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SUBSCRIBER’S DAILY UPDATE

Wednesday, April 27, 2022


TWITTER FOLLOW-UP, GOOGLE EARNINGS, ATT AND GOOGLE

Tuesday, April 26, 2022


ELON MUSK BUYS TWITTER, MUSK’S FINANCING, THE STATUS QUO AND FUTURE VARIANCE

Thursday, April 21, 2022


AN INTERVIEW WITH RAMP FOUNDER ERIC GLYMAN

Wednesday, April 20, 2022


NETFLIX EARNINGS, NETFLIX’S STRUGGLING GROWTH DRIVERS, NETFLIX TO EXPLORE
ADVERTISING


BEYOND AGGREGATION: AMAZON AS A SERVICE

Posted onMonday, April 25, 2022Monday, April 25, 2022 Author by Ben Thompson

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:



“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:
> 
> 
> 
> 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:
> 
> 
> 
> 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

Posted onMonday, April 18, 2022Tuesday, April 19, 2022 Author by Ben Thompson

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 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:



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:
> 
> 
> 
> 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

Posted onTuesday, April 12, 2022Tuesday, April 12, 2022 Author by Ben Thompson

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:



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:



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:



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



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

Posted onMonday, April 4, 2022Sunday, April 10, 2022 Author by Ben Thompson

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:



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

Posted onMonday, March 28, 2022 Author by Ben Thompson

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

Posted onThursday, March 17, 2022Thursday, March 17, 2022 Author by Ben Thompson

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.
> 
> 
> 
> 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.
> 
> 
> 
> 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:
> 
> 
> 
> 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

Posted onMonday, March 7, 2022Monday, March 7, 2022 Author by Ben Thompson

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:

 * Apple has stopped selling its products in Russia (although still operates the
   App Store).
 * Microsoft has suspended all new sales of Microsoft products and services in
   Russia, and SAP and Oracle have suspended operations.
 * Google and Facebook suspended all advertising in Russia.
 * Activision Blizzard, Epic Games, EA, and CD Projekt suspended game sales in
   Russia.
 * Disney, Sony, and Warner Bros. paused film releases in Russia, and Netflix
   suspended its service.
 * Visa and Mastercard cut off Russia from their respective international
   payment networks, and PayPal suspended service.
 * Samsung stopped selling phones and chips, and Nvidia, Intel, and AMD also
   stopped selling chips to Russia.

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

Posted onTuesday, February 22, 2022Friday, February 25, 2022 Author by Ben
Thompson

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:



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):

> 

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:



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.



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:



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:



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:





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.
> 
> 
> 
> […]
> 
> 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.
> 
> 
> 
> 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 Data Exchange
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:



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

Posted onTuesday, February 8, 2022Friday, February 25, 2022 Author by Ben
Thompson

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:





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



This is what that market looked like back in 2016:



This is what the market looks like in 2022:



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. ↩


GAMING THE SMILING CURVE

Posted onTuesday, February 1, 2022Friday, February 25, 2022 Author by Ben
Thompson

Another week, another gaming acquisition. First Take-Two acquired Zynga, then
Microsoft acquired Activision-Blizzard, and now Sony just announced the
acquisition of Bungie.


1 Each of these acquisitions is interesting in its own right, but taken as a set
they paint a picture of industry evolution that extends far beyond gaming.



TAKE-TWO AND MOBILE CONSOLIDATION

The straightforward explanation for Take-Two’s acquisition of Zynga is the fact
that mobile captures more than 50% of gaming industry revenue and it is growing
much faster (7% last year) than PC and console gaming (the gaming industry grew
1.4% as a whole); that is a problem for Take-Two given that nearly all of the
company’s revenue comes from PC and console series like Grand Theft Auto, NBA
2K, Red Dead, Bordlerlands, and more.

Zynga, meanwhile, was among the least prepared of the major mobile gaming
companies for the changes wrought by Apple’s App Tracking Transparency (ATT)
policy, which was introduced with iOS 14 and rolled out over the first half of
2021. In the pre-ATT world everyone from e-commerce sellers to app developers
could effectively offload the collection and analysis of conversion data and
subsequent targeting of advertising to Facebook, to the benefit of everyone
involved: individual developers and retailers did not need to bear the risk or
expense of collecting and analyzing data, and could instead collectively
outsource that job to the Facebook data factory, which had the benefit of making
Facebook advertising that much more effective, not only to the benefit of
Facebook’s bottom line but also to that of those that relied on its advertising
platform.

ATT, meanwhile, didn’t ban data collection or analysis or targeting or any of
the other aspects of advertising that many of its supporters object to; what it
targeted was doing so collectively. That means that the policy has been a huge
boon for fully integrated advertisers (i.e. advertisers that collect data,
target, and show advertisements) like Google and Amazon. In this world the
natural response has been consolidation; compare Zynga’s stock price over the
last year to a company like AppLovin which was ahead of the curve in buying up
multiple parts of the ad stack and combining them with its own titles to
maximize the value of first party data:



AppLovin is down a bit with the general market drawdown, but it’s not an
accident the company increased in price last fall while Zynga plummeted (the
stock is up from its depths because of the not-yet-closed acquisition): one of
the keys to Zynga’s turnaround was buying small independent studios and letting
them stay independent; that’s no longer a viable approach in a post-ATT world,
and Take-Two will have to centralize Zynga and only then leverage Zynga’s
expertise to bring its valuable IP to mobile platforms in a much more complete
way than it has previously.

MICROSOFT AND XBOX GAME PASS

Take-Two wasn’t the only company taking advantage of a company with a plummeting
stock price; Microsoft did the same with Activision Blizzard:



Activision Blizzard does own King Digital, which still provides over $2 billion
in revenue from Candy Crush and its various spin-offs, but in this case the
stock price decline was primarily due to major issues regarding Activision
Blizzard’s internal culture, including a lawsuit by the state of California.
Microsoft, though, was well positioned to take advantage of Activision
Blizzard’s troubles thanks to Xbox Game Pass.

Whenever a major platform acquires a developer on that platform, the first
question users ask is if the platform owner will make the developer’s content
exclusive. It’s an obvious question — why else would the platform owner buy it,
given that they can still collect revenue from the developer, both directly via
platform fees and indirectly via licensing fees? — but the answer is not always
straightforward, thanks to the nature of software.

Software, including games, entails a massive investment in upfront development
costs. You have to build (or license and adapt to) a game engine, write and
build out the story, draw and develop the assets, etc. All of this is work that
is both expensive and also only needs to be done once; it follows, then, that it
is in the software developer’s economic interest to make the game available as
widely as possible; after all, every additional copy of a game has zero marginal
costs, which means that every additional copy of a game sold provides nothing
but leverage on those fixed costs, and, once covered, pure profit (that noted,
there are significant costs associated with supporting multiple platforms — I
have seen estimates around 25~40% of extra costs, depending on the game — so
going exclusive is not an entirely deadweight cost).

This makes the math around developer acquisitions a bit tricky for platform
acquirers: to buy a gaming studio in order to make its games exclusive to the
platform entails destroying a significant part of the game studio’s economic
value; after all, you are acquiring a property like Call of Duty based on the
revenue it grosses from PC, Xbox, and PlayStation — cutting off the latter means
you overpaid. This is why it is not a surprise that Microsoft has already
committed to keeping Activision Blizzard’s and ZeniMax’s most popular
cross-platform games on PlayStation.

What makes Microsoft’s acquisition spree particularly compelling, though, is
that Microsoft is trying to create a new business model for gaming: for
$15/month you can play all of the games Microsoft owns, and those of any
third-party developer who wishes to join up, on any platform that supports them.
This includes not only the Xbox console and Windows PCs,


2 but also the nascent Xbox streaming service, which makes console-level games
available on mobile and PC and, soon enough, smart TVs or a potential Xbox
streaming stick. This is a business model that not only makes sense given the
evolution of technology towards cloud-centric services, but is also in-line with
Microsoft’s core competency and fundamental nature.



More importantly, at least in the context of this Article, is the freedom of
movement this gives Microsoft when it comes to acquisitions: all of ZeniMax’s
titles, and many of Activision Blizzard’s titles in the future, are still
available on PlayStation and Steam as individual purchases; if that is how you
want to pay then Microsoft will accept your money, and avoid the loss of cutting
you off. All of those games, though, are also available on Xbox Game Pass,
because Microsoft is betting that many gamers will realize it’s a pretty good
deal, even as it aligns with the company’s corporate goal of creating lifelong
customers paying via subscription.

SONY AND EXCLUSIVES

Major deals like Sony’s acquisition of Bungie, the once-makers of Halo (while
owned by Microsoft) and current developers of Destiny (for which they negotiated
their freedom), obviously don’t come together in two weeks. It’s tempting,
though, to view it as defensive: if Microsoft were to withdraw a property like
the afore-mentioned Call of Duty, well, Sony can always take away Destiny.

The truth, though, is that this is simply the most visible of a long line of
acquisitions, going back two decades to Sony’s 2001 acquisition of Naughty Dog,
of studios that make content for consoles that is worth switching over. Naughty
Dog has made Crash Bandicoot, Uncharted, and The Last of Us; Incognito made the
Twisted Metal series; Guerrilla Games made the Killzone and Horizon series;
Sucker Punch made Sly Cooper, Infamous, and the Ghost of Tsushima; Insomniac
made Ratchet and Clank and Spider-Man; Bluepoint Games made Shadow of the
Colossus and Demon’s Souls; all were PlayStation exclusives, credited with
Sony’s dominance over the last two console generations.

Sony, rather than chasing Microsoft, appears set for a more Nintendo-like
trajectory: customers will buy their consoles because they have exclusive games
that you can’t get anywhere else; unlike Nintendo, Sony consoles are on the
cutting edge technologically, which means that the remaining 3rd-party
publishers like EA will continue to support them. Sure, Microsoft has a good
subscription, but Sony has games you can’t get anywhere else (and, rumors
suggest, a new subscription service of its own, although it may not have the
best titles available immediately, which makes sense given Sony’s strategy).

That is why I expect Bungie to continue to support Destiny across multiple
platforms (PlayStation, Xbox, and PC), while new content beyond the upcoming
Witch Queen expansion is probably going to come out on PlayStation first;
whatever title lies beyond that, meanwhile, has a good chance of being
PlayStation only (if you haven’t spent the money on supporting multiple
platforms, it is an easier choice to be an exclusive).

Update: Bungie made clear in an FAQ that future Destiny content would be
available on the first day on all platforms, which makes sense given that
Destiny supports cross-play. Moreover, the same FAQ states that any IP beyond
Destiny would also be cross-platform; this doesn’t detract from the general
point about Sony and exclusives, but it certainly suggests that doesn’t apply in
this case. This was an error on my part and I apologize.

GAMING AND THE SMILING CURVE

The Smiling Curve, as I first explained in this 2014 Article, was a concept
created by Acer founder Stan Shih to explain where the profits were in
technological manufacturing; from Wikipedia:

> A smiling curve is an illustration of value-adding potentials of different
> components of the value chain in an IT-related manufacturing
> industry…According to Shih’s observation, in the personal computer industry,
> both ends of the value chain command higher values added to the product than
> the middle part of the value chain. If this phenomenon is presented in a graph
> with a Y-axis for value-added and an X-axis for value chain (stage of
> production), the resulting curve appears like a “smile”.

I argued at the time that this framework was applicable to the publishing
industry:

> When people follow a link on Facebook (or Google or Twitter or even in an
> email), the page view that results is not generated because the viewer has any
> particular affinity for the publication that is hosting the link, and it is
> uncertain at best whether or not their affinity will increase once they’ve
> read the article. If anything, the reader is likely to ascribe any positive
> feelings to the author, perhaps taking a peek at their archives or Twitter
> feed.
> 
> Over time, as this cycle repeats itself and as people grow increasingly
> accustomed to getting most of their “news” from Facebook (or Google or
> Twitter), value moves to the ends, just like it did in the IT manufacturing
> industry or smartphone industry:

I think this framework is also the best way to think about all of these
acquisitions. To generalize the concept, the top right of the curve are
companies that have a direct connection with customers, including the
Aggregators; the top left are highly differentiated content makers:



When it comes to mobile gaming, the dominant Aggregators on the top right side
of the curve are Apple and Google and their respective App Stores; the most
cynical interpretation of ATT is that Facebook was superseding both to become
the most important way in which people discovered apps, and Apple, thanks to its
OS-level control, cut them off at the knees, pushing Facebook down to the
middle. The response from content makers, then, has been to consolidate and
increase the leverage that comes from differentiated content.

Xbox Game Pass, meanwhile, is an attempt to build a position as an Aggregator;
the initiative will be successful to the extent that gamers play games because
they are in Game Pass, and increasingly shun games that have to be purchased
individually (incentivizing holdouts to join Microsoft’s subscription).
Microsoft is kick-starting this effort by buying its own differentiated content
and overlaying their long-term incentives over any individual game studio’s
incentives to maximize their short-term revenue by selling a game individually.

Sony is pursuing a similar strategy, but with a different business model:
whereas Microsoft is increasingly device-agnostic (of course it helps that they
sell both Xbox consoles and Windows), Sony is doubling down on the integration
of hardware and software. Their best content is designed to not only make money
in its own right but to also persuade customers to buy PlayStation consoles; the
more PlayStation consoles there are the more attractive the platform is to
3rd-party developers.

What is much less viable is anything in the middle. The original PlayStation was
almost completely dependent on 3rd-party games, relying on technical superiority
to build its user base and attract developers; that approach reached its limit
with the relative disappointment that was the PlayStation 3, and Sony has been
focused on exclusives ever since. Content developers like Zynga, meanwhile,
can’t depend on companies in the middle either: Apple’s rules have ensured that
anyone who is not an Aggregator has to figure out how to make money on their
own. There is still a market for 3rd-party developers on consoles and PCs —
Steam is a major Aggregator on the latter, challenged by not just Microsoft but
also Epic, who all are competing for the best developers — but it is
increasingly important that content be highly differentiated and costs tightly
contained.

THE UPSIDE OF ACQUISITIONS

There are a lot of seemingly scary implications in this analysis, including
concepts like exclusives, lock-in, and the sense that the big are getting
bigger. I think there is a strong argument, though, that the overall impact on
consumers is on balance a positive one. Gaming, to a much greater extent than
many other industries, is a zero sum game: time spent playing one title is time
not spent playing another one. Moreover, the total cost of ownership for any
particular gaming platform, relative to the time spent playing games, is a very
favorable one. With regards to the latter point, the price of having access to
everything is not an overwhelming one; with regards to the former the incentives
to make a game that is truly exceptional, and thus truly differentiated, are
higher than ever.

Phil Spencer, CEO of Microsoft Gaming, made an argument along these lines when I
challenged him in a Stratechery interview about a potential loss of competition
entailed in the company’s Activision Blizzard acquisition:

> Phil Spencer: Ah. I mean, that’s maybe where we’ll differ in opinion. Some of
> this just comes down to the teams that become part of our team and our
> cultural journey with them that starts long ago. This will sound a little bit
> like a kind of gaming person, but I’ll say the thing that I have found that
> drives the teams internally to our organization is they want to do things
> they’ve never been able to do before. They want to reach more players of their
> creations than they’ve ever been able to create before. And I might argue the
> opposite, that the churn of “I need another holiday release next year” and
> then the year after and then the year after can be more stifle on creativity
> than the freedom that we’re able to give that says, “It’s not about one
> business model that works for us, it’s actually about multiple business
> models. It’s not about one screen that people will consume your game on. You
> pick the screen that’s right for you. And the input, if you want keyboard or
> mouse, you want touch, you want controller, you pick. You pick the subject
> matter that you want to work on.”
> 
> And frankly, when I look at the portfolio of games that we’ve been shipped
> over the last two or three years and some of the subject matter that our
> creators have decided to tackle, not always in the thinnest definition of
> what’s marketable at that time, I think those innovations and that kind of
> risk taking comes from having amazing teams that are thinking about what’s
> possible or even what’s not possible and how our tools and distribution can
> help them in creating things that they’ve never been able to create before.
> That’s what I feel.
> 
> Today, what I did after we announced this morning is I got to sit down with
> our studio leaders. The amount of energy they had for learning from other
> teams, because creators can get isolated because they’re so focused on the
> thing they’re doing right now. Now we get to sit there at the broadest level
> and have discussions about what people are thinking about, whether they’re
> challenging each other with sharing the learning that they have, what they
> aspire to go do. The energy in the room was awesome, it was a virtual room in
> a Teams call, but it was still awesome. I would say that that freedom to
> innovate, to try new things, because it’s not just down to one business model
> or one screen or even one device that somebody might buy is the thing that I
> found is most liberating for the teams here.
> 
> Of course that’s the answer I would expect.
> 
> PS: (laughing)
> 
> I think that one of the early questions about this deal is basically — the big
> company doesn’t think competition is particularly useful or valuable. “We want
> to give people freedom to explore.”
> 
> PS: Well, let me hit on that one. Sorry, I didn’t mean to interrupt, but let
> me hit on competition really quick, because I see competition as a little bit
> different. There’s a ton of competition in the games business. If I rewind 30
> years ago, the video game business was dictated by who had shelf space at
> Egghead because there was such a constriction on distribution and funding and
> marketing of games that the portfolio of games I could choose from was so
> limited. I love the fact that when I look at the top 10 games that are being
> played, how many come from traditional places versus how many now are coming
> from creators that didn’t even exist 10 years ago. I love that there’s that
> creative turnover or just the diversity in where great games come from.
> 
> And then when I think about the platform side, the largest platforms for
> playing games or mobile devices, distribution on those devices are controlled
> by two companies. So for us, it’s how do we go invest in content and community
> so that we can actually have our distribution through our own content
> engagement that we have because the competition is out there and it’s so
> strong? I think the competition you talk about between individual teams and
> the competition to make the next paycheck, I understand maybe that’s
> motivating to certain teams, I’ve just found with our teams that they do much
> better work when our motivation is more about how many customers can we reach.

Forgive the extended excerpt, but I think this is essential, particularly the
second part: so much of our thinking about competition is rooted in the analog
world, a world of scarcity where there really was limited shelf space or limited
telephone lines or limited railroad access; that just isn’t the case on the
Internet, where anyone has access to everyone. This has dramatically increased
the power of creators, who can not only go direct, but also plays Aggregators
off against each other — that is the realm of competition that matters. If we
must accept a world where platforms like the App Store have total power within
their domains, then the answer is to build up alternative Aggregators that have
compelling content of their own, waging a proper fight for the only scarce
resource there is on the Internet: time.

--------------------------------------------------------------------------------

 1. I will save the Wordle acquisition for another day! ↩

 2. Each of which has a standalone $10/month plan ↩


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