Worldwide Mobile Big Data Market 2016-2020
Table of Contents
Chapter 1: Prologue: A fresh perspective for Big Data
Chapter 2: Big Data: Simplified technical concepts, market drivers, challenges, value creation, risk assessment and investment priorities
2.1 Prime reasons for telcos to explore big data
2.1.1 Market saturation slowing conventional growth prospects
2.1.2 ARPU is continuously falling
2.1.3 Telcos need to preserve existing revenue sources
2.1.4 Overcoming churn
2.1.5 Declining profitability from mobile data business: Dumb pipe scenario
2.1.6 OTTs are hurting telcos’ business bottom lines
2.1.7 Telcos continuously losing their relevance in the value chain
2.1.8 Telcos need to add new business and create new sources of revenue
2.2 Telecom perspective on Big Data
2.3 Gauzing Big data strength of telco operators
2.4 Big data monetisation challenges for telco operators
2.5 Advanced analytics and big Data can create big business value
Chapter 3: Big Data: Modern business use cases, analysis & decision making
3.1 Big data Innovative Business models
3.1.1 Enhanced API Enablement and NextGen VAS
3.1.2 Explore transaction data for boosting sales
3.2 Leverage Big Data for Precision Marketing
3.2.1 Offer Optimisation at Individual level
3.2.2 Enhanced Churn Prediction and Prevention
3.2.3 Profitable Product Packaging for Specific OTT
3.3 Improved Operational Efficiency
3.3.1 Smart and pre-emptive Customer care
3.3.2 Intelligent Network Planning and monetisation
3.3.3 Cell-Site Optimisation
3.3.4 Subscriber-Centric Wireless Offloading
3.4 Real Time Network and Subscriber Intelligence
3.4.1 Enhanced prediction and management of temporary/ sudden Network Congestion
3.4.2 Enable Location Based and Personalized Advertising
3.4.3 Social Media and Sentiment Analysis
3.5 Quality of service (QoS) enhancement
3.5.1 Dynamic Subscriber Profiling and Segmentation
Chapter 4: Worldwide Significant Telco Case Studies: Projects, Evolution, Timelines and future strategies
4.1 Verizon’s Precision Market Insights
4.2 Telefonica Dynamic Insights
4.3 Weve, O2
4.4 China Mobile Guangdong billing and customer service.
4.5 LIVE Singapore!
4.6 Singtel’s DataSpark
Chapter 5: Top telco-focused big data vendors: Profile, Market positioning, Investments and solutions
5.1 Accenture
5.2 Argyle Data
5.3 Capgemini
5.4 Cloudera
5.5 CSC
5.6 Ericsson
5.7 Hewlett-Packard (HP)
5.8 Huawei
5.9 IBM
5.10 Microsoft
5.11 Nokia Networks
5.12 Platfora
5.13 SAP
5.14 TIBCO
Chapter 6: Global Big Data Market Forecast 2015-2020
6.1 Europe
6.2 North America
6.3 Latin America
6.4 Asia-Pacific
6.5 Middle East & Africa
Chapter 7: Big Data Best Practices & Recommendations for Telco Operators
7.1 Setting investment priorities for Big Data
7.2 Network Optimization & multilayer Monetization
7.3 Subscriber Insight data & Personalized Services
7.4 Mobile Advertising and LBS
7.5 Data Risks and Regulations are highly crucial
List of Figures
Figure 1 Levels of big data operator
Figure 2 Shift in telecom market leadership & competition
Figure 3 ARPU per year in (In US$), 2015
Figure 4 Global Voice & Messaging Revenues Lost to OTT applications (In US$ Billion), 2014-2020
Figure 5 Global Voice Revenue (In US$ Billion), 2012-2014
Figure 6 Global Voice Revenue by Region (In US$ Billion), 2012-2014
Figure 7 Global SMS Revenue (In US$ Billion), 2012-2014
Figure 8 Global SMS Revenue by Region (In US$ Billion), 2012- 2014
Figure 9 Common telco data sources and information
Figure 10 Formulating steps to use big data
Figure 11 The progression to next-generation customer analytics
Figure 12 Global big data revenue forecasts (In US$ Million), 2016-2020
Figure 13 North America big data revenue forecasts (In US$ Million), 2016-2020
Figure 14 Europe big data revenue forecasts (In US$ Million), 2016-2020
Figure 15 Latin America big data revenue forecasts (In US$ Million), 2016-2020
Figure 16 Asia-Pacific big data revenue forecasts (In US$ Million), 2016-2020
Figure 17 Middle East & Africa big data revenue forecasts (In US$ Million), 2016-2020
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