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1. The MobileDigital LifestyleSegmentationAllot Mobile Trends 02/2013Segmenting the MobileDigital LifestyleAllot MobileTrends Report 02/2013
Analysis Mr. Yossef Arie, Department of Sociology, University of Haifa, Israel Photography, Mr. Yossef Massa, Netanya , IsraelAllot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved. Design, Mr. Guy Ruskin, Israel
Executive Summary This study explores and outlines mobile digital lifestyles in action. The result of this research produces useful and actionable segmentation for operators and provides a unique and important view of subscribers’ online activities. Marketing managers are aware that there is no “average digital user” and no single homogeneous digital lifestyle. Thus, there is a need to identify the differences among subscribers and group them in a way that will better reflect their lifestyle. Actionable segmentation of the digital lifestyles of mobile subscribers can lead to successful operator marketing, customer retention and increased revenues. Instead of defining subscribers based on the usual terms of Gigabytes consumed, this study introduces an innovative approach: segmenting the mobile digital lifestyle from the network operator perspective. The diversity of data consumption is demonstrated in two dimensions: 1. Personal vs. Social online activities 2. Place (web content) and time of the online activities This lifestyle segmentation provides a richer definition of mobile subscribers. Data for this study is based on a sample of over 60,000 digital users from several mobile operators in different geographic regions. Based on analysis of their usage records, we identified five distinct digital lifestyle profiles; Info Seeker, Info Guzzler, Social Monitor, Social Mingler and Digital Mover & Shaker. The last is the most important segment since the subscribers in this category are the drivers of the digital lifestyle. They integrate between personal and social activities online. They create and upload content and they react to the content of others. Like a pebble in a pond, their activity stimulates interest and creates a ripple effect of further activity. They don’t just participate in the online action - they create it! The findings in this paper suggest that the more mobile operators know and understand about the digital activities of their customers, the more effectively and efficiently they can fulfill their role as Digital Lifestyle Provider and increase the value of their network service in the eyes of their customers. The segments we identified are actionable allowing operators to create data delivery and charging policies to capitalize on the data traffic these segments generate. Introduction Approximately two hundred years ago, Malthus recounted the term of “carrying capacity” in order to describe the worldwide gap between the growth of the population and the growth of food production capabilities (Malthus, 1798) “The power of population is indefinitely greater than the power in the earth to produce subsistence for man.” Malthus argued that while population grows in a geometrical series, the means of food production grows is in a mathematical series and the gap is created. This description can successfully delineate the phenomenon of mobile data use worldwide these days. There is a large gap between the growth of data delivery services offered by services providers and the growth of data use. Global mobile data traffic grew 2.3 fold in 2011, more than doubling for the fourth year in a row. Furthermore, mobile data traffic is expected to grow at a year over year rate of 78 % from 2011 to 2016 (Cisco, 2012). In this context, Allot develops and markets innovative products and solutions designed to help mobile network operators capitalize on the explosion in data traffic by providing chargeable value and services to mobile users, and by solving data delivery issues efficiently and effectively. Furthermore, Allot sees the “data explosion” as an opportunity for service providers to increase the value they bring to their subscribers. This paper introduces Allot’s innovative and advancedAllot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved. 1
approach to mobile digital lifestyle segmentation and sheds light on the value of data services to different subscriber segments. Many service providers approach the “data explosion” through the consumption patterns of “average digital users” i.e., light, middle or heavy data users. This classification is based on the volume of traffic they create. However, this approach does not reflect the heterogeneity, complexity, and flexibility of digital lifestyles. In reality, there is no “average digital user,” and no single homogeneous digital lifestyle. Hence, there is a need to identify the differences among subscribers and group them in such a way that will give a better understanding of digital users. Instead of defining users based on Gigabytes consumed, this study introduces an innovative approach for digital lifestyle segmentation and demonstrates the diversity of digital consumption in two dimensions: • Personal vs. Social online activities • Place (web content) and time of the online activities • (where and when online usage occurs) Literature about Information and Communication Technology (ICT) teaches us that with the advancement of ICT, a reconfiguration of our personal and social cycles and behaviors occurs (Dutton, 2005; Wellman, 2001, 2002; Ling, 2008). Therefore, it is very interesting to understand how digital personal activities (i.e., application download, general browsing, and video streaming) and digital social activities (i.e., email, instant messaging, social networks, gaming and VoIP) interact in the mobile data arena. On the same subject, literature teaches us that data users change and rearrange their data usage patterns across place and time (Castells et al., 2007). ICTs create new arrangements between the “place-time” intersection in a given geographical space (Castells et al., 2007, Green, 2002). However, instead of focusing on physical place as has been done by previous studies, this paper emphasizes the virtual place (web content). In this context, this study focuses and delineates subscriber activity based on the content they consume and the time they choose to consume it. Therefore, this paper attempts to answer the following questions: • What types of lifestyle profiles are evident across personal and social activities as well as content and time activities? • What and who are the digital lifestyle influencers? • How can we identify and leverage the distinct digital lifestyle profiles in order to create real value for data users? Methodology To answer those questions, we explored several mobile operators and we researched over 60,000 subscribers, which statistically represented the data users of each one of the mobile service providers. The data sets included the URL of the web content, the time of the sessions and the traffic of a given site for each one of the users during December 2012. Based on these findings we delineate the distinct classifications of digital lifestyle profiles. It is important to note that the data collected for this report was totally subscriber-anonymous. Subscriber identifying information such as IP address, usernames or MSISDN were not retained in the data gathered from the mobile networks.2 Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved.
Findings Table 1 presents the distribution of data usage categories among mobile subscribers during a typical week. A subscriber using a mobile device uses on average 1.76 different categories of data traffic. The most common category is general browsing which is used by 72% of subscribers. Just below that are Social Networks with 29%, Video Streaming with 20% of subscribers, Online Storage with 12% and Instant Messaging with 11% of subscribers. A smaller group uses Email with 8%, Application downloads with 7%, P2P with 7%, VoIP with 5%, and Gaming with 5% of subscribers (see Table 1, Graph 1)Table 1 % Subscribers *Data Traffic Categories General Browsing 72%of Mobile Data Users Social Networks 29% Video Streaming 20% Online Storage 12% Instant Messaging 11% Email 8% App Downloads 7% P2P 7% Gaming 5% VoIP 5% Traffic Heterogeneity 0.84 *Subscribers access more than one category For the purpose of this report, we compared the percentage of subscribers using each category of data against the volume of traffic they generated. As a result, we saw that the data traffic in mobile networks is heterogeneous1 (of mixed makeup and varying usage). Our analysis showed % Subscribers a heterogeneity factor of 0.84 on a scale of 0 to 1, where 1=highly heterogeneous (see Table 1). This heterogeneity factor of data traffic indicates a high potential for distinct segmentation. 72%Graph 1 Percent of Subscribers per Data Category 29% 20% 12% 11% 8% 7% 7% 5% 5% General Browsing Social Networks Video Streaming Online Storage Instant Messaging Email App Downloads P2P Gaming VoIP 1 Based on the Heterogeneity Measure of Blau (1977): 1 –∑Pi2 when Pi is the % of data traffic of the data category. Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved. 3
Overall Usage by Data Category Graph 2 Social Networks Video Streaming Overall Usage by Data Category Facebook Others 39% 32% Others 42% YouTube 68% Twitter 19% Graph 2.1 Within the Social Networks Graph 2.2 Within the Video Streaming category, Facebook accounts for 39% category, YouTube is the overwhelming and Twitter 19% of the content visited. All favorite, accounting for 68% of the content others comprise 42%. visited. All others comprise 32%. Peer to Peer VoIP Others 32% Skype 34% BitTorrent 68% Others 66% Graph 2.3 Within the Peer-to-Peer Graph 2.4 Within the VoIP category, Skype category, BitTorrent is the preferred accounts for 34% of the content visited. destination, accounting for 68% of the All others comprise 66%. (In our study, we P2P content visited. All others comprise did not differentiate between voice calls vs. 32%. chat or instant messaging done via Skype or other VoIP.)4 Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved.
Application Traffic Volume Over an Average 24 Hour Period After one week of monitoring the various networks, the following traffic patterns were noted. BitTorrent, Skype, YouTube and General Browsing are active during all hours of the day. However, Skype use is dominant during the late evening hours 22:00-0:00. General browsing is strong during the evening hours 18:00- 20:00 while traffic to Facebook and YouTube is strongest in the 10% middle of the day 13:00-15:00.Graph 3a 8%DataConsumption Percent of Trafﬁc VolumePatterns by 6%Time-of-Day* 4% 2% 0% 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16.00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 1:00 2:00 3:00 4:00 5:00 BitTorrent Facebook YouTube Skype General Browsing 40%Graph 3b 35%Data 30%Consumption Percent of Trafﬁc VolumePatterns by 25%Day* 20% 15% 10% 5% 0% Morning Mid Day Evening Night BitTorrent Facebook YouTube Skype General Browsing * These graphs show the distribution of data volume for each application over a day. Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved. 5
Types of Usage: Personal, Social and Mixed Our analysis of the data traffic points to three types of subscriber activity online: personally active, socially active, and mixed personally/socially active. It also measures the effect that each style of activity has on the network. Ideally, 38% of the subscribers should generate 38% of the traffic. But we see that subscriber activity can affect traffic volume on the network far below or above the number of subscribers generating it. Personally active (38% of subscribers) data subscribers usually access content and download applications for personal use. Their traffic falls into three main data categories; General Browsing, Application Download and Video Streaming. Socially active (14% of subscribers) data subscribers interact in social networks and share information and media such as pictures, video clips and music files. These subscribers upload and create content that is then shared with other subscribers. Their traffic falls into six main data categories: Email, Instant Messaging, Social Networks, Gaming, Social Video and VoIP. Mixed personally/socially active (48% of subscribers) are the quintessential digital lifestyle subscribers, using online data for both personal and social activities. Table 2 Subscriber % Traffic % Network Effect Usage Types as Percent % Traffic / % Subscribers of Data Subscribers and Percent of Data Traffic Personally active 38% 17% 45% Socially active 14% 9% 64% Mixed Personally/Socially active 48% 74% 154% Total 100% 100% Graph 4a-b Usage Types as Percent Usage Types as Percent of Data Subscribers of Data Traffic Personal Use 17% Personal Use Social 38% Mixed Use 9% Personal/Social Use Mixed 48% Personal/Social Use 74% Social Use 14% Single-tasker, Multi-tasker Our research showed that for each of the usage types – personal, social, and mixed – there are two subtypes: the predominantly Single-tasker and the predominantly Multi-tasker. The Single tasker describes the subscribers whose online activity revolves around a single data category. Their usage pattern is serial, accessing one data category at a time. The Multi-tasker describes subscribers whose online activity includes multiple data categories. Their usage pattern is parallel, accessing multiple data categories at a time. Based on the different types of use that we observed we were able to identify five Digital Lifestyle profiles that represent five distinct segments of mobile data subscribers.6 Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved.
Digital Lifestyle Segments 1 2 3 4 Info Seeker Info Guzzler Social Monitor Social Mingler• 32% of subscribers • 5% of subscribers • 15% of subscribers • 15% of subscribers• 12% of data traffic • 5% of data traffic • 9% of data traffic • 16% of data traffic• 75% use general web • Divided into two • Tends to access Social • Engages in pairs of browsing distinct types: Network content personal and social (24%), Social Video activity• 36% of the traffic a. General Browsing and (28%) and VoIP (18%) is generated in the P2P (33%) • The leading pairs are evening (compared b. General Browsing and • 45% of use occurs General Browsing & to 28% for the total during the middle of Social Networks (35%), Application Download population) the day compared and General Browsing (23%) to 36% for the total & Social Video (11%) • 44% of use occurs population • 64% of use occurs during the middle of during the middle of the day compared the day and evening to 36% for the total which is similar to the population total population 5 Digital Mover & Shaker• 34% of subscribers• 58% of data traffic• Characterized by very high data usage. This segment combines personal data activity with social data activityLeading activity combinations are:a. General Browsing, Social Networks, Video Streaming and Instant Messaging (31%)b. General Web Browsing, Social Video & VoIP (15%)• 21% of use occurs during the night, compared to 18% for the total population• Digital Movers & Shakers are important not just because of the heavy traffic they generate but also mainly because their activity spawns even more usage on the mobile network. The subscribers in this segment connect socially and they upload and share the information and content that interests them.• Subscribers in this segment are the social influencers of the Digital Lifestyle Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved. 7
The digital lifestyle profiles in the following table show the percent of subscribers in each segment, the percent of total traffic each segment generates, and scores the cumulative effect their use on the network. For example, Info Guzzlers generate the same percent of overall traffic (5%) as their representation in the subscriber base. But Digital Movers & Shakers account for more of the data traffic (58%) than their numbers in the subscriber base (34%). This phenomenon is reflected in the “network effect” score of each segment. Based on analysis of this kind, mobile service providers can tailor their offering to deliver the value that is important to each digital lifestyle. Table 3 % Subscribers % Traffic Network Effect Average Use (% Traffic / Mobile Digital Lifestyle % Subscribers) Segmentation 1. Info Seeker 32% 12% 38% Low 2. Info Guzzler 5% 5% 100% Mid 3. Social Monitor 14% 9% 64% Mid 4. Social Mingler 15% 16% 107% Mid 5. Digital Mover & Shaker 34% 58% 171% High Table 4 Digital Lifestyle Segments Info Seeker Info Guzzler Social Monitor Social Mingler Digital Total Mover & Shaker Pop. Percent of Total 32% 5% 14% 15% 34% 100% Subscribers Percent of Total Traffic 12% 5% 9% 16% 58% 100% Average Activity Low Mid Mid Mid High Data Categories Used App Download Browsing & App Email Browsing & IM Browsing, Social Browsing Download Social Networks Networks, Video Browsing & P2P Gaming Streaming & IM Browsing & P2P Social Networks Video Streaming IM Browsing, Social Social Video Browsing & Video & VoIP Social Video Online Storage Info Seeker Info Guzzler Social Monitor Social Mingler Digital Total Mover & Shaker Pop. Morning 16% 15% 17% 17% 19% 18% Mid-Day 29% 44% 44% 36% 32% 36% Evening 37% 29% 24% 29% 28% 28% Night 18% 12% 15% 18% 21% 18% 8 Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved.
Graph 5 Mobile Digital Lifestyle 58% Graph 6 Segment Effect on the Segmentation Network 171% High 34% 32% 107% 100% Mid Mid 64% 14% 15% 16% Mid 12% 38% 9% Low 5% 5% Subscribers Trafﬁc 1. 2. 3. 4. 5. 1. 2. 3. 4. 5. Info Info Social Social Digital Info Info Social Social Digital Seeker Guzzler Monitor Mingler Mover & Seeker Guzzler Monitor Mingler Mover & Shaker ShakerGraphs 7.1-7.5 2% 5% 8%Data Categories 10% 23% 29%Used by Digital 18%Lifestyle Segments 44% 11% 75% 33% 18% 24% Info Seeker Info Guzzler Social Monitor Browsing Browsing & P2P Social Video P2P Browsing & App Downloads Social Networks App Downloads Other Pairs VoIP Video Streaming Gaming IM 4% Email 5% 15% 11% 46% 54% 31% 34% Social Mingler Digital Mover & Shaker Browsing & Social Networks Browsing & Social Networks Browsing & Social Video & Video Streaming & IM Online Storage Browsing & Social Video & Browsing & IM VoIP Other Pairs Other Combinations Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved. 9
Graph 8 Digital Lifestyle Profiles by Time of Day 44% 44% 37% 36% 36% 32% 29% 29% 29% 28% 28% 24% 21% 19% 18% 18% 17% 17% 18% 18% 16% 15% 15% 12% Info Seeker Info Guzzler Social Monitor Social Mingler Digital Mover & Total (32%) (5%) (14%) (15%) Shaker Population (34%) Morning Mid-Day Evening Night Graph 9 Mapping the Digital Lifestyle Profiles Multi-tasker Personal Activities Social Activities Single-tasker Percent of Subscribers (Percent of Traffic)10 Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved.
Conclusion Global mobile data traffic has been doubling every year since 2008 and is expected to continue to grow at a year over year rate of 78%. Clearly, we live in an era of “data explosion.” This paper introduces a method for identifying different user segments within the mobile digital lifestyle. This segmentation is actionable and useful for operators because it provides a unique and important view of data use. The methodology used in this Allot MobileTrends Report identifies the differences and similarities among the traffic generated by mobile subscribers and groups them according to their online behavior. The resulting segmentation provides a richer definition of mobile digital lifestyles and can be duplicated by any mobile operator using Allot data monitoring and analytics solutions. Allot Communications’ wide range of integrated solutions and outstanding solution partners are uncovering the traffic intelligence in mobile networks around the world, and using it to drive innovative and revenue-generating use cases for the Digital Lifestyle.Table 5: Allot’s Leading Use Cases for the Digital Lifestyle Info Seeker Info Guzzler Social Monitor Social Mingler Digital Mover & Shaker Percent of Subscribers 32% 5% 14% 15% 34% Percent of Traffic 12% 5% 9% 16% 58% Average Use Low Mid Mid Mid High Data Categories Used App Download Browsing & App Email Browsing & IM Browsing, Social Browsing Download Social Networks Networks, Video Browsing & Social P2P Gaming Streaming & IM Browsing & P2P Networks Video Streaming IM Browsing, Social Social Video Browsing & Social Video & VoIP Video Online Storage Digital Lifestyle Use Cases Customer Touch Point Optimization Targeted Promotion and Advertising OTT Content Bundling OTT Premium Content OTT Video Caching OTT Video Optimization Service Tiering Application Based Charging Volume Based Charging Happy Hour Turbo Boost Bill Shock Prevention Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved. 11
Glossary Application Download Peer-to-Peer Applications (P2P) Video Streaming General Browsing The ability to download a Applications such as BitTorrent Communication directed HTTP traffic associated with wide range of free and paid and eMule. through video content including website browsing or other HTTP applications from online App YouTube, Hulu, Flash Media, traffic which is not downloading Instant Messaging (IM) Stores, available to users of HTTP Streaming, iPhone HTTP or streaming. In addition, Originally, instant messaging smartphones, tablets, netbooks, Live Streaming, Mobile HTTP web browsing also includes applications delivered real-time etc. App Stores include Apple Streaming etc. “Social Video” applications delivering real time text-based communications App Stores, Google Play, is part of video streaming and updates and statistics over between two or more users Blackberry App World, Nokia includes video sharing web HTTP. This category contains over the Internet. Today’s Ovi, Palm Catalog, Windows content such as YouTube. information sites such as news, IM applications offer a wider Marketplace for Mobile and weather, sports, etc. range of communication Social Networks many others. services including group Social networking content such Email Online Storage messaging, media sharing, as Facebook, Twitter, Indoona, Web email sites such as Gmail, HTTP download service, in video conferencing, voice LinkedIn, etc. Yahoo Mail, Hot Mail, SMTP and particular from one-click hosting communication and file transfer. POP3. Voice over IP (VoIP) sites such as RapidShare and Instant messaging applications Software applications that allow Megaupload, You Send It, include Google Talk, Windows users to conduct audio and Dropbox, etc. Live!, Yahoo!, QQ , WhatsApp, video communications over IP Facebook Messenger, etc. networks. VoIP applications include Skype, GoogleTalk and Vonage. . References Blau, P. M. (1977). Inequality and Heterogeneity, a Primitive Theory of Social Structure. The Free Press, New York Castells, M. Fernandez-Ardevol, M. Linchuan, J. & Sey, A. (2007). Mobile Communication and Society, a Global Perspective. The MIT Press Cambridge, Massachusetts, London, England. Cisco (2012): Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2011–2016 (White Paper). Cisco, February 14, 2012 Dutton, W. H. (2005). The Internet and social transformation: reconfiguring access, in Dutton, W. H., Kahin, B., O’Callaghan R. & Wycoff, A. (Eds). Transforming Enterprise. MIT Press, Cambridge, MA. 375–397. Green, N. (2002) On the move: Technology, Mobility, and mediation of social time and place. The information society, 18, 281-292. Ling, R. (2008). New Tech, New Ties: How Mobile Communication Is Reshaping Social Cohesion. The MIT Press, Cambridge, Masachusetts, London, England. Malthus T.R. ( 1798). An essay on the principle of population. Chapter V, p 39–45. Oxford World’s Classics reprint Wellman, B. (2001). Physical Place and Cyber-Place: Changing Portals and the Rise of Networked Individualism. International Journal for Urban and Regional Research, 25, 227-52. Wellman, Barry. (2002). Little Boxes, Globalization, and Networked Individualism. Tanabe, M. Besselaar, P. & Ishida, T (Eds.). Digital Cities II: Computational and Sociological Approaches, Berlin: Springer. 10-25.12 Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved.
Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved.
© Allot Communications, 02.2013. Specifications subject to change without notice. Allot Communications and the Allot logo are registered trademarks of Allot Communications. All other brand or product names are trademarks of their respective holders.About Allot CommunicationsAllot Communications Ltd. (NASDAQ, TASE: ALLT) is a leading global provider of intelligent broadband solutions that put mobile,fixed and enterprise networks at the center of the digital lifestyle. Allot’s DPI-based solutions identify and leverage the businessintelligence in data networks, empowering operators to shape digital lifestyle experiences and to capitalize on the network trafficthey generate. Allot’s unique blend of innovative technology, proven know-how and collaborative approach to industry standardsand partnerships enables service providers worldwide to elevate their role in the digital lifestyle ecosystem and to open the doorto a wealth of new business opportunities. For more information please visit: www.allot.comwww.allot.com firstname.lastname@example.orgAmericas: 300 TradeCenter, Suite 4680, Woburn, MA 01801 USA · Tel: (781) 939-9300 · Toll free: 877-255-6826 · Fax: (781) 939-9393 D265008 Rev 3Europe: NCI – Les Centres d’Affaires Village d’Entreprises ‘Green Side’, 400 Avenue Roumanille, BP309,06906 Sophia Antipolis Cedex, France · Tel: 33 (0) 4-93-001160 · Fax: 33 (0) 4-93-001165Asia Pacific: 6 New Industrial Road, #08-01, Hoe Huat Industrial Building, Singapore 536199 · Tel: +65-6283 8990 · Fax: +65-6282 7280Japan: 4-2-3-301 Kanda Surugadai, Chiyoda-ku, Tokyo 101-0062 · Tel: 81 (3) 5297-7668 · Fax: 81(3) 5297-7669Middle East and Africa: 22 Hanagar Street, Industrial Zone B, Hod-Hasharon, 45240, Israel · Tel: 972 (9) 761-9200 · Fax: 972 (9) 744-3626