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Estimating iPhone sales in the US during Q4

Verizon has been the first source of data on iPhone sales for Q4. They reported 4.2 million iPhones sold. The first quarter of Verizon iPhone sales had 2.2 million units, followed 2.3 million in Q2 and 2 million in Q3. The total for the calendar year came at 10.7 million.

The total for AT&T during the first three quarters has been 9.9 million. If we assume the same 2x sequential increase in Q4 relative to Q3 as observed by Verizon we obtain an estimate of 5.4 million iPhone for AT&T.[1]

The quarter also saw the addition of Sprint to the US iPhone distribution network. Sprint is rumored to have committed to buy 30.5 million iPhones over the next four years. My estimate for the first year was 7 million, placing first quarter sell-in at about 2 million.

An approximate total for Q4 US iPhone activations results in 11.6 million. The following chart illustrates these estimates: Continue reading “Estimating iPhone sales in the US during Q4”

5by5 | The Critical Path #20: Below the (belt)line

Horace and Dan begin a journey through the financial carnival that is Hollywood and talk about the wonders they encounter.

via 5by5 | The Critical Path #20: Below the (belt)line.

During the show I refer to the diagram below which represents the allocation of costs of production for a sample of movies:

Apple's commoditization discount

When asked where Apple’s growth will come from, most analysts or observers will cite new products. As long as there are new products, then there is growth. Conversely, if there are no new products, then there will be no growth. This is such a commonly held belief that it’s axiomatic: Apple is being valued based on short-term foreseeable growth.

To be more precise, analysts value the wave of growth of every new product and heavily discount the post-growth phase assuming commoditization. There is no value assigned to Apple for extending market reach to the mass market.

Consider: Analysts currently forecast an operating income (or EBIT) of $43.3bn for 2012 and $49.7bn for 2013. That implies growth of 28% in 2012 and 15% in 2013. These growth rates are modest in light of Apple’s recent historic growth and especially 84% in 2011 on EBIT level. Much of this growth has been due to iPhone which quickly captured 4% market share in four years. To suggest 15% growth in 2013 is to suggest that Apple will not increase its phone market share by an appreciable amount. The implicit assumption in that growth figure alone is that Apple will remain a niche player.

Continue reading “Apple's commoditization discount”

Interactive Apple Analyst Data

As the quarter is now at an end, it’s time to once again review the performance of Apple’s most highly paid observers. The data set linked includes published quarterly forecasts starting quarter ending June 2008 to quarter ending September 2011. Thanks to Philip Elmer-Dewitt who collected and processed the data over several years.

Apple Analyst Data | asymco. (Requires Flash)

As with previous interactive data sets, this is based on Motion Charts “gadget” in Google Docs. Try selecting the Motion Charts tab at the bottom of the page and hit the play button.

The way this is set up now is that the origin (0,0) represents actual performance (labeled as “Oppenheimer”). Every bubble is an analyst’s performance measured as a distance from actual. The further the location of a bubble from origin, the worse the error. Placement above zero (or to the right) indicates over-estimation for Revenues (and EPS). Placement below zero (or to the left) indicates under-estimation. Color of bubble represents affiliation (professional or amateur). Size of bubble is iPhone unit error.

You can change the axes, chart type (tabs in upper right), size, colors, and track individual analysts’ performance (by checking a name checkbox). Or just download the data and analyze on your own by selecting from the Data tab.

The curious case of slowing US growth for Android

The latest data from comScore MobiLens is showing an uncharacteristic slowing in smartphone growth. In the survey period ending November, the number of smartphone users in the US was 91.4 million. This is equivalent to 39.1% penetration, an increase of 0.6% (i.e. up from 38.5% in the last period.)

The growth is equivalent to 1.4 million new smartphone users (i.e. users who switched from a non-smart device for the first time.) The problem is that this is half the growth of the previous period. The following chart shows the growth as the weekly add rate.

As you can see, the growth has fallen to a level not seen since 2010. The cause may be seasonal as last November was also a slow month. I added a three month moving average which shows that although there seems to be seasonality, the last period did not show the peak of previous periods.

To better understand what happened, I looked at the performance by platform. The following chart shows the net user gains by platform. Continue reading “The curious case of slowing US growth for Android”

5by5 | The Critical Path #19: The hiring and firing of milkshakes and candy bars

In this episode I talk with Bob Moesta, a pioneer of Job To be Done research. We go over the theory and process of understanding what products are really hired to do and ask why this understanding is so hard to come by.

In a discussion rich with examples from multiple industries Bob illustrates how marketing, design and engineering are all dancing around the question of how product should be developed.

Could the universally accepted compartmentalization of corporate functions be a root cause of product failure?

via 5by5 | The Critical Path #19: The hiring and firing of milkshakes and candy bars.

You can follow up with Bob here: The Re-wired group.

Discerning Apple's international product positioning through the big Mac index

Thanks to all those who contributed to the big Mac index there is a substantial amount of pricing data available in one location.

The analysis that I hoped to perform on the data was to see if Apple was pricing specific products differently in international markets. It was prompted by some apparently anomalous pricing of the iPhone 4S in Brazil.

To summarize, the idea is to calculate the “expected” price of an Apple product by taking the untaxed US price and adding duties and tariffs and taxes to determine what that product “should” cost in another country. Then taking the difference between this “expected” price and the actual price to determine if Apple is using pricing to signal in a particular market.

The analysis basically eliminates the effect of government on price and leaves currency and actual pricing signals from Apple as variables.

The analysis is not simple because there are many obscure tax rules. Some products are taxed differently in the same country. I have not completed the country-level analysis but have been able to see some averages over the countries reported (total of 45 reports.)

The following chart shows the average deviation from “Expected” as a percent:

Here are some potential interpretations of this data: Continue reading “Discerning Apple's international product positioning through the big Mac index”

5by5 | The Critical Path #18: Who's Paying for My Lunch?

Dan and Horace ponder why some companies are more mysterious than others. We ask whether transparency and simplicity of business models is a sign of strength or weakness. We compare the measurement, creation and capture of value and why we should celebrate the mortality of businesses.

via 5by5 | The Critical Path #18: Who’s Paying for My Lunch?.

Notes:

Who is being reasonable now?

Last week Horace wrote about the apparent “reasonableness” of analyst Apple estimates. He explained how the consensus for Apple’s growth was always deeply pessimistic because its performance could be argued to be anomalous. It was just too good to be true. We reproduce the chart here:

The estimates look like characteristic “tell-tales” of a company running strong into the wind.

This conservatism in the face of rapid growth sounds “reasonable” but is it always practiced? And what about the ability of this conservative strategy to predict dramatic changes in growth? To test, we started to look at the predictions for RIM. RIM has also enjoyed strong growth over a similar time frame as Apple. How did analysts predict its performance? The following chart was prepared using the same technique as the one for Apple[1]. Continue reading “Who is being reasonable now?”

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