CSPs can have access to a wealth of information about their customers’ behaviours, preferences and movements but, often, aren’t able to take advantage of this strategic asset to extract business value.
Big Data promises to tackle this challenge although, the question remains:
How can CSPs leverage this rich, complex and, many times, unknown data?
How can it be used to gain valuable, unique insights about the business and customer experience?
We are witnessing the birth of a new Era, fuelled by the advances in mobile technology, convergence, IoT and cloud services, among others. This revolution is empowered by data analytics that is impacting the entire value chain from network optimization to tailored marketing campaigns using location-based and social networking technologies.
One of the most important differences between the two approaches to data exploration - traditional Business Intelligence (BI) and Big Data - is the sheer volume of Big Data processes.
The massive amount of data processed is closely related to the rich variety of sources it deals with. From network sensors, to Moment of Truth (MOT), and so many other sources, Big Data can attune and correlate different formats of structured and unstructured data, in contrast with traditional BI.
Also, velocity can be applied not only to the ability to quickly consolidate massive volumes of data from different sources but also to provide business insights in real or near real-time. Organisations used to have a delayed picture of the business due to time discrepancy between a report request and information receiving. Big Data changes that, having a direct impact on the operations and CSPs ability to quickly react to business threats or opportunities.
By deeply understanding customer’s behaviour patterns, CSPs are in a great position to offer personalised services and apply micro-segmentation campaigns. With customer experience analytics and covering the entire journey, CSPs can generate improved insights, making a difference on identifying the next-best-offer and effectively leverage up and cross sell offers;
To support the constant growth in mobile data, network investment is expected to continue increasing significantly. Big Data can support CSPs’ efforts in infrastructure expansion and, at the same time, control the current infrastructure by proactively helping to detect potential bottlenecks and outages through the correlation of network usage, subscriber density, along with traffic and location data;
Traffic data is a strategic asset that hasn’t been leveraged by CSPs to generate more revenue. For example, location-based data combined with anonymised user profiles, can be offered to retailers to help them understand traffic flows to offer dynamic promotions;
Identifying customer propensity to churn is not new, however Big Data provides a whole new level of predictive analytics by combining the analysis of many different factors, such as customer care interactions, social media sentiment analysis, quality of service and usage patterns.
Although the benefits are clear and there is a strong business case supporting the adoption of Big Data solutions, organisations are still concerned about the complex roadmap to undertake this uncharted terrain - How to mitigate the organisational impact while leveraging the current BI infrastructure and evolving it to a Big Data platform?
Furthermore, CSPs must not only consider which Big Data solutions best fit today’s needs but also how will they scale new data types, integrate disparate data sources and deliver value in a timely manner.
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Analytics provides new insights and tackles different business challenges, supported by a plethora of new tools and technologies, democratising access to information across the organisation, impacting the entire value chain.