Why Big Data Analytics matter to Telecommunication?
The telecommunication industry holds a wealth of customer information and perhaps an ideal sector to benefit from a powerful data analysis tool that help parse complex data into actionable intelligence. Compared to other industries however, the telecommunication industry does prioritize data analytics to increase data visibility and use data insights to improve operational efficiency across the entire telecom value chain, from network operations to service offerings to product development, marketing and sales. Surprisingly, there are still many telecom companies far from capitalizing on their data, putting themselves at a risk by delaying big data analytics adoption. Many companies are also slow to adopt due to the lack of expertise or they are simply constrained by the scalability of legacy systems.
Given data in the telecommunication sector are both structured and unstructured, unifying data from various sources – such as call detail report, network data, social media, and equipment sensors is a challenge to consider. With Ducen’s BI and Advanced Analytics platform, connect and unify multiple data sources with ease. Improve data accuracy and reliability to help decision makers design custom strategies based on its own company performance data and aim to improve subscriber experience, manage and reduce churn, acquire new markets and target new customers more precisely.
3 Ways Telecom Should Prepare to Meet Future Customer Demands
Prepare network and infrastructure - Big data analytic tools help prepare companies to be robust, optimized and scalable. It provides companies with an infrastructure which is now a basic requirement for companies to differentiate themselves. Data is undoubtedly growing rapidly for the telecommunication sector. Just think about how your data grows if you are capturing customer call data. A more extreme example would be the real-time data gathered through connected devices. Deprioritizing the adoption of big data analytics may fail in the future as many organizations will be ill-prepared to play catch up. In other words, it will be too late.
Understand your customer for better service – Analyze network traffic in real-time, social media data, call logs and other sources to serve customers better with differentiated offerings. Drill down into issues that impact customer satisfaction, plan ahead to delight customers with more control and precision, and apply predictive analytics to forecast customer churn. Remember that the existing customers are a valuable source of ongoing business. If a customer exits a service network, costs of acquiring a new one is significantly higher.
Customer centric product development – Analyze customer behavior and usage patterns to help design products and services catered to current and future demands. Innovate by developing entirely new products, identify opportunities to introduce new product features, new product extensions and improve existing product lines. Adopt a proactive, rather than a reactive approach. Don’t devalue your product or your brand by planning your next big move based on your competitor’s action. With big data analytics, stay in control and make intelligent decisions based on your company performance data which will exert more influence to your market.