Consumer smartphone usage: mobile apps and entertainment consumption

Transcription

1 Research Report Consumer smartphone usage: mobile apps and entertainment consumption June 2012 Ronan de Renesse

2 2 Contents [1] Slide no. 7. Executive summary 8. A surprisingly small number of apps drive the smartphone content and app market 9. Many niche apps categories present significant opportunities for the industry 10. Key implications and recommendations 11. Key implications and recommendations for operators [1] 12. Key implications and recommendations for operators [2] 13. Key implications and recommendations for operators [3] 14. Key implications and recommendations for vendors and developers 15. Introduction and panel characteristics 16. Real-world usage: we measured consumer smartphone usage via an on-device monitoring application, in partnership with Arbitron Mobile 17. Comparing the characteristics of passive on-device smartphone usage monitoring with traditional questionnaire-based consumer surveys 18. The smartphone user panel was designed to be representative of the smartphone market in the countries covered 19. More than 50% of our smartphone panel were Android users in all countries except Spain 20. Apple and HTC accounted for almost half of the smartphones monitored in our panel 21. Android addresses the widest range of smartphone profiles 22. Mobile apps: consumption trends and insights, impact of devices and customer segmentation Slide no. 23. Pre-installed platform apps continue to dominate communication and utility app use, but add-on apps are gaining ground 24. Mobile content and apps are gaining ground on legacy communication services in terms of share of consumer time spent on the smartphone 25. More panellists accessed utility and social networking apps than games apps 26. Browsing is a key part of the mobile content experience, driven by searching and Internet links in apps 27. Browsing increases as more apps are used, indicating that the two methods of accessing content are complementary 28. Most categories of add-on apps were used for less than 2 minutes per day by each user, even if they have achieved widespread penetration 29. Unlike other handsets, vendors and/or operators must maintain smartphones 30. The operating system clearly has an impact on the take-up of apps most app categories enjoy more than 50% penetration on Android and ios 31. Average frequency of usage for all apps on ios and Android is diluted by high levels of one-time use of long-tail apps 32. The success of an app distribution strategy is driven by quality of experience, rather than simply by offering a wide choice of apps 33. More than 90% of iphone and Android panellists accessed OS-specific application stores year olds are clearly driving the app market, but this will change as older people increasingly move onto Android devices

3 3 Contents [2] Slide no. 35. App tastes vary across different age groups - pleasing people in the age category should not be the top priority for all app providers 36. Most smartphone panellists used between 10 and 30 apps during the observation period, with younger users tending to use relatively more 37. Rich-media applications: games, music and TV change smartphones into media players 38. The iphone prevails as a media consumption device 39. Gaming [1]: mobile games are most used on Android-based smartphones with users playing on average nearly five games in two months 40. Gaming [2]: several casual games account for the bulk of games usage 41. TV and video: Netflix gets high levels of engagement from a small subset of panellists, while YouTube gets scale with high penetration rates 42. Music: on-demand services are used as much as radio, but are not as widely adopted 43. Social networking and operator apps: consumers manage their own communication services 44. Social networking [1]: dating apps are more addictive than Facebook, although more panellists used Facebook 45. Social networking [2]: social networks are not leading OTT communications yet; only 3.4% of panellists used Facebook IM 46. Operator apps [1]: nearly 30% of smartphone panellists used at least one app published by an operator 47. Operator apps [2]: panellists in France and the USA adopt operator apps at least twice as much as they do in other countries Slide no. 48. Operator apps [3]: ios is not necessarily the best choice for operator app distribution 49. Utility apps: transforming convenience into transactions with m- commerce 50. Utility [1]: handset management, weather, calculator and notepad apps dominate the utility category 51. Utility [2]: Android opens up smartphones to the downloadable utility app market, imitating the PC market 52. Utility [3]: the most popular utility cloud services have low penetration, but note-taking apps and social networking may drive adoption 53. M-commerce [1]: mobile applications published by established online retailers are the most popular 54. M-commerce [2]: Amazon and ebay are the leaders in this market, but local retailers are gaining some ground 55. New app verticals: opportunities in location services, mobile health and e-books 56. Google Maps leads the maps market more than 70% of iphone and Android panellists used the app regularly 57. Nearly 11% of smartphone panellists used an m-health app during the observation period 58. E-books are not just for tablet owners; one in four iphone panellists used an e-reader app 59. National news providers dominate the news apps market 60. Methodology and definitions 61. Methodology and definitions [1]

4 4 Contents [3] Slide no. 62. Methodology and definitions [2] 63. Methodology and definitions [3] 64. About Arbitron Mobile and The Connected Consumer Survey 65. About the author and Analysys Mason 66. About the author 67. About Analysys Mason 68. Research from Analysys Mason 69. Consulting from Analysys Mason

5 5 List of figures [1] Figure 1: Selected panel statistics related to the use of smartphone content and apps during the observation period Figure 2: Penetration rate versus average daily minutes of face time per panellist by category of user-downloaded app Figure 3: Illustration of Analysys Mason Arbitron smartphone data analysis process Figure 4: Characteristics of different types of primary research Figure 5: Number of smartphone users in our panel, by country, August and September 2011 Figure 6: Panel of smartphone users by smartphone operating system Figure 7: Panel of smartphone users by age group Figure 8: Panel of smartphone users by operating system and country Figure 9: Panel of smartphone users, by vendor Figure 10: Android panellists and add-on app usage by versions of the operating system Figure 11: Android device models represented in the panel, by smartphone segment Figure 12: Proportion of platform and add-on apps used by smartphone panellists, by number and face time Figure 13: Average face-time value per smartphone respondent, by category of app Figure 14: Proportion of smartphone panellists who used at least one app during the observation period, by category Figure 15: Average usage per smartphone respondent by category Figure 16: Distribution of panellists by number of add-on apps used and corresponding average browsing face-time per user Figure 17: Add-on app categories penetration rate versus average face-time value for users of the apps Figure 18: Share of Android OS versions and use of add-on apps among Android-user panellists, by handset vendor Figure 19: App/service category penetration among smartphone panellists, by operating system Figure 20: Number of add-on apps per user by usage frequency and operating system Figure 21: Penetration of top 50 add-on apps by operating system Figure 22: Face-time value by operating system for the top 100 apps Figure 23: Penetration of dedicated application stores among panellists Figure 24: Share of smartphone panellists using other application stores, by OS type Figure 25: Age group distribution for each app category Figure 26: Penetration of app categories within each age group Figure 27: Share of smartphone panellists by age group and number of apps used per panellist Figure 28: Share of smartphone panellists by age group for different OSs Figure 29: App/service media category penetration among panellists, by operating system Figure 30: Mobile gaming use among smartphone panellists, by OS Figure 31: Share of total daily mobile game face-time value among panellists, by OS Figure 32: Top-10 mobile games by share of users in the smartphone panel Figure 33: TV app penetration rate versus average face-time value for users of the apps

6 6 List of figures [2] Figure 34: Music app penetration rate versus average face-time value for users of the apps Figure 35: Share of smartphone panellists who used at least one application per category of social networking apps Figure 36: Share of average daily social networking app face-time usage, among social networking app users, by app publisher Figure 37: Penetration of Google Talk within Google+ users and Facebook IM within Facebook users in our panel and vice versa Figure 38: Share of smartphone panellists using the app at least once, by type Figure 39: Daily use of operator apps share of face-time value, by type of app Figure 40: Share of panellists using an operator app at least once, by type and by country Figure 41: Share of panellists who used an operator app at least once Figure 42: Share of panellists using at least one operator app, by OS Figure 43: Share of smartphone panellists using at least one application per category of utility apps Figure 44: Share of smartphone panellists using at least one app per category of utility apps, by OS Figure 45: Penetration and app usage for utility categories presenting opportunities for cloud services Figure 46: Add-on app categories penetration rate versus average face-time value for users of the apps Figure 47: Penetration of retail apps among smartphone panellists (in selected countries) Figure 48: Share of smartphone panellists using Google Maps and other maps app at least once during the observation period, by OS Figure 49: Share of smartphone panellists using at least one add-on app in each category Figure 50: Share of smartphone panellists using a mobile health application at least once, by OS Figure 51: Share of smartphone panellists using at least one app per category, by OS Figure 52: Share of total daily face-time value for e-reader apps, by app publisher Figure 53: Share of smartphone panellists within each country using a local news app at least once Figure 54: Utility app categorisation examples Figure 55: Entertainment app categorisation examples

7 7 Executive summary Key implications and recommendations Introduction and panel characteristics Mobile apps: consumption trends and insights, impact of devices and customer segmentation Rich-media apps: games, music and TV change smartphones into media players Social networking and operator apps: consumers manage their own communication services Utility apps: transforming convenience into transactions with m-commerce New app verticals: opportunities in location services, mobile health and e-books Methodology and definitions About the author and Analysys Mason

8 65 Executive summary Key implications and recommendations Introduction and panel characteristics Mobile apps: consumption trends and insights, impact of devices and customer segmentation Rich-media apps: games, music and TV change smartphones into media players Social networking and operator apps: consumers manage their own communication services Utility apps: transforming convenience into transactions with m-commerce New app verticals: opportunities in location services, mobile health and e-books Methodology and definitions About the author and Analysys Mason

9 66 About the author Ronan de Renesse (Principal Analyst) is the lead analyst for Analysys Mason s Mobile Content and Applications and Mobile Broadband and Devices programmes. His primary areas of specialisation include rich media applications and services on mobile, application store forecasting, mobile broadband, tablets and smartphone adoption. Ronan has been analysing the telecoms and media industry since Prior to joining Analysys Mason, Ronan was a Senior Analyst and the Head of Mobile at IHS Screen Digest, where he had overall responsibility for the Mobile Media Intelligence service and all related activities. For the past five years, Ronan has led the conception and development of various mobile media and technology forecasts, including those for mobile video, mobile music, mobile games, mobile applications, mobile broadband and smartphones. Before becoming an industry analyst, Ronan was an academic researcher at the Centre for Telecommunications Research at King's College London. He had numerous articles published in international technology journals and also gave various presentations at high-profile conferences. Ronan holds a PhD in Telecommunications from King's College London. Published by Analysys Mason Limited Bush House North West Wing Aldwych London WC2B 4PJ UK Tel: +44 (0) Fax: +44 (0) research@analysysmason.com Registered in England No All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher. The opinions expressed are those of the stated authors only. Analysys Mason Limited recognises that many terms appearing in this report are proprietary; all such trademarks are acknowledged and every effort has been made to indicate them by the normal UK publishing practice of capitalisation. However, the presence of a term, in whatever form, does not affect its legal status as a trademark. Analysys Mason Limited maintains that all reasonable care and skill have been used in the compilation of this publication. However, Analysys Mason Limited shall not be under any liability for loss or damage (including consequential loss) whatsoever or howsoever arising as a result of the use of this publication by the customer, his servants, agents or any third party.

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