As automobiles become smartphone accessories, they become an interesting industry to study. Here is a recent (since 1961) history of the US market.
As previously noted, the US smartphone market has followed an almost perfectly logistic growth. The measured data (via comScore, in green below) follows a predictive logistic function (thin blue whose formula is discussed here).
The other notable market observation is how closely the iPhone follows the same pattern as the market. The red line representing the iPhone above is almost perfectly parallel to the green and blue lines which represent the overall market. The reason for this seems to be that consumers are absorbing the product in similar way to how they are absorbing the technology. The “learning model” which underpins logistic models could offer clues as to the cause. It suggests that there is a direct communication that happens between the product and the consumer.Notes:
- Note that this pattern of adoption has happened even though the product has been at least partially unavailable to the entire market until quite recently. [↩]
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The latest comScore US smartphone survey showing three months’ ending October data has been released and there were no surprises. Smartphone penetration grew to 62.5% representing 149.2 million users. I made a slight adjustment to the predictive logistic function parameters (p1 = 93, p2 = 22.5).
The correlation between predictive and actual logistic function (P/(1-P)) is shown below.
My brief appearance on Bloomberg Surveillance last week:
My appearance on Bloomberg West using an iPad to illustrate what it takes to make an iPad.
A history of retail as a series of innovations in transportation. How to think about Amazon in a continuum of changing consumer behavior. The source of Amazon’s market power and its hypothetical disruption. What would Amazon do and not do to improve its business.
(Note: This recording took place a few days before Amazon announced the drone-based Prime Air prototype service.)
A history of Cinema as seen through disruptive lenses. How did the medium evolve from novelty to experimentation to establishment of a predominant business model to concentration of power, regulation and ultimate stagnation. How to measure “performance” of a medium via the median age of the audience and how that affects the advertiser’s calculus.
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IBM Digital Analytics Benchmark (report is here) has published, for the fourth year in a row, US online shopping traffic data with a split between mobile and fixed online traffic. It reveals a pattern of consumer behavior which is quite startling: people seem to prefer to shop using mobile devices.
The data is shown below: