We are in the era of Big data. Big data is presenting excellent optimizing opportunities to the companies in various sectors. Big data when analyzed well, can provide actionable insights that aids in devising strategies to optimize multiple business processes.
Big data has become an essential part of the telecom industry due to the enormous amount of data being generated by the telecom world. Telecom operators are sitting on gold mines as the smart devices have enabled the telecom operators to gain access to specific information about their customers’ behavior, preferences, movement, etc.
Today’s telecom industry is facing many challenges. Telecom operators have been using Big data analytics to evaluate and formalize strategies to enhance customer satisfaction, preparing the network for future demands and to make data-driven decisions to optimize the processes.
Telecom companies have realized that analyzing its data while combining the data of different sources is the key gain a more profound understanding of their customer behavior, preferences, product performance. Through Big data analytics, telecom companies can battle challenges they face today.
A recent study suggested that 47% of the telecom operators are investing in Big data analytics and 19% are expected to implement a Big data strategy soon. Telecom companies are pressed hard against Hyper-competition, slow revenue growth, and increasing network costs that compel telecom companies to deploy advanced analytics solutions.
Big data analytics will help to improve their profitability and gain a competitive advantage by enhancing customer experience and optimizing network usage. Telecommunication companies are using Big data to gain insights about the potential of new product offerings, enhance customer experiences, reduce service truck rolls while improving customer service, forecast network capacity and demand faster and more accurately, optimizing value-based network capacity planning.
Analyzing Big data is a challenge in itself for telecom providers as certain characteristic of Big data such as the variety, velocity, and complexity are challenging to deal with. The data that telecom companies gather is from various sources such as social media networks, connected devices, government portals, call data records, billing information. Thus, it adds to the complexity of Big data. The fact that the data is mostly unstructured adds more to the complexity as its analysis is out of the capacity of traditional databases.
A recent survey reports that every minute, Indians spend ₹ 1.85 million on shopping online. More than 100 hours of video is shared on YouTube every minute. The average time spent by a social media user is 2.5 hours a day. The data generation speed is extremely high and to gain value from this data; it needs to be analyzed in a particular time frame. Real-time processing of Big data is becoming crucial for many applications.
Retaining existing customers along with attracting new ones is one of the most critical challenges in the maturing mobile telecommunications service industry. By deploying predictive models and machine learning algorithms, it is possible to identify customers who are likely to leave the network, accurately. Bringing together data collected on customer usage, complaints, transactions, social media, they can formulate factors which can identify customers at risk of moving out.
In the end, it is safe to conclude that Big data analytics is the key for growing revenue for telecom companies while understand and serve their customers better.