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The Consumer smartphone usage 2014: headline results

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This report presents the collected headline findings from Analysys Mason consumer smartphone usage research, focusing on how the following factors affect usage: form factor, technical specifications, LTE and Wi-Fi, and IP communications.

 6.Executive summary
 7.Consumers are changing the way that they engage with smartphones and screen size is significantly driving this change
 8.Online video accounts for most of handset data use and both LTE and higher-specification devices will encourage greater use
 9.Full service substitution of legacy services remains rare despite high penetration levels of IP communications apps
 10.The adoption of digital economy apps has increased rapidly, reaching a level similar to that of the popular multimedia apps
 11.Recommendations
 12.Recommendations
 13.The relationship between device specifications and app usage
 14.Communication continues to be an important part of smartphone usage, but its role is diminishing to be replaced by digital economy services
 15.Screen size affects app usage – large phones are used about twice as much as small phones
 16.The relationship between the size of the device and the amount of cellular and Wi-Fi data that it generates is strong and clear
 17.Mobile gaming is a key driver for increasing app usage on high-end smartphones
 18.Mobile data usage: the role of 3G, LTE and Wi-Fi
 19.Online video accounts for most handset data use, but gaming and messaging have relatively low data rates despite high usage
 20.LTE users used their devices for 63% longer per day than average and generated 2.7 times as much cellular data traffic as non-LTE users
 21.Handset traffic is, and will remain, predominantly carried over Wi-Fi
 22.The vast majority of smartphone Wi-Fi traffic was generated in the home
 23.Analysis of communication app usage and substitution
 24.IP messaging services are growing rapidly – they have achieved mass adoption in Germany, and the UK is set to follow
 25.WhatsApp and the ‘social messaging’ apps are rivalling Facebook in terms of user engagement
 26.Full service substitution of legacy services remains rare despite high penetration levels of IP communications apps
 27.Mobile operators are not equally affected by communication app adoption
 28.The digital economy, commerce and mobile banking
 29.The adoption of digital economy apps has increased quickly in the past 2 years, reaching a level similar to that of the popular multimedia apps
 30.The barriers to entry into the app development market are lower than previously, which is driving local mobile commerce app development
 31.The adoption of mobile banking apps has risen from 8% of our panel to 44% in 2 years, thanks to a strong industry push
 32.Methodology and panel information
 33.Methodology and definitions [1]
 34.Methodology and definitions [2]
 35.About the authors and Analysys Mason
 36.About the authors [1]
 37.About the authors [2]
 38.About Analysys Mason
 39.Research from Analysys Mason
 40.Consulting from Analysys Mason


List Of Figures

 Figure 1: Average daily app usage by app category, 2011 and 2013 (2011: n = 1079; 2013: n = 1596)
 Figure 2: Key app sub-categories by average percentage of time and average percentage of data traffic (n= 1588)
 Figure 3: Time spent using IP messaging apps as a proportion of overall time spent using messaging services (including SMS/MMS) (n = 1153)
 Figure 4: Penetration of apps by category, and corresponding growth between 2011 and 2013 (2011: n = 1079; 2013: n = 1596)
 Figure 5: Average daily app usage by app category, 2011 and 2013 (2011: n = 1079; 2013: n = 1596)
 Figure 6: Median app usage and number of apps used per panellist, by smartphone screen size (n = 1596)
 Figure 7: Median data usage by network type and smartphone screen size (n = 1588)
 Figure 8: Average app usage by category, by device models for Apple and Samsung (n = 795)
 Figure 9: Top-10 apps by handset traffic (n = 1588)
 Figure 10: Key app sub-categories by average percentage of time and average percentage of data traffic (n=1588)
 Figure 11: Average MoU by app category for panellists (n = 1588)
 Figure 12: Distribution of total smartphone traffic across all panellists (n = 1588)
 Figure 13: Panellists who connected to Wi-Fi by category of hotspot and the average amount of their total cellular data usage attributable to that category, Android users (n = 1211)
 Figure 14: Penetration of social networking and communication apps (excluding email), by country (n = 1596)
 Figure 15: Penetration of IP message apps, by age and country (n = 1596)
 Figure 16: Average daily usage of selected communications and social networking apps (n = 1596)
 Figure 17: Time spent using IP messaging apps as a proportion of overall time spent using messaging services (including SMS/MMS) (n = 1153)
 Figure 18: Penetration of IP messaging services, by network operator and country (n = 1447)
 Figure 19: Penetration of VoIP services, by network operator and country (n = 1447)
 Figure 20: Penetration of apps by category, and corresponding growth between 2011 and 2013 (2011: n = 1079; 2013: n = 1596)
 Figure 21: Commerce apps used by panellists, by type of app (n = 1398)
 Figure 22: Penetration and average app usage by mobile financial services app type (n = 1596)
 Figure 23: Panellists’ gender, by country of observation
 Figure 24: Panellists’ age, by country of observation
 Figure 25: Panellists’ handset OS, by country of observation


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Reports Details

Published Date : Feb 2015
No. of Pages :41
Country :Global
Category :Telecommunications
Publisher :Analysys Mason Limited
Report Delivery By :Email
Report Delivery Time :12 to 24 hours after placing the order.

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