The Value of a Customer

As I remember it, at least 10 years ago, I began to hear anecdotes from developers who built apps for both iOS and Android about their economics. The story is that they tended to have twice as many users using Android but that iPhone App Store revenues were roughly twice those of Google Play Store. From that I devised a rule of thumb that an iPhone user was about 4 times more valuable than an Android user. Half the users, paying 4 times as much means double the income.

Over the years I came across a lot more data about market development (the diffusion of innovations) and market creation (the innovation process) and applied it to transportation. Along the way I also became more aware that figures of consumption and spending are not normally distributed. That it turns out that the governing function of much of human behavior is log-normal. That is, it is skewed rather than balanced or symmetric around an average. Classic examples are income distribution and the distribution of travel distances.

Consider the following diagrams: Trip Distances vs. Trip Speeds for New York Citi Bike travelers (n=42.7 million.)

The different lines represent different time periods spanning the months of the year.

The top graph shows that most trips are short, and the average distance is not the most common distance. The bottom graph shows that the average speed is the most common speed. The top graph is very accurately modeled with the log-normal function. The bottom graph is the classic bell curve of the normal or Gaussian function.

Income is log-normally distributed and so it has to be with services revenues. There must be a definite skew where there is a disproportionate spend by those who have more income. Thus segmenting or, to put it less kindly, discriminating customers properly is super important. Customer quality is just as important, perhaps more so, than quantity.

So let’s revisit the question of user quality for online services.

Unlike 10 years ago, there is a lot more data. The EU, for instance requires a report of the number of users on each platform.

The figures I want to focus on are those of Apple App Store and Google Play Store: 123 million and 284.6 million respectively. These are strikingly similar to the ratio of 2x between iOS and Android from my old anecdotes. However, if we look at global data, Apple claims 650 million active App Store users while Google claims 2.5 billion active users. That makes the global ratio closer to 4x Android. However, if we look at the US, the ratio is 167 million iPhone users vs. 144 million Android. In the US, iOS is a majority.

This is explained by income. The wealthier the user base the more iOS seems to be in use.

Now let’s look at revenues for the platform stores.

On the right side is the history of retail revenues by year from 2016 to 2022 and split between Apple App Store and Google Play Store. Mirrored on the left is the number of users, also split by store but also by region, but only for 2022. [App Store revenues are my own analysis (with validation against other sources) and include billings not just Apple’s own cut. Play Store revenues are from Business of Apps.]

The ratio between revenues has kept remarkably steady, with 2016 revenues at a Apple:Google ratio of 29:15 (1.93) and 2022 at a ratio of 81:42 (1.93).

The global user numbers are, as mentioned, 3.8 to 1.

[Aside: One sanity check on the data is that the 650 million App Store users is about half of my estimate of iPhones in use (1.2 billion). That might be alarming. Why are only 54% of iPhones in use paired with App Store use? However, if we take the sum of both App Store and Play store users (3.15 billion) and compare it with the total number of global smartphone users (6.92 billion), we discover that 45.5% of all smartphone users use some store. Adding Chinese Android stores we can see that the ratio of 54% for iOS is somewhat consistent.]

Thus we can compare the app revenue per user of the two platforms by dividing global revenue number by the global user numbers. The results are shown below:

I scaled the spending to a per-month basis.

So the picture becomes clearer. The iPhone customer is 7.4 times more valuable than the Android customer. This is more impressive than the 4x rule I had 10 years ago. The reasons are mainly that my anecdotes were from developers who sold products in the US or EU whereas expansion of smartphones to 7 billion global users has drawn in more lower spending customers.

But Apple’s base has also grown to over 1 billion users (650 million store users). This highlights that Apple has effectively grown and discriminated customers effectively. It obtained not just 1 billion customers but the best 1 billion customers.

How to discriminate effectively is the holy grail of marketing. The naïve approach is to keep prices high. But that usually only results in a “luxury” branding and a small base that tends not to grow. The alternative “premium” approach is to offer functionality and multiple tiers and distribution options and financing and merchandising. There is no simple formula.

The bottom line is that Apple’s approach is attracting 650 million $10/month app spenders. When we factor in additional subscription services, we get to the juggernaut that is Apple Services. This analysis has shown how difficult it is for anyone to come close to this quality of revenue.

As we look forward to Spatial Computing, the idea of increasing that spend from $10/month for a small glass rectangle in your palm to perhaps $100/month for an immersive 360-degree 3D experience does not sound too crazy.

But only if you can find those customers. I suspect Apple already knows who they are.

If you want to learn more and hear an in-depth discussion on this topic make sure you subscribe to the Asymetric Podcast on Supercast and Apple Podcasts.

The $2 Trillion Economy

The App Store ecosystem crossed $1 Trillion in 2022.

To be precise, in a report published in May 2023 by the Analysis Group the ecosystem is estimated to have exceeded $1.1 trillion. This ecosystem is defined as the total transactional value of the sale or distribution of digital and physical goods and services through apps. It also includes in-app advertising. The analysts relied on a variety of data sources, including data from Apple, app analytics companies, market research firms, and individual companies.

Note that this includes Apple’s own services as well as App Store developers. Unlike Apple’s own reporting of payments to developers (and thus partially revealing its own App Store revenues) this data includes payments which are not captured by Apple directly. In the words of the authors, “More than 90% of this figure originated from transactions that did not happen through the App Store, meaning that these amounts accrued solely to developers and other third parties, and that Apple collected no commission on them.”

This $1.1 trillion figure is almost double the value from 2019. Ecosystem estimates were first provided in 2019 at $519 billion, with $643 billion in 2020, $868 billion in 2021 and $1,123 billion in 2023. These correspond to growth rates of 24% in 2020, 35% in 2021 and 29% in 2022. The compound growth rate has been 29.4% since 2019.

It would be ambitious to expect this CAGR to continue after the Covid boom but at the same time, it’s worth noting that this growth out-paces Apple’s own services growth rate. Services (reported) revenues grew at 18%, 27% and 10%. The actual figures and growth rates are shown below.

This Analysis Group report is very much worth reading and adds an important new metric of resilience and scope and scale of the platform and ecosystem that Apple has created.

However it is also not the complete picture. I strive to see the larger picture of what I call the Apple Economy. This includes the ecosystem as well as the direct revenues Apple obtains from products and services. [Of these revenues, roughly 60% is then passed on to Apple’s suppliers, with less than 20% retained as earnings].

Therefore, the combination of ecosystem and revenues is shown in the following diagram.

Note that the “Economy” size was over $1.4 trillion when the ecosystem alone was $1.1 trillion. Note also that I’m also suggesting that it’s likely to be $1.6 Trillion this year. This diagram shows the story since 2019 but also makes a forecast to 2025.

I’m expecting the ecosystem to grow more modestly at 18% in 2023 (down from 29%) and 16% in 2024 and 15% in 2025. Apple’s own product and services sales are also subject to estimation error.

Nevertheless, it’s not unreasonable to believe the forecast above where the Apple Economy expands to over $2 Trillion by 2025. This is an acceleration from previous forecasts.

It’s difficult to write about the implications of this. Any value in the trillions is hard to put in context. Certainly, Apple’s market capitalization is in the trillions. For fun, we can calculate that Apple is trading at a multiple of 1.74 of its economy.

But rather than trying to assess valuation directly, Apple’s Economy is more like a GDP figure: I think it’s helps to understand the overall scale and resilience. You might even ask what would happen if it were to cease to exist. The number of people who are employed in a $2 trillion economy is in the millions; perhaps 10s of millions of people.

In 2023, global GDP is expected to reach $105 trillion. It’s nice to think that Apple could soon be about 2% of the world.

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Apple’s Fourth Calendar Quarter 2020

As a rule, I don’t like to make a forecast for Apple’s performance during quarters where there is no guidance. There is a good reason why there is no guidance. The management does not feel confident that there is enough information to make a reasonable prediction. Keep in mind that the management has very detailed, very frequent updates on their business metrics.

Anyone who has run a business knows that signals of performance are abundant and one can only imagine how many signals arrive at Apple HQ from the 1.5 billion active devices, tens of thousands of points of sale, and a vast network of resellers. There are also billions of interactions in services. Then there are search queries, store visitor counts (online and physical), developer payments, app downloads, content downloads, subscriptions. All this information is collected and analyzed on (probably) a daily basis.

Also when guidance is given, it’s usually a month into the next quarter. The company will have already seen about a third of the quarter already pass before they predict the next two thirds.

This last quarter in particular was even more difficult given the delays in launching the new iPhones and the dynamics related to the broader portfolio.

And yet, the company feels that they can issue some “insights on our expectations”. Here is what was said about three months ago:

These directional comments assume that COVID-related impacts to our business in November and December are similar to what we’ve seen in October. […] [W]e expect iPhone revenue to grow during the December quarter despite shipping iPhone 12 and 12 Pro 4 weeks into the quarter and iPhone 12 mini and 12 Pro Max 7 weeks into the quarter.

We expect all other products in aggregate to grow double digits, and we also expect services to continue to grow double digits. For gross margin, we expect it to be similar to our most recent quarters despite the costs associated with the launch of several new products. For opex, we expect to be between $10.7 billion and $10.8 billion. We expect OI&E to be around $50 million and the tax rate to be around 16%.

Luca Maestri, Chief Financial Officer

So, given this information and some hints from IDC, Gartner and CIRP and China I’m willing to offer some estimates:

  • iPhone Revenue: $63.9 billion
  • Mac Revenue: $9.3 billion
  • iPad: $7.4 billion
  • Services: $15.1 billion
  • Wearables & Home: $12 billion
  • Net sales: $107.8 billion
  • Gross margin percent: 37.7%
  • EPS: $1.48 (Growth: 19%)

Of course, this is very speculative and I don’t have a lot of confidence in it. If anything it may be on the high side.

I don’t expect there to be guidance for the next quarter with a resumption of guidance only after the pandemic has largely subsided (probably Q3 of this year.)

The Entrant’s Guide to Automotive Industry (updated)

I wrote the initial guide almost exactly six years ago. Also known as “The 10 Commandments of Automotive” it’s time to re-visit it to see how and if anything has changed.

The rules listed are empirical observations. The patterns show how things are and have been and hint at what can and cannot change. Capacity utilization and capital allocation are perhaps the most basic root causes for how the system operates.

Capacity utilization has meant that incumbents needed to produce large quantities even if they were not doing so profitably (1st commandment). The capital invested in plant and equipment had to be amortized. This meant it was difficult to enter with a low volume strategy. Indeed all entrants that succeeded did so with “people’s cars” (2nd commandment) which were destined to mobilize entire nations if not continents.

As production orientation absorbed all attention, innovation in production determined the cycles of dominance. First Ford, then GM, and finally Toyota refined the production system (3rd commandment.) Eventually every producer would adopt the “best practices” but the innovator would have years if not decades of competitive advantage.

The political implications of the automobile became a dominant question as it effectively terraformed its environment. Cities, ancillary industries and even our climate were affected. This meant infrastructure, tax policy, land use policy and financial systems became dependent on automobiles. In return governments began to regulate, creating a symbiosis between government and automakers. (4th commandment).

New technologies were plentiful but they all got absorbed by the industry. Mechanical, chemical and material sciences, computation and communications were all sustaining. (5th commandment.) New fuels, microprocessors, wireless technologies; these immense evolutions did not change the structure of the industry.

As new countries became prosperous they not only adopted cars but they adopted car production. The Europeans were first with the technical invention but the US was first with mass production, followed by Western Europe, Japan, Eastern Europe/USSR, Korea, China and now RoW. (6th) Each new entrant had the advantage of hindsight and would be more efficient, at least for a while.

Low volumes were left to “luxury” brands which survived by solving a different job than transportation, namely that of status signaling. Eventually the low- and high-end merged into brand holding companies. Capacity was traded and cross-ownership, joint ventures and “badge engineering” was widely practiced. Governments kept competition at bay for national champions, mostly. (7th commandment)

Cars grew to over 1.2 billion installed base and, including commercial vehicles, reached 100 million units of production/yr. The problem that arose was that the infrastructure could not keep up. Urbanization was growing faster than motorization and land became scarce. Cars need land. Lots of land. For roads but also for parking (3 spots for every car in use, at least.) As global prosperity increased and as prosperity meant a car the struggle to find room for these modes of transport grew intense. Most users now found the car to be a constraint rather than a liberation. (8th commandment.) Parking and congestion were problems highly evident to the motorist but the externalities of exclusion of public space and emissions became highly evident to the governors who, you remember, are in a symbiotic relationship.

Clearly the pressures were building for drastic improvements in how transportation would be allocated. My response was to promote micromobility, the idea that small is better and smallest is best and that the tendency of the industry to supersize its offering in the face of increasing constraints was classic innovator’s dilemma. Incumbents could respond by rapidly changing their portfolio to include a wider variety of form factors and while they broadened the portfolio (e.g. Audi went from 4 models in the 1960s to 40 in the 2000s) they did not go below a certain line (the 500kg line). They also did not modularize their production system. Production (body-in-white, paint, engine and final assembly) remain in-house while parts are outsourced. (9th commandment) This was peculiar to me and indicated a deeper structural issue.

Instead of a pivot downward, the industry keeps chasing size, mass, volume, power, range. Most trips are short but all the engineering goes toward the long tail of highly improbable distances and loads. (10th) Always the answer to this dilemma is that you build what customers demand. Well, which customers are you asking? Under what circumstances are you framing the question? Well, never mind, let’s build electric versions of the same cars.

These constraints determined the outcomes for the industry for a century and are predicated on decisions allocating limited resources and capital based on we might call classical microeconomics; but all within a bigger political and indeed geo-political context.

So what has changed?

This classical model has one potential flaw: The assumption of capital as a limited resource. An odd thing happened in the last decade. Capital has not only become really cheap, in many cases it has reached a negative cost. This is evident in negative interest rates. When I observed this I thought something fundamental was broken. If there is so much capital that people are paying you to keep it for them then a lot of this “classical microeconomics” begins to break down.

The firms that are husbanding capital can be “disrupted” by those who squander it. Those who observe discipline and pursue efficiency can be defeated by those who are undisciplined and inefficient.

Holy cow!

This entrant’s guide is a rationalization of what governs one of the largest activities we engage in. And yet it may be undermined by an imbalance. The evidence is in the capitalization (and hence free capital availability) to entrants who have little to offer except a dream. The incumbents who thought they could sustain through technology transitions are being out-spent and having their access to what is still limited (raw materials or components) curtailed.

Need more proof? Tesla has single-handedly doubled the value of the automobile industry in a year when overall volumes and sales shrank.

That means that either there will be twice as many cars as we have now or they will be twice as expensive or they will be twice as profitable. And all that will happen really soon. We can’t have twice the cars since there will be nowhere to park them. We can’t double the price unless we double our wealth. We can’t make them twice as profitable unless we disable competitive forces and change the production system.

Or, it could be that half the assets (all the other automakers) are worthless.

Something has to give. The paradoxes multiply.

Into this will, one hopes, step Apple. Things are about to get really interesting. Stay tuned.

App Story

App Store spending was $1.8 billion in the last week of 2020, up from $1.42 billion the previous year —an increase of 27% vs. an increase of 16% from the previous year.

On 1/1/2021 App Store spending reached $540 vs. $386 million for 1/1/2020. This was an increase of 40%. The previous year’s increase was 20%.

Developers selling through the App Store have now earned more than $200 billion since the App Store launched in 2008.

The previous year’s figure was $155 billion, making the 2020 total $45 billion, a 30% increase from $34.5 billion average of the previous two years. Assuming a proportional increase, overall ecosystem transactions rose to $675 billion in 2020. This places Apple’s valuation at a 3.2 multiple of its yearly ecosystem value and each customer is valued at approximately $1400.

The history of App Store revenue and the growth rates involved is shown below.

NB: A substantial amount of App Store revenue is derived through subscriptions which now total about 600 million.

A simple summary is that the App economy accelerated its growth in 2020. This implies an economic value reaching $1 trillion/yr. within two years. It would behoove the investor to evaluate the value of Apple as a multiple of its ecosystem as well as a multiple of its customer base.

As I have repeated over time, the strength and resilience of Apple is in its customer base. Strength in terms of willingness to spend for quality and value and resilience in terms of sustained satisfaction. As that base grows to well over 1 billion people and as this billion are exposed to an increasing spectrum of value options (products, services and ecosystem) the company becomes indispensable.

This is quite the opposite of the perceptions widely held even a few months ago.

In other news:

  • Apple added 52 new territories to Apple Music.
  • Apple TV is now available on over 1 billion screens in over 100 countries and regions, providing access to buy or rent over 100,000 new release and classic movies and TV shows
  • Apple Pay is accepted at more than 90% of stores in the US, 85% of stores in the UK, and 99% of stores in Australia
  • Apple Books now draws over 90 million monthly active users
  • Podcasts are now available in over 175 countries with programming in more than 100 languages
  • More than 85 percent of iCloud users are protected with two-factor authentication

Apple in mid-2023

The Apple product line-up for 2023 is almost completely decided. This is not conjecture but simply an observation of the lead times for developing the types of products that Apple offers. The integration of hardware, software and services, often cited as the key to Apple’s sustainable competitive advantage, has a great cost: the time required to develop in an integrated fashion is far longer than the time required to develop in a modular fashion.

2.5 years is not a long time. The development process on truly new products could take 4 to 5 years. Apple Silicon, new Operating Systems and new services could all take longer than 2.5 years. The products we just saw launch this year were planned and engineered at least 2 years ago. The more integrated, the more time is needed. Wearables, AI/ML and process engineering are additional examples of long arcs of development needed to reach products.

This does not mean we can predict what these products will be. We don’t have visibility to the process but Apple management does and they will make decisions now on adjacent dependencies in the business. For example, visible efforts in planning the use of cash, the carbon offsetting, capital expenditures and R&D are all synchronized to the roadmap and hints may be read into this data.

The biggest hints are the R&D spending and the company’s capital return program. Combined they show a confidence in the roadmap that is hard to overestimate. First, R&D is reaching new highs of about 7% of sales (on a trailing 12 months’ basis, see graph below). This is almost the same as the spending on SG&A which has declined as a percent of sales from above 12% pre-iPhone.

Of course sales have increased significantly over the time shown in the graph below and the absolute spending is shown the following graph. R&D spending is over $5 billion/quarter or about $20 billion/yr. Some of the results of this will be seen in 2023 or beyond.

Next, capital returns. The company is returning almost all the cash it generates and is reducing its cash balance. It has returned about half a trillion dollars to date. Dividends paid has reached $100 billion and share buybacks about $400 billion. This is the largest capital return in US history.

The company has declared its intention to reduce net cash to zero. This means it will still have substantial cash due to loans in the form of bonds but no “excess” cash will be held by the company. This is in contrast to the strategy under Steve Jobs where he sought to keep as much cash on hand as possible due to the need to weather potential storms, Tim Cook’s Apple is being very “casual” about cash.

Steve Jobs had his reasons for hoarding cash. The company had been through periods of existential crisis. The absence of cash jeopardized its independence and it was something he vowed never to happen again.

However if that strategy would be maintained to this day, as the graph shows, the company would have cash of nearly $700 billion today. It would make Apple the world’s largest hedge fund, by far. Second only to a very few sovereign funds. Given a conservative cash preservation mandate it also means that that capital would largely go unrewarded because the return on it would have been minimal, negligible. Not to mention also the target it would paint on the company’s balance sheet.

So given the trajectory in net cash being so consistent, it’s probable that the goal of net zero will be reached mid 2023.

That leaves the question of what will happen at that time?

The answer is nothing. Nothing will happen. The capital return programs will probably be ended and additional cash generation will be paid as dividends going forward. That’s it.

Rather than suggesting a change, the capital return program (and the R&D program) suggest a lack of change, consistency. The company management is anticipating a steady capital generation rate, a steady product roadmap (with predictable growth) and a steady customer base (with predictable loyalty).

This future for Apple in 2023 may seem boring. But that’s exactly the plan. This is a plan that the company management has been making for a long time and has been executing for a long time. The plan is to be boring on the business side but exciting on the customer product side.

Consistency has been the characteristic trait of the Tim Cook era. It is a smoothing of seasonality with services. It is the clockwork delivery of product updates, regardless of macro and externalities. It is a growth in user base consistent for a decade.

It is perhaps because more people believe that consistency is the future that we have Apple’s P/E ratio now in-line with its peers. Paradoxically, being boring is what makes Apple shares so exciting today.

A Long-Lens Look at Apple and Disruption—Part 1: Is Apple Disruptive?

Recently, I met Farshad Nayeri and Dave Sundahl—formerly of Christensen Institute, now at Disruptive MBA (dx.MBA)—when the topic of M1 Macs came up. The result was a multifaceted conversation where we took a long-lens look at Apple & Disruption around three core questions:

1. Is Apple Disruptive?
2. Is Apple Overserving with M1 Macs?
3. How does Apple defy Disruption?

You can read part 1 of our conversation at A Long-Lens Look at Apple and Disruption on the dx.MBA blog.

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Post PC

Remember the Post-PC era?

The term Post-PC was first coined by MIT scientist David D. Clark in 1999 and was quickly adopted by both Microsoft’s and Apple’s former CEOs. Jobs popularized the term “post-PC” in 2007 (the launch of the first iPhone), and in 2011 when he launched iCloud, a service enabling Apple devices to synchronize data through cloud services, freeing them from dependency on a PC.

The Post-PC era was posited during the late 2000s and early 2010s presupposing a decline in the sales of personal computers (PCs) in favor of devices, phones, tablets, wearables, IoT, etc. These devices were mobile first (i.e. battery-first as opposed to plug-first), connected second and cloud-powered third. They were designed to run “apps” not “applications” and had new ecosystems with millions of developers selling through online-only stores, priced often as subscriptions rather than seat licenses.

In the last decade or so, the PC did endure an overall decline in sales while phones, tablets and wearables climbed to at least 10x volumes of the PC. But the last few months have shown a resurgence in PC sales. Certainly the necessity of working from home is the reason but will this last?

The fact is that the PC did not disappear. It certainly is still in use and there are buyers for it. There just isn’t a lot of growth or energy. There hasn’t been for a decade. The software and hardware efforts are uninspiring because the talent has moved elsewhere. The creativity, R&D budget have gone the same way.

But what about the Mac? The Mac is the PC from the company that more or less defined the Post-PC era. Would it not be the first to be sacrificed for the new future? As it stands, as the graph below shows, the Mac today is double the business it was decade ago and although it has been overtaken by wearables, it has kept ahead (after a time) of the iPad.

As it turns out the Mac is doing just fine.

The trouble with PCs, including the Mac, is that they are stubborn in how they define themselves. Like the power user, they see performance along certain dimensions. They also don’t see performance along new dimensions which devices offer with glee. For example connectivity to cellular networks (still missing in even the fanciest laptop but available on my watch.) Then there are the sensors which measure my heart rate, activity level, location, altitude, etc. Then there are cameras which on phones now boggle the mind. PC cameras are comical in comparison.

Then there is portability and usability without being plugged in.

Well, it was. With the M1, Apple has finally delivered the always-on feel of a tablet or phone and the more-than-one-day battery life. It also added a lot of neural engine horsepower and a lot of on-chip memory. Apple is delivering a system on a chip which makes the Mac more device-like in its integration. And sales are likely to rise, on the back of a great 2020 for the Mac. The form of the machine might even change with new designs being made possible by the lower heat profile and space savings.

And so I’m writing this post on a Mac. The graph you see above was created on the Mac. It’s possible to do all this my iPad and even on my iPhone but it would be harder. But I’m also willing to bet you’re reading this on a phone.

And that’s the crux of it. The PC is still the machine of choice for authoring while the device is the machine of choice for consuming and consuming will always be more popular. What the iPad has done is taken a share of PC use and in my case I do use it for some tasks like email a lot more frequently. The theory would suggest that the iPad will continue its upward trajectory while the PC would abandon the low end.

This disruption has already happened but it hasn’t been complete. The median performance band now belongs to devices but the professional will always ask for more of the performance which they see as productive while the consumer will always ask for more of the performance which they see as convenience. Here the market bifurcates.

What has been problematic with the smaller of the two markets has been the vicious cycle of lack of investment due to decreasing margins, commoditization and talent flight. What Apple is doing once again is ratcheting up the bar for the PC to make sure it’s the top choice for creative professionals. And as long as they are productive, the consumers will keep them employed if not in riches.