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Mobile Broadband Grand Prix 2013-2016

LONDON, Jan. 20, 2014 /PRNewswire/ -- Reportbuyer.com just published a new market research report:

Mobile Broadband Grand Prix 2013-2016

Formula 1 MBB Strategies to Fuel-up ARPU Tanks, Fostering Consumer Adoption, Locking Churn, and Traffic Offloading Techniques in Rural & Urban Global Mobile Markets, Constituting up-to-the An accurate study of the present and the expected face of the telecom market based on detailed research by our experts has been supported by true data extracted from the grass root levels. This study is a conclusive report based on interviews, data mining techniques, in depth analysis, scrutiny of factual data and possible innovative propositions that could equip an entity to tackle the ongoing advancements in the industry. Executive Summary Mobile Broadband Grand Prix 2013 [aka MBG 2013] is the latest version of our Bestseller report for 2 years. Unlike earlier, this updated version takes on price wars, user segmentation, mobile Internet usages & content, urbanisation, traffic management, infra leasing & network collaborations, and App business modeling. A brief snapshot of the update: • A complete accuracy check based on new information and estimates gathered via numerous interviews with C-level executives & survey polling; • Approximately 40-50% of the makeover is attributable to the real-time, genuine feedback of existing customers; • Concrete guidelines & recommendations for small to mid-sized service providers (MNOs, ISPs, Device Manufacturers, etc.); • Re-evaluation of the industry forecasts & expected scenarios emerging ahead; • Innovative Mobile Revenue Sourcing strategies; And, much more... Here comes another run-of-the-mill Report…is probably you might be thinking when we talk of Mobile Broadband. Enough has been written about it over and over again and understandably, you might smirk at another Report on the same subject. But TeleResearch Labs has a different psychology altogether when it comes to research – Our analysts, even though veterans in their field, never preen themselves on being 'experts'; instead, they adopt a naïve approach to every research project, and 'attempt' to become 'experts'. And that's why when our sleuths are assigned any project, they dig right uptill they obliterate the chances of anything being left out or overlooked regarding the subject. MBB Grand Prix 2013 – 2016 is another such attempt. 2010 & 2011 were disruptive years for the telecom industry worldwide. This was probably the first time the industry realised just how mammoth the task is to manage the spiraling data traffic on their networks as it reached nearly 597 petabytes per month at 2011 year-end. The consumer has been pampered with way too many promises, but have you – operator, vendor, device maker, really come up with a foolproof business solution to accommodate all those promises? Are you even close to managing it? Or, for some, we might ask – Can you ever manage it at all? MBB is here to stay – and it's nothing short of pathetic that nearly every research house is doing the subject to death with a stale approach. We, at TeleResearch Labs took upon this study from a different perspective altogether – over the past 1 year, our team scrutinised over 100,000 pages of official data; reviewed performance of over 300 companies globally; interviewed nearly 100 executives; and studied more than 80 business models. What the analyses revealed was shocking – We deduced that the majority of businesses are hurtling towards a bleak abyss if they continue their MBB strategies the way they are. What was even more disconcerting was the fact that many have not bothered to think beyond and are smugly sure they are up the right track. All that hoopla about sure-shot business models – be it pricing or revenue sharing, innovative VAS, ARPU enhancers, traffic offloading etc. has been shredded in our Report for we unearthed that a sea-change is required if MNOs, vendors and the app community finally get down to doing things differently rather than running up the same old path and following the same old staid business models. So that all businesses/ concerns even remotely connected to MBB ensure that they do not skid off the track in the period which is nothing short of a 'Grand Prix' of the telecoms, we have presented solutions keeping 'differentiation' in mind – to ensure that all who have what it takes, achieve their revenues and ARPU targets during the next 4 years, while cutting back churn and enhancing consumer loyalty. Pricing is fast approaching to becoming a second-hand tool for cutting churn – VAS would be the stronger one, but then again, are you sure you are tapping enough into the average consumer's psychology to keep on enticing him with your VAS? Moreover, is your technology really supportive to all the VAS your marketing team might be envisaging? There's a sea of 'unexploited' consumers left to fish in. Do not think the fish will bite the hook – You have to bait them. Europe and North America would lag behind Asia Pacific in MBB growth. Why? MNOs in these regions need to drive consumer adoption in strategically different ways. Asia Pacific is huge in terms of population – and that alone is one of the factors; but then you must consider that relatively larger portions of the region are highly underserved. Socio-economic constraints of the sub-regions have to be conquered to blast them with MBB. Towards this the MNOs must adopt a long-term strategy, one in which they should not be expecting too much too soon. On the other hand, markets in Europe and North America have a different composition. The challenge lies not really in expanding the MBB base, but rather, to 'enhance' it. The psychological make-up of an average user in these regions is like a child reaching adolescence overnight – it is the case of too much too soon. MNOs and vendors need a different approach now. More customisation is required, both in terms of MBB offerings and smartphones. The next 4 years are do-or-die for many players – it's the 'Grand Prix' of the Telecoms industry in which the winner would be the one who drives Mobile Broadband the hardest, smartest way. Our Report essentially provides you the tools to do that very thing – Drive Mobile Broadband till you annihilate each and every potential consumer segment, worldwide, to the point they come to depend upon MBB, be it the ritzy settings in the USA and Western Europe or the murky darkness of Africa or the vast sands of the Middle East. MBB Grand Prix 2013 – 2016 spans across the telecom globe and covers every nerve of the industry – Be it the ammunition on MBB market penetration in unserved, underserved regions, stifling churn in saturating markets; analysing the scope of various technological platforms vis-à-vis MBB, traffic management and offloading solutions, innovative VAS and many more…our analysts haven't left out anything. Besides, we have given detailed MBB forecasts (global and regional) on subscribers, revenues, ARPUs (including 3 global giants), mobile apps, mobile messaging traffic like SMS, MMS, mobile e-mail and IM, consumer adoption of various technology platforms etc. in a whooping number of 128 figures and 39 tables. As an add-on, we have packed in numerous compelling case studies on MNOs and app stores. So, do not wait – The MBB Grand Prix has begun. Fuel-up, get set, and step on the accelerator now!
Chapter 1: Executive Summary Chapter 2: Competitive Strategies and Analyses of the Worldwide Mobile, Fixed-Line Broadband Operators/ Vendors, and Propositions for 2011 - 2016 2.1 A Market Survey - Decoding the MBB Mindset of Consumers 2.2 Fixed-Line Broadband versus Mobile Broadband – Their Past, Your Future Figure 2-1 Global Mobile Broadband and Fixed-Line Broadband Subscriptions (In Billion), 2011 & 2012 Figure 2-2 Mobile Broadband Subscriptions by Region (In Million), 2011 & 2012 Figure 2-3 Mobile Broadband Subscriptions by Region (In %), 2010 – 2012 Figure 2-4 Mobile Broadband Subscriptions by Region (In %), 2012 Figure 2-5 Fixed-Line Broadband Subscriptions by Region (In Million), 2011 & 2012 Figure 2-6 Fixed-Line Broadband Subscriptions by Region (In %), 2012 Table 2-1 Mobile Broadband and Fixed-Line Broadband Annual Growth (In %), 2011 Figure 2-7 Mobile Broadband Subscriptions per 100 Inhabitants (World and by Level of Development), 2010 - 2012 Figure 2-8 Fixed-Line Broadband Subscriptions per 100 Inhabitants (World and by Level of Development), 2010 - 2012 Figure 2-9 Fixed-Line Broadband & Mobile Broadband Subscriptions per 100 Inhabitants by Region, 2011 2.3 Pros and Cons of Mobile Broadband and Fixed-Line Broadband 2.3.1 Mobile Broadband 2.3.2 Fixed-Line Broadband 2.4 How fixed-line/ wireless broadband can maneuver around mobile broadband? 2.5 Competitive Strategies for Mobile and Fixed-Line Broadband Players 2.5.1 Fixed-Line Operators 2.5.2 Fixed-Line Vendors 2.5.3 Mobile Operators 2.5.4 Mobile Vendors 2.6 The Know-How of Prepaid and Postpaid MBB 2.7 Viability, Comparison and Evaluation of the Different Internet Mediums 2.7.1 Narrowband Dial-up 2.7.2 Narrowband ISDN 2.7.3 DSL Broadband 2.7.4 Cable Broadband 2.7.5 Wireless Broadband 2.7.6 Satellite Broadband Table 2-2 Comparison of Broadband and Narrowband Table 2-3 Comparison of Download Time in Dial-Up & Broadband Internet Chapter 3: Regional Mobile Broadband Forecasts – Subscriptions and Revenues 2013 – 2016 3.1 MBB Subscriptions Forecast (2013 - 2016) Figure 3-1 Global MBB Subscriptions Forecast (In Million), 2011 - 2016 Figure 3-2 MBB Subscriptions by Region (In Million), 2011 & 2012 Figure 3-3 MBB Subscriptions by Region (In %), 2012 Figure 3-4 MBB Subscriptions Forecast by Region (In Million), 2016 Figure 3-5 MBB Subscriptions Forecast by Region (In %), 2016 Figure 3-6 MBB Subscriptions Forecast by Region (In Million), 2012 – 2016 Figure 3-7 MBB Subscriptions Forecast by Region (In Million), 2012 & 2016 3.2 MBB Revenues Forecast 2013 – 2016 Figure 3-8 Global MBB Revenues (In Billion US$), 2010 – 2012 Figure 3-9 Global MBB Revenues Forecast (In US$ Billion), 2012 – 2016 Figure 3-10 MBB Revenues Forecast by Region (In US$ Billion), 2012 - 2016 Table 3-1 MBB Revenues Forecast by Region (In US$ Billion), 2012 - 2016 Chapter 4: Roadmap to Build a Fail-safe MBB Business Platform 4.1 MBB Staircase 4.2 GSM/ 3GPP1 Family 4.2.1 EDGE Evolution Table 4-1 Benefits of EDGE 4.2.2 UMTS (Universal Mobile Telecommunications System) 4.2.3 HSPA (High Speed Packet Access) and HSPA+ 4.2.4 LTE (Long Term Evolution) LTE, a Road to LTE Advanced Table 4-2 LTE Vs. LTE-Advanced: Key Performance Indicators 4.2.5 CDMA/ 3GPP2 Family CDMA2000 1XEV-DO (Evolution Data Only) Revision 0 Standard Revision and path towards CDMA EV-DO Revision A and Revision B TIA-856 Revision 0 4.2.6 WiMAX (Worldwide Interoperability for Microwave Access) LTE vs. WiMAX: Who would win, finally? Figure 4-1 MBB Subscriptions Market Share by Technology (In %), 2016 Figure 4-2 MBB Subscriptions Forecast by Technology (In Million), 2016 4.2.7 Wi-Fi Table 4-3 Wi-Fi SWOT Analysis Figure 4-3 Wi-Fi Hotspots for Selected Operators (In Numbers), 2012 4.2.8 Mi-Fi Table 4-4 Regional Penetration of Rest of the Technologies 4.3 Mobile Broadband Catalysts and Hindrances Table 4-5 Mobile Broadband Catalysts Table 4-6 Mobile Broadband Hindrances 4.4 Mobile Broadband Devices – Viability and Usage 4.4.1 USB Modems/ USB Dongles 4.4.2 Embedded Modems 4.4.3 PC Cards and Express Cards 4.4.4 Mobile Phone Handsets Chapter 5: Mobile Internet Traffic – Regional Forecasts, Smart Offloading and Innovative Techniques to Rein-in the 'Raging Bull'; and Methodology to Fuel MBB ARPUs 2013 – 2016 5.1 Global Traffic Meter – Accidents Waiting to Happen! Figure 5-1 Mobile Data Traffic Y-o-Y Growth by Application Category (In %), 2012 Figure 5-2 Global Monthly Mobile Data Traffic Forecast (In EB), 2012 – 2016 Figure 5-3 Global Monthly Mobile Data Traffic per User Forecast (In GB), 2012 - 2016 Table 5-1 Mobile Data Traffic per Month by Region (In TB), 2012 - 2016 Figure 5-4 Mobile Data Traffic per Month by Region (In %), 2012 - 2016 Table 5-2 Mobile Data Traffic per Month by Device Type (In TB), 2012 - 2016 Figure 5-5 Mobile Data Traffic per Month by Device Type (In TB), 2012 - 2016 Table 5-3 Mobile Data Traffic per Month by Application Category (In TB), 2012 - 2016 Figure 5-6 Mobile Data Traffic per Month by Application Category (In %), 2012 – 2016 5.2 Manage Your Data Traffic Now, or Perish! 5.3 Traffic Offloading Techniques – A Shredding Analysis 5.4 Scope of Traffic Offloading Solutions – An Eye-Opener 5.5 Femtocell vs. Wi-Fi for Data Offloading – Which would make the ultimate cut? 5.6 What are the Alternatives to Traffic Offloading Solutions? Figure 5-7 Traffic Management Chaos 5.7 Feasibility of Offloading onto Other Networks 5.8 Different Devices Need Different Concepts 5.9 MBB Data ARPUs – Let's Fuel-up Your Tanks Now! 5.9.1 The Effect of Mobile Broadband on Operator's Revenue (ARPU) Figure 5-8 Blended ARPU, MBB Operators and Non-MBB Operators, 2005 - 2012 5.9.2 Mobile Operator's Revenue from Non-Voice Services Figure 5-9 Share of Mobile Operator's Revenue from Non-Voice Services (In %), 2005, 2011, 2012 & 2016 5.10 MBB ARPU Trends of Major MNOs 5.10.1 AT&T Inc., USA Figure 5-10 AT&T Total Wireless Data ARPU (In US$), Q2 2011 – Q1 2012 Figure 5-11 AT&T Postpaid Wireless Data ARPU (In US$), Q3 2011 & Q3 2012 5.10.2 Bharti Airtel Ltd., India Figure 5-12 Bharti Airtel Indian Market Data ARPU (In INR), Q4 FY12 & Q1 FY13 5.10.3 NTT, Japan Figure 5-13 NTT Packet ARPU of MBB Services (FOMA, Xi), (In Yen), 2010 - 2012 Chapter 6: Mobile Broadband –Tasting the Success by Unheard-Of VAS Strategies; Driving MBB in Underserved Regions and Crashing the Untapped 6.1 How to create an irresistible need for mobile broadband? Table 6-1 Affect of Development, Resource Management and Networking on Society 6.2 Have you really exhausted your VAS pipeline? Think Again! 6.3 VAS Based on Subscription Services 6.4 VAS Embedded In the Mobile Phone 6.5 Have you thought of these VAS…? Perhaps Not! 6.6 Rural/ Underserved Regions – Opportunities and Challenges 6.6.1 Opportunities 6.6.2 Challenges 6.7 Unserved Regions - Would they ever become penetrable? 6.8 Metropolitan Regions – Emerging Challenges Chapter 7: Mobile Broadband – Regional Consumer Psychology, Usage Patterns and Volumes 2013 – 2016 Figure 7-1 Mobile Broadband Subscriptions by Region (In %), 2012 Figure 7-2 Mobile Broadband Subscriptions by Region (In Million), 2011 & 2012 7.1 Europe Figure 7-3 Europe Mobile Broadband Subscriptions Forecast (In Million), 2012 – 2016 7.2 Asia Pacific Figure 7-4 Asia Pacific Mobile Broadband Subscriptions Forecast (In Million), 2012 – 2016 7.3 The Americas Figure 7-5 The Americas Mobile Broadband Subscriptions Forecast (In Million), 2012 – 2016 7.4 Africa Figure 7-6 Africa Mobile Broadband Subscriptions Forecast (In Million), 2012 – 2016 7.5 Arab States & CIS Figure 7-7 Arab States Mobile Broadband Subscriptions Forecast (In Million), 2012 – 2016 Figure 7-8 CIS Mobile Broadband Subscriptions Forecast (In Million), 2012 – 2016 Chapter 8: Mobile Broadband - Innovative Pricing Models for Different Consumer Segments and Churn Poisoning Ploys Figure 8-1 Important Factors behind a Successful Pricing Strategy 8.1 Corporate 8.1.1 Vodafone Ireland's Business Share Plan Table 8-1 Vodafone Ireland's Business Share Plan, November 2012 Table 8-2 Vodafone Ireland's Business Share Plan, November 2012 – Key Features Table 8-3 MBB (Tablet) Corporate Pricing Models by Vodafone UK, November 2012 8.2 Individual/ Personal Table 8-4 Individual/ Personal MBB Plans by Vodafone New Zealand, November 2012 8.2.1 A Possible Special Pricing Model for Individual Users 8.3 Students 8.3.1 A Possible Pricing Model for Students Vodafone Greece 'University Mobile Internet' 8.4 Heavy Users or Frequent Travelers Table 8-5 Vodafone UK MBB Plan for Business Travelers, November 2012 8.4.1 A Possible Pricing Plan for Frequent Travelers and Business Executives 8.5 Light Users Table 8-6 Vodafone Australia's Prepaid Mobile Broadband Plans, November 2012 8.5.1 A Possible MBB Tariff Structure for Light Users 8.6 Mobile Broadband Churn Poisoning Ploys 8.6.1 Effective Strategies to Reduce Churn Rate and Retain Customers Table 8-7 Effective Techniques to Cut Churn Table 8-8 Management of Post-paid and Pre-paid User Class Figure 8-2 How to Drive Customer Retention and Loyalty? Chapter 9: Global Mobile Messaging – Forecasts on Volumes, Users (Consumer Vs. Business) & Revenues, and Key Factors Affecting Usage 2013 – 2016 Figure 9-1 Global Mobile Messaging Traffic (In Trilion), 2012 – 2016 Figure 9-2 Global Mobile Messaging Revenue (In US$ Billion), 2011 – 2016 9.1 OTT Messaging Figure 9-3 Global OTT Messaging Traffic (In Trilion), 2011 – 2016 9.2 SMS, MMS, Mobile E-Mail and IM – What the Future Holds? Figure 9-4 Global Mobile Messaging Traffic by Type (In Billion), 2012 - 2016 Figure 9-5 Global Mobile Messaging Traffic by Type (In %), 2012 - 2016 Figure 9-6 Global Mobile Messaging Traffic Share by Type (In %), 2012 Figure 9-7 Global Mobile Messaging Traffic Share by Type (In %), 2016 Figure 9-8 Global SMS Traffic (In Billion), 2011 - 2016 Figure 9-9 Global MMS Traffic (In Billion), 2011 - 2016 Figure 9-10 Global Mobile Email Traffic (In Billion), 2012 - 2016 Figure 9-11 Global Mobile IM Traffic (In Billion), 2011 - 2016 Figure 9-12 Global SMS Users (In Million), 2011 - 2016 Figure 9-13 Global MMS Users in Consumer segment (In Million), 2011 - 2016 Figure 9-14 Global Mobile Email Users (In Million), 2011 - 2016 Figure 9-15 Global Business Mobile IM Users (In Million), 2011 - 2016 Figure 9-16 Influential Factors that affect Uptake of Mobile Messaging Services Chapter 10: MBB - Thought Provoking Case Studies 10.1 Case Study 1: NTT DoCoMo, Japan Table 10-1 Quick Facts – NTT DoCoMo, Japan 10.1.1 About the Operator 10.1.2 Why NTT DoCoMo? Figure 10-1 NTT DoCoMo Subscriptions (In Thousands), FY2008 – FY2011 Figure 10-2 Subscriber Share of MNOs in Japan (In %), FY2011 Figure 10-3 FOMA (3G) Subscriptions of NTT DoCoMo (In Million), FY2010 & FY2011 Figure 10-4 Xi (LTE) Subscriptions of NTT DoCoMo (In Thousands), FY2010 & FY2011 Figure 10-5 Packet ARPU of NTT DoCoMo (In JPY), FY2008 – FY2011 Figure 10-6 NTT DoCoMo Subscriptions (In Million) & Churn Rate (In %), FY2008 – FY2011 Figure 10-7 NTT DoCoMo Subscriber Segment by Network Coverage (In %), October 2012 Figure 10-8 NTT DoCoMo Smartphone Sales FOMA Vs. Xi (In Million Units), Fy2010 – FY2012 Figure 10-9 NTT DoCoMo d-market Revenue (in Yen Billion), FY2012 & FY2015 Figure 10-10 NTT DoCoMo VIDEO Store Subscribers (In Million), 2012 10.2 Case Study 2: Ncell, Nepal Table 10-2 Quick Facts – Ncell, Nepal 10.2.1 About the Operator 10.2.2 Rationale behind selecting Ncell 10.2.3 Ncell – Outperforming Competition! Figure 10-11 Ncell Subscribers (In Million), mid-July 2012 & mid-August 2012 Figure 10-12 Ncell Revenue Share (In %), FY2009 – FY2011 Figure 10-13 Ncell Revenue (In NPR Billion), FY2009 – FY2011 10.2.4 Recent Strategies and Developments Call UK at Rs. 4.99/min Ncell's Utsav Pack Ncell Express 10.3 Case Study 3: Telkomsel, Indonesia Table 10-3 Quick Facts – Telkomsel, Indonesia 10.3.1 About the Operator 10.3.2 Rationale behind the Case Figure 10-14 Telkomsel Revenue (In IDR Trillion), 2009 – 2011 & Q1 2012 Figure 10-15 Telkomsel Revenue Break-up (Data & VAS Vs. SMS Vs. Voice) (In IDR Trillion), 2009 – 2011 & Q1 2012 Figure 10-16 Telkomsel Revenue Break-up (Data & VAS Vs. SMS Vs. Voice) (In %), 2009 – 2011 & Q1 2012 Figure 10-17 Telkomsel Data Revenue Contribution (In %), 2009 – Q1 2012 Figure 10-18 Telkomsel Subscribers (In Million), 2012 March, 2012 June & 2012 Oct Figure 10-19 Telkomsel Subscribers (In Thousands), 2007-2011 Figure 10-20 Telkomsel SMS (Chargeable) Traffic (In Billion), 2007-2011 10.3.3 Success Enablers Table 10-4 Telkomsel, Indonesia - VAS, SMS & Broadband Services 10.4 Case Study 4: Vodafone, India Table 10-5 Quick Facts – Vodafone, India 10.4.1 About the Operator 10.4.2 Rationale behind the Case Figure 10-21 Vodafone India Total Revenue (In INR Billion), H1 FY2011 - H1 FY2013 Figure 10-22 Vodafone India Messaging Revenue (In INR Billion), H1 FY2011 - H1 FY2013 Figure 10-23 Vodafone India Data Revenue (In INR Billion), H1 FY2011 - H1 FY2013 Figure 10-24 Vodafone India Messaging Vs. Data Revenue (In INR Billion), H1 FY2011 - H1 FY2013 Figure 10-25 Vodafone India Customers (In Million), Q3 FY2011 – Q2 FY2013 Figure 10-26 Vodafone India ARPU (In INR), Q3 FY2011 – Q2 FY2013 Figure 10-27 Vodafone India Prepaid ARPU (In INR), Q3 FY2011 – Q2 FY2013 Figure 10-28 Vodafone India Contract ARPU (In INR), Q3 FY2011 – Q2 FY2013 10.4.3 Key Strategies to Drive Mobile Broadband Usage Table 10-6 Vodafone India 3G Services, November 2012 Vodafone India 3G Data Plans Table 10-7 Vodafone India Prepaid 3G Tariff Plans, November 2012 Table 10-8 Vodafone India Postpaid 3G Tariff plans, November 2012 Table 10-9 Vodafone India Unlimited Postpaid 3G Tariff plans, November 2012 Chapter 11: Mobile Applications – An Exhaustive Analysis of Platforms, App Stores, Business Models, and Regional Forecasts on App Downloads and Revenues 2013 – 2016 11.1 Mobile Applications Overview Figure 11-1 Average Number of Apps Installed on a Smartphone, 2011 & 2012 Figure 11-2 US Web vs. Mobile App vs. TV Consumption per day (In Minutes), 2010 – 2012 11.2 Mobile App Stores – Flooding To Quench Users' Thirst Table 11-1 Major App Stores 11.3 Developments in Smartphone App Markets Table 11-2 Six Major Trends Shaping the Smartphone Application Ecosystem 11.4 Business Models of App Stores Figure 11-3 Obstacles of Third Party App Developer Programs Table 11-3 Different Approaches to Working with ACPs 11.5 Market Trends & Outlook 11.5.1 Free Mobile Applications Dominate the App Market Figure 11-4 Worldwide Mobile Apps Downloads - Free vs. Paid (In %), 2012 Table 11-4 Worldwide Mobile Apps Downloads Forecast - Free vs. Paid (In Million), 2011 - 2016 Figure 11-5 Worldwide Mobile Apps Downloads Forecast - Free vs. Paid (In Million), 2011 - 2016 Figure 11-6 Worldwide Mobile Apps Downloads Forecast (In Billion), 2011 – 2016 Figure 11-7 Worldwide Free Mobile Apps Downloads Forecast (In Billion), 2011 - 2016 Figure 11-8 Worldwide Mobile Apps Downloads Forecast - Free vs. Paid (In %), 2012 & 2016 11.5.2 Competitive Landscape Figure 11-9 Mobile App Store Size (In Numbers), September 2012 Figure 11-10 Worldwide Average App Revenue per User by Operating System (In US$), 2012 11.5.3 Application Categories Figure 11-11 Worldwide Smartphone App Consumption per day by Category (In Minutes), Q1 2011 & Q1 2012 Figure 11-12 Fastest Growing App Categories - Based on Growth in Minutes Spent per Active User from October 2011 to March 2012 11.5.4 Sources of Revenue Table 11-5 Mobile Apps Revenue Sources (In %), 2012 Figure 11-13 Mobile Apps Revenue Sources (In %), 2012 11.5.5 Mobile App Revenue Figure 11-14 Worldwide Mobile App Revenue Forecast (In US$ Billion), 2011 - 2016 Figure 11-15 iOS Revenue in Key Markets (In %), October 2012 Figure 11-16 Google Play Revenue in Key Markets (In %), October 2012 Figure 11-17 Revenue Generated by Applications Available in the Local Languages & Apps Available in Local Language (In %), May 2012 11.6 Overview of top Five Most Popular Social Networking Sites, and their Affect on MBB Uptake Table 11-6 Worldwide Top Five Most Popular Social Networking Sites, 2012 Figure 11-18 Facebook Users by Region (In Million), September 2012 Figure 11-19 Worldwide Facebook Penetration Rate (In %), Q1 2011 & Q1 2012 Figure 11-20 Facebook Net Income (In US$ Billion), 2009 - 2011 Figure 11-21 Top 20 Countries by Number of Twitter Accounts (In Million), July 2012 Figure 11-22 Worldwide Twitter Ad Revenue Forecast (In US$ Million), 2010 - 2016 Figure 11-23 Twitter Ad Revenue Forecast – US vs. Non-US (In US$ Million), 2011 -2016 Figure 11-24 LinkedIn Total Revenue (In US$ Million), Q2 2010 – Q2 2012 Figure 11-25 LinkedIn Total Revenue by Segment (In US$ Million), Q2 2010 – Q2 2012 Figure 11-26 Myspace Revenue (In US$ Million), 2011 & 2012 Figure 11-27 Google+ Users (In Million), June 2011June 2012 11.7 Key Elements of Facebook and Twitter 11.7.1 Why people love Facebook? 11.7.2 What's so special about Twitter? 11.8 Communication Styles in different Social Settings 11.9 So Which Social Network is the Best? 11.10 What is an App-Centric Business Model? Figure 11-28 App-Centric Business Model – Explained 11.11 What is an Operator-Centric Business Model? Figure 11-29 Operator-Centric Business Model – Explained Figure 11-30 Revenue sharing in Operator-Centric Business Model Chapter 12: Mobile Applications – Business Models and Case Studies 12.1 Case Study 1: Apple App Store [Side by Side Comparison with Google Play] Figure 12-1 Number of Applications on iTunes App Store vs. Google Play, July 2008July 2012 Figure 12-2 Apple App Store Paid vs. Free Applications (In %), 2012 Figure 12-3 iOS Application Downloads in Key Markets (In %), October 2012 Figure 12-4 Google Play Application Downloads in Key Markets (In %), October 2012 Figure 12-5 Apple App Store Revenue (In US$ Billion), 2011 & 2012 Figure 12-6 Average Prices of Most Popular Apps – iPad vs. iPhone vs. Android (In US$), January 2012 12.1.1 Business Model 12.1.2 Key Developments 12.2 Case Study 2: BlackBerry World Figure 12-7 BlackBerry Apps (in Numbers), January 2012, April 2012 & September 2012 Figure 12-8 BlackBerry Apps Downloads, January 2012 & September 2012 Figure 12-9 Average Revenue per App per Month (in US$), 2012 Table 12-1 BlackBerry World – App Categories, 2012 12.2.1 Business Model Chapter 13: So, Are You Ready for 'The MBB Grand Prix 2013 – 2016'? 13.1 Present Situation of Mobile Broadband (2011-2012) 13.2 The Path Ahead 13.2.1 Underserved Markets 13.2.2 Unserved Markets 13.2.3 Matured Markets Table 13-1 Strategies to Cope with Increasing Demand for Data Services over Mobile Networks

Read the full report:
Mobile Broadband Grand Prix 2013-2016

For more information:
Sarah Smith
Research Advisor at Reportbuyer.com
Email: [email protected]  
Tel: +44 208 816 85 48
Website: www.reportbuyer.com

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A critical component of any IoT project is what to do with all the data being generated. This data needs to be captured, processed, structured, and stored in a way to facilitate different kinds of queries. Traditional data warehouse and analytical systems are mature technologies that can be used to handle certain kinds of queries, but they are not always well suited to many problems, particularly when there is a need for real-time insights.
DevOps is being widely accepted (if not fully adopted) as essential in enterprise IT. But as Enterprise DevOps gains maturity, expands scope, and increases velocity, the need for data-driven decisions across teams becomes more acute. DevOps teams in any modern business must wrangle the ‘digital exhaust’ from the delivery toolchain, "pervasive" and "cognitive" computing, APIs and services, mobile devices and applications, the Internet of Things, and now even blockchain. In this power panel at @...
One of biggest questions about Big Data is “How do we harness all that information for business use quickly and effectively?” Geographic Information Systems (GIS) or spatial technology is about more than making maps, but adding critical context and meaning to data of all types, coming from all different channels – even sensors. In his session at @ThingsExpo, William (Bill) Meehan, director of utility solutions for Esri, will take a closer look at the current state of spatial technology and ar...
Everyone knows that truly innovative companies learn as they go along, pushing boundaries in response to market changes and demands. What's more of a mystery is how to balance innovation on a fresh platform built from scratch with the legacy tech stack, product suite and customers that continue to serve as the business' foundation. In his General Session at 19th Cloud Expo, Michael Chambliss, Head of Engineering at ReadyTalk, will discuss why and how ReadyTalk diverted from healthy revenue an...
SYS-CON Media announced today that @WebRTCSummit Blog, the largest WebRTC resource in the world, has been launched. @WebRTCSummit Blog offers top articles, news stories, and blog posts from the world's well-known experts and guarantees better exposure for its authors than any other publication. @WebRTCSummit Blog can be bookmarked ▸ Here @WebRTCSummit conference site can be bookmarked ▸ Here
SYS-CON Events announced today that Streamlyzer will exhibit at the 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Streamlyzer is a powerful analytics for video streaming service that enables video streaming providers to monitor and analyze QoE (Quality-of-Experience) from end-user devices in real time.
You have great SaaS business app ideas. You want to turn your idea quickly into a functional and engaging proof of concept. You need to be able to modify it to meet customers' needs, and you need to deliver a complete and secure SaaS application. How could you achieve all the above and yet avoid unforeseen IT requirements that add unnecessary cost and complexity? You also want your app to be responsive in any device at any time. In his session at 19th Cloud Expo, Mark Allen, General Manager of...
In past @ThingsExpo presentations, Joseph di Paolantonio has explored how various Internet of Things (IoT) and data management and analytics (DMA) solution spaces will come together as sensor analytics ecosystems. This year, in his session at @ThingsExpo, Joseph di Paolantonio from DataArchon, will be adding the numerous Transportation areas, from autonomous vehicles to “Uber for containers.” While IoT data in any one area of Transportation will have a huge impact in that area, combining sensor...
Almost everyone sees the potential of Internet of Things but how can businesses truly unlock that potential. The key will be in the ability to discover business insight in the midst of an ocean of Big Data generated from billions of embedded devices via Systems of Discover. Businesses will also need to ensure that they can sustain that insight by leveraging the cloud for global reach, scale and elasticity.