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Forget Bitcoin, Data Is Currency of the FutureForget Bitcoin, Data Is Currency of the Future

CSPs armed with real-time operational intelligence are uniquely positioned to realize the true monetary value of the new data economy.

Anukool Lakhina

November 24, 2014

5 Min Read
Forget Bitcoin, Data Is Currency of the Future

I was reading a recent article in Light Reading that talked about whether big data could be used as a future currency, which got me to thinking: Isn't data already a form of currency? (See Could Data Be the New 'Currency'?)

The article cited a new Telefónica SA (NYSE: TEF)-sponsored report that raises the question of whether "data can be the basis of a new transactional relationship between people and companies in which both sides benefit from new products and services and increased economic growth." This is certainly a view that we at Guavus Inc. hold, and are seeing it become a reality for a number of our customers.

For communication service providers, big data can unlock completely new revenue streams and opportunities by enabling this new transactional relationship between businesses and their customers. The operational intelligence provided by big data analytics solutions can help CSPs to better understand consumer preferences and behaviors, helping them to create a new set of personalized and targeted services that are more closely aligned with customer needs. These new services will help us to move closer to the mutually beneficial vision of how marketing will evolve, as outlined in the report.

For example, we have one customer using our Big Data Profiling Engine application to deliver a new range of hyper-targeted SMS marketing services to third parties, with an initial pilot delivering a six-fold increase in click through rates. By using operational intelligence around how users interact with mobile services, CSPs can deliver more personalized, timely and relevant messages to subscribers based on their consumption of mobile data services and content. Yet all subscriber data is protected by the fact it is opt-in: as such, neither the operator nor the brand using the service is able to identify an individual user as they appear only as a randomly assigned number.

The result is a win/win for all: customers only get messages that are relevant to them; brands get to the people they want to reach faster and more effectively; and the CSP can use its unique position at the center of the data highway to deliver value and drive revenues.

However, it is not just mobile messaging services that can help CSPs to deliver value to enterprise' through the use of data; their role can be a lot more strategic than that. CSPs are totally unique in terms of the insights they can deliver. People live their lives through their mobile devices. For example, a person's mobile phone can tell you what food, music or clothes they like, or where they want to go on holiday, helping to build a picture of who they are as a person. When you gather this information on a larger, opt-in scale then you can spot trends as they happen.

For companies that are able to spot these trends and respond in real-time, it can make the difference between being a follower or a front-runner, which will translate to increased market share, customer loyalty and, ultimately, increased revenues. CSPs are uniquely placed to help businesses spot these trends and create services that help them to respond in real-time by providing up-to-the-minute operational intelligence; a valuable asset in today's fast-paced world. As CSPs extend the range and sophistication of the data services they provide to third parties, data will be the bedrock of these new services, which will help operators to deliver unique insights that shape business transformation across a range of industries.

Services such as these will really hold the key to CSP transformation in the coming years; yet this services revolution goes beyond marketing. We are already seeing the role of the operator evolve into a much more dynamic value creator. As mobility becomes increasingly central to both our business and personal lives, industries are being turned on their heads, and operator networks are the backbone of this innovation.

Machine to Machine (M2M) communications are transforming manufacturing and logistics, mining, healthcare, emergency services, not to mention the homes we live in. This is leading to some interesting partnerships for CSPs, who are the central hub for this activity. For example, Telstra Corp. Ltd. (ASX: TLS; NZK: TLS) recently announced that it is making an "aggressive push" into the healthcare market, partnering with a telemedicine company, Medgate, to provide better patient connectivity to health services. Similarly, following its acquisition of HUGHES Telematics in 2012, Verizon Communications Inc. (NYSE: VZ) is now pushing its range of connected car solutions helping the company to get a jump on the Internet of Things revolution.

By analyzing network, sensor and machine generated data, CSPs can offer managed data management and analytics solutions along with M2M connectivity, and in doing so both accelerate the proliferation of and the value from Internet of Things across industries.

So is data a currency? And will it ever be? My answer is yes, and yes, and it is more important today than ever. As the weight of data continues to strain operator networks, increasing the need for expensive infrastructure modernization and investment, monetizing this data is going to be critical to future CSP success and profitability. Yet, as the world of consumers, CSPs and enterprises become increasingly interconnected, CSPs armed with real-time operational intelligence are uniquely positioned to realize the true monetary value of the new data economy.

— Anukool Lakhina, CEO & Founder, Guavus Inc.

About the Author(s)

Anukool Lakhina

CEO & Founder, Guavus

Anukool founded Guavus with a vision to provide solutions for dynamic, data-driven decision-making. He brings more than a decade of thought leadership in large-scale data analytics and has published more than a dozen papers on the subject. His Ph.D. dissertation put forth the theory and algorithms for streaming analytics on high-dimensional data, which forms the basis for the technology at Guavus. Prior to Guavus, Anukool was at Intel Research and Sprint Labs. He holds a B.S., M.S. and a Ph.D. in Computer Science from Boston University.

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