Operators are under immense and ever increasing pressure as a result of the changing competitive landscape, with the commoditisation of traditional services and over-the-top (OTT) players such as Google and Skype eating into their revenues. Operators are no longer simply worried about reducing costs; they are competing to deliver value-added offerings, improve customer experience and ultimately to retain and grow a profitable customer base.
Data has been described as the oil that will fuel operators’ future growth (Ovum, 2011), with some operators looking to transform themselves into companies that primarily manage data as well as providing communications services. They will have to devise a fresh revenue model which can ultimately impact their bottom line. Its worth to mention here that “Consumers trust Telecom operators, second only to banks, with their personal data – in terms of Safety & Security”
The growth of mobile data traffic and the customer demands for better and personalized services are forcing Operators/ Communication Service Providers (CSPs) to invest significantly to upgrade their networks and devices. There are a lot more similar challenges that CSPs face; however, the key point is that the CSPs have to focus on new sources of revenue to augment what they generate from their infrastructure, services portfolio and customer base.
Clear edge/differentiator here a CSP has over the OTT is the access to real time subscriber Intelligence. CSP has access to all the transactions which subscriber initiates or accepts, this in turn results in a huge information base / data set; this is BIG Data for CSP.
Let me simplify here what Big Data is: According to Wikipedia, “Big Data includes data sets that cannot be captured, managed, and processed by common software tools within a reasonable timeframe. Big data involves a huge amount and variety of data from different sources that is rapidly fed in and out.”
BIG Data – An Opportunity:
CSP has information about an individual subscriber’s taste, preferences, favourites, location, their consumption behaviour of different voice and data services, service experience, payment history, etc. In addition to the current and contextual subscriber information, the CSPs also have access to a massive amount of untapped historical data (e.g., subscriber and service history) that can be aggregated and brought back into the present to build a richer subscriber profile and identity. The information is captured from different sources in the network at different times using different techniques and, in most cases, scattered across different databases and data warehouses. The CSPs can understand a lot more about their customers’ expectations and deliver a much more personalized experience by investing in deeper real-time analytics capabilities, leveraging all these subscriber data and deriving a practical and intelligent Business model.
BIG Data – Customer Retention Tool:
Big Data analytics enables service providers to better segment subscribers to provide more targeted marketing spend and the insight to predict churn, cross-sell and upsell opportunities, the quality of customer experience and the lifetime value of a customer. The product managers get a better understanding of which services are most profitable, the impact of competitive offerings and the effect of cannibalization caused by a new product roll-out. It also gives network operations the ability to predict capacity issues and the impact of a new service launch.
This has proven to be particularly fruitful when it comes to prepaid mobile customers. While telcos value acquiring new post-paid customers for a consistent and locked-in revenue stream, retaining prepaid customers is also an important facet of Subscriber Acquisition Module. With no contractual obligations, Prepaid Subscriber base is not obliged to stay with one CSP, and can make the switch as soon as their phone credit runs out. With prepaid customers, there is essentially a churn decision that gets made on a monthly or on an even more frequent basis, here Big Data can play a pivotal role by generating the Short term patters on the usage of single subscribe which can ultimately help in retention.
BIG Data – Road Ahead:
Most of the CSPs are aware of these opportunity areas. To implement any of these use cases, it’s important to look at the end-to-end processes, integration points, analytics tools, storage and above all, applying the right logic to derive intelligence out of data. As per the global trends, many CSPs will start investing this year in Big Data Analytics. Those with dominant market share might start with customer experience management whereas others might start with monetizing the customer intelligence. By 2015, Big Data analytics will be one of the critical areas for CSPs to maintain their market-share.
In India, where more than 90% of our Subscriber base comprises of Prepaid Customers, I personally believe Effective and Efficient use of “Big Data” can result into (1) Customer Satisfaction (2) Reduction in Churn (3) Loyalty (4) Steady ARPU. All combined together can help a CSP retain or enhance their market share.
Additional Inputs:
Znet & Virtualization.Sys-con
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