Bridgewater Systems, the mobile personalization company, today announced the publication of new research into the mobile data surge, highlighting cost reduction strategies that can save mobile operators up to 60 per cent per annum by 2013. The report, "Towards a Profitable Mobile Data Business Model" is available to download at http://campaigns.bridgewatersystems.com/forms/ProfitableMobileDataModel.
*Towards a Profitable Mobile Data Business Model highlights the impact of growing 3G penetration, lower cost smartphones and USB dongles, new tablets like the iPad, and the popularity of mobile applications on the growth in mobile data traversing operators' networks.
*It investigates the causes of mobile network congestion and the best methods to alleviate it based on exclusive research conducted by independent research firm Chetan Sharma Consulting. It also provides insights into new service models underpinned by Bridgewater's deployment experiences with operators and customer case studies from Ovum and Morgan Stanley.
*Towards a Profitable Mobile Data Business Model looks at both network congestion management strategies and operator data pricing models with the following conclusions:
- Policy control could contribute substantial annual cost savings of over 10 per cent, equating to more than $15 billion in annual cost reduction by 2013 in the US market.
- Operators deploying a data traffic offload strategy to Wi-Fi,femtocells or 4G could expect savings of 20 to 25 per cent per annum by 2013, representing $30 to $40 billion in the US market.
- The evolution to HSPA and LTE could save just under 20 per cent in network costs by 2013, saving US operators $25 billion by 2013.
- Flexible, dynamic, and personalised pricing models that reflect subscribers' preferences and context, bandwidth and application usage, and network conditions will better align data revenues with network costs for the first time. New models include:
- Tiered and usage based models that take a smarter approach to service personalization and fair usage;
- Application-specific charging, to generate appropriate revenues from high-bandwidth services;
- Time-based models that charge based on time spent on the network; and
- Mobile advertising and mobile commerce funded approaches.