising was done.

    Incredibly enough, it was a mere eight years ago that Facebook IPO’d with this as its business model: content that was important to you was in the center of the webpage, and ads were on the side (mobile didn’t monetize at all, which was why growth in mobile usage was listed as a risk factor in Facebook’s S-1); the company was optimistic that the Facebook Platform would provide a more traditional-to-tech means of monetization that could augment its ads business.

    That, though, was the other “problem” with mobile: it made Facebook just an app, not a platform. It turned out, though, that this was the best possible thing that could have happened to the social media company: freed to be “just an app” the company doubled down on the News Feed, which already delivered personalized content, as the primary means of delivering personalized ads.

    The rest, as they say, is history:

    Facebook's stock price since IPO

    Today would-be experts talk about Facebook’s business model as if it were always inevitable, that of course the same mechanism would work for Instagram, not to mention the company’s ever increasing number of competitors like Snapchat and TikTok; I presume they all purchased the company’s stock when it was down 50% from its IPO price in the fall of 2012, five months after the Instagram purchase. For the rest of us, though, including Facebook, it wasn’t obvious at all: succeeding on the Internet didn’t simply mean making a digital product, but also finding a business model that was native as well.

    Easy Mode

    And yet, for all of Facebook’s initial challenges, the truth is that the company was, relatively speaking, playing on easy mode. Yes, the company practically invented the modern growth hacking discipline and feed advertising, but its core product was about digitizing offline relationships that already existed, and the means by which it did that — text and photos, at least at the beginning — were native to the Internet. To the extent it was difficult to figure out how to monetize advertising it was because advertising was so easy that there was effectively infinite inventory.

    You can make a similar argument about Google: yes, Larry Page and Sergey Brin created something truly superior with PageRank and the Google search engine, but once deployed Google instantly had access to an entire universe of web pages seemingly tailor-made to to make Google better at giving you the results you need. If anything the ease with which Google came to dominate the web has hindered the company in adjacent markets where skills like marketing and sales make a difference.

    Twitter and Snapchat, in contrast to Facebook, had to create networks in Facebook’s shadow; Twitter focused on the interest graph, while Snapchat defined itself by being the anti-Facebook for a new generation. This was a more difficult path, but one still defined by zero marginal costs in terms of distribution and monetization. Google’s vertical search competitors faced a similar challenge: build something unique and differentiated in Google’s shadow, acquiring not just demand but also supply along the way. Still, like Facebook’s challengers, all of these companies are safely cocooned in the virtual world.

    Amazon, in contrast, has played on a much higher difficulty setting from the beginning, selling and shipping physical items, with all of the marginal costs that entails. If anything the company has doubled down on the physical world, investing billions to deliver items in one day; I don’t think it is a coincidence it is Amazon that is Google’s true competitor.

    OTAs and Pizza

    Perhaps the easiest mode of all, though, was layering the Internet on top of real world business models. Consider OTAs — “Online Travel Agents” — the name gives it away! Instead of calling up a travel agent and being inherently limited to their knowledge and connections (and paying their commission), customers could access search engines that aggregated every flight and every hotel, displaying them in a way that was easy to compare and contrast. From a customer perspective it was a better experience in nearly every way: both more comprehensive and cheaper as well.

    Of course, like most suppliers in an Aggregator-based value chain, hotels weren’t too pleased, but given that demand was increasingly concentrated on the likes of Booking.com they had no choice but to come onto the platform on the OTAs terms. Their response was, rationally, to consolidate and focus on loyalty programs and repeat customers. The OTAs, meanwhile, could simply take a skim off of all of the bookings they made, without needing to build their own hotels on one hand, or worry about infinite inventory depressing prices on the other.

    There was a similar dynamic in an industry like pizza delivery: a company like Dominos existed for decades relying on phone calls for delivery; with the advent of the smartphone, though, the company quickly pivoted to mobile ordering, augmenting that capability with innovative apps and tracking services that let you make the exact pizza you wanted whenever you wanted and trace its route to your front door. The company’s success has been extraordinary, much like the OTAs, and for similar reasons: the Internet made an existing real world business model better, even as the real world constraints ensured the money-making opportunity existed.

    Airbnb and Trust

    There will be time over the next few days and weeks to get into the particulars of Airbnb and DoorDash’s businesses, but I thought this observation from FinTwit regular @modestproposal1 was notable:

    This is, in a vacuum, a valid point; frankly, the biggest takeaway from my perspective is that Booking was drastically undervalued circa 2011 — the stock market certainly agrees:

    Booking.com's stock price over time

    The truth is that, as I just explained, the company was playing in easy mode: OTAs were an obvious business, with real world constraints that brought digital’s advantages to bear without its commoditizing downsides. At the same time, notice how BKNG’s share price has leveled out: over the last few years in particular, Google, the Super-Aggregator, has been extracting an ever greater share of OTA margins. Indeed, that’s the downside to having a business built on easy mode: anyone else can play the game just as easily.

    Airbnb, on the other hand, has been building something truly unique; the company explains in its S-1:

    Travel is one of the world’s largest industries, and its approach has become commoditized. The travel industry has scaled by offering standardized accommodations in crowded hotel districts and frequently-visited landmarks and attractions. This one-size-fits-all approach has limited how much of the world a person can access, and as a result, guests are often left feeling like outsiders in the places they visit.

    Airbnb has enabled home sharing at a global scale and created a new category of travel. Instead of traveling like tourists and feeling like outsiders, guests on Airbnb can stay in neighborhoods where people live, have authentic experiences, live like locals, and spend time with locals in approximately 100,000 cities around the world. In our early days, we described this new type of travel with the tagline “Travel like a human.” Today, people simply refer to it with a single word: “Airbnb.”

    Unsurprisingly Airbnb frames the commoditization of hotels as a negative, but it was precisely this commoditization that unlocked the OTAs, even as the OTAs accelerated said commoditization in a way that benefited customers with low prices and wide selections. And, as noted, left the OTAs susceptible to Google. Airbnb’s relationship with Google, though, is different:

    We focus on unpaid channels such as SEO. SEO involves developing our platform in a way that enables a search engine to rank our platform prominently for search queries for which our platform’s content may be relevant.

    The company explained in its Key Factors Affecting Our Performance:

    We grow GBV by attracting new guests to book stays and experiences on our platform and through past guests who return to our platform to make new bookings. We attract most guests to Airbnb directly or through unpaid channels. During the nine months ended September 30, 2020, approximately 91% of all traffic to Airbnb came organically through direct or unpaid channels, reflecting the strength of our brand. We have also used paid performance marketing, for example on search terms including “Airbnb,” to attract guests. Our strategy is to increase brand marketing and use the strength of our brand to attract more guests via direct or unpaid channels and to decrease our performance marketing spend relative to 2019.

    Airbnb did not, as far as I could see, specify the exact split between brand and performance marketing, but it makes intuitive sense that the company would be less dependent on Google search ads than other OTAs: its supply is unique, and its brand is a verb.

    This is, to be sure, a far more difficult path to building a business than the OTAs on one hand, which simply layered digital onto real world business models, and search engines and social networks on the other, which created new business models with supply that was inherently digital. Airbnb created an entirely new sort of supply that previously didn’t exist. As the company notes in its S-1 introduction, the key was trust:

    In 2008, Nate, a software engineer, joined Brian and Joe, and together the three founders took on a bigger design problem: how do you make strangers feel comfortable enough to stay in each other’s homes? The key was trust. The solution they designed combined host and guest profiles, integrated messaging, two-way reviews, and secure payments built on a technology platform that unlocked trust, and eventually led to hosting at a global scale that was unimaginable at the time.

    I wrote about Airbnb and trust back in 2015 in Airbnb and the Internet Revolution:

    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. 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.

    This is what it takes to succeed in hard mode: Airbnb took a core differentiator of hotels — trust, a differentiator that OTAs depended on — and digitized it. But, critically, that digitization and resultant commoditization happened only on Airbnb, and was thus captured exclusively by the company. This, by extension, is what the comparison to OTAs miss: Airbnb is not riding the same wave that Booking et al did a decade ago, but are instead undertaking something far more ambitious: creating their own wave where none previously existed.

    DoorDash and Selection

    DoorDash has been playing on hard mode as well: while a company like Dominos created its own standardization and commoditized product designed for delivery, now with tech on top, DoorDash has undertaken the more Herculean task of creating a three-sided market of restaurants, drivers, and customers. This is the ultimate example of seeking to “make it up in volume”; the company explains in its S-1:

    Our local logistics platform benefits from three powerful virtuous cycles:

    • Local Network Effects: Our ability to attract more merchants, including local favorites and national brands, creates more selection in our Marketplace, driving more consumer engagement, and in turn, more sales for merchants on our platform. Our strong national merchant footprint enables us to launch new markets and quickly establish a critical mass of merchants and Dashers, driving strong consumer adoption.

    • Economies of Scale: As more consumers join our local logistics platform and their engagement increases, our entire platform benefits from higher order volume, which means more revenue for local businesses and more opportunities for Dashers to work and increase their earnings. This, in turn, attracts Dashers to our local logistics platform, which allows for faster and more efficient fulfillment of orders for consumers.

    • Increasing Brand Affinity: Both our local network effects and economies of scale lead to more merchants, consumers, and Dashers that utilize our local logistics platform. As we scale, we continue to invest in improving our offerings for merchants, selection, experience, and value for consumers, and earnings opportunities for Dashers. By improving the benefits of our local logistics platform for each of our three constituencies, our network continues to grow and we benefit from increased brand awareness and positive brand affinity. With increased brand affinity, we expect that we will enjoy lower acquisition costs for all three constituencies in the long term.

    DoorDash's flywheel

    We have been successful in becoming the category leader in U.S. local food delivery logistics because of the value we create for merchants, consumers, and Dashers. DoorDash only works if it works for merchants, consumers, and Dashers, and we continually strive to improve how we serve all constituents.

    DoorDash’s success relative to its competitors, particularly UberEats, is noteworthy:

    We believe that the value we deliver to merchants, consumers, and Dashers is a key reason why we have become the largest and fastest growing business in the U.S. local food delivery logistics category, with 50% U.S. category share and 58% category share in suburban markets.

    DoorDash versus the competition

    What made DoorDash different from UberEats is that the former focused on maximum merchant selection and suburban markets, while the latter initially prioritized efficient delivery in urban areas. The problem for UberEats, though, is that it was not competing with only DoorDash, but also local delivery networks, and the shop with carryout right down the street. DoorDash, meanwhile, was creating an entirely new market in places filled with little else other than the aforementioned Dominos, which would always be far more efficient, with far less choice.

    To put it another way, whereas Airbnb digitized trust, DoorDash digitized the urban experience of a wide selection of options and relative convenience for a suburban population that had the added benefit of large order sizes and convenient parking. And now, given the fact that both restaurants and drivers can multi-home, DoorDash can increasingly rely on its dominant share of customers to drive the other two sides of its market.

    This isn’t all there is to say about these two companies: both deserve deeper dives into their financials on one hand, and a consideration of their broader societal impact on the other.

    What both companies represent, though, is what it means to play on hard mode. Neither lodging nor logistics is inherently digital; both companies had to make them so, creating new markets that didn’t previously exist. That both Airbnb and DoorDash have done so to a sufficient degree to go public is not only impressive, but will increasingly be a roadmap for new startups, and a model for how the Internet will transform more and more components of the “real” world.

  • Apple’s Shifting Differentiation

    If you ask Apple — or watch their seemingly never-ending series of events — they will happily tell you exactly what the company’s differentiation is based on; from this year alone:

    This integration is at the core of Apple’s incredibly successful business model: the company makes the majority of its money by selling hardware, but while other manufacturers can, at least in theory, create similar hardware, which should lead to commoditization, only Apple’s hardware runs its proprietary operating systems.

    Of course software is even more commoditizable than hardware: once written, software can be duplicated endlessly, which means its marginal cost of production is zero. This is why many software-based companies are focused on serving as large a market as possible, the better to leverage their investments in creating the software in the first place. However, zero marginal cost is not the only inherent quality of software: it is also infinitely customizable, which means that Apple can create something truly unique, and by tying said software to its hardware, make its hardware equally unique as well, allowing it to charge a sustainable premium.

    This is, to be sure, a simplistic view of Apple: many aspects of its software are commoditized, often to Apple’s benefit, while many aspects of its hardware are differentiated. What is fascinating is that while modern Apple is indeed characterized by the integration of hardware and software, the balance of which differentiates the other has shifted over time, culminating in yesterday’s announcement of new Macs powered by Apple Silicon.

    Apple 1.0: Software Over Hardware

    When Steve Jobs returned to Apple in 1996, the company was famously in terrible financial shape; unsurprisingly the company’s computer lineup was in terrible shape as well: too many models that were too unremarkable. The only difference from PCs was that Macs had a different operating system that was technically obsolete, PowerPC processors that were falling behind x86, and also they were more expensive. Not exactly a winning combination!

    Jobs made a number of changes in short order: he killed off the Macintosh clone market, re-asserting Apple’s integrated business model; he dramatically simplified the product lineup; and, having found a promising young designer already working at Apple named Jony Ive, he put all of the company’s efforts behind the iMac. This was truly a product where the hardware carried the software; the iMac was a cultural phenomenon, not because of Classic Mac OS’s ease-of-use, and certainly not because of its lack of memory protection, but simply because the hardware was so simple and so adorable.

    Foxtrot and the iMac

    OS X brought software to the forefront, delivering not simply a technically sound operating system, but one that was based on Unix, making it particularly attractive to developers. And, on the consumer side, Apple released iLife, a suite of applications that made a Mac useful for normal users. I myself bought my first Mac in this era because I wanted to use GarageBand; 16 years on and my musical ambitions are abandoned, but my Mac usage remains.

    By that point I was buying a Mac despite its hardware: while my iBook was attractive enough, its processor was a Motorola G4 that was not remotely competitive with Intel’s x86 processors; later that year Jobs made the then-shocking-but-in-retrospect-obvious decision to shift Macs to Intel processors. In this case having the same hardware as everyone else in the industry would be a big win for Apple, the better to let their burgeoning software differentiation shine.

    Apple 2.0: The Apex of Integration

    Meanwhile, Apple had an exploding hit on its hands with the iPod, which combined beautiful hardware and superior storage capacity with iTunes, software that offloaded the complexity of managing your music to your far more capable Mac and, starting in 2003, your PC; notably Apple avoided the trap of integrating hardware (the iPod) with hardware (the Mac), which would have handicapped the former to prop up the latter. Instead the company took advantage of the flexibility of software to port iTunes to Windows.

    The iPhone followed the path blazed by the iPod: while the first few versions of the iPhone were remarkably limited in their user-facing software capabilities, that was acceptable because much of that complexity was offloaded to the PC or Mac you plugged it into. To that point much of the software work had gone into making the iPhone usable on hardware that was barely good enough; RIM famously thought Jobs was lying about the iPhone’s capabilities at launch.

    Over time the iPhone would gradually wean itself off of iTunes and the need to sync with a PC or Mac, making itself a standalone computer in its own right; it was also on its way to being the most valuable product in history. This was the ultimate in integration, both in terms of how the product functioned, and also in the business model that integration unlocked.

    Apple 3.0: Hardware Over Software

    Sixteen years on from the PowerPC-to-Intel transition, and Apple’s software differentiation is the smallest it has been since the dawn of OS X. Windows has a Subsystem for Linux, which, combined with the company’s laser focus on developers, makes Microsoft products increasingly attractive for software development. Meanwhile, most customers use web apps on their computers, PC or Mac. There has been an explosion in creativity, but that explosion has occurred on smartphones, and is centered around distribution channels, not one’s personal photo or movie library.

    Those distribution channels and the various apps customers use to create and consume are available on both leading platforms, iOS and Android. I personally feel that the iPhone retains an advantage in the smoothness of its interface and quality of its apps, but Android is more flexible and well-suited to power users, and much better integrated with Google’s superior web services; there are strong arguments to be made for both ecosystems.

    Where the iPhone is truly differentiated is in hardware: Apple has — for now — the best camera system, and has had for years the best system-on-a-chip. These two differentiators are related: smartphone cameras are not simply about lenses and sensors, but also about how the resultant image is processed; that involves both software and the processor, and what is notable about smartphone cameras is that Google’s photo-processing software is generally thought to be superior. What makes the iPhone a better camera, though, is its chip.

    Apple Silicon and Sketch

    It is difficult to overstate just how far ahead Apple’s A-series of smartphone chips is relative to the competition; AnandTech found that the A14 delivered nearly double the performance of its closest competitors for the same amount of power — indeed, the A14’s only true competitor was last year’s A13. At least, that is, as far as mobile is concerned; the most noteworthy graph from that AnandTech article is about how the A14 stacks up against those same Intel chips that power Macs:

    AnandTech charts A-series chips versus Intel chips

    Whilst in the past 5 years Intel has managed to increase their best single-thread performance by about 28%, Apple has managed to improve their designs by 198%, or 2.98x (let’s call it 3x) the performance of the Apple A9 of late 2015.

    Apple’s performance trajectory and unquestioned execution over these years is what has made Apple Silicon a reality today. Anybody looking at the absurdness of that graph will realise that there simply was no other choice but for Apple to ditch Intel and x86 in favour of their own in-house microarchitecture – staying par for the course would have meant stagnation and worse consumer products.

    Today’s announcements only covered Apple’s laptop-class Apple Silicon, whilst we don’t know the details at time of writing as to what Apple will be presenting, Apple’s enormous power efficiency advantage means that the new chip will be able to offer either vastly increased battery life, and/or, vastly increased performance, compared to the current Intel MacBook line-up.

    What makes the timing of this move ideal from Apple’s perspective is not simply that this is the year that the A-series of chips are surpassing Intel’s, but also the Mac’s slipping software differentiation. Sketch, makers of the eponymous vector graphics app, wrote, on the occasion of their 10th anniversary, a paean to Mac apps:

    Ten years after the first release of Sketch, a lot has changed. The design tools space has grown. Our amazing community has, too. Even macOS itself has evolved. But one thing has remained the same: our love for developing a truly native Mac app. Native apps bring so many benefits — from personalization and performance to familiarity and flexibility. And while we’re always working hard to make Cloud an amazing space to collaborate, we still believe the Mac is the perfect place to let your ideas and imagination flourish.

    The fly in Sketch’s celebratory ointment is that phrase “even macOS itself has evolved”; the truth is that most of the macOS changes over Sketch’s lifetime — which started with Snow Leopard, regarded by many (including yours truly) as the best version of OS X — have been at best cosmetic, at worst clumsy attempts to protect novice users that often got in the way of power users.

    Meanwhile, it is the cloud that is the real problem facing Sketch: Figma, which is built from the ground-up as a collaborative web app, is taking the design world by storm, because rock-solid collaboration with good enough web apps is more important for teams than tacked-on collaboration with native software built for the platform.

    Sketch, to be sure, bears the most responsibility for its struggles; frankly, that native app piece reads like a refusal to face its fate. Apple, though, shares a lot of the blame: imagine if instead of effectively forcing Sketch out of the App Store with its zealous approach to security, Apple had evolved AppKit, macOS’s framework for building applications, to provide built-in support for collaboration and live-editing.

    Instead the future is web apps, with all of the performance hurdles they entail, which is why, from Apple’s perspective, the A-series is arriving just in time. Figma in Electron may destroy your battery, but that destruction will take twice as long, if not more, with an A-series chip inside!

    Integration Wins Again

    This isn’t the first time I have noted that Apple is inclined to fix ecosystem problems with hardware; five years ago, after the launch of the iPad Pro, I wrote in From Products to Platforms:

    Note that phrase: “How could we take the iPad even further?” Cook’s assumption is that the iPad problem is Apple’s problem, and given that Apple is a company that makes hardware products, Cook’s solution is, well, a new product.

    My contention, though, is that when it comes to the iPad Apple’s product development hammer is not enough. Cook described the iPad as “A simple multi-touch piece of glass that instantly transforms into virtually anything that you want it to be”; the transformation of glass is what happens when you open an app. One moment your iPad is a music studio, the next a canvas, the next a spreadsheet, the next a game. The vast majority of these apps, though, are made by 3rd-party developers, which means, by extension, 3rd-party developers are even more important to the success of the iPad than Apple is: Apple provides the glass, developers provide the experience.

    The iPad has since recovered from its 2017 nadir in sales, but seems locked in at around 8% of Apple’s revenue, a far cry from the 20% share it had in its first year, when it looked set to rival the iPhone; I remain convinced that the lack of a thriving productivity software market that treated the iPad like the unique device Jobs thought it was, instead of a laptop replacement, is the biggest reason why.

    Perhaps Apple Silicon in Macs will turn out better: it is possible that Apple’s chip team is so far ahead of the competition, not just in 2020, but particularly as it develops even more powerful versions of Apple Silicon, that the commoditization of software inherent in web apps will work to Apple’s favor, just as the its move to Intel commoditized hardware, highlighting Apple’s then-software advantage in the 00s.

    Apple is pricing these new Macs as if that is the case: the M1 probably costs around $75 (an educated guess), which is less than the Intel chips it replaces, but Apple is mostly holding the line on prices (the new Mac Mini is $100 cheaper, but also has significantly less I/O). That suggests the company believes it can take both share and margin, and it’s a reasonable bet from my perspective. The company has the best chips in the world, and you have to buy the entire integrated widget to get them.

    I wrote a follow-up to this article in this Daily Update.

  • Is the Internet Different?

    Tim Wu has a new piece up on Medium called Ben Thompson’s “Stratechery”; the subtitle, I think, is more descriptive of Wu’s premise:

    Smart, but a little too much Kool-Aid

    Said premise is in the second paragraph:

    Thompson has more recently begun to pronounce and analyze in the field of tech antitrust, and here he is on less solid ground. I appreciate that deep industry expertise is important in his area, especially, say, when designing remedies that make sense. Lacking a background in law or economics is not disqualifying. Nonetheless, I’d say Thompson’s readers are at risk of being misled if they rely too much on what he has to say about tech antitrust. For, as we shall see, his analysis relies too much on an idiosyncratic “digital markets are fundamentally different” thesis that really doesn’t hold up too well. Stated simply, I’d say he’s inducing his readers to drink too much of his “aggregation theory” Kool-Aid, as opposed to encouraging them to think more broadly or read more deeply to understand a slightly messier reality than he presents.

    I appreciate Wu’s article, both in terms of its specifics (which I disagree with), its goals (which are implied), and its means (which I value). Time to drink some Kool-Aid!

    (Orange-flavored, of course).

    Wu’s Argument

    Wu’s primary focus is my recent piece United States v. Google:

    According to Thompson, the Google case needs be understood primarily through what he calls aggregation theory, which is something of a specialized version of what economists call a two-sided markets theory. His theory asserts that 1) the quality of the user experience, rather than control over distribution, is what determines the winners in digital markets; and 2) a lead based on quality is self-reenforcing, because either more suppliers are attracted or the winner, with more customers, gets more feedback on what makes for a better product. (For those with a background in economics, Thompson’s aggregation theory is basically a mixture of a two-sided market theory with some positive feedback loop stuff thrown in.) Thompson says that “aggregators” (platforms, in economic, if not technological, parlance) are in this manner different than traditional monopolists, for they “win by building ever better products for consumers”…

    The problem is that his aggregation theory isn’t aspirational. Instead, it is presented as a description of how the internet has “fundamentally changed the plane of competition” in a world where “on the internet everything is just zero marginal bits.” It also takes as its assumptions: “Zero distribution costs. Zero marginal costs. Zero transactions.” In that, in some ways, it is like the older economic models from the 1960s, except that they were at least billed as models, not depictions of reality.

    Wu appears to be serious in his statement that assertions about the importance of zero marginal costs are best understood by looking to the past; his analogy for Aggregation Theory reaches back to the 1920s:

    Here’s my send-up of aggregation theory: Imagine this is the 1920s and we were speaking of the invention of brand advertising, and someone says, “whichever brand has the most people attracting it will create a buzz that further favors the winner. Hence, traditional metrics of competition are out the window.” I think we’d all agree that brand matters, and indeed the invention of powerful brands did change competition. But it might be a little too easy to think competition actually has changed forever. And we can see Thompson falling into the novelty trap by asserting things like “the internet has made transaction costs zero” — a sentence that would make any serious economist howl with laughter.

    I can’t speak for serious economists — I’ve generally enjoyed my interactions with them, and have been treated with nothing but respect while presenting the idea of Aggregation Theory — but the only thing I find humorous here is the idea that the Internet has not had a massive impact on transactions costs.

    Transactions Costs

    Consider various iterations of two-sided markets, of which Wu believes the companies I call Aggregators are a not particularly special version of. At the most basic level you might have something like a neighborhood flea market: on one side the market is a place for people to sell things, and on the other a place to buy things. Ultimately, though, every transaction entails sourcing supply, acquiring a customer, and executing the transaction itself. All three of those activities are costly.

    Over the course of the 20th century, larger and larger firms became more and more efficient at managing these transaction costs. The Great Atlantic & Pacific Tea Company, more commonly known as A&P, was the best example of this. The company expanded rapidly in the late 1800s, which was critical in acquiring ever more customers (the company was also a pioneer in advertising and using low prices on select items to get customers into stores); meanwhile, A&P built a back-end operation to match, vertically integrating into being a wholesaler, particularly of its own private label goods, which, combined with A&Ps scale, helped it deliver on those low prices. By 1930 the company had 16,000 stores doing nearly $3 billion in sales, accounting for a 10% share of nationwide grocery stores.

    By 1950 A&P’s market share peaked at 15%, although by that time A&P had transitioned to fewer, larger stores (around 4,500); the company was also facing an antitrust lawsuit, that it would eventually settle with a favorable consent decree. What ultimately doomed A&P, though, was its inability to adjust to a grocery market increasingly dominated by national brands advertised on television, along with uncompetitive labor costs and a failure to expand from city centers to the exploding suburbs. Each of these entailed higher transaction costs, and A&P couldn’t bear them.

    A few decades later Walmart would follow in A&P’s footsteps as far as dominance is concerned, although their strategy started with exurbs and suburbs and worked backwards; the fundamental limitations of needing to open stores to acquire customers, build out logistical networks to acquire and distribute goods at scale, and actually stock shelves and check out customers remained, though. Walmart too has reached about 15% market share (albeit of a larger general merchandise market).

    Amazon, meanwhile, has leveraged the Internet to dramatically decrease its customer acquisition costs in particular: the fundamental insight driving the retailer is that on the Internet shelf space is both infinite and available to anyone with an Internet connection; the company is still smaller than Walmart — 5% of general merchandise last year, although that number surely made a huge leap because of the pandemic — but it got there much more quickly: Amazon is only 26 years old, while Walmart is 58.

    Still, as Wu notes, Amazon has plenty of transaction costs of its own:

    Here is the danger: If you think competition is all about flavor and buzz (in the 1890s) or Thompson’s aggregation theory (right now), you might end up overlooking all of the other strategies and factors that could also lead to a lasting advantage. Consider Amazon. Thompson says that “the internet has made distribution (of digital goods) free.” But, as implied, that hasn’t made the distribution of physical goods free. And that is why a company like Amazon can, and has, gained a major advantage by building up a large physical infrastructure (warehouses), not unlike a steel producer in the 20th century, and strongly relying on a loyalty program (Prime). So, it turns out Amazon’s competitive advantage isn’t all about the fact that “on the internet everything is just zero marginal bits.”

    I completely agree; that’s why I have stated — contra Wu’s assertion — that Amazon is not an Aggregator. I mentioned Amazon specifically in 2017’s Defining Aggregators:1

    Aggregators have all three of the following characteristics; the absence of any one of them can result in a very successful business (in the case of Apple, arguably the most successful business in history), but it means said company is not an Aggregator.

    Direct Relationship with Users

    This point is straight-forward, yet the linchpin on which everything else rests: Aggregators have a direct relationship with users. This may be a payment-based relationship, an account-based one, or simply one based on regular usage (think Google and non-logged in users).

    Zero Marginal Costs For Serving Users

    Companies traditionally have had to incur (up to) three types of marginal costs when it comes to serving users/customers directly.

    • The cost of goods sold (COGS), that is, the cost of producing an item or providing a service
    • Distribution costs, that is the cost of getting an item to the customer (usually via retail) or facilitating the provision of a service (usually via real estate)
    • Transaction costs, that is the cost of executing a transaction for a good or service, providing customer service, etc.

    Aggregators incur none of these costs:

    • The goods “sold” by an Aggregator are digital and thus have zero marginal costs (they may, of course, have significant fixed costs)2
    • These digital goods are delivered via the Internet, which results in zero distribution costs3
    • Transactions are handled automatically through automatic account management, credit card payments, etc.4

    This characteristic means that businesses like Apple hardware and Amazon’s traditional retail operations are not Aggregators; both bear significant costs in serving the marginal customer (and, in the case of Amazon in particular, have achieved such scale that the service’s relative cost of distribution is actually a moat).

    Demand-driven Multi-sided Networks with Decreasing Acquisition Costs

    Because Aggregators deal with digital goods, there is an abundance of supply; that means users reap value through discovery and curation, and most aggregators get started by delivering superior discovery.

    Then, once an Aggregator has gained some number of end users, suppliers will come onto the Aggregator’s platform on the Aggregator’s terms, effectively commoditizing and modularizing themselves. Those additional suppliers then make the Aggregator more attractive to more users, which in turn draws more suppliers, in a virtuous cycle.

    This means that for Aggregators, customer acquisition costs decrease over time; marginal customers are attracted to the platform by virtue of the increasing number of suppliers. This further means that Aggregators enjoy winner-take-all effects: since the value of an Aggregator to end users is continually increasing it is exceedingly difficult for competitors to take away users or win new ones.

    This is in contrast to non-Aggregator and non-platform companies that face increasing customer acquisition costs as their user base grows. That is because initial customers are often a perfect product-market fit; however, as that fit decreases, the surplus value from the product decreases as well and quickly turns negative. Generally speaking, any business that creates its customer value in-house is not an Aggregator because eventually its customer acquisition costs will limit its growth potential.

    Google is the canonical example of this definition, and the difference from Amazon, much less non-Internet two-sided markets, is significant. Start with the transaction costs: while scaling an Internet service is a profoundly difficult thing to do, requiring tremendous ingenuity, invention, and investment, the marginal transaction costs for serving one additional customer are zero. That is why Google, from the moment it launched, could be used by anyone in the world. Like Amazon, the company didn’t need to build out physical stores, but unlike Amazon, the company didn’t need to build out delivery infrastructure either. And unlike every retailer in existence it didn’t need to pay for supply. And — this is the part that makes Google truly unique — it didn’t even need to generate supply. The web already existed!

    This is why Google can achieve 88 percent market share in the U.S. search market (according to the Department of Justice lawsuit), and achieve a similar level of share all over the entire world. The company’s scalability is effectively infinite, because serving additional customers is a function of fixed costs, not transaction costs; it really is not comparable to Amazon at all, in this regard, as the companies’ respective market shares demonstrates.

    The same reality applies to Google’s marginal costs (including distribution); while Google spends a tremendous amount of fixed costs on its data centers and networking, any one search is “free”, including Google accepting the search term, computing the result, and delivering it to the user. Moreover, this same principle applies to Google’s advertising business: the vast majority of advertising on Google is acquired via self-service portals that price ads automatically via real-time auctions. Yes, the infrastructure necessary to enable this business requires substantial investment, but the only transaction costs on any one specific advertising purchase are credit card fees.

    This is a business that requires more analysis than calling it a “two-sided market…with some positive feedback loop stuff thrown in”; for one, I would argue that all two-sided markets have positive feedback loops. Any market that touches the physical world, though, accumulates an ever increasing number of tiny costs along the way, whether that be labor costs, shipping costs, rent costs, etc.; moreover, the logistical challenges entailed in managing those costs incur their own cost in managerial complexity, and every investment to overcome those challenges become sunk costs, making it difficult to adjust when the market changes (this is particularly acute because it takes time to make these investments).

    Google, on the other hand, faces none of these natural drags on scale. More search means better search, thanks to the ongoing feedback of billions of users ranking every Google search result (by clicking on the best result); more advertisers means better advertising results, for the same reason. This matters greatly for antitrust because at some point you need a theory of harm: how exactly is Google making things worse for users or advertisers?

    Switching Costs

    This is also why I disagree with Wu’s characterization of switching costs:

    Whether this is core to his theory or not, Thompson also takes a highly anti-empirical approach to switching costs. He endorses the old 1990s idea that “competition is just one click away,” which may have been true in 1999, but that can’t be taken seriously now — if what he means is that the costs of leaving Google or Amazon or Facebook are close to zero. The real question is whether there are, for the average person, costs to switching from Facebook or Google to use something else — leaving behind Gmail, friends, and so on. The assertion that those costs are near zero is magical thinking. Indeed, one of Google’s most important strategies over this decade — its tell — has been to increase those switching costs, those barriers to entry.

    Consider Google specifically: the company’s core product, Search, has for its supply the open web. Indeed, that is what let the company be at scale, instantly, in a way no other company ever has. It follows, though, that every other search engine — including Bing, DuckDuckGo, etc. — has access to the exact same supply.

    Admittedly, Google does have its own local results in particular; Yelp has an entire website complaining about this fact, arguing that the search engine should be forced to include third-party content in its local search results because those results are better for consumers. That, though, is a mark in the competition’s favor: is Wu’s position that Google’s allegedly inferior local search results is lock-in?

    Meanwhile, I am puzzled by the reference to Gmail; it is unclear to me why it is a competition concern when a user chooses to use a free email service that is quite obviously locked to the service provider. The relevant market here is not Gmail, it is email, and not only is there a huge amount of competition for hosted email, it is fairly simple to set up your own email server. Critically, there is absolutely nothing Google can do to stop you from doing so, even if they wanted to.

    This drives at the biggest reason why I believe a distinct definition for “Aggregators” is important; while Wu casually conflates Aggregators and platforms (“in economic, if not technological, parlance”), I believe the distinction is substantial and crucial. I explore that distinction at length in A Framework for Regulating Competition on the Internet, but the critical point goes back to the email example:

    • Platforms are essential to their value chains. You can’t have a Windows app, for example, without the Windows API.
    • Aggregators, in contrast, are not essential, but they are convenient. You can go to a website directly — just type in its URL — but for most consumers, for most pieces of information, it is far easier to search.

    What is fascinating about many of Google’s most ardent critics is that they themselves aspire to be Aggregators. Yelp, for example, doesn’t operate any local businesses. It doesn’t prepare the food, or cut the hair, or teach the class: its business model is to aggregate so many users that local businesses feel compelled to be on Yelp, the better to reach more customers than they could on their own. The same applies to Trip Advisor, or Expedia, or any other vertical search company. All of those sites are only a click away.

    And, critically, so are the entities that actually provide the services or information that the user is seeking. Airlines and hotels invest heavily in loyalty programs, for example, because they want their best customers to come to them directly, not via an Aggregator, whether that Aggregator be Google or Booking.com. That not only sounds like competition, it also sounds like an exceptionally customer-friendly outcome.

    The Missing Intersection

    Where I think Wu and many tech critics go wrong is missing how the question of zero marginal costs and zero switching costs intersect. First, because Wu does not believe that Google is unique as far as scalability is concerned, he appears to assume that the company must be doing something nefarious to command such market share. And, by the same token, there must be some sort of unfair lock-in, because again, companies ought not be so dominant. This is a sure recipe for lazy arguments that end up criminalizing the basics of business.

    How does all this relate to antitrust? Antitrust should be dealing with the reality of anticompetitive behavior in markets, not ideals of how companies work. And it is the difficult job of the law to determine which of these durable advantages just described are part of fair competition (for example, a better user experience) and which are not (for example, buying out dangerous rivals, or exclusionary deals that keep out competitors)…

    We may summarize the problem for Thompson this way: Why, exactly, did Google pay Apple billions to gain control over distribution rights? And why, to bring the law into it, hasn’t Google settled the case? If aggregation theory is right — if competition has changed in the digital market and the best user experience wins — then Google doesn’t need to spend that money.

    I honestly don’t think this is too complicated: defaults do matter, and given the fact that Google makes somewhere north of $250 in revenue per U.S. user it is well worth sharing some of that revenue to ensure it gets as many users as possible. Consider iOS specifically:

    • According to the Department of Justice “This agreement covers roughly 36 percent of all general search queries in the United States”; assuming that share of search queries is inline with share of revenue (which is almost certainly not the case, given the relative spending power of Apple’s userbase), the agreement covers $26.9 billion worth of revenue.
    • Further assume that, were Google not the default, the company would lose 25% of Apple device searches it might have gained otherwise; this equates to a revenue loss of $6.7 billion for the U.S. alone, and again, this number is almost certainly conservative given the relative spending power of Apple users.

    Moreover, those searches would go to Google’s competitors, not only giving valuable data that would help make their search engines better, but also increasing the efficiency and relative attractiveness of their ad products. I do still believe that Google would continue to win on the merits, but it would be more costly, not less.

    Which, of course, is why I support the Department of Justice’s lawsuit, and why I have been outspoken about acquisitions by Aggregators. Aggregators already have intrinsic advantages given the nature of costs on the Internet; I don’t believe they should be able to augment those advantages with contracts or by acquiring customers (I do not, however, favor a ban on other types of acquisitions).

    The difference I have with Wu, as far as I can tell, is that I see these agreements and acquisitions as frosting on an Aggregation cake, as opposed to the fundamental drivers of their dominance. Google isn’t dominant because they broke the law, they are (arguably) breaking the law well after their dominance was established, and that distinction matters when it comes to crafting remedies and regulations that actually work.

    Differentiation and Gatekeepers

    The most disappointing part of Wu’s essay, though, at least on a personal level, is the conclusion:

    This may be too much for some readers, but a last problem with aggregation theory is that its “winner take all” assertion assumes away the importance of differentiated user preferences. In other words, it tends to assume that there is one “user experience” that is preferred by everyone, and by depending on feedback, the product can be improved to match that…

    Perhaps Thompson has addressed this somewhere, but I thought it important to point out. The model only works well, I think, either when consumers have identical preferences or when they want the greatest number of suppliers for some reason, or maybe when consumer value convenience even over what they’d called their own stated preferences (the so-called tyranny of convenience).

    The very premise of this site is that the Internet takes preference differentiation to the extreme, resulting in never-ending niches that can be profitably filled. Moreover, this isn’t simply about small websites: just last month I wrote about how Disney is pursuing an integration strategy that is an antidote to Aggregators like Google and Facebook, and how that can be model for other media companies. The Article included this distinction:

    Aggregators are content agnostic. Integrators are predicated on differentiation.

    Facebook reduces all content to similarly sized rectangles in your feed: a deeply reported investigative report is given the same prominence and visual presentation as photos of your classmate’s baby; all that Facebook cares about is keeping you engaged. Content created by Disney, on the other hand, must be unique to Disney, and memorable, as it is the linchpin for their entire business.

    So yes, I have “addressed this somewhere” — I addressed it three weeks ago. Contrary to Wu’s caricature of me, I don’t believe that Aggregation Theory applies to everything, but the things to which it does apply — like when “consumers have identical preferences or when they want the greatest number of suppliers” for something like search results — it matters a great deal. To that end, it seems rich to criticize me for “false confidence” and an unwillingness to “think more broadly or read more deeply” when one can’t be bothered to scroll down my home page.

    Then again, perhaps an honest debate isn’t the goal. Wu foreshadowed his essay on Twitter:

    Wu added, in a tweet he seems to have deleted, that my writing is “quack medicine”:

    Tim Wu's tweet calling Stratechery "Quack Medicine"

    This casts Wu’s comment that “Lacking a background in law or economics is not disqualifying”, in a different, more backhanded, light. For decades antitrust was indeed limited to those with a background in law or economics; that is the only way politicians, attorneys general, judges, general counsels, or the media would pay attention to what you had to say. The media in particular had a monopoly on the dissemination of information, and credentials were the way to get into their channel. It’s hard to escape the sense that a breakdown in gatekeepers bothers Wu.

    And, by the same token, perhaps this is why I do believe that the Internet is something profoundly different; it has certainly made my career far different than it might have been were I a decade or two older. And, by extension, perhaps this is why I can see the benefit of Aggregators: Google and Facebook and Twitter may have been terrible for traditional media companies whose business models depended on controlling distribution, but they are fantastic for giving consumers exactly what they want, including a perhaps heretical view of antitrust.

    Truth Seeking

    This does raise the question as to why you should believe me, or anything else you read on the Internet. This interaction arose in response to Wu’s initial tweet:

    My response:

    This is why, whatever Wu’s motivations, I appreciated his piece. I do disagree, in part because I don’t think Wu understands my argument, but that’s ok: it’s an opportunity to make my argument in a different way, as I tried to do today, and perhaps change his mind, or yours. Or perhaps I failed, and you agree with Wu that I have created a theory where one ought not exist. Again, that’s fine: now you know what you believe better than you did before this piece, and perhaps you will view my other writing with increased skepticism. That’s a good thing!

    More broadly, the pre-Internet world, governed as it was by gatekeepers, was certainly a more unified one, at least as far as conventional wisdom was concerned — this applied to law and economics just as much as anything else. At the same time, that does not mean the pre-Internet world had a better overarching grasp on the truth, given how much more difficult it was for dissenting voices to gain distribution. If I happen to be correct about Aggregation Theory, and that the way to understand Google depends on more than “two-sided market theory with some positive feedback loop stuff thrown in”, then I would like to think the fact that Stratechery can exist, without anyone’s permission, is a good thing.

    After all, I am concerned about just how powerful these companies are. I am not intrinsically opposed to regulation — I believe in democratic oversight — but the risk of getting regulation wrong is that companies like Google become more entrenched, not less. This is why I objected to GDPR before it came in force, and why I spend time writing about antitrust (which, I might add, is not a traffic driver!). Getting the law and the economics right are important, particularly if the Internet challenges the fundamental assumptions underlying them.

    1. Please forgive me for the long excerpt, but despite Wu’s exhortation that one needs to read deeply to understand these issues, it appears he has not done me the same honor ↩

    2. And yes, in the very long run, all fixed costs are marginal costs; that said, while the amount of capital costs for Aggregators is massive, their userbase is so large that even over the long run the fixed costs per user are infinitesimal, particularly relative to revenue generated ↩

    3. In terms of the marginal customer; in aggregate there are of course significant bandwidth costs, but see the previous footnote ↩

    4. Credit card fees are a significant transaction cost that do limit some types of businesses, but will generally be ignored in this analysis ↩