Category: Industry

All theoretical and empirical diffusion studies agree that an innovation diffuses along a S-shaped trajectory. Indeed, the S-shaped pattern of diffusion appears to be a basic anthropologic phenomenon.

This observation dates as far back as 1895 when the French sociologist Gabriel Tarde first described the process of social change by an imitative “group-think” mechanism and a S-shaped pattern.1 In 1983 Everett Rogers, developed a more complete four stage model of the innovation decision process consisting of: (1) knowledge, (2) persuasion, (3) decision and implementation, and (4) confirmation.

Consequently, Rogers divided the population of potential adopters according to their adoption date and categorized them in terms of their standard deviation from the mean adoption date. He presented extensive empirical evidence to suggest a symmetric bell shaped curve for the distribution of adopters over time. This curve matches in shape the first derivative of the logistic growth and substitution curve as shown below. 

In the graph above I applied the Rogers adopter characterization to the data we have on the adoption of smartphones in the US. The latest data covering September is included.

Continue reading “The diffusion of iPhones as a learning process”

1. Tarde was probably influenced by mathematician Pierre François Verhulst who first published the logistic function in 1845 [↩]

Microsoft spent $2.6 billion for Advertising in the fiscal year ended June. Apple spent $1.1 billion in its fiscal year ended October.

Other companies will report their full year ad spending later but their previous years’ spending is shown below.

I added a second graph showing the percent of sales that each ad budget represents. Note that Coca Cola retains the crown as the most prolific advertiser when it comes to budgeting.1

Continue reading “Do ads work? The ad budgets of various companies”

1. Think of it as 7 percent of every Coke purchase going to pay for the ad that presumably got you to buy it. [↩]

In fiscal 2013 there were 395 million visits to Apple retail stores. In 2012 there were 372 million.

The difference is approximately the population of Australia. This was in addition to the population of the US and Canada already passing through. Although this is a fun way to think about total traffic, it does not reflect performance of the stores themselves since new stores are always being opened. 21 new stores in 2013, to be precise.

The better benchmark should be the number of visitors per store.

This shows that, except for seasonal peaks, the visitors per store per quarter has been a fairly steady 240k since mid-2010. What’s more, this rate was also remarkably steady at around 160k/store/quarter from 2007 to 2010.

So what caused this quantum jump1 in traffic? Continue reading “The Quantum Leap in Retail”

1. “Quantum leap” is often used to mean “giant leap” but in the original usage it meant a specific, discrete jump [↩]

Apple’s latest product launch (new OSX, iPads, Macs and iWork/iLife) came with a change in pricing for software. OS X and iWork and iLife and updates are now made available free on new Macs and, in the case of the suites, on iOS devices as well.

Recall also that iOS updates are now free as well and that OS X had been reduced in price from about $129 to $29 with Snow Leopard in August 2009 and to $19 with Mountain Lion in July 2012. The iSuites have also dropped in price over time so the pattern of evaporating software prices is long-running.

But how fast and what is the impact? The historic performance Apple’s Software business is not easily determined since it was always blended with additional businesses. Until September of last year, Software was reported as part of “Software and Services” and since then as part of “iTunes, Software and Services.” Some assumptions allow the following picture to be drawn:

One additional wrinkle to the Apple software story is that OS X and iWork/iLife are not all the software titles available. Apple’s software includes Pro apps as well as the non-free OS X server. The non-free software US prices are: Continue reading “The value of zero-priced software”

The analyses of adoption of smartphones in the US and EU5 are remarkably consistent with each other. They also turn out to be consistent with the valuation of Apple.

I show the stages of adoption overlaid with the derivative of the Logistic Function and Apple’s enterprise value. The derivative of the Logistic Function shows the speed of adoption, peaking at the inflection point when adoption ceases to accelerate and begins to decelerate. Continue reading “The iPhone company”

Thanks to Symbian, the EU5 countries (France, Germany, Italy, Spain and the UK) had an earlier start in the conversion of phone usage from non-smart to smart devices. According to published comScore data, in July 2010 the EU5 were at 26.6% penetration of smartphones and the US was at 22.8%1.

However, with the aid of mobile operator subsidies, by the beginning of this year, the US caught up. According to comScore EU5 reached 57% penetration in March 2013 while the equivalent figure for the US was 58%.

Using the logistic curve model introduced last week, it’s possible to get an approximate categorization of the adopters of the technology:

As with the previous analysis, the graph identifies the following dates: Continue reading “When will the European Union Five reach smartphone saturation?”

1. The population is defined as adults using phones for themselves. Meaning it excludes children and phones purchased by companies. [↩]

Gartner reported that PC shipments totaled 80.3 million units in Q3. Subtracting an estimated 4.4 million Macs yields an estimated 75.9 million Windows PCs.1

This total is lower than the total shipped in the same period of 2008.

The graphs above show the Continue reading “The Five Year Plan”

1. The total will be less than this as some PCs will not ship with Windows [↩]

In May 2012 I wrote:

The pattern may be that companies either have short post-trauma lives of about two to three years or relatively long post-trauma lives lasting 4 to 5 years. What determines this life expectancy and how long do RIM, Nokia and LG have?

via Post-traumatic life expectancy of phone vendors | asymco.

These comments came right after BlackBerry (then RIM) announced a loss and thus entered what I called the “post-traumatic” phase of its existence.1 The observation I have been making is that once a company begins to generate negative operating margins from phone sales, that phone business never recovers.

The question then becomes one of gauging how long they have before the business is sold, dissolved or merged. Since that update, both Nokia and RIM have tentatively agreed to be sold. If the sales go through then we can update the graphs as follows:

[Graph note: solid bars in the second graph indicate companies which exited and thus the duration of life post-trauma. Continue reading “Estimating HTC's post-traumatic life expectancy”

1. The analysis began earlier, in June 2011 [↩]