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SmartData Collective > Big Data > Data Mining > AT&T studies user data to cope with iPhone crunch
Business IntelligenceData Mining

AT&T studies user data to cope with iPhone crunch

StephenBaker1
StephenBaker1
4 Min Read
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An excellent piece in the WSJ (behind subscriber wall) about AT&T’s push to cope with the exploding data traffic of iPhone users. The company has to get this under control, because by early next year unhappy iPhone subscribers, especially in overloaded NY and SF markets, will likely have the chance to switch to Verizon.

To fine-tune its network, AT&T is studying ever more user data:

Before the iPhone, it used to be able to accurately forecast to the minute the type of phone usage each new customer would add to its network based on basic demographics such as age and income levels. The forecast always held true across cities and towns.

But with the iPhone, such bets are off, AT&T executives painfully learned. It now looks at a broader set of customer profiles to forecast behaviors. For example, in a metro area with a large proportion of students, the phone operator schedules network upgrades to occur outside of colleges’ nine-month academic terms.

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…’I’m as interested now in what you’re doing when you’re not on the network’… said John Stankey, head of AT&T’s operations arm.

One interesting note from the article is while AT&T has …


An excellent piece in the WSJ (behind subscriber wall) about AT&T’s push to cope with the exploding data traffic of iPhone users. The company has to get this under control, because by early next year unhappy iPhone subscribers, especially in overloaded NY and SF markets, will likely have the chance to switch to Verizon.

To fine-tune its network, AT&T is studying ever more user data:

Before the iPhone, it used to be able to accurately forecast to the
minute the type of phone usage each new customer would add to its
network based on basic demographics such as age and income levels. The
forecast always held true across cities and towns.

But with the iPhone, such bets are off, AT&T executives painfully
learned. It now looks at a broader set of customer profiles to forecast
behaviors. For example, in a metro area with a large proportion of
students, the phone operator schedules network upgrades to occur outside
of colleges’ nine-month academic terms.

…’I’m as interested now in what you’re doing when you’re not on the
network’… said John Stankey, head of AT&T’s operations arm.

One interesting note from the article is while AT&T has taken its bruises in this data-intensive market, at least it’s learning. Some beleaguered users may jump to Verizon and other carriers just as those companies start to struggle with the same issues. It might be smart for Verizon to pay top-dollar for an AT&T engineer or two, just to get the know-how.

For example, AT&T said when iPhone customers started checking their
email and surfing the Web from their high-rise offices, AT&T
repositioned its cellular antennas to point up, instead of down.

There must be scores of similar lessons they’ve learned.

***

I’m in Seattle for a couple of days on book research. I’ve been interviewing folks at Vulcan Inc. about artificial intelligence. Now I’m in a coffee shop (surprise, surprise). I think I’ll head across the street to the art museum before meeting with Ed Lazowska, head of the computer science dept at U. Washington (the U-Dub, as they call it around here).

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