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Network Operator Monetization Strategies: Leveraging New Sources of Revenue

Arguably, the cellular communications marketplace has reached a point of saturation in terms of customer acquisition. Network operators are increasingly reliant upon cannibalizing customers from each other and growing revenue from non-voice communications.

There are many other potential areas for driving revenue growth and improved profitability including:

  • Subscriber data mining and management
  • Leveraging presence and location determination
  • Value-added Service (VAS) applications and content
  • Working with third party application and content providers
  • Mobile advertising, commerce, stored value and subsidized services
  • Expanding the scope of Machine-to-Machine (M2M) communications
  • Leveraging network improvements such as Self Organizing Networks (SON)
  • Provide Free-to-End-user (FTEU) applications and services paid by third parties
This research evaluates opportunities for network operators to grow revenue from new sources including mobile Value Added Services (VAS) applications. The report analyzes many other revenue potential areas including subscriber data management, working with third party sources such as mobile marketing and mobile commerce companies, improving margins through better network management such as Self Organizing Networks (SON), and more.

Target Audience:
  • Mobile network operators
  • OSS/BSS solution providers
  • Software and application developers
  • Content and applications Aggregators

General Methodology

Mind Commerce Publishing's research methodology encompasses input from a wide variety of sources.

We rely heavily upon our Subject Matter Experts (SME) in terms of their market knowledge, unique perspective, and vision. We utilize SME industry contacts as well as previous customers and participants in our market surveys and interactive interviews.

In addition, we rely upon our extensive internal database, which contains modeling, qualitative analysis, and quantitative data. We review secondary sources and compare to our primary sources to update previous findings (for prior version reports) and/or compile baseline information for technology and market modeling.

We share preliminary models with industry contacts (select previous clients, experts, and thought leaders) to verify the veracity of initial modeling. Prior to final report production (analysis, findings, and conclusions), we engage in an internal review with internal SMEs as well as cross-expertise, senior staff members to challenge results.

We believe that forecasts should be prepared as part of an integrated process which involves both quantitative as well as qualitative factors. We follow the following 3-step process for forecasting.

Forecasting Methodology

Step 1 - Forecasts Input: The inputs for the present and historical revenues are derived from industry players. Financial and other quantitative data for individual sub-market categories are derived from original research and tested with interviews with major industry constituents.

Step 2 - Forecasting of Future Years: Mind Commerce extends forecasts based on a variety of factors including demand drivers as well as supply side data. Key success factors and assumptions are considered.

Step 3 - Validation of Data: The final step is to validate projections, which is accomplished in consultation with both internal and external industry experts, including both topic and regional experts. Adjustments are made to the forecasts based on factors identified throughout this process.

Executive Summary
1.1 Mobile Application Store And Its Potential Revenues For Mobile Operators
1.1.1 Conclusion
Mobile Payment And Its Potentials For Operators To Make Profit
1.1.2 Mobile Payment Systems
1.1.3 Current M-payment Market
1.1.1 Money Transfers
1.1.2 M-banking Eco-system
1.1.3 Mobile Wallets
1.1.4 Comparison Between Current Wallet Systems
1.1.5 Advantages Of The M-payments Systems
Mobile Commerce And Its Profit For Operators
1.1.6 Factors To Affect The M-commerce Industry
1.1.7 The Future Of M-commerce
1.1.8 M-commerce Future Trends
1.1.9 M-commerce Challenges
1.1.10 Conclusion
Mobile Network Management: Ways To Increase Profits
1.1.11 Network Management Functionality
1.1.12 Mobile Network Management Methods
1.1.13 Simple Network Management Protocol (Snmp)
1.1.14 Other Network Management Protocols
1.1.15 Managing Internet Protocol For Mobiles
1.1.16 Case Study: How To Manage Networks To Increase Profits
1.1.17 Core Diameter Networks Management
1.1.18 Subscriber Data Management
1.1.19 Policy Management
Mobile Marketing And Advertising
1.2 Mobile Advertising Methods
1.2.1 Messaging Services
1.2.2 Business On The Go Applications
1.3 The Secure Authentication Infrastructure For Mobile Users
1.4 Different Secured Connections
1.4.1 Authentication
1.4.2 Access Rights
1.4.3 Payment Credentials
1.4.4 Privacy Of Communication
1.4.5 Integrity Of Message Exchanges
1.4.6 Anonymity
1.5 Authentication Methods And Protocols For Business On The Go Concept
1.5.1 Symmetric Authentication
1.5.2 Asymmetric Authentication,
1.5.3 Authentication Based On Biometric Information
1.5.4 Requirements For Mobile Internet (Business On The Go) Authentication
1.5.5 Password-based Authentication With Support For Public Key Technology
1.5.6 Protocol Description
1.5.7 Verification Of The Authentication Requirements
1.5.8 Symmetric Cryptography (Sim-based Authentication)
1.6 Public Key Cryptography
1.6.1 Digital Signatures
1.6.2 Certificate Authorities
1.6.3 How To Combine Both Public And Secret Key Cryptography
1.6.4 Authentication Codes
1.6.5 Wap Security (Wim Module)
1.7 New Value Added Services To Be Used
1.7.1 Tracking Sales And Controlling The Companies Resources
Privacy And Security Of M-banking And How To Increase Profits Through Nfc Payments And Nfc Marketing
1.7.2 Nfc Usage And Applications
1.7.3 Nfc Analysis (Where Is The Profit?)
1.7.4 Security Of The Nfc And Its Payment Systems
1.7.5 Attacks On Nfc Security
1.7.6 Using Nfc As Secure Key Storage
Data Mining And Management In Telecommunications
1.7.7 Data Mining Tools And Techniques
1.7.8 The Performance Of Data Mining Techniques When Applied To Churn Prediction
1.7.9 Data Mining For Calls
1.7.10 Data Mining In Data Networks
1.7.11 Data Mining In Customers Data And Its Privacy
New Value Added Services Application For The 4g And Lte Era
1.8 E-government
1.8.1 Mobile Applications For The Government
1.8.2 The Future Of E-government Concept
1.8.3 E-government To Mobile Government (Government On Go Concept)
1.8.4 The Return On The Investment Of The Mobile Government
1.8.5 The Use Of Telecommunication In Public Service Applications
1.8.6 Case Study: How Telecommunication Can Save Costs For The Governments And Make Profits
1.8.7 The Effect On The Economy And The Roi
1.8.8 Cell Broadcast Service (Cbs)
1.8.9 Celltick
1.8.10 (Mms) Multimedia Messaging Service
1.8.11 Mozat
1.8.12 Anny Way Mms
1.8.13 Unified Messaging
1.8.14 Cycos Ag
1.9 Augmented Reality
1.9.1 Introduction
1.9.2 AR 3d Applications
1.9.3 Tracking User's Position
1.9.4 QR Codes
1.9.5 Mobile Systems In AR
1.9.6 Collaborative Applications
1.9.7 Augmented Reality Challenges
1.9.8 AR Applications
1.9.9 AR In Tourism
1.9.10 AR And Face Recognition
1.9.11 Case Study: How Mobile Can Benefit From Augmented Reality
1.10 Web 2.0 And Social Software
1.10.1 Location-based Service In AR
1.10.2 Conclusion
The Current Challenges Facing The Telecommunication Industry And The Impact Of Mobile Value Added Services On The Market
Lte Benefits For The Mobile Operators
1.10.3 Key Service Advances
1.10.4 Devices Developments
1.10.5 Network Interfaces
1.10.6 Mobile Interfaces
1.10.7 High-performance Broadband Systems Strategies
1.10.8 Edge/Hspa/Lte Features
1.10.9 Adoption Of Technologies To 2030
1.10.10 Migration From The Current Networks To Lte Strategies
1.11 Future Trends
1.12 Evolution Of The Telecommunication Industry To 2016
1.13 Future Technologies For A Universal Radio Environment
1.14 Future Technologies For A Universal Radio Environment TDD System
1.15 Features Of Future TDD System
1.16 Challenges Of The TDD System
1.17 The Upcoming Technology Of TDD System
1.18 TDD Topology
1.19 Radio Access Network (Ran)
1.19.1 Control Plane And User Plane
1.20 Peak Data Rate
1.21 Multiple Access Methods
1.21.1 Ofdm Modulation
1.21.2 Random Access Procedure
Self Organizing Networks
1.22 Introduction
1.23 ARchitecture Of Son
1.23.1 Ieee 802.16
1.23.2 Ngmn Standards For Son
1.23.3 Son Categories And Cases
1.23.4 Distributed/Self-organizing (Dso)
1.23.5 Cooperative Relaying (Cr) In Son
1.23.6 Feedback Overhead In Son
1.23.7 Codebook-based Pre-coding In Son
1.23.8 Feedback Delay In Son
1.24 Installing Son
1.25 Stages Of Installing Son
1.25.1 Self Configuration
1.25.2 Self Optimization
1.25.3 Self Healing
1.25.4 Problems With Self Healing
1.25.5 Installing Phases

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