Analysys Mason has published the ?Big data analytics: How to generate revenue and customer loyalty using real-time network data? report.
As per the report, more than a quarter of communication service providers (CSPs) have not chalked out a strategy for big data analytics. The report reveals that CSPs have generated more data in the last two years than in the preceding 50 years. However, merely one out of four CSPs has a strategic plan for using the information generated.
About 27 per cent of CSPs have no strategy for big data analytics in 2013, and the vast amount of subscriber information held by CSPs has remained largely untapped. According to the report, the volume of data on telecom networks has increased a thousand fold in the last 20 years.
Patrick Kelly, lead author of the report and research director, Analysys Mason Telecoms Software research division, says, ?The data that CSPs are creating has four key attributes. The data has volume variety (from call logs to machine to machine sensor data, it is extremely varied), velocity (it can be gathered in real time) and value (if structured and analysed correctly, it can be extremely valuable and profitable).?
However, the report also cautions that CSPs should strive to understand the outcomes for specific areas of their businesses before investing in big data and analytics. The report estimates that CSPs can increase their net profit margins by 12 per cent with the right cross-marketing and sales promotions, and customer retention can be increased by 0.2 per cent with effective loyalty programmes. Moreover, CSPs can use these insights to defer capital investments in the radio access network without degrading the service, saving hundreds of millions in capital spending.
Most importantly, the report indicates that only a fraction of the data that traverses telecoms networks needs to be captured for analysis. Three types of data are important for CSPs: customer data (usage, location, device, etc.), market intelligence (dimension, demographics, segmentation, etc.) and real-time network data (service quality, call centre efficiency, revenue optimisation).
