Category Market

Apple Watch Keeps Top Gift Spot Ahead Of Black Friday

The Apple Watch continues to hold the top spot among products that will be hot this holiday season, as predicted by the IBM Trend app.

Source: Apple Watch Keeps Top Gift Spot Ahead Of Black Friday

The Apple Watch scored 100 out of 100 on the “IBM Watson Trend Scale”. According to various surveys, about 100 million people will shop this Thanksgiving weekend in the US. One wonders how many purchases by 100 million shoppers merit a score of 100/100.

My estimate for units shipped has been 20 million in the first calendar year. About 7 million have been sold in the first two quarters. That leaves 13 for the holiday and Q1 (which includes Chinese New Year.) I still like these odds.

To learn more about the reasoning around this estimate and hear additional supporting data, join us at Glance conference.

Why does Apple TV deserve to exist?

Since writing Peak Cable six months ago, surveys, research and analysis have contributed to the themes of unbundling the TV package. The data under scrutiny is, as usual, the data that can be gathered. Unfortunately the data that can’t be gathered is where the insight into what is happening may lie. For instance, what matters for an entertainer is not how much you’re watched but how much you’re loved. Measuring love is done poorly with data on payment for subscriptions.

A better proxy might be time. Liam Boluk makes the point in his post that “focusing on cord cutting or even cord shaving largely misses the point.” Don’t follow the dollars, he says, follow the time or engagement. “Relevance” is what matters.

His data shows how linear TV has fallen by roughly 30% among the young (12-34) in the last five years. The trouble for the TV bundle (and advertisers) is that this is the most culturally influential group. They are also the group which will grow into the highest income group over the next decade. And this group does not love TV.

We have to remember that it was the youth who drove early radio, TV and consumer electronics markets. Those young are now the old which still cling to the old media, served by companies that grew old with them. They are the “high-end” customers with which Nielsen itself has grown. They have the most money to spend and they are the targets for the ads[1]

Paying $150/month to watch incontinence and erectile dysfunction ads—at a time not of your choosing—is preposterous for the young. They may like the programs but not the way they are packaged, delivered or interrupted. They are not smarter than their parents. They, like their parents, took to new technology more quickly. What makes the technology new is also what lets its makers separate the content from its delivery. These new technologies allow “modularizing” or unbundling that which was was integrated/bundled and thus allow their developers to focus on the customer’s real jobs-to-be-done.

Unsurprisingly, incumbents have responded by throttling access to original programming–an asset over which they still exert influence as distributors. Netflix and Amazon are taking the path of responding with their own blockbuster productions. Although Silicon Valley has more capital to deploy than Hollywood  this battle of attrition is by no means one that incumbents will win, and generally, it’s not going to be pretty.

Tweaking the nose of the incumbent might not be the way to establish asymmetry. The better tactic may be to help the system survive but offer a “short-term alternative”. This is how iTunes took on and won Music. When Napster and file sharing created a clear and present danger to the industry, Apple’s approach of a controlled alternative allowed the industry to finally move to a digital download model.

  1. no longer the Pepsi generation, they are the Depend and Viagra and pharmaceuticals generation []

Meaningful Contribution

What if Apple did make a car? How significant could their products be? What would it take to influence the industry’s architecture?

The global market is forecast to reach 88.6 million vehicles in 2015 and there are many ways to segment it. One could look at geography or at product configurations or the emergence of new powertrain technologies.

One could also look at the participants.

In 2014 Toyota was the top selling automaker with a total sales volume of 10.23 million vehicles. The following graph shows the leading 15 producers and the percent of total production.

Screen Shot 2015-09-25 at 9-25-2.19.47 PM


How quickly will ads disappear from the Internet?

I was always bemused by the notion that the Internet was able to exist solely because most users did not know they could install an ad blocker. Like removing Flash, using an Ad blocker was a rebellious act but one which paid off only for early adopters. But like all good ideas, it seemed obvious that this idea would spread.

What we never know is how quickly diffusion happens. I’ve observed “no-brainer” technologies or ideas lie unadopted for decades, languishing in perpetual indifference and suddenly, with no apparent cause, flip into ubiquity and inevitability at a vicious rate of adoption.

Watching this phenomenon for most of my life, I developed a theory of causation. This theory is that for adoption to accelerate there has to be a combination of conformability to the adopter’s manifest needs (the pull) combined with a concerted collaboration of producers to promote the solution (the push). Absent either pull or push, adoption of even the brightest and most self-evident ideas drags on.

Ad blocking offers a real-time example of this phenomenon. On desktop or even laptop computers ads were tolerable and the steps required to naviagate in order to implement effective[1] blocking were non-trivial. In addition, no platform vendors were keen to promote products which hindered revenues for their most important ecosystem partners.

Ad blocking as an activity had neither the pull nor the push.

  1. By effective I mean a combination of whitelists and customizations []

The new switchers

During the last quarterly earnings call, Tim Cook said that Apple has seen the highest switching rate from Android ever. That there is switching isn’t surprising. We’ve seen many surveys which show higher loyalty with iOS than with Android. But it’s been very hard to spot the evidence in the data which is visible publicly. Both iOS and Android are adding users and sales for both platforms are still increasing.

The switching effect is easier to discern when the market is not growing overall. In that situation one platform’s growth has to be at the expense of another. However, some markets do show evidence of “churn” in users.

Screen Shot 2015-08-10 at 8-10-12.52.52 PM

Consider the ComScore data on US platform users (above). If we look at the last six months’ data[1] we can count that there are about 8.2 million more Americans using iPhones than there were six months ago. At the same time, there are 1.6 million Android users. One million users left the BlackBerry platform and about 700,000 left Windows Mobile. The data also suggests that the total number of first-time smartphone users is about 8.3 million.

  1. these data are actually three month averages []

What next for iPad?

ComScore suggests that there are 100 million tablet owners in the US. On a per capita basis that implies penetration of about 30%. As a percent of mobile phone subscribers (above age of 13) that implies 40%. As a percent of smartphone users that implies 43%. As a percent of iPhone users that represents 47%. As a percent of households assuming one device per household that implies 85% penetration. By another measure (Pew) household penetration is around 50%.

Regardless of the difficulty in defining what is the correct “addressable market”, the more important question is whether tablets will be an ubiquitous object. Perhaps what we are seeing in the US is something similar to the MP3 player market or video game console markets where penetration saturated at around 50%. Perhaps tablets will reach PC levels which are closer to 80% of population or perhaps they will reach phone levels which are above 90%. The reason we can’t answer the question of ubiquity easily is because competing solutions can carve the usage out of a category “disrupting” it with alternatives.

The idea that jobs are the segments into which products fit and not demographics or product attributes is key to understanding this migration. The reason phones have subsumed more jobs onto themselves is because they have a rapid rate of evolution and because they have larger scale of economy and because they are conformable to our life spaces. As phones get better they take on more jobs and some of those jobs are those of tablets. The MP3 did not become ubiquitous because the phone took its job. Same for the video game and same perhaps for the PC and tablet.

Where are Maps going?

At the 2015 WWDC Apple stated that it receives 5 billion requests per week for its maps service. It also said that Apple maps is used 3.5 times more frequently than “the next leading maps app.”

These two data points are the total number of data points we have about the global maps market. Neither Google nor Nokia provide usage or share or performance data. Regardless, commentary on the usage, share and performance of Apple Maps has been abundant for the three years since its inception.

The data presented allows us to make a few estimates for the first time and we can hope that additional data can allow a picture to emerge of where maps are going.

With these first two data points we can finally make some estimates. But some assumptions are still needed: We need to assume that the “next leading maps app” is Google Maps. Although there are other maps apps on the iOS platform they are probably insignificant and it’s a two-horse race between Google and Apple on iOS.

This means that the 3.5:1 split in usage results in a 78% share for Apple Maps and a 22% share for Google. If we assume that there are about 400 million iOS users of maps[1], it leads to about 90 million Google Maps users on iOS and about 310 million Apple Maps users on iOS.  This includes iPad.[2]

Given that Google also reported 1 billion downloads in 2014[3] we can assume between 25% to 33% Apple Maps “market share” of usage.

  1. Note that not all iOS users are maps users. Maps are not used by all users []
  2. We are excluding OS X use of Maps. []
  3. though not necessarily all of these downloads lead to active use, obviously []

Schiller’s Law

We know how many iPhones Apple ships but we don’t know exactly how many of each model. We can try to come close in such estimates of “mix” by looking also at the market pricing of the phones and the average price Apple obtains[1]

Combining what we know with some guesses allows some of us to estimate the composition of iPhone models in any given quarter’s sales. Here is a graph showing my estimates:


Screen Shot 2015-05-22 at 2.53.36 PM

Having this, we can then assess how each generation of iPhones has performed. Remember that although we had a new iPhone for each of the last eight years, there are only 5 generations in total. Starting with the 3G (second generation) the generations were two yearly product cycles long.

The resulting estimates for generational growth are shown below. 

  1. ASP = Revenue/Units shipped. However, note that there are deferrals in revenue as part of this. []

How many iOS devices will Apple Ship in the next six months?

Of the $42.5 billion Apple spend buying capital assets[1] more than half was acquired in the last three years. Net of depreciation these assets are currently worth $20.1 billion and the spending rate is about $12 billion per year.

This strategy of spending on capital assets is primarily in support of its particularly integrated approach to its product strategy. The purchasing of tooling for product manufacturing gives many benefits, including ability to deliver uniquely differentiated hardware, a predictable ramp and availability of parts throughout the product lifecycle.

Screen Shot 2015-05-05 at 3.02.04 PM

One additional benefit (for us) is that we get to inspect the allocation of resources prior to production and therefore we can more easily forecast the product’s supply. Spending on tooling happens in advance of production and the company also provides full year predictions of its spending.

The fiscal year forecasts relative to actual spending is shown below. Note the correlation with iOS units shipped one quarter after the spending was booked.

Screen Shot 2015-05-05 at 3.08.24 PM

After reporting its second quarterly earnings, we received an update on what amount to half of the full year’s spending giving us only two more quarters of variability. The current projections for the next two quarters imply about $2.8 billion per quarter spending.

Screen Shot 2015-05-05 at 3.05.29 PM

The pattern from previous years is shown below for comparison. Note the Even/Odd year patterns.

Screen Shot 2015-05-05 at 3.05.35 PM


The company also offered revenue guidance for FQ3 and therefore we can even make an educated guess on the next data point (57 million iOS devices) on the following graph:



Screen Shot 2015-05-05 at 3.20.52 PM


The result is likely to be 120 million shipped between April and September.

It’s remarkably predictable.


  1. Includes land and buildings $5.6b, Machinery, equipment and internal-use software $32.1b and Leasehold Improvements $4.7b []

How will we measure Apple’s Watch success?

It won’t be easy. The company will not be reporting the Watch segment revenues or (presumably) unit sales and therefore we won’t have an accurate unadulterated view of the business. In addition, the large number of products in the mix and wide price variance means that it will be difficult for analysts to determine demand and price.

There is a hidden benefit to not having this data. All data is a creation and it tends to lead thinking in directions led by whatever is being measured (and whoever chose those measures and their motives). And yet without data there is no evidence and no credibility. In other words: You can’t manage without measurement but you can’t be sure what to measure.

The analyst is then faced with a requirement to have good taste or at least judgement about what to measure. This judgement is based on experience and good theory. Given that, what could we measure to determine whether the Apple Watch will be a success?

Here are some suggestions:

  1. Language. Measure whether “Watch” will come to mean “Apple Watch”. “Phone” has come to mean not only “smartphone” but also all mobile/cellular phones and not just things used for calling but things used for all manner of information. This is a great test because the theft of semantics can only be accomplished through a degree of ubiquity of influential mindshare. Incidentally, the brand may well have been designed to do just that.[1]
  2. A measurable and significant reduction in the use of the iPhone. The Watch peels off uses from the iPhone and therefore the more it peels off, the less remains. However, that which remains will be more uniquely valuable to the incumbent. This is the process of carving and erosion that the PC experienced vs. mobile devices in general.
  3. An increase in the mix of large-screen iPhones. As iPhones are removed from pockets more rarely, the larger version might be more comfortable to carry and more useful to use for the immersive tasks that are outside the scope of Watch.
  4. An overall increase in iPhone sales beyond the foreseeable trajectory. This would suggest switchers from Android would be drawn to the platform purely for the value of the “accessory”. Note that this is not inconsistent with the lower usage and higher spec mix measurements.
  5. Apps uniquely targeting the Watch. It’s hard to imagine how this will develop as it involves millions of creative minds, but as smartphones created new economic value through the solving of new jobs to be done, the Watch should do the same. As a side-effect it should lead to new empires (or at least Unicorns) being formed around Watch use.
  6. Iteration. How quickly and deeply will the product be improved? Basic accessories like headphones and Apple TV have a leisurely update cycle. Smarter devices are faster. The cycle time of iteration should indicate how seriously Apple takes the platform and that itself should be fueled by positive consumer sentiment for the product.

These indicators are vague and the data will be weakly signaled but in many ways it will be more meaningful than any financial performance figures.

  1. It leaves open the question as to what watches as currently defined will come to be known as. []