Tablet Share of Mobile Web Traffic Predicted to Grow at Smartphones’ Expense

March 5, 2013

This article is included in these additional categories:

Connected Device Comparisons | Digital | Mobile Phone

Jumptap-Mobile-Web-Consumption-Trends-by-Device-2011-2013-Mar2013Tablets accounted for just 7% of traffic on the Jumptap network in 2011, half the share accounted for by feature phones, according to [download page] the latest MobileSTAT report. But that quickly changed last year, as tablet share of traffic more than doubled to 18%, and feature phones plummeted to 4% share. With feature phone advertising fading rapidly, Jumptap’s forecast for this year calls for tablets to cannibalize share of internet traffic from smartphones. Indeed, while they’ll continue to dominate mobile web traffic this year, Jumptap predicts that the share of network traffic accounted for by smartphones will decline from 78% to 70%, while tablet share will grow from 18% to 29%.

A recent study from Millennial Media revealed a very similar device make-up on its platform. In 2012, according to that report, smartphones accounted for 75% of impressions, tablets 20%, and feature phones 5%.

But while the Millennial Media report showed a remarkably constant operating system mix, the Jumptap study shows Apple to be rising fast. Between 2011 and 2012, Apple iOS increased its market share from 26% to 43% on the network, with Android gaining a comparatively smaller 4% points, to 51%. And while on the Millennial Media network, RIM’s share held steady at 16% from 2011 to 2012, on the Jumptap network, RIM’s share plunged from 22% to 5%.

About the Data: Jumptap’s MobileSTAT (Simple Targeting & Audience Trends) is a monthly glance into targeting and audience trends in mobile advertising through the company’s network of over 30 billion impressions, 134 million U.S. users and 40,000 apps and websites. MobileSTAT contains analysis of dozens of terabytes of log data, powered by the scalable, efficient Jumptap technology.

The Jumptap MobileSTAT reports mine large quantities of network data to identify targeting and audience trends. Jumptap uses proprietary algorithms to analyze and normalize this data. In some cases, when sufficient conditions are met, subsets of data may have been used as proxies to represent the overall network.


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