Cable’s Last Laugh

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If there is one industry people in tech are eternally certain is doomed, it is cable. However, the reality is that cable is both stronger than ever and poised for growth; the reasons why are instructive to not just tech industry observers, but to tech companies themselves.

The Creation of Cable

Robert J. Tarlton was 29 years old, married with a son, when he volunteered to fight in World War II; thanks to the fact he owned a shop in Lansford, Pennsylvania that sold radios, he ended up repairing them all across the European Theater, learning about not just reception but also transmission. After the war Tarlton re-opened his shop, when Motorola, one of his primary suppliers, came out with a new television.

Tarlton was intrigued, but he had a geography problem; the nearest television station was in Philadelphia, 71 miles away; in the middle lie the Pocono Mountains, and mountains aren’t good for reception:

Lansford is separated from Philadelphia by the Pocono Mountains

It turned out, though, that some people living in Summit Hill, the next community over, could get the Philadelphia broadcast signal; that’s where Tarlton sold his first television sets. Of course Tarlton couldn’t demonstrate this new-fangled contraption; his shop was in Lansford, not Summit Hill. However, it was close to Summit Hill: what if Tarlton could place an antenna further up the mountain in Summit Hill and run a cable to his shop? Tarlton explained in an interview in 1986:

Lansford is an elongated town. It’s about a mile and a half long and there are about eight parallel streets bisected with cross streets about every 500 feet. There are no curves; everything is all laid out in a nice symmetrical pattern. Our business place was about three streets from the edge of Summit Hill and Lansford sits on kind of a slope. The edge of Lansford inclines from about a thousand feet above sea level to about fifteen hundred feet above sea level in Summit Hill. So to get television into our store, my father and I put an antenna partly up the mountain. No, we didn’t go all the way up, but we put up an antenna, kind of a crude arrangement, and then from tree to tree we strung a twin lead that was used in those days as a transmission line. We ran this twin lead, crossed a few streets, and into our store. And we had television.

The basic twin lead was barely functional, but that didn’t stop everyone from demanding a television with a haphazard wire to their house; Tarlton realized that new coaxial cable amplifiers designed for a single property could be chained together, re-amplifying the signal so it could reach multiple properties. After getting all of the other electronics retailers on board — Tarlton knew that a clear signal would sell more TV sets, but that everyone needed to use the same system — the first commercial cable system was born, and it sold itself. Tarlton reflected:

You didn’t have to advertise. You had to keep your door locked because the people were clamoring for service. They wanted cable service. You certainly didn’t have to advertise.

People couldn’t get enough TV; Tarlton explained:

Cable is dependent upon advances in technology because people who originally saw one channel wanted to see the second channel, wanted to see the third, and after you had five, they wanted more. So it was a case of more begets more. At one time three channels seemed to be quite sufficient but when we added one more channel, it created a new interest in the cable system. People then had variety. They had alternatives. At one time later five channels seemed enough. As a matter of fact, a man who is often quoted, former FCC Commissioner Ken Cox, said that five channels was enough, and that’s quite a story in itself. The engineers were able to continually refine equipment to add more channels…All these technical advances‑‑continuing advances, automatic gain control, automatic temperature compensation, etc. have made cable what it is today.

One of the most important technological developments was satellite: now cable systems could get signals both more reliably and from far further away; this actually flipped geography on its head. Tarlton said:

At that time we went to the highest possible point to look to the transmitter. Today with satellites, we go to the lowest possible point because we don’t want the interference from other signals. So it is ironic that we have changed so much from what we used to do.

Within these snippets is everything that makes the cable business so compelling:

  • Cable is in high demand because it provides the means to get what customers most highly value.
  • Cable works best both technologically and financially when it has a geographic monopoly.
  • Cable creates demand for new supply; technological advances enable more supply, which creates more demand.

It’s that last bit about satellites being better on lower ground that stands out to me, though: as long as you control the wires into people’s houses you can and should be pragmatic about everything else.

Cable’s Evolution

Tarlton would go on to work for a company called Jerrold Electronics, which pivoted its entire business to create equipment for cities that wanted to emulate Lansford’s system; Tarlton would lead the installation of cable systems across the United States, which for the first two decades of cable mostly retransmitted broadcast television.

The aforementioned satellite, though, led to the creation of national TV stations, first HBO, and then WTCG, an independent television station in Atlanta, Georgia, owned by Ted Turner. Turner realized he could buy programming at local rates, but sell advertising at national rates via cable operators eager to feed their customers’ hunger for more stations. Turner soon launched a cable only channel devoted to nothing but news; he called it the Cable News Network — CNN for short (WTCG would later be renamed TBS).

Jerrold Electronics, meanwhile, spun off one of the cable systems it built in Tupelo, Mississippi to an entrepreneur named Ralph Roberts; Roberts proceeded to systematically buy up community cable systems across the country, moving the company’s headquarters to Philadelphia and renaming it to Comcast Corporation (Roberts would eventually hand the business off to his son, Brian). Consolidation in the provision of cable service proceeded in conjunction with consolidation in the production of content, an inevitable outcome of the virtuous cycle I noted above:

  • Cable companies acquired customers who wanted access to content
  • Studios created content that customers demanded

The more customers that a cable company served, the stronger their negotiating position with content providers; the more studios and types of content that a content provider controlled the stronger their negotiating position with cable providers. The end result were a few dominant cable providers (Comcast, Charter, Cox, Altice, Mediacom) and a few dominant content companies (Disney, Viacom, NBC Universal, Time Warner, Fox), tussling back-and-forth over a very profitable pie.

Then came Netflix, and tech industry crowing about cord cutting.

Netflix and other streaming services were obviously bad for television: they did the same job but in a completely different way, leveraging the Internet to provide content on-demand, unconstrained by the linear nature of television that was a relic of cable’s origin with broadcast TV. Here, though, cable’s ownership of the wires was an effective hedge: the same wires that delivered linear TV delivered packet-based Internet content.

Moreover, this didn’t simply mean that cable’s TV losses were made up for by Internet service: Internet service was much higher margin because companies like Comcast didn’t need to negotiate with a limited number of content providers; everything on the Internet was free. This has meant that the fortunes of cable companies has boomed over the last decade, even as cord-cutting has cut the cable TV business by about a third.

Cable companies today, though, are yet another category down from their pandemic highs, thanks to fear that the broadband growth story is mostly over; fiber offers better performance, 5G opens the door to wireless in the home, and anyone who doesn’t have broadband now is probably never going to get it. I think, though, this underrates the strategic positioning of cable companies, and ignores the industry’s demonstrated ability to adapt to new strategic environments.

The Wireless Opportunity

From the Wall Street Journal in 2011:

Verizon Wireless will pay $3.6 billion to buy wireless spectrum licenses from a group of cable-television companies, bringing an end to their years-long flirtation with setting up its own cellphone service. The sellers—Comcast Time Warner Cable Inc. and Bright House Networks—acquired the spectrum in a government auction in 2006 and now will turn it over to the country’s biggest wireless carrier at more than a 50% markup. While cable companies have dabbled with wireless, the spectrum has largely sat around unused, prompting years of speculation about the industry’s intentions…

Under the deal, Verizon Wireless will be able to sell its service in the cable companies’ stores. The carrier, in turn, will be able to sell the cable companies’ broadband, video and voice services in its stores. Verizon’s FiOS service only reaches 14% of U.S. households, according to Bernstein Research. In four years’ time, the cable companies will have the option to buy service on Verizon’s network on a wholesale basis and then resell it under their own brand.

The joint marketing arrangement “amounts to a partnership between formerly mortal enemies,” wrote Bernstein analyst Craig Moffett in a research note.

Moffett would later partner with Michael Nathanson to form their own independent research firm (called MoffettNathanson, natch); Moffett released an updated report last month that explained how that Verizon deal ended up playing out:

When Comcast and Time Warner Cable sold their AWS-1 spectrum to Verizon back in 2011, they believed at the time that they were walking away from ever becoming facilities-based wireless players. They therefore viewed it as imperative that the sale come with an MVNO agreement with Verizon to compensate for that forfeiture. They got precisely what they wanted, an MVNO contract with Verizon that was described at the time as “perpetual and irrevocable“…

It took another six years after that transaction before Comcast finally launched Xfinity Mobile in mid-2017. Charter [which merged with Time Warner Cable, acquiring the latter’s MVNO rights] followed suit a year later…in four short years, the Cable operators have become the fastest growing wireless providers in the country, accounting for nearly 30% of wireless industry net additions. Cable’s 7.7 million mobile lines represent ~2.5% of the U.S. mobile phone market (including prepaid and postpaid phones).

As Moffett notes, this growth is particularly impressive given that most cable companies couldn’t feasibly offer family plans under the terms of the original deal, which was negotiated before such a concept even existed; the deal has been re-negotiated, though, and almost certainly to the cable companies’ advantage: if Verizon is going to lose customers to an MVNO, it would surely prefer said MVNO be on their network; this means that the cable companies have negotiating leverage.

What, though, makes the cable companies such effective MVNOs? One of the most interesting parts of Moffett’s note was proprietary data about the amount of data used by cellular subscribers; it turns out that cable MVNO customers are far more likely to consume data over WiFi, perhaps because of cable company out-of-home WiFi hot spots. This could become even more favorable in the future as cable companies build out Citizens Broadband Radio Service (CBRS) service, particularly in dense areas where cable companies have wires from which to hang CBRS transmitters. Moffett writes:

In a perfect world, Cable will offload traffic onto their own facilities where doing so is cheap (high density, high use locations) and leave to Verizon the burden of carrying traffic where doing so is/would be expensive. Because the MVNO agreement is “perpetual and irrevocable,” and is based on average prices (i.e., the same price everywhere, whether easy or hard to reach), Cable is presented with a perfect ROI arbitrage; they can take the high ROI parts of the network for themselves, and leave the low ROI parts of the network to their MVNO host… all without sacrificing anything with respect to their national coverage footprint.

One can understand why Verizon gave the cable companies these rights in 2011; the phone company desperately needed spectrum, and besides, everyone knew that MVNOs could never be economically competitive with their wholesale providers, who were the ones that actually made the investments in the network.

That’s the thing, though: cable companies had their own massive build-out, one that was both much older in its origins and, because it connected the house, actually carried more data. This was to the benefit of Verizon and other cellular providers, of course: a Verizon iPhone uses WiFi at home just as much as a Comcast iPhone does; here, though, it was cable that had internet economics on its side: there is no competitive harm in giving equal access to an abundant resource; it is cellular access that is scarce, which means that the cable companies’ MVNO deal, in conjunction with their out-of-home Internet access options, gives them a meaningful advantage.

Customer Acquisition

Moffett spends less time on customer acquisition; anecdotally speaking, it’s clear that Charter’s Spectrum, which provides the cable service I consume (via the excellent Channels application), is pushing wireless service hard: phones are front-and-center in their stores, and Spectrum wireless commercials fill local inventory. Moreover, this is a well-trodden playbook: cable companies came to dominate the fixed line phone service business simply because it was easier to get your TV, Internet, and phone all in the same place (and of those, the most important was TV, and now Internet); it’s always easier to upsell an existing subscriber than it is to acquire a new one.

Of course cable companies long handled customer acquisition for content creators — that was the cable bundle in a nutshell. What is interesting is how this customer acquisition capability is attractive to the companies undoing that bundle: Netflix, for example, put its service on Comcast’s set-top boxes in 2016, and made a deal for Comcast to sell its service in 2018. I wrote in a Daily Update at the time:

Netflix, meanwhile, is laddering up again: the company doesn’t actually need a billing relationship with end users, it just needs ever more end users (along with the data about what they watch) to spread its fixed content costs more widely; the company said in its shareholder letter that:

These relationships allow our partners to attract more customers and to upsell existing subscribers to higher ARPU packages, while we benefit from more reach, awareness and often, less friction in the signup and payment process. We believe that the lower churn in these bundles offsets the lower Netflix ASP.

What is particularly interesting is that this arrangement moves the industry closer to the endgame I predicted in The Great Unbundling…

“Endgame” was a bit strong: that Article was, as the title says, about unbundling; one of my arguments was that the traditional cable TV bundle would become primarily anchored on live sports and news, while most scripted content went to streaming. That is very much the case today (TBS, for example, is abandoning scripted content, while becoming ever more reliant on sports). What was a mistake was insinuating that this was the “end”; after all, as Jim Barksdale famously observed, the next step after unbundling is bundling.

To that end, Netflix + Xfinity TV service was a bundle of sorts, but the real takeaway was that Comcast was fine with being simply an Internet provider (which ended up helping with TV margins, since cable companies mostly gave up on fighting to keep cord cutters). Shortly after the Netflix deal Comcast launched Xfinity Flex, a free 4K streaming box for Internet-only subscribers that included a storefront for buying streaming services (which would be billed by Comcast). You can even subscribe to digital MVPDs like YouTube TV!

The free Xfinity Flex streaming box

The first takeaway of an offering like Xfinity Flex ties into the wireless point: cable companies already have a billing relationship with the customer — because they provide the most essential utility for accessing what is most important to said customer — which makes them particularly effective at customer acquisition. That is why Netflix, YouTube, etc. are all willing to pay a revenue share for the help.

The Great Rebundling?

The second takeaway, though, is that the cable companies are better suited than almost anyone else to rebundle for real. Imagine a “streaming bundle” that includes Netflix, HBO Max, Disney+, Paramount+, Peacock, etc., available for a price that is less than the sum of its parts. Sounds too good to be true, right? After all, this kind of sounds like what Apple was envisioning for Apple TV (the app) before Netflix spoiled the fun; I wrote in Apple Should Buy Netflix in 2016:

Apple’s desire to be “the one place to access all of your television” implies the demotion of Netflix to just another content provider, right alongside its rival HBO and the far more desperate networks who lack any sort of customer relationship at all. It is directly counter to the strategy that has gotten Netflix this far — owning the customer relationship by delivering a superior customer experience — and while Apple may wish to pursue the same strategy, the company has no leverage to do so. Not only is the Apple TV just another black box that connects to your TV (that is also the most expensive), it also, conveniently for Netflix, has a (relatively) open app platform: Netflix can deliver their content on their terms on Apple’s hardware, and there isn’t much Apple can do about it.

Six years on and Netflix is in a much different place, not only struggling for new customers but also dealing with elevated churn. Owning the customer may be less important than simply having more customers, particularly if those customers are much less likely to churn. After all, that’s one of the advantages of a bundle: instead of your streaming service needing to produce compelling content every single month, you can work as a team to keep customers on board with the bundle.

The key point about a bundle, as longtime YouTube executive and Coda CEO Shishir Mehrotra has written, is that it minimizes SuperFan overlap while maximizing CasualFan overlap; in other words, effective bundles have more disparate content that you are vaguely interested in, instead of a relatively small amount of focused content that you care about intensely. This makes the bundle concept even more compelling to new entrants in the streaming wars, who may not have as large of libraries as Netflix, and certainly don’t have as many subscribers over which to spread their content costs.

Moreover, the fact that the streaming services have largely done their damage to traditional TV, leaving the cable TV bundle as the sports and news bundle, means it is actually viable to create a lower-priced bundle than what was previously available (if you don’t want sports). After all, you’re not cannibalizing TV, but rather bringing together what has long since been broken off (unbundling then bundling!).

This isn’t something that is going to happen overnight: despite the fact that bundles are good for everyone it is hard to get independents into a bundle as long as they are growing; Netflix’s recent struggles are encouraging in this regard, particularly if other streaming services start to face similar headwinds. Moreover, cable companies are not the only entities that will seek to pull something like this off: Apple, Amazon, Google, and Roku already make money from revenue shares on streaming subscriptions they sell; all of them sell devices that can be used as interfaces for selling a bundle. And, of course, there are more Internet providers than just the cable companies: there is fiber, wireless, and even Starlink.

The breadth of the cable company bundle, though, is unmatched: not only might it include streaming services, but also linear TV; more than that, this is the company selling you Internet access, and increasingly wireless phone service. That gives even more latitude for discounts, and perks like no data caps on streamed content, not just at home but also on your phone.

All of these advantages go back to Robert J. Tarlton and Lansford, Pennsylvania. A recurring point on Stratechery this past year has been the durability and long-term potential inherent in technology rooted in physical space. I wrote in Digital Advertising in 2022:

Real power in technology comes from rooting the digital in something physical: for Amazon that is its fulfillment centers and logistics on the e-commerce side, and its data centers on the cloud side. For Microsoft it is its data centers and its global sales organization and multi-year relationships with basically every enterprise on earth. For Apple it is the iPhone, and for Google is is Android and its mutually beneficial relationship with Apple (this is less secure than Android, but that is why Google is paying an estimated $15 billion annually — and growing — to keep its position). Facebook benefited tremendously from being just an app, but the freedom of movement that entailed meant taking a dependency on iOS and Android, and Apple has exploited that dependency in part, if not yet in full.

For cable companies, power comes from a wire; it would certainly be ironic if the cord-cutting trumpeted by tech resulted in cable having even more leverage over customers and their wallets than the pre-Internet era.

Beyond Aggregation: Amazon as a Service

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Five months and $134 billion in market cap ago (before the stock slipped by 68%), Bloomberg Businessweek purported to explain How Shopify Outfoxed Amazon to Become the Everywhere Store. One of the key parts of the story was how Shopify pulled one over on Amazon seven years ago:

An even more critical event came a few months after the IPO. Amazon also operated a service that let independent merchants run their websites, called Webstore. Bang & Olufsen, Fruit of the Loom, and Lacoste were among the 80,000 or so companies that used it to run their online shops. If he wanted to, Bezos surely had the resources and engineering prowess to crush Shopify and steal its momentum.

But Amazon execs from that time admit that the Webstore service wasn’t very good, and its sales were dwarfed by all the rich opportunities the company was seeing in its global marketplace, where customers shop on Amazon.com, not on merchant websites…In late 2015, in one of Bezos’ periodic purges of underachieving businesses, he agreed to close Webstore. Then, in a rare strategic mistake that’s likely to go down in the annals of corporate blunders, Amazon sent its customers to Shopify and proclaimed publicly that the Canadian company was its preferred partner for the Webstore diaspora. In exchange, Shopify agreed to offer Amazon Pay to its merchants and let them easily list their products on Amazon’s marketplace. Shopify also paid Amazon $1 million—a financial arrangement that’s never been previously reported.

Bezos and his colleagues believed that supporting small retailers and their online shops was never going to be a large, profitable business. They were wrong—small online retailers generated about $153 billion in sales in 2020, according to AMI Partners. “Shopify made us look like fools,” says the former Amazon executive.

If only we could all make such excellent mistakes; Amazon’s move looks like a strategic masterstroke.

Shopify’s Revenue Streams

Three major things have changed, will change, or should change about Shopify’s business in the years since the company made that deal with Amazon.

What has changed is the composition of Shopify’s business. While the company started out with a SaaS model, the business has transformed into a commission-based one:

Shopify's two revenue streams

“Subscription Solutions” are Shopify’s platform fees, including the cost to use the platform (or upgrade to the company’s Pro offering), commissions from the sales of themes and apps, and domain name registration. “Merchant Solutions”, meanwhile, are all of the fees that are generated from ongoing sales; the largest part of this are payment processing fees from Shopify Payments, but other fees include advertising revenue, referral fees, Shopify Shipping, etc.

It’s the shipping part that is line for big changes: while Shopify first announced the Shopify Fulfillment Network back in 2019, it is only recently that the company has committed to actually building out important pieces of said network on its own, the better to compete with Amazon’s full-scale offering.

As for what should change, I argued back in February that Shopify needed to build out an advertising network; this recommendation is more pertinent than ever, in large part because the second item on this list might be in big trouble.

Buy With Prime

From the Wall Street Journal:

Amazon.com Inc. is extending some of the offerings of its popular Prime membership program to merchants off its platform with a new service that embeds the online retailing giant’s payment and fulfillment options onto third-party sites. Called Buy with Prime, the service will allow merchants to show the Prime logo and offer Amazon’s speedy delivery options on products listed on their own websites…

The company said the Buy with Prime offer will be rolled out by invitation only through 2022 for those who already sell on Amazon and use the company’s fulfillment services. Later, Amazon plans to extend Buy with Prime to other merchants, including those that don’t sell on its platform. Participating merchants will use the Prime logo and display expected delivery dates on eligible products. Checkout will go through Amazon Pay and the company’s fulfillment network. Amazon will also manage free returns for eligible orders.

This is a move that you could see coming for a long time; back in 2016 I wrote an article called The Amazon Tax that explained that the best way to understand Amazon as a whole was to understand Amazon Web Services (AWS):

The “primitives” model modularized Amazon’s infrastructure, effectively transforming raw data center components into storage, computing, databases, etc. which could be used on an ad-hoc basis not only by Amazon’s internal teams but also outside developers:

A drawing of The AWS Layer

This AWS layer in the middle has several key characteristics:

  • AWS has massive fixed costs but benefits tremendously from economies of scale
  • The cost to build AWS was justified because the first and best customer is Amazon’s e-commerce business
  • AWS’s focus on “primitives” meant it could be sold as-is to developers beyond Amazon, increasing the returns to scale and, by extension, deepening AWS’ moat

This last point was a win-win: developers would have access to enterprise-level computing resources with zero up-front investment; Amazon, meanwhile, would get that much more scale for a set of products for which they would be the first and best customer.

As I noted in that article, the AWS model was being increasingly applied to e-commerce as Amazon shifted from being a retailer to being a services provider:

Prime is a super experience with superior prices and superior selection, and it too feeds into a scale play. The result is a business that looks like this:

A drawing of The Transformation of Amazon’s E-Commerce Business

That is, of course, the same structure as AWS — and it shares similar characteristics:

  • E-commerce distribution has massive fixed costs but benefits tremendously from economies of scale
  • The cost to build-out Amazon’s fulfillment centers was justified because the first and best customer is Amazon’s e-commerce business
  • That last bullet point may seem odd, but in fact 40% of Amazon’s sales (on a unit basis) are sold by 3rd-party merchants; most of these merchants leverage Fulfilled-by-Amazon, which means their goods are stored in Amazon’s fulfillment centers and covered by Prime. This increases the return to scale for Amazon’s fulfillment centers, increases the value of Prime, and deepens Amazon’s moat

My prediction in that Article was that Amazon’s burgeoning logistics business would eventually follow the same path:

It seems increasingly clear that Amazon intends to repeat the model when it comes to logistics…how might this play out? Well, start with the fact that Amazon itself would be this logistics network’s first-and-best customer, just as was the case with AWS. This justifies the massive expenditure necessary to build out a logistics network that competes with UPS, Fedex, et al, and most outlets are framing these moves as a way for Amazon to rein in shipping costs and improve reliability, especially around the holidays.

However, I think it is a mistake to think that Amazon will stop there: just as they have with AWS and e-commerce distribution I expect the company to offer its logistics network to third parties, which will increase the returns to scale, and, by extension, deepen Amazon’s eventual moat

Today Amazon’s logistics is massive and fully integrated from the fulfillment center to the doorstep, even though it only serves Amazon; the obvious next step is opening it up to non-Amazon retailers, and that is exactly what is happening.

Beyond Aggregation

At first glance, this might seem like a bit of a surprise; after all, Stratechery is well known for describing Aggregation Theory, which is predicated on controlling demand. In the case of Amazon that has meant controlling the website where customers order goods — Amazon.com — even if those goods were sold by 3rd-party merchants. Why would Amazon give that up?

The reasoning is straightforward: while Amazon has had Aggregator characteristics, the company’s business model and differentiation has always been rooted in the real world, which, by extension, means it is not an Aggregator at all. I noted in 2017’s Defining Aggregators that Aggregators benefit from zero marginal costs, which only describes a certain set of digital businesses like Google and Facebook:

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)
  • These digital goods are delivered via the Internet, which results in zero distribution costs
  • Transactions are handled automatically through automatic account management, credit card payments, etc.

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).

Amazon’s control of demand has been — and will continue to be — a tremendous advantage; Amazon not only has power over its suppliers, but it also gets all of the relevant data from consumers, which it can feed into a self-contained ad platform that is untouched by regulation from either governments or Apple.

At the same time, limiting a business to customer touchpoints that you control means limiting your overall addressable market. This may not matter in markets where there are network effects (which means you appeal to everyone) and you are an Aggregator dealing with zero marginal costs (and thus can realistically cover every consumer); in the case of e-commerce, though, Amazon will never be the only option, particularly given The Anti-Amazon Alliance working hard to reach consumers.

A core part of the Anti-Amazon Alliance are companies that have invested in brands that attract customers on their own; these companies don’t need to be on Amazon fighting to be the answer to generic search terms, but can rather drive customers to their own Shopify-powered websites both organically and via paid advertising (Facebook is a huge player in the Anti-Amazon Alliance). Still, every customer that visits these websites has an Amazon-driven expectation in terms of shipping; Shippo CEO Laura Behrens Wu told me in a Stratechery interview:

Consumers have those expectations from Amazon that shipping should be free, it should be two days, and whatever those are expectations are, returns should be free. That is still carried over when I’m buying on this branded website. If the expectations are not met, consumers decide to buy somewhere else…Merchants are constantly trying to play catch up, whatever Amazon is doing they need to follow suit.

Now Amazon has — or soon will have, in the case of Shopify-only merchants — a solution: the best way to get an Amazon-like shipping experience is to ship via Amazon. And, in contrast to the crappy Webstore product, you can keep using Shopify and its ecosystem for your website. Amazon may have given away business to Shopify in 2015, but that doesn’t much matter if said business ends up being a commoditized complement to Amazon’s true differentiation in logistics. That business, thanks to the sheer expense necessary to build it out, has a nearly impregnable moat that is not only attractive to all of the businesses competing to be consumer touchpoints — thus increasing Amazon’s addressable market — but is also one that sees its moat deepen the larger it becomes.

Shopify’s Predicament and Amazon’s Opportunity

The reason this announcement is so damaging to Shopify goes back to the transformation in the company’s revenue I charted above: Amazon’s shipping solution requires the customer to pay with Amazon; I love Shop Pay’s checkout process, but it’s not as if I don’t have an Amazon account with all of my relevant details already included, and I absolutely trust Amazon’s shipping more than I do whatever option some Shopify merchant offers me. If I had a choice I’m taking the Amazon option every time.

Granted, I may not be representative; I’m a bit of a special case given where I live. What is worth noting, though, is that every transaction that Amazon processes is one not processed by Shopify, which again, is the company’s primary revenue driver. Moreover, the more volume that Amazon processes, the more difficult it will be for Shopify to get their own shipping solution to scale. This endangers the company’s current major initiative.

That is why I think the company needs to think more deeply than ever about advertising: the implication of Amazon being willing to be a services provider and not necessarily an Aggregator is that Amazon is surrendering some number of customer touchpoints to competitors; to put it another way, Amazon is actually making competitive customer touchpoints better — touchpoints that Shopify controls. Shopify ought to leverage that control.

That noted, there is a potential wrench in this plan: if Shopify doesn’t own payment processing, will they have sufficient data to build a competitive conversion-data-driven advertising product? Amazon — and Apple — would likely argue that that data is Amazon’s, but the merchant will obviously know what is going on (by the same token, will Amazon be able to tie this off-platform conversion data back to its own advertising product? It’s not clear what would stop them).

Shopify has two additional saving graces:

  • First, the fact that Amazon will be able to collect data is a big reason for many merchants not to use Amazon’s new offering. Shopify’s offering will always be differentiated in this regard.
  • Second, as the announcement noted, this is going to take Amazon a year or two to fully roll out, and lots of stuff can change in the meantime.

Moreover, while AWS has always been excellent at serving external customers — which it did before Amazon.com ever actually moved over — Amazon’s off-Amazon.com merchant offerings have never been particularly successful (including the aforementioned Webstores).

With that in mind, I think it’s meaningful that “Buy With Prime” is the first major initiative of new CEO Andy Jassy’s regime; I don’t think it’s an accident that it is so clearly inspired by AWS. AWS’s strength is its focus on infrastructure at scale; successfully moving e-commerce beyond aggregation to the same type of service business model would put his stamp on the company in a meaningful way, and, contra that quote in Bloomberg Businessweek, mark Jassy as nobody’s fool.

Back to the Future of Twitter

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Elon Musk wrote in a letter to Twitter’s board:

I invested in Twitter as I believe in its potential to be the platform for free speech around the globe, and I believe free speech is a societal imperative for a functioning democracy.

However, since making my investment I now realize the company will neither thrive nor serve this societal imperative in its current form. Twitter needs to be transformed as a private company.

As a result, I am offering to buy 100% of Twitter for $54.20 per share in cash, a 54% premium over the day before I began investing in Twitter and a 38% premium over the day before my investment was publicly announced. My offer is my best and final offer and if it is not accepted, I would need to reconsider my position as a shareholder.

Twitter has extraordinary potential. I will unlock it.

The vast majority of commentary about the Musk-Twitter saga has focused on the first three paragraphs: what does Musk mean by making Twitter more free speech oriented? Why doesn’t Musk believe he can work with the current board and management? Does Musk have the cash available to buy Twitter, and would the Twitter board accept his offer (no on the latter, but more on this below)?

The most interesting question of all, though, is the last paragraph: what potential does Musk see, and could he unlock it? For my part, not only do I agree the potential is vast, but I do think Musk could unlock it — and that itself has implications for the preceding paragraphs.

What is Twitter?

It’s popular on Twitter to point to a funny tweet or exchange and marvel that “This website is free“, or alternatively, “This app is free“. That raises the question, though, what is Twitter: is it a website or an app, or something different?

The answer, of course, is “All of the above”, but it’s worth being clear about the different pieces that make up Twitter; “Jin” made this illustration on Medium:

Twitter's architecture

Twitter is actually a host of microservices, including a user service (for listing a user’s timeline), a graph service (for tracking your network), a posting service (for posting new tweets), a profile service (for user profiles), a timeline service (for presenting your timeline), etc.; the architecture to tie all of these together and operate at scale all around the world is suitably complex.

The key thing to note, though, is that only the green boxes in the diagram above are actually user-facing; a dramatically simplified version of Twitter, that condenses all of those internal services to a big blue “Twitter” box and focuses on the green interfaces might look something like this:

A dramatic over-simplification of Twitter's architecture

Again, this is a dramatic oversimplification, but the important takeaway is that the user-facing parts of Twitter are distinct from — and, frankly, not very pertinent to — the core Twitter service.

Twitter’s API Drama

The general idea behind a services architecture is that various functionalities are exposed via application programming interfaces, more commonly known as APIs; a “client” will leverage these APIs to build an end user experience. There is no requirement that these clients be owned or managed by the centralized service, and for the first several years of Twitter’s existence, that is exactly how the service operated: Twitter the company ran the service and the Twitter.com website, while third-parties built clients that let you access Twitter first on the desktop and then on smartphones.

Mobile was an absolute boon for Twitter: the public messaging service, modeled on SMS, was a natural fit for a smartphone screen, and the immediacy of Twitter updates was perfectly suited to a device that was always connected to the Internet. The explosion in mobile usage, though, led to a situation where Twitter didn’t actually control the user experience for a huge portion of its users. This actually led to a ton of innovation: Twitterrific, for example, the earliest third party client, came up with the Twitter bird, the term “tweet” for a Twitter message, and early paradigms around replies and conversations. It also led to problems, the solutions to which fundamentally changed Twitter’s potential as a business.

The first problem that came from Twitter the service relying on third party clients is that the company, which descended into politics and backstabbing from the board level on down almost immediately, was drifting along without a business model; the obvious candidate was advertising, but the easiest way to implement advertising was to control the user interface (and thus insert ads — ads, including promoted tweets, are another distinct service from Twitter itself). Thus Twitter bought Tweetie, widely regarded as the best Twitter mobile client (I was a user), in April 2010, and rebranded and relaunched it as the official Twitter for iPhone app a month later.

The second problem is that starting in 2010, a Silicon Valley entrepreneur named Bill Gross (who invented search advertising) started trying to build his own Twitter monetization product called TweetUp; when Twitter acquired Tweetie and made clear they were going to monetize it via advertising, Gross started buying up multiple other third party Twitter clients with the idea of creating a competing network of clients that would monetize independently. Twitter responded in the short term by kicking several of Gross’s clients off of the platform for dubious terms-of-service violations, and in the long term by killing the 3rd party API for everyone. Clients could keep the users they had but could only add 100,000 more users — ever.

The net result of these two decisions was that Twitter, its architecture notwithstanding, would be a unified entity where Twitter the company controlled every aspect of the experience, and that that experience would be monetized via advertising.

Twitter’s Reality

Twitter has, over 19 different funding rounds (including pre-IPO, IPO, and post-IPO), raised $4.4 billion in funding; meanwhile the company has lost a cumulative $861 million in its lifetime as a public company (i.e. excluding pre-IPO losses). During that time the company has held 33 earnings calls; the company reported a profit in only 14 of them.

Given this financial performance it is kind of amazing that the company was valued at $30 billion the day before Musk’s investment was revealed; such is the value of Twitter’s social graph and its cultural impact: despite there being no evidence that Twitter can even be sustainably profitable, much less return billions of dollars to shareholders, hope springs eternal that the company is on the verge of unlocking its potential. At the same time, these three factors — Twitter’s financials, its social graph, and its cultural impact — get at why Musk’s offer to take Twitter private is so intriguing.

Start with the financials: Twitter’s business stinks. Yes, you can make an argument that this is due to mismanagement and poor execution — who enjoys seeing a stale promoted tweet about something that happened weeks ago?1 — but I have also made the argument that Twitter just isn’t well suited to direct response advertising in particular:

Think about the contrast between Twitter and Instagram; both are unique amongst social networks in that they follow a broadcast model: tweets on Twitter and photos on Instagram are public by default, and anyone can follow anyone. The default medium, though, is fundamentally different: Twitter has photos and videos, but the heart of the service is text (and links). Instagram, on the other hand, is nothing but photos and video (and link in bio).

The implications of this are vast. Sure, you may follow your friends on both, but on Twitter you will also follow news breakers, analysts, insightful anons, joke tellers, and shit posters. The goal is to mainline information, and Twitter’s speed and information density are unparalleled by anything in the world. On Instagram, though, you might follow brands and influencers, and your chief interaction with your friends is stories about their Turkey Day exploits. It’s about aspiration, not information, and the former makes a lot more sense for effective advertising.

It’s more than just the medium though; it’s about the user’s mental state as well. Instagram is leisurely and an escape, something you do when you’re procrastinating; Twitter is intense and combative, and far more likely to be tied to something happening in the physical world, whether that be watching sports or politics or doing work:

Instagram is a lean-back experience; on Twitter you lean forward

This matters for advertising, particularly advertising that depends on a direct response: when you are leaning back and relaxed why not click through to that Shopify site to buy that knick-knack you didn’t even know you needed, or try out that mobile game? When you are leaning forward, though, you don’t have either the time or the inclination.

That article made the argument for Twitter to move towards more of a subscription offering; that may be the wrong idea, but the bigger takeaway is that what Twitter has been trying to build for years just isn’t working, and the challenges aren’t just bad management. To put it another way, when it comes to Twitter’s business, there really isn’t much to lose, but Twitter could only risk losing what there is if it were a private company, free from the glare of public markets who, for very justifiable reasons, give Twitter’s management a very short leash.

What is valuable is that social graph: while Facebook understands who you know, Twitter, more than any other company, understands what its users are interested in. That is, in theory, much more valuable; said value is diminished by the fact that Twitter just doesn’t have that many users, relatively speaking; the users it has, though, are extremely influential, particularly given the important of Twitter in media, tech, and finance. For this group Twitter is completely irreplaceable: there is no other medium with a similar density of information or interest-driven network effects.

This, by extension, drives Twitter’s cultural impact: no, most people don’t get their news off of Twitter; the places they get their news, though, are driven by Twitter. Moreover, Twitter not only sets the agenda for media organizations, it also harmonizes coverage, thanks to a dynamic where writers, unmoored from geographic constraints or underlying business realities of their publications, end up writing for other writers on Twitter, oftentimes radicalizing each other in plain sight of their readership. Twitter itself is part of this harmonization, going so far as to censor politically impactful stories in the weeks before an election; it’s no surprise that when Musk says he wants to impose a stronger free speech ethos that the reaction is fierce and littered with motte-and-baileys (“actually we just care about limiting abuse and spam!”).

Back to the Future

This is all build-up to my proposal for what Musk — or any other bidder for Twitter, for that matter — ought to do with a newly private Twitter.

  • First, Twitter’s current fully integrated model is a financial failure.
  • Second, Twitter’s social graph is extremely valuable.
  • Third, Twitter’s cultural impact is very large, and very controversial.

Given this, Musk (who I will use as a stand-in for any future CEO of Twitter) should start by splitting Twitter into two companies.

  • One company would be the core Twitter service, including the social graph.
  • The other company would be all of the Twitter apps and the advertising business.

TwitterAppCo would contract with TwitterServiceCo to continue to receive access to the Twitter service and social graph; currently Twitter earns around $13/user/year in advertising, so you could imagine a price of say $7.50/user/year, or perhaps $0.75/user/month. TwitterAppCo would be free to pursue the same business model and moderation policies that Twitter is pursuing today (I can imagine Musk sticking with TwitterServiceCo, and the employees upset about said control being a part of TwitterAppCo).

However, that relationship would not be exclusive: TwitterServiceCo would open up its API to any other company that might be interested in building their own client experience; each company would:

  • Pay for the right to get access to the Twitter service and social graph.
  • Monetize in whatever way they see fit (i.e. they could pursue a subscription model).
  • Implement their own moderation policy.

This last point would cut a whole host of Gordian Knots:

  • Market competition would settle the question about whether or not stringent moderation is an important factor in success; some client experiences would be heavily moderated, and some wouldn’t be moderated at all.
  • The fact that everyone gets access to the same Twitter service and social graph solves the cold start problem for alternative networks; the reason why Twitter alternatives always fail is because Twitter’s network effect is so important.
  • TwitterServiceCo could wash its hands of difficult moderation decisions or tricky cultural issues; the U.S. might have a whole host of Twitter client options, while Europe might be more stringent, and India more stringent still. Heck, this model could even accommodate a highly-censored China client (although this is highly unlikely).

I strongly suspect that a dramatic increase in competition amongst Twitter client services would benefit TwitterServiceCo, growing its market in a way that hasn’t happened in years. What is most exciting, though, is the potential development of new kinds of services that don’t look like Twitter at all.

Step back a moment and think about the fundamental infrastructure of the Internet: we have a media protocol in HTTP/web, and a communications protocol in SMTP/email; what is missing is a notifications protocol. And yet, at the same time, if there is one lesson from mobile, it is just how important notifications are; a secondary consideration is how important identity is. If you can know how to reach someone, and have the means to do so, you are set, whether you be a critical service, an advertiser, or anything in-between. Twitter has the potential to fill that role: the ability to route short messages to a knowable endpoint accessible via a centralized directory has far more utility than political signaling and infighting. And yet, thanks to Twitter’s early decisions and lack of leadership, the latter is all the service is good for; no wonder user growth and financial results have stagnated!

A truly open TwitterServiceCo has the potential to be a new protocol for the Internet — the notifications and identity protocol; unlike every other protocol, though, this one would be owned by a private company. That would be insanely valuable, but it is a value that will never be realized as long as Twitter is a public company led by a weak CEO and ineffective board driving an integrated business predicated on a business model that doesn’t work.

Twitter’s Reluctance

The surest evidence of the Twitter board’s lack of imagination and ineffectiveness is that their response to Musk’s proposal is to further dilute existing shareholders as a means of denying Musk control. This is, in my estimation, clearly against the interest of Twitter shareholders (which, for what it’s worth, don’t in any meaningful way include Twitter’s board members); given Twitter’s performance over the last decade, though, this isn’t really a surprise.

Indeed, when you consider the fact that Twitter’s board members not only don’t own much of Twitter, but famously, barely use Twitter at all, it is easy to wonder if the actual goal is not financial results but rather harnessing that immense cultural impact. This suspicion only intensifies when you consider that the bidder in this case is one of the most successful entrepreneurs of all time: if there was one person in the world who could realize Twitter’s latent value, wouldn’t Musk be at the top of the list? And yet he is anathema, not for his business acumen, but despite it.

This, more than anything, makes me even more sure that my proposal for competition amongst Twitter client companies is essential: not only do I think that more competition would lead to dramatically more innovation, but it would also solve the problem of who decides what we see by undoing the centralization of that power and subjecting decisions to market forces. That this is unacceptable to some says more about their ultimate motivations than anything else.

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

  1. A friend sent me this promoted tweet on April 15, almost a full month since Kentucky had been eliminated from March Madness, and well over a week after the entire tournament had ended ↩

DALL-E, the Metaverse, and Zero Marginal Content

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Last week OpenAI released DALL-E 2, which produces (or edits) images based on textual prompts; this Twitter thread from @BecomingCritter has a whole host of example output, including Teddy bears working on new AI research on the moon in the 1980s:

Teddy bears working on new AI research on the moon in the 1980s

A photo of a quaint flower shop storefront with a pastel green and clean white facade and open door and big window:

A photo of a quaint flower shop storefront with a pastel green and clean white facade and open door and big window

And, in the most on-the-nose example possible, A human basking in the sun of AGI utopia:

A human basking in the sun of AGI utopia]

OpenAI has a video describing DALL-E on its website:

While the video does mention a couple of DALL-E’s shortcomings, it is quite upbeat about the possibilities; some excerpts:

Dall-E 2 is a new AI system from OpenAI that can take simple text descriptions like “A koala dunking a basketball” and turn them into photorealistic images that have never existed before. DALL-E 2 can also realistically edit and re-touch photos…

DALL-E was created by training a neural network on images and their text descriptions. Through deep learning it not only understands individual objects like koala bears and motorcycles, but learns from relationships between objects, and when you ask DALL-E for an image of a “koala bear riding a motorcycle”, it knows how to create that or anything else with a relationship to another object or action.

The DALL-E research has three main outcomes: first, it can help people express themselves visually in ways they may not have been able to before. Second, an AI-generated image can tell us a lot about whether the system understands us, or is just repeating what it’s been taught. Third, DALL-E helps humans understand how AI systems see and understand our world. This is a critical part of developing AI that’s useful and safe…

What’s exciting about the approach used to train DALL-E is that it can take what it learned from a variety of other labeled images and then apply it to a new image. Given a picture of a monkey, DALL-E can infer what it would look like doing something it has never done before, like paying its taxes while wearing a funny hat. DALL-E is an example of how imaginative humans and clever systems can work together to make new things, amplifying our creative potential.

That last line may raise some eyebrows: at first glance DALL-E looks poised to compete with artists and illustrators; there is another point of view, though, where DALL-E points towards a major missing piece in a metaverse future.

Games and Medium Evolution

Games have long been on the forefront of technological development, and that is certainly the case in terms of medium. The first computer games were little more than text:

A screenshot from Oregon Trail

Images followed, usually of the bitmap variety; I remember playing a lot of “Where in the world is Carmen San Diego” at the library:

A screenshot from "Where in the world is Carmen San Diego"

Soon games included motion as you navigated a sprite through a 2D world; 3D followed, and most of the last 25 years has been about making 3D games ever more realistic. Nearly all of those games, though, are 3D images on 2D screens; virtual reality offers the illusion of being inside the game itself.

Still, this evolution has had challenges: creating ever more realistic 3D games means creating ever more realistic image textures to decorate all of those polygons; this problem is only magnified in virtual reality. This is one of the reasons even open-world games are ultimately limited in scope, and gameplay is largely deterministic: it is through knowing where you are going, and all of your options to get there, that developers can create all of the assets necessary to deliver an immersive experience.

That’s not to say that games can’t have random elements, above and beyond roguelike games that are procedurally generated: the most obvious way to deliver an element of unpredictability is for humans to play each other, albeit in well-defined and controlled environments.

Social and User-Generated Content

Social networking has undergone a similar medium evolution as games, with a two-decade delay. The earliest forms of social networking on the web were text-based bulletin boards and USENET groups; then came widespread e-mail, AOL chatrooms, and forums. Facebook arrived on the scene in the mid-2000s; one of the things that helped it explode in popularity was the addition of images. Instagram was an image-only social network that soon added video, which is all that TikTok is. And, over the last couple of years in particular, video conferencing through apps like Zoom or Facetime have delivered 3D images on 2D screens.

Still, medium has always mattered less for social networking, just because the social part of it was so inherently interesting. Humans like communicating with other humans, even if that requires dialing up a random BBS to download messages, composing a reply, and dialing back in to send it. Games may be mostly deterministic, but humans are full of surprises.

Moreover, this means that social networking is much cheaper: instead of the platform having to generate all of the content, users generate all of the content themselves. This makes it harder to get a new platform off of the ground, because you need users to attract users, but it also makes said platform far stickier than any game (or, to put it another way, the stickiest games have a network effect of their own).

Feeds and Algorithms

The first iterations of social networking had no particular algorithmic component other than time: newer posts were at the top (or bottom). That changed with Facebook’s introduction of the News Feed in 2006. Now instead of visiting all of your friends’ pages you could simply browse the feed, which from the very beginning made decisions about what content to include, and in what order.

Over time the News Feed evolved from a relatively straightforward algorithm to one driven by machine learning, with results so inscrutable that it took Facebook six months to fix a recent rankings bug. The impact has been massive: not just Facebook but also Instagram saw huge increases in engagement and increased growth the better their algorithmically-driven feeds became; it was also great for monetization, as the same sort of signals that decided what content you saw also influenced what ads you were presented.

However, the reason why this discussion of algorithmically-driven feeds is in a different section than social networking is because the ultimate example of their power isn’t a social network at all: it’s TikTok. TikTok, of course, is all user-generated content, but the crucial distinction from Facebook is that you aren’t limited to content from your network: TikTok pulls in the videos it thinks you specifically are most interested in from across its entire network. I explained why this was a blindspot for Facebook in 2020:

What is interesting to point out is why it was inevitable that Facebook missed this: first, Facebook views itself first-and-foremost as a social network, so it is disinclined to see that as a liability. Second, that view was reinforced by the way in which Facebook took on Snapchat. The point of The Audacity of Copying Well is that Facebook leveraged Instagram’s social network to halt Snapchat’s growth, which only reinforced that the network was Facebook’s greatest asset, making the TikTok blindspot even larger.

TikTok combines the zero cost nature of user-generated content with a purely algorithmic feed that is divorced from your network; there is a network effect, in that TikTok needs lots of content to choose from, but it doesn’t need your specific network.

The Machine Learning Metaverse

I get that metaverses were so 2021, but it strikes me that the examples from science fiction, including Snow Crash and Ready Player One, were very game-like in their implementation. Their virtual worlds were created by visionary corporations or, in the case of the latter, a visionary developer who also included a deterministic game for ultimate ownership of the virtual world. Yes, third parties could and did build experiences with strong social components, most famously Da5id’s Black Sun club in Snow Crash, but the core mechanic — and the core economics — were closer to a multi-player game than anything else.

That, though, is exceptionally challenging in the real world: remember, creating games, particularly their art, is expensive, and the expense increases the more immersive the experience is. Social media, on the other hand, is cheap because it uses user-generated content, but that content is generally stuck on more basic mediums — text, pictures, and only recently video. Of course that content doesn’t necessarily need to be limited to your network — an algorithm can deliver anything on the network to any user.

What is fascinating about DALL-E is that it points to a future where these three trends can be combined. DALL-E, at the end of the day, is ultimately a product of human-generated content, just like its GPT-3 cousin. The latter, of course, is about text, while DALL-E is about images. Notice, though, that progression from text to images; it follows that machine learning-generated video is next. This will likely take several years, of course; video is a much more difficult problem, and responsive 3D environments more difficult yet, but this is a path the industry has trod before:

  • Game developers pushed the limits on text, then images, then video, then 3D
  • Social media drives content creation costs to zero first on text, then images, then video
  • Machine learning models can now create text and images for zero marginal cost

In the very long run this points to a metaverse vision that is much less deterministic than your typical video game, yet much richer than what is generated on social media. Imagine environments that are not drawn by artists but rather created by AI: this not only increases the possibilities, but crucially, decreases the costs.

Zero Marginal Content

There is another way to think about DALL-E and GPT and similar machine learning models, and it goes back to my longstanding contention that the Internet is a transformational technology matched only by the printing press. What made the latter revolutionary was that it drastically reduced the marginal cost of consumption; from The Internet and the Third Estate:

Meanwhile, the economics of printing books was fundamentally different from the economics of copying by hand. The latter was purely an operational expense: output was strictly determined by the input of labor. The former, though, was mostly a capital expense: first, to construct the printing press, and second, to set the type for a book. The best way to pay for these significant up-front expenses was to produce as many copies of a particular book that could be sold.

How, then, to maximize the number of copies that could be sold? The answer was to print using the most widely used dialect of a particular language, which in turn incentivized people to adopt that dialect, standardizing languages across Europe. That, by extension, deepened the affinities between city-states with shared languages, particularly over decades as a shared culture developed around books and later newspapers. This consolidation occurred at varying rates — England and France several hundred years before Germany and Italy — but in nearly every case the First Estate became not the clergy of the Catholic Church but a national monarch, even as the monarch gave up power to a new kind of meritocratic nobility epitomized by Burke.

The Internet has had two effects: the first is to bring the marginal cost of consumption down to zero. Even with the printing press you still needed to print a physical object and distribute it, and that costs money; meanwhile it costs effectively nothing to send this post to anyone in the world who is interested. This has completely upended the publishing industry and destroyed the power of gatekeepers.

The other impact, though, has been on the production side; I wrote about TikTok in Mistakes and Memes:

That phrase, “Facebook is compelling for the content it surfaces, regardless of who surfaces it”, is oh-so-close to describing TikTok; the error is that the latter is compelling for the content it surfaces, regardless of who creates it…To put it another way, I was too focused on demand — the key to Aggregation Theory — and didn’t think deeply enough about the evolution of supply. User-generated content didn’t have to be simply pictures of pets and political rants from people in one’s network; it could be the foundation of a new kind of network, where the payoff from Metcalfe’s Law is not the number of connections available to any one node, but rather the number of inputs into a customized feed.

Machine learning generated content is just the next step beyond TikTok: instead of pulling content from anywhere on the network, GPT and DALL-E and other similar models generate new content from content, at zero marginal cost. This is how the economics of the metaverse will ultimately make sense: virtual worlds needs virtual content created at virtually zero cost, fully customizable to the individual.

Of course there are many other issues raised by DALL-E, many of them philosophical in nature; there has already been a lot of discussion of that over the last week, and there should be a lot more. Still, the economic implications matter as well, and after last week’s announcement the future of the Internet is closer, and weirder, than ever.

Why Netflix Should Sell Ads

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The Information reported over the weekend that Netflix executives have told employees to keep an eye on the bottom line:

In two separate meetings over the past few weeks, Netflix executives cautioned employees to be more mindful about spending and hiring, according to three people familiar with the discussions. The comments, made at an employee town hall on Monday as well as during a management offsite held last month in Anaheim, Calif., come as the streaming giant grapples with sharply slowing subscriber growth…

Netflix has also been pondering steps that could help offset the revenue impact of the subscriber slowdown, including cracking down on people sharing the passwords to their accounts. While Netflix has long allowed such password sharing, it has become more common in the U.S. and other parts of the world than executives anticipated, the people said. This effort has been underway for about a year, however, well before the slowdown became apparent.

These are presented as two different issues, but there is a connection between them: Netflix should be hiring more people — a lot of them — and those people should be building a product that increases subscriber numbers and revenue. That product is advertising.

Netflix’s Business Model: Subscriptions

Netflix is, incredibly enough, 24 years old, and a subscription model has served the company well. Not that Netflix had much choice when it started: the company briefly sold DVDs online, before focusing exclusively on renting them; neither approach offered much surface area for advertising, and besides, the subscription model was revolutionary in its own right.

DVDs-by-mail was, from a certain perspective, inconvenient: you couldn’t simply drive to your local Blockbuster and peruse the selection; on the other hand, Netflix’s model gave you access to nearly every movie ever released, not just those in stock at your local store. The real innovation, though, was that business model: instead of paying to rent a DVD and being gouged with late fees, you could pay a set amount each month and keep the DVDs Netflix mailed to you as long as you wanted; send one back to get the next one in your queue.

Consumers loved it, and Netflix has stuck with the model even as the shift to streaming flipped their value proposition on its head: streaming is even more convenient than hopping in your car, but only a subset of content (ever-expanding, to be sure) is on Netflix. That has been more than enough to fuel Netflix’s growth; the service had 222 million subscribers at the end of 2021.

Still, as The Information noted, that number isn’t increasing as quickly as it used to. Netflix sported over 20% year-over-year subscriber growth for years (usually more than that), but hasn’t broken the 20% mark since Q4 2020; growth for the last three quarters was in the single digits. Some of that is likely due to growth that was pulled forward by the pandemic:

Netflix subscriber additions by year

The bigger problem, though, is saturation: Netflix has 75 million subscribers in the US and Canada, where there are around 132 million households. That is nearly as many subscribers as linear TV (84 million), and once you consider shared passwords, penetration may be higher. Other markets like India have more room to grow, but much lower household incomes, and Netflix’s relatively high prices have been an obstacle.

Netflix has ways to grow other than subscribers, most obviously by raising prices. The company has done just that on a mostly annual basis for eight years: in the U.S. the price of a Standard subscription (HD, 2 screens) has increased from $7.99 to $15.49. Netflix executives argue that customers don’t mind because Netflix keeps increasing the amount of content they find compelling; it’s an argument that is easier to accept when subscriber growth is up-and-to-the-right. Now the task is to keep raising prices while ensuring subscriber numbers don’t start going in the opposite direction.

Netflix’s New Initiative: Gaming

To accomplish this Netflix is not only continuing to invest in original programming, but also branching out into new kinds of content, including games. This may seem an odd idea at first: sure, Netflix is generating some new IP, but it would generally be much easier to license that IP than to become proficient at gaming. Netflix, though, believes it has a unique advantage when it comes to gaming: its business model. Chief Product Officer Greg Peters said in the company’s Q2 2021 earnings interview:

Our subscription model yields some opportunities to focus on a set of game experiences that are currently underserved by the sort of dominant monetization models and games. We don’t have to think about ads. We don’t have to think about in-game purchases or other monetization. We don’t have to think about per-title purchases. Really, we can do what we’ve been doing on the movie and series side, which is just hyper laser-focused on delivering the most entertaining game experiences that we can. So we’re finding that many game developers really like that concept and that focus and this idea of being able to put all of their creative energy into just great gameplay and not having to worry about those other considerations that they have typically had to trade off with just making compelling games.

Netflix’s gaming efforts to date have been fairly limited; the company launched with five titles in November, but the fact the company has bought three gaming studios suggests a strong appetite for more — at least amongst Netflix executives.

But what about consumers?

Netflix’s Job: TV

Consumers don’t care so much about business models; they have jobs that they want to get done, and the traditional cable bundle used to do a whole bunch of jobs: information gathering, education, sports, story-telling, escapism, background noise, and more. As I noted in The Great Unbundling, these jobs are increasingly done by completely different services: we get news on the Internet, education from YouTube, story-telling from streaming services, etc.

Netflix is obviously one of those streaming services, but the company is also investing in movies (escapism), and is increasingly the default choice when it comes to the under-appreciated “background noise” category: the service has oceans of low-brow content ready to be streamed while you are barely paying attention. This is a big reason why for many people their choice of streaming services is a matter of which service do they subscribe to in addition to Netflix.

Still, all of these jobs are about passively consuming content; from a consumer perspective gaming is something different, in that you are an active participant. To that end, it’s not clear to me why consumers would even think to consider Netflix when it comes to gaming: that’s not what the service’s job is, nor was it the job of the linear TV bundle that Netflix is helping replace.

Netflix’s Market: Attention

Then again, as founder and co-CEO Reed Hastings likes to say, Netflix’s competition is much broader than TV; Hastings wrote in the company’s Q4 letter to shareholders:

In the US, we earn around 10% of television screen time and less than that of mobile screen time. In 2 other countries, we earn a lower percentage of screen time due to lower penetration of our service. We earn consumer screen time, both mobile and television, away from a very broad set of competitors. We compete with (and lose to) Fortnite more than HBO. When YouTube went down globally for a few minutes in October, our viewing and signups spiked for that time. Hulu is small compared to YouTube for viewing time, and they are successful in the US, but non-existent in Canada, which creates a comparison point: our penetration in the two countries is pretty similar. There are thousands of competitors in this highly-fragmented market vying to entertain consumers and low barriers to entry for those with great experiences. Our growth is based on how good our experience is, compared to all the other screen time experiences from which consumers choose. Our focus is not on Disney+, Amazon or others, but on how we can improve our experience for our members.

Hastings’ point was that analysts should not be overly focused on the threat posed by other streaming services; Netflix has been fighting for attention for years. This is correct, by the way: thanks to the Internet everything from television to social networking to gaming can be delivered at zero marginal cost; the only scarce resource is time, which means attention is the only thing that needs to be competed for.

Well, that and money: companies competing for customer money need a way to communicate to customers what they have to sell and why it is compelling; that means advertising, and advertising requires attention. It follows, then, that the most effective business model in the attention economy is advertising: if customers rely on Google or Facebook to navigate the abundance of content that is the result of zero marginal costs, then it is Google and Facebook that are the best-placed to sell effective ads.

Notice, though, the trouble this Internet reality presents to Netflix: if content is abundant and attention is scarce, it’s easier to sell attention than content; Netflix’s business model, though, is the exact opposite.

Netflix’s Differentiation: Unique Content

Netflix, of course, sees this as a differentiator, and for a long time it was: linear TV had commercials, while Netflix had none. Linear TV made you wait for your favorite show, while Netflix gave you entire seasons at once. This was particularly compelling when Netflix had similar content to linear TV: why would you put up with commercials and TV schedules when you could just stream what you wanted to?

However, as more and more content has moved away from TV and to competing streaming services, differentiation is no longer based on the user experience, but rather uniqueness; on-demand no-commercials is no longer unique, but Stranger Things can only be found on Netflix.

Here Netflix’s biggest advantage is the sheer size of its subscriber base: Netflix can, on an absolute basis, pay more than its streaming competitors for the content it wants, even as its per-subscriber cost basis is lower. This advantage is only accentuated the larger Netflix’s subscriber base gets, and the more revenue it makes per subscriber; the user experience of getting to that unique content doesn’t really matter.

All of these factors make a compelling case for Netflix to start building an advertising business.

First, an advertising-supported or subsidized tier would expand Netflix’s subscriber base, which is not only good for the company’s long-term growth prospects, but also competitive position when it comes to acquiring content. This also applies to the company’s recent attempts to crack down on password sharing, and struggles in the developing world: an advertising-based tier is a much more accessible alternative.

Second, advertising would make it easier for Netflix to continue to raise prices: on one hand, it would provide an alternative for marginal customers who might otherwise churn, and on the other hand, it would create a new benefit for those willing to pay (i.e. no advertising for the highest tiers).

Third, advertising is a natural fit for the jobs Netflix does. Sure, customers enjoy watching shows without ads — and again, they can continue to pay for that — but filler TV, which Netflix also specializes in, is just as easily filled with ads.

Above all, though, is the fact that advertising is a great opportunity that aligns with Netflix’s business: while the company once won with a differentiated user experience worth paying for, today Netflix demands scarce attention because of its investment in unique content. That attention can be sold, and should be, particularly as it increases Netflix’s ability to invest in more unique content, and/or charge higher prices to its user base.

This, I will note, is an about face for me; I’ve long been skeptical that Netflix would ever sell advertising, or that they should. The former may still be warranted, particularly in light of Netflix’s gaming initiative. This feels like solipsism: Netflix’s executives think a lot about their business model, so they are looking for growth opportunities that seem to leverage said business model; I’m not convinced, though, that customers appreciate or care about the differentiation that Netflix claims to be leveraging in gaming, whereas they would appreciate lower prices for streaming, and already have the expectation for ads on TV.

Meanwhile, subscriber growth has stalled, even as the advertising market has proven to be much larger than even Google or Facebook can cover. Moreover, the post-ATT world is freeing up more money for the sort of top-of-funnel advertising that would probably be the norm on a Netflix advertising service. In short, the opportunity is there, the product is right, and the business need is pressing in a way it wasn’t previously.

Of course this would be a lot of work, and a big shift in Netflix’s well-defined value proposition; Netflix, though, has made big shifts before: the entire reason why advertising is a possibility is because Netflix is a streamer, not a DVD mailer. In that view a new (additional) business model is just another rung on Netflix’s ladder.

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

An Interview with Nvidia CEO Jensen Huang about Manufacturing Intelligence

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It took a few moments to realize what was striking about the opening video for Nvidia’s GTC conference: the complete absence of humans.

That the video ended with Jensen Huang, the founder and CEO of Nvidia, is the exception that accentuates the takeaway. On the one hand, the theme of Huang’s keynote was the idea of AI creating AI via machine learning; he called the idea “intelligence manufacting”:

None of these capabilities were remotely possible a decade ago. Accelerated computing, at data center scale, and combined with machine learning, has sped up computing by a million-x. Accelerated computing has enabled revolutionary AI models like the transformer, and made self-supervised learning possible. AI has fundamentally changed what software can make, and how you make software. Companies are processing and refining their data, making AI software, becoming intelligence manufacturers. Their data centers are becoming AI factories. The first wave of AI learned perception and inference, like recognizing images, understanding speech, recommending a video, or an item to buy. The next wave of AI is robotics: AI planning actions. Digital robots, avatars, and physical robots will perceive, plan, and act, and just as AI frameworks like TensorFlow and PyTorch have become integral to AI software, Omniverse will be essential to making robotics software. Omniverse will enable the next wave of AI.

We will talk about the next million-x, and other dynamics shaping our industry, this GTC. Over the past decade, Nvidia-accelerated computing delivered a million-x speed-up in AI, and started the modern AI revolution. Now AI will revolutionize all industries. The CUDA libraries, the Nvidia SDKs, are at the heart of accelerated computing. With each new SDK, new science, new applications, and new industries can tap into the power of Nvidia computing. These SDKs tackle the immense complexity at the intersection of computing, algorithms, and science. The compound effect of Nvidia’s full-stack approach resulted in a million-x speed-up. Today, Nvidia accelerates millions of developers, and tens of thousands of companies and startups. GTC is for all of you.

The core idea behind machine learning is that computers, presented with massive amounts of data, can extract insights and ideas from that data that no human ever could; to put it another way, the development of not just insights but, going forward, software itself, is an emergent process. Nvidia’s role is making massively parallel computing platforms that do the calculations necessary for this emergent process far more quickly than was ever possible with general purpose computing platforms like those undergirding the PC or smartphone.

What is so striking about Nvidia generally and Huang in particular, though, is the extent to which this capability is the result of the precise opposite of an emergent process: Nvidia the company feels like a deliberate design, nearly 29 years in the making. The company started accelerating defined graphical functions, then invented the shader, which made it possible to program the hardware doing that acceleration. This new approach to processing, though, required new tools, so Nvidia invented them, and has been building on their fully integrated stack ever since.

The deliberateness of Nvidia’s vision is one of the core themes I explored in this interview with Huang recorded shortly after his GTC keynote. We also touch on Huang’s background, including immigrating to the United States as a child, Nvidia’s failed ARM acquisition, and more. One particularly striking takeaway for me came at the end of the interview, where Huang said:

Intelligence is the ability to recognize patterns, recognize relationships, reason about it and make a prediction or plan an action. That’s what intelligence is. It has nothing to do with general intelligence, intelligence is just solving problems. We now have the ability to write software, we now have the ability to partner with computers to write software, that can solve many types of intelligence, make many types of predictions at scales and at levels that no humans can.

For example, we know that there are a trillion things on the Internet and the number things on the Internet is large and expanding incredibly fast, and yet we have this little tiny personal computer called a phone, how do we possibly figure out of the trillion things in the internet what we want to see on our little tiny phone? Well, there needs to be a filter in between, what people call the personalized internet, but basically an AI, a recommender system. A recommender that figures out based on the nature of the content, the characteristics of the content, the features of the content, based on your implicit and your explicit and implicit preferences, find a way through all of that to predict what you would like to see. I mean, that’s a miracle! That’s really quite a miracle to be able to do that at scale for everything from movies and books and music and news and videos and you name it, products and things like that. To be able to predict what Ben would want to see, predict what you would want to click on, predict what is useful to you. I’m talking about things that are consumer oriented stuff, but in the future it’ll be predict what is the best financial strategy for you, predict what is the best medical therapy for you, predict what is the best health regimen for you, what’s the best vacation plan for you. All of these things are going to be possible with AI.

As I note in the interview, this should ring a bell for Stratechery readers: what Huang is describing is the computing functionality that undergirds Aggregation Theory, wherein value in a world of abundance accrues to those entities geared towards discovery and providing means of navigating this world that is fundamentally disconnected from the constraints of physical goods and geography. Nvidia’s role in this world is to provide the hardware capability for Aggregation, to be the Intel to Aggregators’ Windows. That, needless to say, is an attractive position to be; like many such attractive positions, it is one that was built not in months or years, but decades.

Read the full interview with Huang here.

The Current Thing

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One of the most amazing things about the Internet is how it provides a level playing field for everyone: this post that you are reading was written by a single person, and it is just as accessible as an article written by the New York Times, or a proclamation issued by the President of the United States.

It used to be that media organizations had a big advantage by virtue of owning printing presses and delivery trucks, or broadcast licenses; celebrities and politicians would have their proclamations carried across those same mediums by virtue of their popularity or power. The same advantages applied to other areas of the economy like retail and consumer packaged goods: building physical stores is a big barrier of entry if you want to be the former, and having a large and popular set of products gave big companies access to those retail channels.

What is common to both examples was the importance of controlling physical space, but that control came with inherent limitations: a paper newspaper could not be delivered everywhere, and TV broadcasts were limited by the signal strength of broadcast towers. Stores had to be built, and packaged goods had to be stocked on shelves.

The Internet changes all of that: now articles and videos are simply digital bits, easily created and easily transmitted anywhere on the globe, effectively for free. Physical goods still need to be made, but they can be sold to anyone by anyone, and shelf space has been replaced by the commoditized cardboard box.

This first order reality, though, has had a multitude of second order effects. Newspapers, for example, were amongst the first online sites, and it seemed like a massive boon: now an article that was only accessible by those within a limited geographic area delineated by the reach of delivery trucks could be read by anyone in the world. The problem is that that same reach was available to everyone; back in 2014 I wrote in Economic Power in the Age of Abundance:1

One of the great paradoxes for newspapers today is that their financial prospects are inversely correlated to their addressable market. Even as advertising revenues have fallen off a cliff — adjusted for inflation, ad revenues are at the same level as the 1950s — newspapers are able to reach audiences not just in their hometowns but literally all over the world.

A drawing of The Internet has Created Unlimited Reach

The problem for publishers, though, is that the free distribution provided by the Internet is not an exclusive. It’s available to every other newspaper as well. Moreover, it’s also available to publishers of any type, even bloggers like myself.

A city view of Stratechery's readers in 2014

To be clear, this is absolutely a boon, particularly for readers, but also for any writer looking to have a broad impact. For your typical newspaper, though, the competitive environment is diametrically opposed to what they are used to: instead of there being a scarce amount of published material, there is an overwhelming abundance. More importantly, this shift in the competitive environment has fundamentally changed just who has economic power.

That article was one of the first articulations of the concepts undergirding Aggregation Theory, which is downstream from the shift from geographic-driven scarcity to Internet-driven abundance: now the most valuable companies in the world were those that helped users navigate abundance, whether that be via search (Google), contacts (Facebook), or retail (Amazon).

The Current Thing Meme

Most of my discussion of Aggregation Theory has been about economics and concepts like zero marginal costs; just as it doesn’t cost anything to publish, it doesn’t cost Google anything (on a marginal basis) to help every person in the world find the specific piece of content they are looking for. This, by extension, motivates publishers to work well with Google, motivates users to use Google more, and gives Google the best possible opportunity to show ads, attracting more and more advertising.

In other words, centralization is a second order effect of decentralization: when all constraints on content are removed, more power than ever accrues to the entity that is the preferred choice for navigating that content; moreover, that power compounds on itself in a virtuous feedback loop.

This dynamic, though, goes beyond economics; consider the meme that inspired the title of this Article:

This meme has, for rather obvious reasons, made a fair number of people upset, particularly to the extent it suggests that support for a country fighting for its existence in the face of a brutal invasion is somehow inauthentic. I think, though, that interpretation is too literal; after all, the meme can be extended in lots of different ways:

What I think is captured here is orthogonal to the actual issue at hand (in the case of Musk’s version, Ukraine); the entire point of the generic labeling (“The Current Thing”) is that there is a dynamic that exists independent of the issue being critiqued, and my contention in this Article is that said dynamic is Aggregation Theory for ideas.

Aggregating Ideas

Go back to the point about the explosion of content on the Internet: the first order implication is that there is an explosion of ideas; after all, anyone can publish anything. Presumably this means that there are far more categories of thought than ever before! And, if you dig deep enough into the Internet, this is true.

Most people, though, don’t dig that deep, just as they don’t dig that deep for content or contacts or commerce: it’s just far easier and more convenient to rely on Google or Facebook or Amazon. Why wouldn’t this same dynamic apply to ideas? Being informed about everything happening in the world is hard if not impossible: humans evolved to care intensely about what happened in their local environment; however, first mass media, and then the Internet, brought news from everywhere to our immediate attention.

Given that, it seems entirely reasonable — expected even — that we all outsource our intuition for what events matter, and what our position on those events should be, to the most convenient option, especially if that option has obvious moral valence. Police brutality against people of color is obviously bad; people dying from COVID is obviously bad; Russia invading Ukraine is obviously bad; why wouldn’t each of us snap into opposition to obviously bad things?

This dynamic is exactly what the meme highlights: sure, the Internet makes possible a wide range of viewpoints — you can absolutely find critics of Black Lives Matter, COVID policies, or pro-Ukraine policies — but the Internet, thanks to its lack of friction and instant feedback loops, also makes nearly every position but the dominant one untenable. If everyone believes one thing, the costs of believing something else increase dramatically, making the consensus opinion the only viable option; this is the same dynamic in which publishers become dependent on Google or Facebook, or retailers on Amazon, just because that is where money can be made.

Again, to be very clear, that does not mean the opinion is wrong; as I noted, I think the resonance of this meme is orthogonal to the rightness of the position it is critiquing, and is instead concerned with the sense that there is something unique about the depth of sentiment surrounding issues that don’t necessarily apply in any real-life way to the people feeling said sentiment.

Righteousness and Dissent

Here I think it is useful to go back to economics. The more that an entity becomes dependent on an Aggregator, the more perilous the economic outlook for said entity. If you depend on Google or Facebook for traffic, or Amazon for sales, the more liable you are to have your margin consumed by said entities. A truly sustainable business model depends on being able to connect to your customers on your own terms, not an Aggregator’s.

A similar critique can be made of ideas; I thought this tweet was very well-stated:

It is very counter-intuitive to see how “bad” ideas are in fact extremely valuable: not only do they highlight why the good ideas are better, but they also sometimes show that the “good” ideas are in fact wrong. Arguing that the earth was not the center of the universe was once a “bad” idea; it was also correct. At the same time, to think that the Catholic church of 500 years ago was the only time where the dominant mode of thinking clearly missed the mark seems exceptionally arrogant; we rightly believe that allowing room for dissidents was, in the past, a good thing. It seems clear to me that doing the same today is likely to prove more valuable than not.

Here is the problem: it turns out it was much easier to believe in the value of dissidents in a world of meaningful marginal costs for the propagation of ideas. Most people never encountered contrary opinions when spreading said opinions entailed publishing them on paper and spreading them in the physical world; on the Internet, on the other hand, bad ideas are only a search away. Moreover, the means by which to suppress those opinions are far more obvious: instead of having to shut down a printing press, one only needs to pressure those same centralized Aggregators that arose for economic reasons to suppress “wrong” speech.

The end result is a world where the ability for anyone to post any idea has, paradoxically, meant far greater mass adoption of popular ideas and far more effective suppression of “bad” ideas. That is invigorating when one feels the dominant idea is righteous; it seems reasonable to worry about the potential of said sense of righteousness overwhelming the consideration of whether particular courses of action are actually good or bad.

Moderation Frameworks

In 2019 I wrote an Article entitled A Framework for Moderation, which argued for a finely-tuned examination of the Internet stack as a driver of moderation decisions:

It makes sense to think about these positions of the stack very differently: the top of the stack is about broadcasting — reaching as many people as possible — and while you may have the right to say anything you want, there is no right to be heard. Internet service providers, though, are about access — having the opportunity to speak or hear in the first place. In other words, the further down the stack, the more legality should be the sole criteria for moderation; the further up the more discretion and even responsibility there should be for content:

A drawing of The Position In the Stack Matters for Moderation

Note the implications for Facebook and YouTube in particular: their moderation decisions should not be viewed in the context of free speech, but rather as discretionary decisions made by managers seeking to attract the broadest customer base; the appropriate regulatory response, if one is appropriate, should be to push for more competition so that those dissatisfied with Facebook or Google’s moderation policies can go elsewhere.

In this view the decision of Cogent and Lumen to cut-off backbone capacity to Russia feels like a mistake. Both companies are the very definition of infrastructure, with no user-facing presence; it follows that they should not be making any decisions based on political considerations (with Carl von Clausewitz’s observation that “war is simply the continuation of political intercourse with the addition of other means” in mind).

And yet they have cut off Russia all the same, along with a whole host of Western companies. To be very clear, I get it: what Russia is doing to Ukraine is wrong, above and beyond the significant economic challenges in serving a country hit with the most comprehensive set of sanctions in history.

At the same time, I can’t help but worry about a world where every level of the Internet stack feels empowered to act based on political considerations, and it makes me think that my Framework for Moderation was wrong. In a world of idea aggregation the push to go along with the current thing is irresistible, making any sort of sober consideration of one’s position in the stack irrelevant. The only effective counter is a blanket policy of not censoring or cutting off service under any circumstance: it’s easier to appeal to consistency than it is to make a nuanced decision that runs counter to the current thing.

That’s the thing about aggregation: one can understand how it works, and yet be powerless to resist its incentives. It seems foolhardy to think that this might be true for economics and not true for ideas, even — especially! — if we are sure they are correct.

  1. The image in the excerpt is from 2014; the updated view of the last thirty days is broadly similar, but there has been a big relative increase in Washington DC, Los Angeles, India, and Singapore. ↩

Tech and War

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While it has been only 11 days since Russia invaded Ukraine, it is already clear that the long-term impact on the tech industry is going to be substantial. The goal of this Article is to explore what those implications might be.

Let me start with some caveats:

  • First, while I presume it goes without saying, I condemn Russia’s invasion of Ukraine in the strongest possible terms.
  • Second, the situation is obviously extremely fluid. My goal is to write about impacts that seem likely to endure, but some issues, particularly those involving China, could shift considerably.
  • Third, the long-term is inherently difficult to predict. Nearly every major event that has has happened over the last several years, from Donald Trump’s election, to COVID, to this invasion, was not only not anticipated by most people, but was in fact dismissed even after there were signs in place that they might occur. So take all of this with the appropriate grain of salt.

The most important thing to make clear about this Article, though, is that much of it is focused on capabilities, not intentions. In much of our daily life we rely on the good intentions of others, even if they have dangerous capabilities. One mundane example is traffic on a two-way street: oncoming cars have the capability of swerving into my lane and hitting me head-on; I trust that they do not intend to do so. There are a whole host of similar examples, for good reason: societies that trust each other’s intentions function much more smoothly and efficiently; no one wants every single street to be built with concrete dividers between traffic.

In an ideal world international relations would work the same way, and there is an argument that much of the prosperity of the last few decades has been driven by the sort of increased trust and interconnectedness that comes from assuming the good intentions of other countries — or at a minimum enlightened self-interest — leading to increased economic efficiency for everyone engaged in global trade. In this arena, though, the question of capabilities is never far from the surface: what can one country do to another, should the intentions of the first country change, and what must the second country do to ameliorate that risk? And here there is very much a tech angle.

Public Versus Private Sanctions

In response to the invasion Western governments unleashed an unprecedented set of sanctions on Russia; these sanctions were primarily financial in nature, and included:

  • Disconnecting sanctioned Russian banks from the SWIFT international payment system
  • Cutting off the Russian Central Bank from foreign currency reserves held in the West
  • Identifying and freezing the assets of sanctioned Russian individuals

The sanctions, which were announced last weekend, led to the crashing of the ruble and the ongoing closure of the Russian stock market, and are expected to wreak havoc on the Russian economy; now the U.S. and E.U. are discussing banning imports of Russian oil.

This Article is not about those public sanctions, by which I mean sanctions coming from governments (Noah Smith has a useful overview of their impact here); what is interesting to me is the extent to which these public sanctions have been accompanied by private sanctions by companies, including:

This is an incomplete list! The key thing to note, though, is few if any of these actions were required by law; they were decisions made by individual companies.

This, though, is where the intentions versus capabilities distinction arises, in two different respects:

  • First, the public/private distinction that I just noted may not be so apparent to people outside of the U.S. or the West generally; one could certainly understand how other countries might interpret this collection of public and private sanctions as being different parts of a single whole. To that end, this collection of actions demonstrates the capability of effectively wiping an economy off of the map.
  • Second, to the extent that the public/private distinction is understood, it highlights the capability of private companies to impose sanctions, and their willingness to do so in pursuit of political goals — even if those political goals are to stop an unjust invasion and save lives.

I suspect that both of these interpretations matter and will have long-reaching effects, in part because they are not a new trend, but a continuation of an ongoing one.

Internet 3.0 and the Rise of Politics

Last January I wrote an article entitled Internet 3.0 and the Beginning of (Tech) History that argued that technology broadly has passed through two eras: 1.0 was the technological era, and 2.0 was the economic era.

The technological era was defined by the creation of the technical building blocks and protocols that undergird the Internet; there were few economic incentives beyond building products that people might want to buy, in part because few thought there was any money to be made on the Internet. That changed during the 2000s, as it became increasingly clear that the Internet provided massive returns to scale in a way that benefited both Aggregators and their customers. I wrote:

Google was founded in 1998, in the middle of the dot-com bubble, but it was the company’s IPO in 2004 that, to my mind, marked the beginning of Internet 2.0. This period of the Internet was about the economics of zero friction; specifically, unlike the assumptions that undergird Internet 1.0, it turned out that the Internet does not disperse economic power but in fact centralizes it. This is what undergirds Aggregation Theory: when services compete without the constraints of geography or marginal costs, dominance is achieved by controlling demand, not supply, and winners take most.

Aggregators like Google and Facebook weren’t the only winners though; the smartphone market was so large that it could sustain a duopoly of two platforms with multi-sided networks of developers, users, and OEMs (in the case of Android; Apple was both OEM and platform provider for iOS). Meanwhile, public cloud providers could provide back-end servers for companies of all types, with scale economics that not only lowered costs and increased flexibility, but which also justified far more investments in R&D that were immediately deployable by said companies.

There is no economic reason to ever leave this era, which leads many to assume we never will; services that are centralized work better for more people more cheaply, leaving no obvious product vector on which non-centralized alternatives are better. The exception is politics, and the point of that Article was to argue that we were entering a new era: the political era.

Go back to the two points I raised above:

  • If a country, corporation, or individual assumes that the tech platforms of another country are acting in concert with their enemy, they are highly motivated to pursue alternatives to those tech platforms even if those platforms work better, are more popular, are cheaper, etc.
  • If a country, corporation, or individual assumes that tech platforms are themselves engaged in political action, they are highly motivated to pursue alternatives to those tech platforms even if those platforms work better, are more popular, are cheaper, etc.

Again, just to be crystal clear, these takeaways are true even if the intentions are pure, and the actions are just, because the question at hand is not about intentions but about capabilities. And while I get it can be hard to appreciate that distinction in the case of a situation like Ukraine, it’s worth noting that similar takeaways could be drawn from de-platforming controversies after January 6 and the attempts to control misinformation during COVID; if anything the fact that there are multiple object lessons in recent history of the willingness of platforms to both act in concert with governments and also of their own volition emphasizes the fact that from a realist perspective capabilities matter more than intentions, because the willingness to exercise those capabilities (to a widely varying degree, to be sure) has not been constrained to a single case.

India and Sanctions

The two countries where these questions are likely to loom largest are China and India.

Start with the latter: India is widely considered the most important long-term growth market for a whole host of tech companies, thanks to its massive population that is only just now coming online, combined with a growing economy that, to the extent it can follow a similar path to China, promises more opportunity than anywhere else in the world. In the economic era it has made perfect sense for India to be a core market for Google, Facebook, Amazon, etc.

It was India, though, that raised some of the most strident objections to Twitter and Facebook’s decision to take down President Trump’s accounts after January 6, with several politicians pointing out that tech executives in San Francisco could do the same to them; in the case of the Ukraine invasion India is staying neutral, thanks in part to its significantly longer-term relationship with Russia, particularly from a military perspective. That makes it all-the-more likely that the aforementioned private sanctions are being interpreted in terms of capabilities, not intentions, clouding the long-term prospects of those tech companies counting on India for growth.

It’s important to note that this isn’t an abstract idea for India: the country’s nuclear program was started in response to India’s defeat in the 1962 Sino-Indian War, but the country’s first nuclear test in 1974 led to sanctions from the United States, as did far more extensive tests in 1998. The United States also sailed a fleet into the Bay of Bengal during a conflict with Pakistan in 1971, shortly after India signed a treaty with the USSR, and the fleet was there to oppose India, not to support it. This matters not because it excuses India’s neutrality in the current conflict, but to explain why these private sanctions from U.S. tech companies may have different interpretations and unintended consequences in a market they were counting on.

China is in a very different position, thanks to the long-run effects of the Great Firewall: U.S. consumer services companies obviously can’t sanction China, because China has already blocked them and built its own alternatives (one does wonder to what extent Moscow and perhaps even New Delhi look at the Great Firewall with jealousy). China’s problem — and potentially the West’s opportunity — lies with a far more fundamental piece of technology: semiconductors.

Semiconductors and China

China’s leading semiconductor foundry is the Semiconductor Manufacturing International Corporation — SMIC for short. While the majority of SMIC’s volume is on older 55nm and 65nm process nodes, the company has a sizable and growing business at the extremely popular 28nm node. The company has also recently started mass production of 14nm and has demonstrated the ability to build 7nm chips. Even so, the most cutting edge companies in China have long been used to buying their chips abroad, whether that be Intel chips for servers or contracting with TSMC for everything else.

The Trump administration took square aim at both vectors: in the case of the latter all American chip companies and companies that relied on American technology — which is to say, all of them, including TSMC — were barred from selling to Huawei, effectively killing the company’s smartphone business and severely damaging its telecom business. SMIC, meanwhile, has been barred from acquiring ASML’s cutting-edge extreme ultroviolet (EUV) lithography machines, which are essential for building 7nm and below chips cost-effectively.

What is notable in terms of this conflict is that China has given every appearance of supporting Russia (although the country, like India, abstained from the United Nations motion to condemn Russia’s invasion). The big question in terms of Russian sanctions is just how far this support will go: on the one hand, working with Russia risks sanctions in the West, which is a much larger market for China; this is a big deterrent for SMIC, which has a big opportunity to undercut TSMC in price on trailing edge nodes. Seizing that opportunity means sanctioning Russia; from Bloomberg:

Washington is expected to lean on major Chinese companies from Semiconductor Manufacturing International Corp. to Lenovo Group Ltd. to join U.S.-led sanctions against Russia, aiming to cripple the country’s ability to buy key technologies and components. China is Russia’s biggest supplier of electronics, accounting for a third of its semiconductor imports and more than half of its computers and smartphones. Beijing has opposed the increasingly severe measures that the U.S. has taken to restrict Russia’s trade and economy in response to its invasion of Ukraine, however U.S. officials expect tech suppliers such as SMIC to uphold the new rules and curtail trade of sensitive technology with American origin, especially as it relates to Russia’s defense sector.

Any items produced with certain U.S. inputs, including American software and designs, are subject to the ban, even if they are made overseas, a U.S. official told Bloomberg News on Monday. Companies that attempt to evade these new controls would face the prospect of themselves being cut off from U.S.-origin technology and corporate executives risk going to jail for violations…Beijing has made self-sufficiency in the semiconductor sector a national priority, but for now its tech companies still rely heavily on U.S. designs and technology. SMIC continues to use chipmaking equipment from American vendors including Applied Materials Inc. even after it got blacklisted by the U.S. in 2020. If the company fails to comply with U.S. sanctions, it could face tightening of restrictions that may make it more difficult or impossible to secure licenses for repair parts and new equipment.

China, though, may be tempted by the prospect of resource-rich Russia being dependent on Beijing for a functioning economy, as well as the longer-term project of building economic and technical systems that are independent of the West. That could entail pushing SMIC to send chips to Russia in defiance of Western sanctions, with the thought being that short-term pain is worth the long-term gain. The risks of this approach are huge though: even if SMIC can’t get EUV, it can still get pretty far with deep ultraviolet (DUV), but the Biden administration is already pushing to cut China off from any more of those machines as well:

The chip maker, SMIC, a year ago had been added to the entity list, which restricts companies from exporting U.S.-origin technology without a license. That, however, has proven ineffective in keeping many manufacturing tools used to make semiconductors out of SMIC’s hands, the people familiar said. Under the current designation, SMIC is restricted from buying U.S. tools “uniquely required” to build chips with 10-nanometer circuits and smaller, which is close to the leading edge of semiconductor manufacturing technology. Since many manufacturing tools can be used to produce chips at a variety of sizes, exporters took the view that they were still able to sell tools that could be adjusted to produce the smaller chips and the restriction “became effectively language that means nothing,” one of the people said…

The Defense Department, with the support of officials at the State and Energy Departments, as well as the National Security Council, wants to change the wording to restrict SMIC’s access to items “capable of” producing semiconductors with 14-nanometer circuits and smaller, the people familiar said, broadening the list of items SMIC won’t be able to get.

This is context for what may be the single biggest strategic question confronting the Biden administration:

  • The U.S. has already damaged Huawei and constrained SMIC’s long-term prospects on the cutting edge, and there is a credible threat that the U.S. could further damage SMIC’s current capabilities.
  • The U.S. doesn’t simply want SMIC to not sell to Russia, it also wants broader support from China for sanctions against Russia, particularly since China almost certainly has more influence over Russian President Vladimir Putin than any other country.

The strategic choice is this:

  • The U.S. could relax sanctions on SMIC and address China’s broader semiconductor needs in exchange for cooperation on Russia, at the medium-term risk of increasing China’s technological capability (albeit with the upside of helping U.S. firms that undergird much of the semiconductor industry).
  • Alternatively, the U.S. could simply pressure China to not sell to Russia, or even ratchet up pressure on SMIC, at the short-term risk of China taking a hit to its technological industry in exchange for supporting Russia and building an alternative to the U.S.-dominated world order.

This is not an easy question, particularly in the heat of the current moment. China, not Russia, is the U.S.’s long-term strategic rival; more than that, though, is another long-term issue that very much has a semiconductor component: Taiwan.

Taiwan and Deterrence

While China has framed its refusal to condemn Russia mostly in terms of NATO expansion, it’s not hard to draw the obvious parallel to Taiwan: given that Beijing sees Taiwan as a part of China that it has the right to take back, by military means if necessary, it’s understandable why China might view Russian rhetoric about Ukraine’s historical ties to Russia with sympathy; given this, it’s possible that China is going to support Russia no matter what. Moreover, this also raises questions about the wisdom of enhancing China’s technological capabilities with American-derived technology, given the high likelihood that said enhancement will go towards increased military capabilities.

At the same time, cutting China off from TSMC has brought its own risks; I wrote in the context of Huawei in 2020:

Should the United States and China ever actually go to war, it would likely be because of Taiwan. In this TSMC specifically, and the Taiwan manufacturing base generally, are a significant deterrent: both China and the U.S. need access to the best chip maker in the world, along with a host of other high-precision pieces of the global electronics supply chain. That means that a hot war, which would almost certainly result in some amount of destruction to these capabilities, would, as the Wall Street Journal notes, be devastating:

Taiwan, China and South Korea “represent a triad of dependency for the entire U.S. digital economy,” said an influential 2019 Pentagon report on national-security considerations regarding the supply chain for microelectronics. “Taiwan, in particular, represents a single point-of-failure for most of the United States’ largest, most important technology companies,” said the report, written by Rick Switzer, who served as a senior foreign-policy adviser to an Air Force unit. He concluded that the U.S. needs to strengthen its industrial policies to address the situation.

It’s the same for China, as I noted in that Daily Update about Huawei; one of the risks of cutting China off from TSMC is that the deterrent value of TSMC’s operations is diminished. At the same time, though, Taiwan — and South Korea, for that matter, where Samsung’s most advanced fabs are located — are a whole lot closer to China than they are to the U.S., and the location of land masses is not changing, at least on a time scale that is significant to this discussion!

This point applies to semiconductors broadly: as long as China needs U.S. technology or TSMC manufacturing, it is heavily incentivized to not take action against Taiwan; when and if China develops its own technology, whether now or many years from now, that deterrence is no longer a factor. In other words, the short-term and longer-term are in opposition to the medium-term:

  • The short-term upside of relaxing sanctions against China in semiconductors in exchange for supporting sanctions against Russia is a potentially earlier end to the conflict in Ukraine.
  • The medium-term risk of giving China access to Western technology is that China develops more advanced products that could be used by its military.
  • The long-term risk of cutting China off is the development of an alternative to the West that is completely unconstrained by sanctions, public or private.

There is no obvious answer, and it’s worth noting that the historical pattern — i.e. the Cold War — is a complete separation of trade and technology. That is one possible path, that we may fall into by default. It’s worth remembering, though, that dividers in the street are no way to live, and while most U.S. tech companies have flexed their capabilities, the most impressive tech of all is attractive enough and irreplaceable enough that it could still create dependencies that lead to squabbles but not another war.

Tech Power

The most powerful takeaway from the past ten days, though, at least from a tech perspective, is related to the nuclear question. To return to India, from the Nuclear Weapons Archive:

A most telling (and often quoted) exchange between [India Prime Minister Inder Kumar] Gujral and Pres. Clinton occurred on 22 September 1997 at the occasion of the U.N. General Assembly session in New York. Gujral later recounted telling Clinton that an old Indian saying holds that Indians have a third eye. “I told President Clinton that when my third eye looks at the door of the Security Council chamber it sees a little sign that says ‘only those with economic power or nuclear weapons allowed.’ I said to him, ‘it is very difficult to achieve economic wealth’.”

The implication is that nuclear capability was a more attainable route to great nation status than was economic dominance; what, then, to make of an industry that can, via private sanction, destroy economic wealth above and beyond government action? The capability wielded by the tech industry is incredible; it is easy to cheer when it is being used in the service of intentions that are so clearly good. It’s equally easy to understand how much fear that capability may generate in the long run.

Shopify’s Evolution

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Tobi Lütke, who famously started Shopify when he realized that the software he built to run his snowboard shop was a much bigger opportunity than the shop itself, was reminiscing on Twitter about how cheap it used to be to run digital advertising:

This isn’t just a fun story: it’s a critical insight into the conditions that enabled Shopify to become the company that it is today; understanding how those conditions have changed give insight into what Shopify needs to become.

Shopify’s Evolution

Back in 2004 a lot of the pieces that were necessary to run an e-commerce site existed, albeit in rudimentary and hard-to-use forms. One could, with a bit of trouble, open a merchant account and accept credit cards; 3PL warehouses could hold inventory; UPS and Fedex could deliver your goods. And, of course, you could run really cheap ads on Google. What was missing was software to tie all of those pieces together, which is exactly what Lütke built for Snowdevil, his snowboard shop, and in 2006 opened up to other merchants; the software’s name was called Shopify:

Shopify started as the center of multiple third party services

This idea of Shopify as the hub for an e-commerce shop is one that has persisted to this day, but over the ensuing years Shopify has added on platform components as well; a platform looks like this (from The Bill Gates Line):

A drawing of Platform Businesses Attract Customers by Third Parties

The first platform was the Shopify App Store, launched in 2009, where developers could access the Shopify API and create new plugins to deliver specific functionality that merchants might need. For example, if you want to offer a product on a subscription basis you might install Recharge Subscriptions; if you want help managing your shipments you might install ShipStation. Shopify itself delivers additional functionality through the Shopify App Store, like its Facebook Channel plugin, which lets you easily sync your products to Facebook to easily manage your advertising.

A year later Shopify launched the Shopify Theme Store, where merchants could buy a professional theme to make their site their own; now the hub looked like this:

Shopify added two platforms for apps and themes

At the same time Shopify also vertically integrated to incorporate features it once left to partners; the most important of these integrations was Shopify Payments, which launched in 2013 and was rebranded as Shop Pay in 2020. Yes, you could still use a clunky merchant account, but it was far easier to simply use the built-in Shop Pay functionality. Shop Pay was also critical in that it was the first part of the Shopify stack to build a consumer brand: users presented with a myriad of payment options know that if they click the purple Shop Pay button all of their payment and delivery information will be pre-populated, making it possible to buy with just one additional tap.

Shopify integrated into payments with Shop Pay

Even with this toehold in the consumer space, though, Shopify has remained a company that is focused first-and-foremost on its merchants and its mission to “help people achieve independence by making it easier to start, run, and grow a business.” That independence doesn’t just mean one-person entrepreneurs either: good-size brands like Gymshark, Rebecca Minkoff, KKW Beauty, Kylie Cosmetics, and FIGS leverage Shopify to build brands that are independent of Amazon in particular.

Apple and Facebook

In 2020’s Apple and Facebook I explained the symbiotic relationship between the two companies when it came to the App Store:

Facebook’s early stumbles on mobile are well-documented: the company bet on web-based apps that just didn’t work very well; the company completely rewrote its iOS app even as it was going public, which meant it had a stagnating app at the exact time mobile was exploding, threatening the desktop advertising product and platform that were the basis of the company’s S-1.

The re-write turned out to be not just a company-saving move — the native mobile app had the exact same user-facing features as the web-centric one, with the rather important detail that it actually worked — but in fact an industry-transformational one: one of the first new products enabled by the company’s new app were app install ads. From TechCrunch in 2012:

Facebook is making a big bet on the app economy, and wants to be the top source of discovery outside of the app stores. The mobile app install ads let developers buy tiles that promote their apps in the Facebook mobile news feed. When tapped, these instantly open the Apple App Store or Google Play market where users can download apps.

The ads are working already. One client TinyCo saw a 50% higher click through rate and higher conversion rates compared to other install channels. Facebook’s ads also brought in more engaged users. Ads tech startup Nanigans clients attained 8-10X more reach than traditional mobile ad buys when it purchased Facebook mobile app install ads. AdParlor racked up a consistent 1-2% click through rate.

Facebook’s App Install product quickly became the most important channel for acquiring users, particularly for games that monetized with Apple’s in-app purchase API: the combination of Facebook data with developer’s sophisticated understanding of expected value per app install led to an explosion in App Store revenue. 

It’s worth underlining this point: the App Store would not be nearly the juggernaut it is today, nor would Apple’s “Services Narrative” be so compelling, were it not for the work that Facebook put in to build out the best customer acquisition engine in the industry (much to the company’s financial benefit, to be clear); Apple and Facebook’s relationship looked like this:

Apple and Facebook's symbiotic relationship

Facebook was by far the best and most efficient way to acquire new users, while Apple was able to sit back and harvest 30% of the revenue earned from those new users. Yes, some number of users came in via the App Store, but the primary discovery mechanism in the App Store is search, which relies on a user knowing what they want; Facebook showed users apps they never knew existed.

Facebook and Shopify

Facebook plays a similar role for e-commerce, particularly the independent sellers that exist on Shopify:

Shopify's dependence on Facebook

What makes Facebook’s approach so effective is that its advertising is a platform in its own right. Just as every app on a smartphone or every piece of software on a PC shares the same resources and API, every advertiser on Facebook, from app maker to e-commerce seller and everyone in-between, uses the same set of APIs that Facebook provides. What makes this so effective, though, is that the shared resources are not computing power but data, especially conversion data; I explained how this worked in 2020’s Privacy Labels and Lookalike Audiences, but briefly:

  • Facebook shows a user an ad, and records the unique identifier provided by their phone (IDFA, Identifier for Advertisers, on iOS; GAID, Google Advertising Identifer, on Android).
  • A user downloads an app, or makes an e-commerce purchase; Facebook’s SDK, which is embedded in the app or e-commerce site, again records the IDFA or notes the referral code that led the user to the site, and charges the advertiser for a successful conversion.
  • The details around this conversion, whether it be which creative was used in the ad, what was purchased, how much was spent, etc., is added to the profile of the user who saw the ad.
  • Advertisers take out new ads on Facebook asking the company to find users who are similar to users who have purchased from them before (Facebook knows this from past purchases seen by its SDK, or because an advertiser uploads a list of past customers).
  • Facebook repeats this process, further refining its understanding of customers, apps, and e-commerce offerings in the process, including the esoteric ways (only discoverable by machine learnings) in which they relate to each other.

The critical thing to understand about this process is that no one app or e-commerce seller stands alone; everyone has collectively deputized Facebook to hold all of the pertinent user data and to figure out how all of the pieces fit together in a way that lets each individual app maker or e-commerce retailer acquire new customers for a price less than what that customer is worth to them in lifetime value.

This, by extension, means that Shopify doesn’t stand alone either: the company is even more dependent on Facebook to drive e-commerce than Apple ever was to drive app installs.1 That’s why it’s not a surprise that Facebook’s recent plunge in value was preceded (and then followed) by Shopify’s own:

Shopify and Facebook's faltering stocks

Part of Shopify’s decline is likely related to the fact that it is another pandemic stock: the sort of growth the company saw while customers were stuck at home with nothing to do other than shop online couldn’t go on forever. Moreover, the company announced big increases in spending (more on this in a moment). However, the major headwind the company shares with Facebook is Apple.

ATT’s Impact

I have been writing regularly about Apple’s App Tracking Transparency (ATT) initiative since it was announced two years ago, so I won’t belabor the point; the key thing to understand is that ATT broke the Facebook advertising collective. On the app install side this was done by technical means: Apple made the IDFA an opt-in behind a scary warning about tracking, which most users declined.

The e-commerce side is more interesting: while Apple can’t technically limit what Facebook collects via its Pixel on a retailer’s website, ATT bans said broad collection all the same. To that end Facebook originally announced plans to not show the ATT prompt and abandon the IDFA; a few months later the company did an about-face announcing that it would indeed show the ATT prompt, and also limit what it collected in its in-app browser via the Facebook Pixel.

It’s unclear what happened to change Facebook’s mind; had they continued on their original path then their app advertising business would have suffered from a loss of data, but the e-commerce advertising would have been relatively unaffected (the loss of IDFA-related app install data would have decreased the amount of data available for that machine learning-driven targeting). What seems likely — and to be clear, this is pure speculation — is that Apple threatened to kick Facebook and its apps out of the App Store if it didn’t abide by ATT’s policies, even the parts that were technically unenforceable.

Regardless, the net impact is that it was suddenly impossible for Facebook to tie together all of the various pieces of that virtuous cycle I described above deterministically. Ads were hard to tie to conversions, conversions were hard to tie to users, which meant that users and advertisers were hard to tie to each other, resulting in less relevant ads for the former that cost more money for the latter.2 The monetary impact is massive: Facebook forecast a $10 billion hit to 2022 revenue, and as noted, its market value has been cut by a third.

Note, however, that ATT didn’t hurt all advertisers: companies like Google and Amazon are doing great; I explained why in Digital Advertising in 2022:

Amazon’s advertising business has three big advantages relative to Facebook’s.

  1. Search advertising is the best and most profitable form of advertising. This goes back to the point I made above: the more certain you are that you are showing advertising to a receptive customer, the more advertisers are willing to bid for that ad slot, and text in a search box will always be more accurate than the best targeting.
  2. Amazon faces no data restrictions. That noted, Amazon also has data on its users, and it is free to collect as much of it as it likes, and leverage it however it wishes when it comes to selling ads. This is because all of Amazon’s data collection, ad targeting, and conversion happen on the same platform — Amazon.com, or the Amazon app. ATT only restricts third party data sharing, which means it doesn’t affect Amazon at all.
  3. Amazon benefits from ATT spillover. That is not to say that ATT didn’t have an effect on Amazon: I noted above that Snap’s business did better than expected in part because its business wasn’t dominated by direct advertising to the extent that Facebook’s was, and that more advertising money flowed into other types of advertising. This almost certainly made a difference for Amazon as well: one of the most affected areas of Facebook advertising was e-commerce; if you are an e-commerce seller whose Shopify store powered-by Facebook ads was suddenly under-performing thanks to ATT, then the natural response is to shift products and advertising spend to Amazon.

All of these advantages will persist: search advertising will always be effective, and Amazon can always leverage data, and while some degree of ATT-related pullback was likely due to both uncertainty and the fact that Facebook hasn’t built back its advertising stack for a post-ATT world, the fact that said future stack will never be quite as good as the old one means that there is more e-commerce share to be grabbed than there might have been otherwise.

This last point is not set in stone: Shopify is already making major investments to compete with Amazon; it has the opportunity to do even more.

The Shopify Fulfillment Network

In 2019 I wrote about Shopify and its orthogonal competition with Amazon in Shopify and the Power of Platforms:

The difference is that Shopify is a platform: instead of interfacing with customers directly, 820,000 3rd-party merchants sit on top of Shopify and are responsible for acquiring all of those customers on their own.

A drawing of The Shopify Platform

[…]

This is how Shopify can both in the long run be the biggest competitor to Amazon even as it is a company that Amazon can’t compete with: Amazon is pursuing customers and bringing suppliers and merchants onto its platform on its own terms; Shopify is giving merchants an opportunity to differentiate themselves while bearing no risk if they fail.

The context of that Article was Shopify’s announcement of yet another platform initiative: the Shopify Fulfillment Network.

From the company’s blog:

Customers want their online purchases fast, with free shipping. It’s now expected, thanks to the recent standard set by the largest companies in the world. Working with third-party logistics companies can be tedious. And finding a partner that won’t obscure your customer data or hide your brand with packaging is a challenge.

This is why we’re building Shopify Fulfillment Network—a geographically dispersed network of fulfillment centers with smart inventory-allocation technology. We use machine learning to predict the best places to store and ship your products, so they can get to your customers as fast as possible.

We’ve negotiated low rates with a growing network of warehouse and logistic providers, and then passed on those savings to you. We support multiple channels, custom packaging and branding, and returns and exchanges. And it’s all managed in Shopify.

The first paragraph explains why the Shopify Fulfillment Network was a necessary step for Shopify: Amazon may commoditize suppliers, hiding their brand from website to box, but if its offering is truly superior, suppliers don’t have much choice. That was increasingly the case with regards to fulfillment, particularly for the small-scale sellers that are important to Shopify not necessarily for short-term revenue generation but for long-run upside. Amazon was simply easier for merchants and more reliable for customers.

Notice, though, that Shopify is not doing everything on their own: there is an entire world of third-party logistics companies (known as “3PLs”) that offer warehousing and shipping services. What Shopify is doing is what platforms do best: act as an interface between two modularized pieces of a value chain.

A drawing of Shopify as an Interface

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. The same benefit applies in the opposite direction: merchants don’t have the means to negotiate with multiple 3PLs such that their inventory is optimally placed to offer fast and inexpensive delivery to customers; worse, the small-scale sellers I discussed above often can’t even get an audience with these logistics companies. Now, though, Shopify customers need only interface with Shopify.

Over the intervening three years, though, Shopify has moved away from this vision: Shopify Fulfillment Network (SFN) is not going to be a platform like the Shopify App Store but rather an integrated part of Shopify’s core offering like Shop Pay. President Harley Finkelstein explained on the company’s recent earnings call:

We are consolidating our network to larger facilities. We’ll operate more of them ourselves, and we’ll unify the warehouse management software that we’ve been building and testing over the past 18 months. We expect that these changes will enable us to deliver packages in 2 days or less to more than 90% of the U.S. population, while minimizing the inventory investment for SFN merchants. While Amy will go into more detail as to what our evolved vision looks like from a financial perspective, I can tell you, from a merchant’s perspective, Shopify Fulfillment can be life-changing for their businesses. We hear from merchants that fulfillment is only something you think about when it isn’t working well, and they are thrilled that they now never have to think about it. The stockouts and pre-orders that took the shine off strong demand for the new releases, largely became, I think, in the past, with Shopify Fulfillment. And just recently, I heard from a merchant who tells me that he sleeps even better because Shopify Fulfillment just works. Comments like these fuel our ambition, and we’ll continue to explore opportunities to give merchants more visibility and control over their most important assets.

Building and managing warehouses itself is a major commitment: Shopify is going to spend a billion dollars in capital expenditures in 2023 and 2024 building out the Shopify Fulfillment Network, and it seems safe to assume that that spending will only increase over time. I think, though, that this makes sense: Shopify learned from Shop Pay that it can decrease complexity for merchants and deliver a better experience for customers by doing essential functionality itself, and those same needs exist in logistics as well, particularly given Amazon’s massive investment in its own integrated operations.

Keep in mind, though, logistics isn’t the only advantage that Amazon has.

Shopify Advertising Services

Remember the fundamental challenge that ATT presents to Facebook: the company can no longer pool the conversion and targeting data of all of its advertisers such that the sum of effectiveness vastly exceeds what any one of those advertisers could accomplish on their own. The response of the gaming market has been a wave of consolidation to better pool and leverage data. Amazon, as noted, is well ahead of the curve here: because the company’s third-party merchant ecosystem lives within the Amazon.com website and app, Amazon has full knowledge of conversions and the ability to target consumers without any interference from Apple.

Shopify is halfway there: a massive number of e-commerce retailers are on Shopify, but today Shopify mostly treats them all as individual entities, having left the pooling of data for advertising to Facebook. Now that Facebook is handicapped by Apple, Shopify should step up to provide substitute functionality and build its own advertising network.

This advertising network, though, would look a bit different than what you might expect. First, Shopify doesn’t have any major customer-facing properties to display ads; it could potentially build some cross-shop advertising, but that doesn’t seem very ideal for either merchants or customers. The reality is that Shopify merchants still need to find customers on other sites like social networks; the challenge is doing so without knowing who is actually seeing the ads.

Here Shopify’s ability to act on behalf of the entire Shopify network provides an opening: instead of being an advertising seller at scale, like Facebook, Shopify the company would become an advertising buyer at scale. Armed with its perfect knowledge of conversions it could run probabilistically-targeted campaigns that are much more precise than anyone else, using every possible parameter available to advertisers on Facebook or anywhere else, and over time build sophisticated cohorts that map to certain types of products and purchase patterns. No single Shopify merchant could do this on their own with a similar level of sophistication, which Facebook indirectly admitted on its recent earnings call; COO Sheryl Sandberg said:

On measurement, there were 2 key areas within measurement, which were impacted as a result of Apple’s iOS changes. And I talked about this on the call last quarter as you referenced. The first is the underreporting gap. And what’s happening here is that advertisers worry they’re not getting the ROI they’re actually getting. On this part, we’ve made real progress on that underreporting gap since last quarter, and we believe we’ll continue to make more progress in the years ahead. I do want to caution that it’s easier to address this with large campaigns and harder with small campaigns, which means that part will take longer, and it also means that Apple’s changes continue to hurt small businesses more.

Sandberg’s comment was primarily about the sheer amount of data produced by larger campaigns, but the same principle applies to the sheer number of campaigns as well: any one advertiser is, thanks to ATT, limited in the data points they can get from Facebook, making it more difficult to run multiple campaigns to better understand what works and what doesn’t. However, Shopify could in theory run campaigns for each of its individual merchants and collate the data on the back-end; this is the inverse of Amazon’s advantage of being one website, because in this case Shopify benefits from having a hand in such a huge number of them.

I suspect the response of many close Shopify watchers is that such an initiative is not in the company’s DNA; that, though, is why the evolution of the Shopify Fulfillment Network is so notable: building and operating warehouses wasn’t really in the company’s DNA either, but it is the right thing to do if the company is going to continue to power The Anti-Amazon Alliance. The same principle applies to this theoretical ad network, particularly given that it is Amazon who is a big winner from Apple’s changes.

What is interesting is that it appears that Shopify is already flirting with this idea:3 Last summer the company quietly introduced the concept of Shopify Audiences during an invite-only presentation; Tanay Jaipuria fleshed out the concept on Substack:

Shopify Audiences is a data exchange network, which uses aggregated conversion data (i.e., data around which people bought a merchant’s product) across all opted-in merchants on Shopify to generate a custom audience for a given merchant’s product. This audience is essentially a set of people Shopify believes are likely to be interested in your product given the data around all transactions that have taken place across all opted-in merchants on Shopify.

Merchants can then use these audiences when advertising on FB, Snap, Twitter, and other ad platforms1 either as custom audiences or lookalike audiences which should result in higher-performing ads and lower cost per conversion to acquire customers/sales.

This is a big step, and is very valuable for Facebook advertising in particular; however, it doesn’t address the Apple issue, because ATT bans custom and lookalike audiences from external data sources. That means that this data can’t be used in any campaign targeting iOS users. That is why Shopify Audiences is only the first step: to make this work Shopify Audiences needs to become Shopify Advertising Services, where Shopify doesn’t just collect the targets but buys the ads to target them as well, in a way no one else in the world can.

The Conservation of Attractive Profits

Shopify Advertising Services, Shopify Fulfillment Network, and Shop Pay would, without question, result in a very different looking company than the one I sketched out at the beginning of this Article:

Shopify with integrated payments, fulfillment, and advertising

This sort of monolith, though, makes sense not only because of the specifics of what is happening in the market, but from a theoretical perspective as well. I wrote another article about Shopify a year ago called Market-Making on the Internet, highlighting how major consumer-facing platforms were increasingly incorporating Shopify into their sites and apps:

What makes the Shopify platform so fascinating is that over time more and more of the e-commerce it enables happens somewhere other than a Shopify website. Shopify, for example, can help you sell on Amazon, and in what will be an increasingly important channel, Facebook Shops. In the latter case Facebook and Shopify are partnering to create a fully-integrated market: Facebook’s userbase and advertising tools on one side, and Shopify’s e-commerce management and seller base on the other. The broader takeaway, though, is that Shopify’s real value proposition is working across markets, not creating an exclusive one.

Facebook’s motivations are clear: conversions in Facebook Shops can be tracked in a way conversions on websites no longer can be, which will result in in more effective advertising; it is to Shopify’s credit that they are seen as such an important and credible partner that Facebook is going as far as incorporating Shop Pay as well. Even so, this is very much an example of Facebook integrating and Shopify, as it must, modularizing to accommodate them. That is a recipe for long run commoditization.

That is why it is a good thing that Shopify is integrating elsewhere in its business: profits in a value chain follow integration, and the more that Shopify is intertwined with the biggest players the more it needs to find other ways to differentiate. Shop Pay is already a massive win, and fulfillment has the chance to be another one; advertising shouldn’t be far behind.

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

  1. While you can make purchases from brands in the Shop Pay app, it’s an insignificant channel that isn’t at all comparable to Apple’s own direct route to customers via the App Store. ↩

  2. Facebook’s advertising is sold on an auction basis, and advertisers often bid against desired outcomes, like conversions; the more difficult it is to target users the more users there are who need to be showed an ad, which increases demand for inventory, increasing prices. ↩

  3. Thanks to Eric Seufert for tipping me off to this. ↩

Digital Advertising in 2022

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Six years ago tomorrow, in The Reality of Missing Out, I wrote that the digital advertising market was settled, and Google and Facebook won:

I have been arguing for a while that in the aggregate the tech sector is fine, and the state of advertising-based services is a perfect example of what I mean: taken as a basket the six companies in this article (Google, Facebook, Yahoo, Twitter, LinkedIn, and Yelp) are up 19% over the last year, even though the latter four companies are down a collective 53%; the fact that Google and Facebook are up a combined 31% more than makes up for it.

This makes sense: while advertising as a whole is a zero-sum game, there is a secular shift from not just print but also radio and TV to digital, which is why this basket of digital advertising companies is up. Digital, though, is subject to the effects of Aggregation Theory, a key component of which is winner-take-all dynamics, and Facebook and Google are indeed taking it all.

The Article was prescient for a time; Yahoo has been passed around for peanuts, LinkedIn was bought by Microsoft a few months later, and while Yelp and Twitter’s stock have more-or-less doubled since then,1 that gain pales in comparison to that of Google and Facebook:

Google, Facebook, Twitter, and Yelp's market gains over the last six years

That chart, though, only runs through last Wednesday; here is the new chart post-Facebook earnings:

Google, Facebook, Twitter, and Yelp's market gains over the last six years, including Facebook's recent earnings

It turns out that, for now anyways, buying $TWTR on the day I wrote that article would have provided a better return than $FB.

Direct Response and the Collapse of the Funnel

In that Article I painted an idealized picture of the traditional marketing funnel and how Google and Facebook’s advertising products mapped onto it:

What Sandberg is detailing here is really quite extraordinary: Facebook helped Shop Direct move customers through every part of the funnel: from awareness through Instagram video ads to consideration through retargeting and finally to conversion with dynamic product ads on Facebook (and, in the not too distant future, a direct customer relationship to build loyalty via Messenger).

A drawing of Digital Advertising 2.0

Google is promising something similar: awareness via properties like YouTube, consideration via DoubleClick, and conversion via AdSense. Just as importantly, both companies are promising that leveraging their respective platforms will provide benefits on both sides of the ROI equation: the return will be better given the two companies’ superior targeting capabilities and ability to measure conversion, and the investment will be smaller because you can manage your entire funnel from a single ad-buying interface.

Herein lies the first thing that I got wrong: the traditional marketing funnel made sense in a world where different parts of the customer journey happened in different places — literally. You might see an advertisement on TV, then a coupon in the newspaper, and finally the product on an end cap in a store. Every one of those exposures was a discrete advertising event that culminated in the customer picking up the product in question in putting it in their (literal) shopping cart.

On the Internet, though, that journey is increasingly compressed into a single impression: you see an ad on Instagram, you click on it to find out more, you login with Shop Pay, and then you wonder what you were thinking when it shows up at your door a few days later. The loop for apps is even tighter: you see an ad, click an ‘Install’ button, and are playing a level just seconds later. Sure, there are things like re-targeting or list building, but by-and-large Internet advertising, particularly when it comes to Facebook, is almost all direct response.

This can make for an exceptionally resilient business model: because the return-on-investment (ROI) of direct response advertising is measurable to a fantastically greater degree than traditional advertising measurement, advertisers can spend right up to the level they place on a particular customer or transaction’s value; Facebook, of course, is willing to help them do that as easily as possible, squeezing out margin in the process. Moreover, because these ads are sold at auction, the company is insulated from events like COVID or boycotts; I explained in 2020’s Apple and Facebook:

This explains why the news about large CPG companies boycotting Facebook is, from a financial perspective, simply not a big deal. Unilever’s $11.8 million in U.S. ad spend, to take one example, is replaced with the same automated efficiency that Facebook’s timeline ensures you never run out of content. Moreover, while Facebook loses some top-line revenue — in an auction-based system, less demand corresponds to lower prices — the companies that are the most likely to take advantage of those lower prices are those that would not exist without Facebook, like the direct-to-consumer companies trying to steal customers from massive conglomerates like Unilever.

In this way Facebook has a degree of anti-fragility that even Google lacks: so much of its business comes from the long tail of Internet-native companies that are built around Facebook from first principles, that any disruption to traditional advertisers — like the coronavirus crisis or the current boycotts — actually serves to strengthen the Facebook ecosystem at the expense of the TV-centric ecosystem of which these CPG companies are a part.

The problem for Meta is in the title of that article: Apple. The latter’s App Tracking Transparency (ATT) initiative severed the connection amongst e-commerce sellers, app developers, and Facebook by which Facebook achieved that ROI, and while the company is better positioned than anyone else to build a replacement, it is important to note that the impairment entailed in probabilistically measuring ad effectiveness instead of deterministically is a permanent one.

This isn’t just a Facebook problem: Snap said on its earnings call:

Our advertising partners who prefer to leverage lower-funnel goals such as in-app purchases, have been most impacted by [ATT]. We are seeing these advertisers migrate to mid-funnel goals where they have greater visibility such as install or click. Advertisers who optimize via web-based goal-based bids or GBBs have been less impacted, given that many of them have adopted the Snap pixel.

Snap’s direct response business is not nearly as good as Facebook’s, and is a much smaller business both overall and in terms of the overall company’s revenue; that left a lot more cushion to absorb ATT, both because Snap’s performance had less to lose, and also because the company’s brand-business could help pick up the slack. This, paradoxically, led many investors to overfit Facebook’s disappointing forecast to Snap’s outlook; the reality is that advertising dollars will find a way to be spent, and the alternatives to direct response on Snap were more impactful to the bottom line than they are on Facebook, in part because the latter was so dominant in direct response until now.

The Amazon Advertising IPO

What made the Facebook model tick was the way in which the company could convert conversion tracking to targeting: because Facebook knew a lot about someone who saw an ad and then converted, they could easily find other people who were similar — lookalike audiences — and show them similar ads, continually optimizing their targeting and increasing their understanding along the way.

Google Search, though, has a built-in advantage: Google doesn’t have to figure out what you are interested in because you do the company the favor of telling it by searching for it. The odds that you want a hotel in San Francisco are rather high if you search for “San Francisco hotels”; it’s the same thing with life insurance or car mechanics or e-commerce.

Google is not the only search engine that monetizes e-commerce effectively. Back in 2015 I described the breakout of Amazon Web Services’ financials as The AWS IPO:

This is why Amazon’s latest earnings were such a big deal: for the first time the company broke out AWS into its own line item, revealing not just its revenue (which could be teased out previously) but also its profitability. And, to many people’s surprise, and despite all the price cuts, AWS is very profitable: $265 million in profit on $1.57 billion in sales last quarter alone, for an impressive (for Amazon!) 17% net margin.

Those numbers pale in comparison to what I guess we might call the Amazon Advertising IPO, given that the company broke out its advertising for the first time this quarter, revealing $9.7 billion in revenue, a 32% increase year-over-year (Amazon did not break out the unit’s profitability). While that is still a fraction of Google’s $61.2 billion last quarter, or Facebook’s $32.6 billion, it is a larger fraction than you might expect, and several multiples of Snap’s $1.3 billion in revenue. Indeed, given the fact that Amazon is closer in revenue to Facebook than Facebook is to Google it seems fair to characterize the advertising market as dominated not by a big two but a big three.

Amazon’s advertising business has three big advantages relative to Facebook’s.

  1. Search advertising is the best and most profitable form of advertising. This goes back to the point I made above: the more certain you are that you are showing advertising to a receptive customer, the more advertisers are willing to bid for that ad slot, and text in a search box will always be more accurate than the best targeting.

  2. Amazon faces no data restrictions. That noted, Amazon also has data on its users, and it is free to collect as much of it as it likes, and leverage it however it wishes when it comes to selling ads. This is because all of Amazon’s data collection, ad targeting, and conversion happen on the same platform — Amazon.com, or the Amazon app. ATT only restricts third party data sharing, which means it doesn’t affect Amazon at all.

  3. Amazon benefits from ATT spillover. That is not to say that ATT didn’t have an effect on Amazon: I noted above that Snap’s business did better than expected in part because its business wasn’t dominated by direct advertising to the extent that Facebook’s was, and that more advertising money flowed into other types of advertising. This almost certainly made a difference for Amazon as well: one of the most affected areas of Facebook advertising was e-commerce; if you are an e-commerce seller whose Shopify store powered-by Facebook ads was suddenly under-performing thanks to ATT, then the natural response is to shift products and advertising spend to Amazon.

All of these advantages will persist: search advertising will always be effective, and Amazon can always leverage data, and while some degree of ATT-related pullback was likely due to both uncertainty and the fact that Facebook hasn’t built back its advertising stack for a post-ATT world, the fact that said future stack will never be quite as good as the old one means that there is more e-commerce share to be grabbed than there might have been otherwise.

Google’s Dominance

Of course you could just as easily make an argument that when it comes to digital advertising there is Google and everyone else. Google clearly faces competition from Amazon for e-commerce search advertising — the European Commission’s Google Shopping case is only surpassed by the FTC’s Facebook lawsuit when it comes to overly narrow market definitions that ignore reality — but is dominant in terms of nearly every other vertical. Moreover, that dominance is shored up by the same factors favoring Amazon, at least in part.

The first one is obvious: search advertising works great, and Google is the best at it.

The second one, about data collection, is more interesting, particularly in the context of ATT. Facebook CFO Dave Wehner groused on the company’s recent earnings call:

We believe the impact of iOS overall as a headwind on our business in 2022 is on the order of $10 billion, so it’s a pretty significant headwind for our business. And we’re seeing that impact in a number of verticals. E-commerce was an area where we saw a meaningful slowdown in growth in Q4. And similarly, we’ve seen other areas like gaming be challenged. But on e-commerce, it’s quite notable that Google called out, seeing strength in that very same vertical. And so given that we know that e-commerce is one of the most impacted verticals from iOS restrictions, it makes sense that those restrictions are probably part of the explanation for the difference between what they were seeing and what we were seeing.

And if you look at it, we believe those restrictions from Apple are designed in a way that carves out browsers from the tracking prompts Apple requires for apps. And so what that means is that search ads could have access to far more third-party data for measurement and optimization purposes than app-based ad platforms like ours. So when it comes to using data, that it’s not really apples-to-apples for us. And as a result, we believe Google’s search ads business could have benefited relative to services like ours that face a different set of restrictions from Apple. And given that Apple continues to take billions of dollars a year from Google Search ads, the incentive clearly exists for this policy discrepancy to continue.

Apple, it should be noted, has always treated the browser as a carve-out from its App Store restrictions (not that it has any choice: Apple, in contrast to the App Store, doesn’t have any points of leverage over the open web), so it is fair to dismiss Wehner’s conspirational musings about the iPhone maker’s motivations.

At the same time, the broader observation is a smart one: Google, thanks to the combination of being the default search engine on Safari and having a business built on the web, basically has first-party privileges on the iPhone when it comes to data. It can show ads to iPhone users on the default browser and track how those ads perform on third-party websites to a much greater extent than an app like Facebook directing users to the exact same third-party websites can.

In terms of ATT, it is notable that the only part of Google’s business that fell short of Wall Street expectations was YouTube; I suspect it is not a coincidence that YouTube has a significant app-install business of its own, and ATT’s restrictions on what those installed apps can report back to Google may have hurt business a bit. At the same time, the same dynamics that drove advertising to other parts of Snap’s business and to Amazon advertising likely benefited Google as well, including Android.

Facebook Risk

There is no question that Facebook has been significantly impaired, but the company is by no means doomed, in large part because while search is very effective at finding what you want, there remains the need to make you aware of what you didn’t know existed. This is what Facebook excels at more than any other platform: by knowing who you are and what you have liked or purchased in the past, Facebook can place ads for products or apps you have never heard of in the Feed, in Stories, or, going forward in Reels.

This, in my opinion, is actually a far more important form of advertising than search ads: yes, there are scenarios where a firm can surface something that fits exactly what you are searching for, but oftentimes search ads feel like a rake on organic results that would have given you what you were looking for anyways. Facebook-style display advertising, on the other hand, is the foundation upon which an entirely new host of Internet-only businesses are built. These niche-focused companies are only possible when the entire world is your market, but they would founder without a way to find the customers who are looking for exactly what they have to offer; Facebook ads solve that problem.

That discovery mechanism, though, doesn’t just depend on data; it also depends on attention. This is where the TikTok challenge looms large: Apple and ATT may have had the largest financial impact on Facebook, but TikTok and the loss of attention are the more existential risk.

Illustrating the Ad Market

Still, Facebook’s forecast, disappointing as they were to investors, was for $27-29 billion in revenue this quarter; this is still a major player in an advertising market dominated by the three companies mentioned in this article, with one looming dark horse. To illustrate the market — and with the caveat that this is a massive oversimplification of what is a large and varied opportunity — consider a two-by-two defined by apps and commerce (both physical and digital) on one axis, and search and display on the other:

A two-by-two graph with search and display on one axis, and apps and commerce on the other

This is what that market looked like back in 2016:

The 2x2 graph in 2016, when Google and Facebook were dominant

This is what the market looks like in 2022:

The 2x2 graph in 2022, with challenges from Amazon and Apple

First off, note that this illustration doesn’t include a huge part of Google’s market, which is basically search for anything other than e-commerce. It also doesn’t include the still substantial market for brand advertising. Direct response advertising, though, is the truly Internet-native advertising form, and while Google and Facebook are important, note the two new entrants who have substantial advantages:

Amazon:

Amazon has the best fulfillment and logistics operation in e-commerce,2 which it uses to not only drive its own first-party retail but also third-party merchant services. Indeed, this is another way to think about how Amazon is insulated from ATT: it’s not that the company doesn’t have a multitude of third-party merchants on its platform, it is that by taking on the role of an Aggregator instead of a platform it gets to fold all of those third party merchants into its app and website, beyond the limitations enforceable by Apple. Then it effectively gives those third party merchants no choice but to buy ads if they want to be noticed by customers.

Apple:

Apple launched its App Store advertising business in the fall of 2016, starting with the most obvious place: search. Apple hasn’t disclosed how much it makes in advertising, but there are analyst estimates of $5 billion annually. Not all of this is search — Apple has since added inventory in the App Store’s “Suggested” section as well as owned-and-operated apps like Apple News — but most of it is; Apple is confined to the top right corner…for now.

One of the biggest questions about the advertising landscape going forward is if Apple is going to move down to the “Apps + Discovery” quadrant that remains Facebook’s purview. If the company did they would have an unbeatable advantage: remember, Apple has made clear through its App Store policies and testimony in the Epic case that it views apps on the App Store as first party for Apple (this is how the company justifies its anti-steering provisions, likening links to websites to putting up signs in its own store for another, even though the signs in question are in the app and not the App Store). It follows, then, that Apple would see no inconsistency in denying Facebook the ability to have knowledge about installation and conversions derived from a Facebook ad, even as Apple has perfect knowledge of those installations and conversions from its own ads.

This isn’t a hypothetical! Apple’s Advertising & Privacy page states:

We may use information such as the following to assign you to segments:

  • Account Information: Your name, address, age, gender, and devices registered to your Apple ID account. Information such as your first name in your Apple ID registration page or salutation in your Apple ID account may be used to derive your gender. You can update your account information on the Apple ID website.
  • Downloads, Purchases & Subscriptions: The music, movies, books, TV shows, and apps you download, as well as any in-app purchases and subscriptions. We don’t allow targeting based on downloads of a specific app or purchases within a specific app (including subscriptions) from the App Store, unless the targeting is done by that app’s developer.
  • Apple News and Stocks: The topics and categories of the stories you read and the publications you follow, subscribe to, or enable notifications from.
  • Advertising: Your interactions with ads delivered by Apple’s advertising platform.

When selecting which ad to display from multiple ads for which you are eligible, we may use some of the above-mentioned information, as well as your App Store searches and browsing activity, to determine which ad is likely to be most relevant to you. App Store browsing activity includes the content and apps you tap and view while browsing the App Store. This information is aggregated across users so that it does not identify you. We may also use local, on-device processing to select which ad to display, using information stored on your device, such as the apps you frequently open.

As you can see, Apple does not currently allow developers to target downloads or purchases from within a specific app the developer does not own,3 but that doesn’t mean Apple cannot; again, the company has made clear it sees every app on the iPhone — especially their purchases — as Apple data, and this document makes very clear that Apple only sees data collection as problematic when it involves third parties. To that end, Apple could set up an auction-based advertising network that monetized on a per-install basis and run those ads within an Apple-controlled network that is available to third-party apps. It would basically be a better version of Facebook — well, in theory, Apple has admittedly never been really good at this sort of thing — but since only Apple sees the data (just as only Facebook sees the data from third-party apps), Apple gets to pat itself on the back all of the way to the bank.

This would, needless to say, be a breathtaking example of anti-competitive behavior; kneecapping your competitor via platform control and then taking over their business is what one would think antitrust law would be designed to stop. But then you look up and Apple has gotten away with its App Store policies for years, and Facebook is getting sued for limiting competition even as it faces an existential threat from TikTok, and who knows, maybe it would work.

I hinted at one of the objections to this happening above: Apple has tried to do advertising before, and failed miserably. As any Apple aficionado will tell you, ads aren’t in their nature, products are. But then again, had you told those same aficionados that Apple would be facing developer ire, antitrust lawsuits, and regulatory obstacles all over the world because of its insistence that it is owed 15-30% of all digital content consumed on the iPhone, they probably would have said that was impossible too. What is clear is that the $10 billion in revenue that Facebook won’t see this year will go somewhere, and Apple’s Services Narrative has never felt like a bigger opportunity.

There is a broader takeaway to this discussion; I wrote in the conclusion of 2020’s The End of the Beginning:

In other words, today’s cloud and mobile companies — Amazon, Microsoft, Apple, and Google — may very well be the GM, Ford, and Chrysler of the 21st century. The beginning era of technology, where new challengers were started every year, has come to an end; however, that does not mean the impact of technology is somehow diminished: it in fact means the impact is only getting started.

There was one company conspicuous in its absence, and that was Facebook. Real power in technology comes from rooting the digital in something physical: for Amazon that is its fulfillment centers and logistics on the e-commerce side, and its data centers on the cloud side. For Microsoft it is its data centers and its global sales organization and multi-year relationships with basically every enterprise on earth. For Apple it is the iPhone, and for Google is is Android and its mutually beneficial relationship with Apple (this is less secure than Android, but that is why Google is paying an estimated $15 billion annually — and growing — to keep its position). Facebook benefited tremendously from being just an app, but the freedom of movement that entailed meant taking a dependency on iOS and Android, and Apple has exploited that dependency in part, if not yet in full.

This, more than anything, is the way to understand the Meta bet, and why it matters so much to CEO Mark Zuckerberg. Investors may want the company to focus on what it is best at; Zuckerberg wants to build a company that is truly independent of anyone.

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

  1. Twitter did have a large run-up a year ago that has since disappeared ↩

  2. ex-China, anyways ↩

  3. This is why I have been intrigued by AppLovin’s approach. ↩