Mobile trends report, Allot'2013

The Mobile Digital Lifestyle SegmentationAllot Mobile Trends 02/2013

Segmenting the Mobile Digital LifestyleAllot MobileTrends Report 02/2013

© 2013 Allot Communications. All rights reserved.Allot MobileTrends Report Q2/2013

Analysis Mr. Yossef Arie, Department of Sociology, University of Haifa, Israel

Photography, Mr. Yossef Massa, Netanya , Israel

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 advanced

Allot 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.

Allot MobileTrends Report Q2/2013 © 2013 Allot Communications. All rights reserved.2

29%

11%12%

8% 7% 7%5% 5%

20%

72%

% Subscribers

Gen

eral

Bro

wsi

ng

Soc

ial N

etw

orks

Vid

eo S

trea

min

g

Onl

ine

Sto

rage

Inst

ant

Mes

sagi

ng

Em

ail

Ap

p D

ownl

oad

s

P2P

Gam

ing

VoIP

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)

*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 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.

Table 1 Data Traffic Categories of Mobile Data Users

% Subscribers *

General Browsing 72%

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

Graph 1 Percent of Subscribers per Data Category

1 Based on the Heterogeneity Measure of Blau (1977): 1 –∑Pi2 when Pi is the % of data traffic of the data category.


Social Networks

Graph 2.1 Within the Social Networks category, Facebook accounts for 39% and Twitter 19% of the content visited. All others comprise 42%.

Peer to Peer

Graph 2.3 Within the Peer-to-Peer category, BitTorrent is the preferred destination, accounting for 68% of the P2P content visited. All others comprise 32%.

Video Streaming

Graph 2.2 Within the Video Streaming category, YouTube is the overwhelming favorite, accounting for 68% of the content visited. All others comprise 32%.

VoIP

Graph 2.4 Within the VoIP category, Skype accounts for 34% of the content visited. All others comprise 66%. (In our study, we did not differentiate between voice calls vs. chat or instant messaging done via Skype or other VoIP.)

Overall Usage by Data Category

Graph 2

Overall Usage by Data Category

Others42%

Twitter19%

Facebook39%

BitTorrent68%

Others 32%

YouTube68%

Others 32%

Skype34%

Others 66%


6:00

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BitTorrent Facebook YouTube Skype General Browsing

0%

2%

4%

6%

8%

10%P

erce

nt o

f Tra

ffic

Volu

me

Graph 3a

Data Consumption Patterns by Time-of-Day*

Graph 3b Data Consumption Patterns by Day*

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 middle of the day 13:00-15:00.

BitTorrent Facebook YouTube Skype General Browsing

Morning Mid Day Evening Night0%

10%

20%

30%

5%

15%

25%

35%

40%

Per

cent

of T

raffi

c Vo

lum

e

Application Traffic Volume Over an Average 24 Hour Period

* These graphs show the distribution of data volume for each application over a day.


Mixed Personal/Social

Use48%

Social Use 14%

Personal Use38%

Mixed Personal/Social

Use74%

Social Use 9%

Personal Use17%

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.

Subscriber % Traffic % Network Effect% Traffic /

% Subscribers

Personally active 38% 17% 45%

Socially active 14% 9% 64%

Mixed Personally/Socially active 48% 74% 154%

Total 100% 100%

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.

Table 2 Usage Types as Percent of Data Subscribers and Percent of Data Traffic

Graph 4a-b

Types of Usage: Personal, Social and Mixed

Usage Types as Percent of Data Subscribers

Usage Types as Percent of Data Traffic


Types of Usage: Personal, Social and Mixed Digital Lifestyle Segments

Info Seeker

• 32% of subscribers

• 12% of data traffic

• 75% use general web browsing

• 36% of the traffic is generated in the evening (compared to 28% for the total population)

Info Guzzler



• Divided into two distinct types:

a. General Browsing and P2P (33%)

b. General Browsing and Application Download (23%)

• 44% of use occurs during the middle of the day compared to 36% for the total population

Social Monitor



• Tends to access Social Network content (24%), Social Video (28%) and VoIP (18%)

• 45% of use occurs during the middle of the day compared to 36% for the total population

Social Mingler



• Engages in pairs of personal and social activity

• The leading pairs are General Browsing & Social Networks (35%), and General Browsing & Social Video (11%)

• 64% of use occurs during the middle of the day and evening which is similar to the total population

1 32

5

4

Digital Mover & Shaker



• Characterized by very high data usage. This segment combines personal data activity with social data activity

Leading 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


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.

% Subscribers % Traffic Network Effect(% Traffic /

% Subscribers)

Average Use

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 3 Mobile Digital Lifestyle Segmentation

Info Seeker Info Guzzler Social Monitor Social Mingler Digital Mover & Shaker

Total Pop.

Percent of Total Subscribers

32% 5% 14% 15% 34% 100%

Percent of Total Traffic 12% 5% 9% 16% 58% 100%

Average Activity Low Mid Mid Mid High

Data Categories Used App DownloadBrowsingP2PVideo Streaming

Browsing & App Download

Browsing & P2P

EmailSocial NetworksGamingIMSocial Video

Browsing & IM

Browsing & Social Networks

Browsing & Social Video

Online Storage

Browsing, Social Networks, Video Streaming & IM

Browsing, Social Video & VoIP


Total 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%

Table 4 Digital Lifestyle Segments


1. Info

Seeker

2. Info

Guzzler

3. Social

Monitor

4. Social

Mingler

5. Digital

Mover & Shaker

32%

12%

5% 5%

14%

9%

15% 16%

34%

58%

Subscribers

Traffic

Graph 5 Mobile Digital Lifestyle Segmentation

Graphs 7.1-7.5

Data Categories Used by Digital Lifestyle Segments

1. Info

Seeker

2. Info

Guzzler

3. Social

Monitor

4. Social

Mingler

5. Digital

Mover & Shaker

38%

100%

64%

107%

171%

Low

Mid

Mid

Mid

High

Segment Effect on the Network

Graph 6

18%

5%

2%

75%

Browsing

P2P

App Downloads

Video Streaming

34%

11%

4%

5%

46%



Online Storage

Browsing & IM

Other Pairs

Browsing & P2P

Browsing & App Downloads

Other Pairs

23%

33%

44%

31%

15%

54%


& Video Streaming & IM

Browsing & Social Video &

VoIP

Other Combinations

24%18%

10%

8%

11%

29%

Social Video

Social Networks

VoIP

Gaming

IM

Email

Info Seeker Info Guzzler

Social Mingler

Social Monitor

Digital Mover & Shaker


Graph 8 Digital Lifestyle Profiles by Time of Day

Mapping the Digital Lifestyle ProfilesGraph 9

Info Seeker(32%)

Info Guzzler(5%)

Social Monitor(14%)

Social Mingler(15%)

Digital Mover & Shaker(34%)

Total Population

16%

29%

18%

37%

15%

44%

12%

29%

17%

44%

15%

24%

17%

36%

18%

29%

19%

32%

21%

28%

18%

36%

18%

28%

Morning Mid-Day Evening Night


Percent of Subscribers (Percent of Traffic)

Personal Activities

Multi-tasker

Single-tasker

Social Activities


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 DownloadBrowsingP2PVideo Streaming

Browsing & App Download

Browsing & P2P

EmailSocial NetworksGamingIMSocial Video

Browsing & IM



Online Storage

Browsing, Social Networks, Video Streaming & IM

Browsing, Social Video & VoIP

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

Table 5: Allot’s Leading Use Cases for the Digital Lifestyle

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.


Glossary

.

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.

Application Download The ability to download a

wide range of free and paid

applications from online App

Stores, available to users of

smartphones, tablets, netbooks,

etc. App Stores include Apple

App Stores, Google Play,

Blackberry App World, Nokia

Ovi, Palm Catalog, Windows

Marketplace for Mobile and

many others.

Online StorageHTTP download service, in

particular from one-click hosting

sites such as RapidShare and

Megaupload, You Send It,

Dropbox, etc.

Peer-to-Peer Applications (P2P)Applications such as BitTorrent

and eMule.

Instant Messaging (IM)Originally, instant messaging

applications delivered real-time

text-based communications

between two or more users

over the Internet. Today’s

IM applications offer a wider

range of communication

services including group

messaging, media sharing,

video conferencing, voice

communication and file transfer.

Instant messaging applications

include Google Talk, Windows

Live!, Yahoo!, QQ , WhatsApp,

Facebook Messenger, etc.

Video StreamingCommunication directed

through video content including

YouTube, Hulu, Flash Media,

HTTP Streaming, iPhone HTTP

Live Streaming, Mobile HTTP

Streaming etc. “Social Video”

is part of video streaming and

includes video sharing web

content such as YouTube.

Social NetworksSocial networking content such

as Facebook, Twitter, Indoona,

LinkedIn, etc.

Voice over IP (VoIP)Software applications that allow

users to conduct audio and

video communications over IP

networks. VoIP applications

include Skype, GoogleTalk and

Vonage.

General BrowsingHTTP traffic associated with

website browsing or other HTTP

traffic which is not downloading

or streaming. In addition,

web browsing also includes

applications delivering real time

updates and statistics over

HTTP. This category contains

information sites such as news,

weather, sports, etc.

EmailWeb email sites such as Gmail,

Yahoo Mail, Hot Mail, SMTP and

POP3.


© 2013 Allot Communications. All rights reserved.Allot MobileTrends Report Q2/2013

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Middle East and Africa: 22 Hanagar Street, Industrial Zone B, Hod-Hasharon, 45240, Israel · Tel: 972 (9) 761-9200 · Fax: 972 (9) 744-3626

www.allot.com [email protected]

About Allot Communications

Allot 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 business intelligence in data networks, empowering operators to shape digital lifestyle experiences and to capitalize on the network traffic they generate. Allot’s unique blend of innovative technology, proven know-how and collaborative approach to industry standards and partnerships enables service providers worldwide to elevate their role in the digital lifestyle ecosystem and to open the door to a wealth of new business opportunities. For more information please visit: www.allot.com

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