Category Market

The job the iPhone is hired to do

In the latest quarterly report Apple changed how it reports product revenues. In previous quarters the iPhone and iPad were reported including accessory revenues while iPod accessories were reported under “Music” revenues.

“Under this new format revenue from iPhone, iPad, Mac and iPod sales is presented exclusive of related service and accessory revenue […] revenue from all Apple and third party accessory sales is presented as a single line item [Accessories.]“

Apple provided a document showing re-classified product summary data.  By measuring the difference between original revenue and re-stated revenue per product we can determine how much service and accessory revenue was being attached to each product.

I did this for two quarters as a sample:

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The analysis shows that the iPhone has been receiving about $15 of accessory attached value and the iPad about $25. Interesting trivia, but how is this insightful?

Consider the impact on this analysis of revenues/unit shipped:

The iPhone MOQ

[Kaoru] Kato, president of NTT DoCoMo Inc., said that the firm would want to add the iPhone to its lineup of serviced smartphones if it could form a mutually beneficial contract with Apple, Inc.

Apple requires that carriers servicing its devices sell a fixed amount per year. Katō said that his company could handle such quotas if iPhones accounted for approximately 20%-30% of its overall smartphone sales.

via NTT DoCoMo President Interested in Servicing iPhone — BrightWire

When thinking about an iPhone launch, especially with a new operator, the crucial question is what is the minimum order quantity (MOQ). Some of the iPhone production is sold direct (as in the case of orders coming from Apple’s online store) but the majority of units are sold via operator who order in batches.

This issue came to light when Sprint’s order was leaked in late 2011.  I discussed the order size at the time and put it in context. I concluded that Sprint MOQ was on average 7 million/yr., ramping with 4, 6, 9 and 12 million over a four year period.  I concluded that this was not a particularly aggressive gamble.

Data published since then shows that Sprint actually sold 6.3 million during the first year, well ahead of my expected minimum order of 4 million and above even the expectations for the second year of sales. So far then Sprint and Apple gauged minimum demand quite accurately.

I also showed that the Sprint MOQ was probably indexed off their sub base. I suggested that, based on subs data at the time, Sprint was committing to roughly 13% of its subs buying an iPhone every year. This was indexed off the data showing that 17% of AT&T subs were buying iPhones every year and 10% for Verizon. (I also assumed that this run level would be ramped over time).

The updated totals for the 12 months ended October 2012 are 19% of AT&T subs purchased an iPhone, 12% for Verizon and 12% of Sprint. The performance is shown in the following graph:

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Which leads us to think about how the MOQ for the iPhone is calculated. If we assume Sprint and Verizon performance is typical it would imply that an operator like DoCoMo would be required to purchase iPhones at the rate of about 10% to 12% of its sub base each year, modulated to some degree by a ramp.

NTT DoCoMo had 60.7 million subs in September 2012. 10% is about 6 million. Is Mr. Kato’s quote above of 20%-30% of smartphone sales consistent with this?

In an earlier interview (in July) Mr. Katō also stated that the target for smartphone sales in the year to March 2013 was 13 million. 30% of that would be 4 million units.

This suggests that the iPhone MOQ for DoCoMo is only about 6% of subs. (4 million) Perhaps this is the basis of negotiation for an iPhone deal. Apple may have held out for 10% subs/yr. with Sprint on the basis of performance of the iPhone in the US but might be willing to settle for 6% subs/yr with DoCoMo, at least for the first year.

The MOQ figure as percent of subs for China Mobile would also be an interesting point of debate.


Measuring iPhone 5 vs. iPhone 4S availability

In 2011 Apple increased the availability of the iPhone by adding operators. In 2012 Apple increased availability by bringing the phone to operators more quickly. The question is: how much did iPhone 5 availability increase, exactly?

There is a way to find out. As an approximation, Apple periodically reports the availability of new iPhones by country. For example, Apple stated that they reached 100 countries for the iPhone 5 before 2012 ended. They also gave similar launch data for the iPhone 4S. Graham Spencer did a good job showing how country roll-outs changed over time.

However, country-level availability is not ideal because countries vary greatly in their ability to absorb iPhones. Announcing availability in Mauritius is not nearly as important as announcing Madagascar. A better measure would be to track the countries’ populations being added, or, better still, the populations which subscribe to operators who have a distribution contract with Apple.

Which is what is shown in the following graph:

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Getting to know the meaning of sisu

Nokia announced 4.4 million Lumia smartphones were shipped in Q4. That’s about 14 million since the Lumia line was launched a year earlier. It isn’t however nearly enough to replace the lost sales from Symbian. One year earlier Nokia shipped 19 million Symbian phones in the fourth quarter and the year before 28.3 million. The history of smartphone sales from Nokia is shown below:

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I repeated the forecast I drew up in February 2011 when the platform switch was announced. That forecast was based on the company stating that 150 million Symbian phones would still be shipped. Symbian fell far more rapidly than I (and Nokia) expected and to date only 98 million have shipped. The last quarter’s 2.2 million seems to be so low that it will be hard to imagine the platform lasting more than a few quarters.

A more complete picture of the iTunes economy

As it did yesterday, on occasion Apple reports the cumulative total downloads and payments to developers. Since this is done in variable time intervals, it makes analysis of the value of the app store difficult.

But not impossible.

The provision of developer revenues means we can determine the pricing of apps. The pricing of apps and the download totals allows us to determine the revenue of the store. Using the time stamps of the reports allows us to determine these quantities over time.

I’ve combined the data we have so far into the following graph.

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It shows three quantities (on three separate scales) at a monthly resolution:

  1. Download rate (in millions/day, interpolated from download totals)
  2. Payment rate to developers (reported change in payment to developers/reported time interval)
  3. Resulting revenue per download (in red, trailing average over a 10 month period)

Having a price and quantity of app downloads allows for a complete picture of App Store revenues over time, shown below:

App Store Download Rate Forecast

Apple reported over 2 billion unique app downloads (excluding re-downloads and updates) in December. The total downloads reached 40 billion, payments to developers reached $7 billion and the total iTunes accounts reached one half billion.

The total downloads is shown relative to total songs is shown in the following graph:

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Although we have not received an update on song downloads for some time, it’s probably safe to assume that twice as many apps have been downloaded as songs.

This data can be reduced to a download rate:

When will smartphones reach saturation?

50% penetration for smartphones in the US turned out to be fairly predictable. I tracked my predictions based on comScore data and the results are shown in the following graph.

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I began making predictions in May 2010 and updated the estimate every month since. As the chart shows, the prediction converged to early September 2012 by early 2011. The actual date was sometime in late August 2012.

How much do maps cost and what are they worth?

How much does it cost to have the world’s best maps?

The answer may seem simple: $8.1 billion.

That was the cost to Nokia in cash for buying Navteq in October 2007. It would seem that buying that asset (or another one like it) is a cut-and-dried solution to anyone needing a mapping “solution”. But it’s not an answer that is either complete or explanatory of how mapping solutions are valued.

Navteq was not priced as a database for an app. It was a business which was expected to create licensing revenues and profits[1]. The actual price for this business net of cash was $7.7 billion but the following graph shows the net sales and operating profits since Nokia began reporting its performance:

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The blue area represents the difference between sales and costs and hence the operating expenses–the payments needed to “keep the lights on”.

Calibrating launch performance for the iPhone in China

When the iPhone 5 launched Apple promised availability in 100 countries before the end of year. This was a very aggressive plan given the gradual release of previous products. Last year the iPhone 4S only arrived in China (along with 21 additional countries) on January 13th. This year it was almost a month earlier.

Apple also announced for the first time this year first weekend sales for China: 2 million. This is, as far as I know, the first weekend sales data for a single market outside of the US. The time span was three days and therefore the daily sales rate was 2/3 million per day.

The following chart compares the launch performance for the launches which Apple reported:

Screen Shot 2012-12-17 at 12-17-2.44.04 PM

If we normalize by population,

Below the Surface

Early data shows that the PC market has not experienced a “pop” from Windows 8. Market watchers have been anticipating this pop since every previous version of Windows has led to a surge in shipments. PC vendors have also been hoping for this to lift their volumes. Volumes have been stagnant for a while, as the following chart shows:

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If we combine the traditional PC and tablet markets—what I refer to as “large and medium screen PCs”— there has been growth. However the growth is all due to the tablets. When seen in a share split (blue tablets vs. brown Windows PC’s) the shift toward tablet computing is clear.