A recent presentation by César Alierta, Telefónica chairman and CEO, illustrates the significant issues even the relatively-robust mobile phone business faces these days. Consider organic revenue growth, the rate at which a tier-one carrier is able to grow revenues on its existing customer base and lines of business, without making an acquisition.
Telefónica grew at an organic rate of about 2.5 percent in 2010, as did Vodafone. AT&T grew revenues organically by a bit below one percent.
And those were the fortunate companies. France Telecom saw negative organic growth of about 1.25 percent. Deutsche Telekom saw two percent negative organic growth in 2010. BT saw negative three percent organic revenue growth that same year. Telecom Italia saw organic revenue shrink about 3.8 percent.
Saturday, April 23, 2011
Telefonica Illustrates Mobile Communications Carrier Challenges and Trends
Gary Kim has been a digital infra analyst and journalist for more than 30 years, covering the business impact of technology, pre- and post-internet. He sees a similar evolution coming with AI. General-purpose technologies do not come along very often, but when they do, they change life, economies and industries.
Users Likely are Downloading More Mobile Apps Than They Think
Consumers often incorrectly estimate their habits and behaviors. Yankee Group researchers say consumers report downloading about two apps a month. But tracking software installed on a test group by Yankee Group researchers revealed that respondents actually downloaded an order of magnitude more applications for their smartphones than the consumers reported by recollection.
Android owners download an average of more than 20 apps per month, while BlackBerry owners download only two. That is a finding consistent with other surveys. This behavior may be explained by the variety of apps available, Yankee Group researchers say: Android app stores offer more than 130,000 apps, while RIM’s App World offers only 23,000.
Android owners download an average of more than 20 apps per month, while BlackBerry owners download only two. That is a finding consistent with other surveys. This behavior may be explained by the variety of apps available, Yankee Group researchers say: Android app stores offer more than 130,000 apps, while RIM’s App World offers only 23,000.
Consumers remove an average of 11 apps each month. In fact, the tracking software shows consumers remove 73 percent of the apps they download.
Labels:
mobile apps,
smart phone
Gary Kim has been a digital infra analyst and journalist for more than 30 years, covering the business impact of technology, pre- and post-internet. He sees a similar evolution coming with AI. General-purpose technologies do not come along very often, but when they do, they change life, economies and industries.
Here's a Concrete Marketing Question Mobile Payments Could Help Answer
That "women control 80 percent or more of consumer spending" is a commonplace bit of marketing rules of thumb that researchers now say might not be true.
In a survey conducted last year of nearly 4,000 Americans 16 and older by Futures Co., a London consulting firm, 37 percent of women said they have primary responsibility for shopping decisions in their household, while 85 percent said they have primary or shared responsibility. The respective figures for men were similar: 31 percent claimed primary responsibility while 84 percent said it was shared.
In a survey conducted last year of nearly 4,000 Americans 16 and older by Futures Co., a London consulting firm, 37 percent of women said they have primary responsibility for shopping decisions in their household, while 85 percent said they have primary or shared responsibility. The respective figures for men were similar: 31 percent claimed primary responsibility while 84 percent said it was shared.
That's one issue mobile payments capability probably could help answer more definitively. It might never be possible to precisely identify how "responsibility, participation or influence" actually operate. But it should be possible to "prove" who actually made a purchase, with greater accuracy, once mobile payments become popular.
Sure, there are tons of privacy issues to be settled before personalized data can be gathered and analyzed. In principle, however, an actual purchase will be a quantifiable bit of data quite a lot more accurate than a survey respondent's guess about what percentage of the time "influence" or "decision making"occurs.
Recent surveys tend to show, as often happens, that claimed buying influence is more than 100 percent. That's the logical outcome of fuzzy consumer estimations. But transaction data is "hard" evidence, untainted by errors of recollection or opinion.
Gary Kim has been a digital infra analyst and journalist for more than 30 years, covering the business impact of technology, pre- and post-internet. He sees a similar evolution coming with AI. General-purpose technologies do not come along very often, but when they do, they change life, economies and industries.
"We'll give you the phone and service, it's the data we want"
Some of the more-important revenue streams communications service providers have uncovered and discovered have been of the accidental sort. Some enhanced services, such as caller identification (caller ID) were essentially a byproduct of a conversion from analog to digital switching. The switches needed that information to work, but new features were possible as a consequence.
Many consumers considered "push button" phones to be a premium device when the transition to digital happened. Engineers would simply have said that using DTMF tones was simply a better way of inputting number information to switches that now were digital, in fact computers rather than electrical appliances.
There now seems a glimmer of understanding that among the next great wave of value provided by mobile networks, sensor data might prove an unexpected boon. There already is talk of the growing value of "machine to machine" networks, of course, where remote sensors such as meters and gauges of various sorts communicate with servers located elsewhere.
But there is something of potentially equally-interesting value growing, and like M2M, will be a business-to-business value, with potential revenue streams that match. "At Northeastern University in Boston, network physicists discovered just how predictable people could be by studying the travel routines of 100,000 European mobile-phone users," the Wall Street Journal reports. "The scientists said that, with enough information about past movements, they could forecast someone's future whereabouts with 93.6 percent accuracy."
That, of course, requires the permission of the users tracked, as the data is personally identifiable, so there is an opt-in requirement.
In other cases, anonymous data might be equally useful, even when anonymous. Researchers are studying user data, in aggregate, to understand social effects, influence, the spread of ideas and trends.
Of immediate value to mobile service providers themselves are the business-relevant social effects uncovered in one study. By mining their calling records for social relationships among customers, several European telephone companies discovered that customers were five times more likely to switch carriers if a friend had already switched. The companies now selectively target people for special advertising based on friendships with people who dropped the service. That's a practical illustration of applying knowledge about social influence for a very concrete business problem.
Marketers try to use knowledge about social influence to reach people who, their social graphs indicate, can persuade others in their social networks, and who have bigger social networks. It takes little to imagine that firms will be eager to strike deals giving them access to opt-in data from mobile service providers that help them identify and reach such people.
All of which suggests that data mining for patterns could develop into quite a value driver and revenue stream. Perhaps it always will be a stretch to imagine a time when such data is so valuable that a service provider can afford to give away devices and services in exchange for opt-in rights to track and sell such information. But it isn't hard to see that it could become a major revenue stream, either.
That, of course, requires the permission of the users tracked, as the data is personally identifiable, so there is an opt-in requirement.
In other cases, anonymous data might be equally useful, even when anonymous. Researchers are studying user data, in aggregate, to understand social effects, influence, the spread of ideas and trends.
Of immediate value to mobile service providers themselves are the business-relevant social effects uncovered in one study. By mining their calling records for social relationships among customers, several European telephone companies discovered that customers were five times more likely to switch carriers if a friend had already switched. The companies now selectively target people for special advertising based on friendships with people who dropped the service. That's a practical illustration of applying knowledge about social influence for a very concrete business problem.
Marketers try to use knowledge about social influence to reach people who, their social graphs indicate, can persuade others in their social networks, and who have bigger social networks. It takes little to imagine that firms will be eager to strike deals giving them access to opt-in data from mobile service providers that help them identify and reach such people.
All of which suggests that data mining for patterns could develop into quite a value driver and revenue stream. Perhaps it always will be a stretch to imagine a time when such data is so valuable that a service provider can afford to give away devices and services in exchange for opt-in rights to track and sell such information. But it isn't hard to see that it could become a major revenue stream, either.
The fear is that such data could be stolen, a genuine concern, or that personally-identifiable information already is being shared with third parties, a concern that might strike some of us as far fetched, though the danger continues to exist.
But if researchers are correct, mobile phones will have immense new value as sensors. The data the sensors monitor will have value for marketing, sales and promotion, as well as many non-profit endeavors. You can say its one application of M2M, or you might argue it is related but separate. Either way, mobile sensor data looks like a huge potential deal.
But if researchers are correct, mobile phones will have immense new value as sensors. The data the sensors monitor will have value for marketing, sales and promotion, as well as many non-profit endeavors. You can say its one application of M2M, or you might argue it is related but separate. Either way, mobile sensor data looks like a huge potential deal.
The Really Smart Phone - WSJ.com (subscription required)
Gary Kim has been a digital infra analyst and journalist for more than 30 years, covering the business impact of technology, pre- and post-internet. He sees a similar evolution coming with AI. General-purpose technologies do not come along very often, but when they do, they change life, economies and industries.
Friday, April 22, 2011
Google Highlights Data Center Security Measures
Labels:
data center,
Google
Gary Kim has been a digital infra analyst and journalist for more than 30 years, covering the business impact of technology, pre- and post-internet. He sees a similar evolution coming with AI. General-purpose technologies do not come along very often, but when they do, they change life, economies and industries.
Apple's iPhones and Google's Androids Gather Location Data
Apple iPhones and Google's Android smartphones regularly transmit their locations back to Apple and Google, respectively, according to data and documents analyzed by The Wall Street Journal. No doubt the data is used only in aggregated, anonymous ways, but there always is the worry that personally-identifiable information could be compromised.
The issue is that some applications and features people might like do require location information. So there always will be a tension between a user desire for privacy and a user desire for sharing some information to obtain benefits.
Google and Apple are gathering location information as part of their race to build massive databases capable of pinpointing people's locations via their cellphones. These databases could help them tap the $2.9 billion market for location-based services, expected to rise to $8.3 billion in 2014, according to research firm Gartner.
The issue is that some applications and features people might like do require location information. So there always will be a tension between a user desire for privacy and a user desire for sharing some information to obtain benefits.
Looking up the closest supplier of something a user wants, such as a local Starbucks, a Thai restaurant or a grocery store, require location knowledge. Social networking features that allow a user to find friends are another example.
Gary Kim has been a digital infra analyst and journalist for more than 30 years, covering the business impact of technology, pre- and post-internet. He sees a similar evolution coming with AI. General-purpose technologies do not come along very often, but when they do, they change life, economies and industries.
Review of Sprint Personal Wi-Fi Hotspot
Gary Kim has been a digital infra analyst and journalist for more than 30 years, covering the business impact of technology, pre- and post-internet. He sees a similar evolution coming with AI. General-purpose technologies do not come along very often, but when they do, they change life, economies and industries.
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