With millions of transactions, the telecommunication industry deals with an enormous amount of data every second. Data Analytics is becoming a crucial part of the business. With the rising amount of competition and low cost of migration, customers immediately change their service providers the moment they experience dissatisfaction in the service.
According to a survey conducted by IBM, about 66% of CSPs (Communications Service Providers) identified customer-centric objectives for adopting Big Data as their organization’s top priority.
The focus of CSPs has long back shifted from product-centric to customer-centric. With digitization, customers are well aware of their services in the market, forcing the Telcos to invest in new technologies and advanced analytics to understand the needs of their individual customers and improve their customer experience in telecom. However, today’s customer wants more than just understanding- a valuable relationship, which may come through more timely, informed or relevant interactions.
According to an article published in Forbes, almost 53% of companies have already adopted Big Data, with Telecom services being the early adopters.
What customers expect from their operators?
- A personalized CX which requires the company to gain an in-depth knowledge of each customer
- Maximum benefits out of minimum costs, which is possible by taking advantage of actionable information available along with the insights from the market
- Innovative offerings
Challenges faced by Telecom Companies
Although Big Data Analytics provides actionable insights for decision making, telcos find it challenging to adapt to it and continue using legacy analytics. Some of the challenges that these companies face are-
- Determining a strategy to leverage the benefits of big data
- Acquiring the resources to understand and analyze big data
- Cost and efforts associated with Big Data Analytics
- Identifying the best software and hardware solutions and determining the best overall solution
How Big Data Analytics Improves Customer Experience
Even if the telecom industry faces multiple challenges in implementing Big Data Analytics, once implemented it actually results in higher ROI since the companies are able to leverage customer services in telecom. Big Data Analytics can help in several ways to enhance CX.
- Lower Churn Rate
Retaining its customers is one of the major challenges faced by Telcos. Big Data Analytics not only help the companies to reduce the churn rates but also help them understand why a customer leaves and how to stop them from leaving. With Big Data Analytics, teams can understand customer sentiment and identify value proposition and create targeted strategies which enable to reduce acquisition costs, improve customer experience and increase marketing efficiency.
- Predictive Campaigns
Big Data Analytics helps businesses get access to real-time data so that they can make the offerings more targeted. And when the customers get what they want, they tend to remain loyal and know that they are not just understood, but are also valued. When digital technology is combined with analytics and predictive intelligence, marketers will be able to adopt a one-to-one personalization approach which results in greater customer experience in telecom.
- Location-Based Services
There’s a reason why about 70% of telcos consider location-based services critical for their success. For a competitive industry like telecommunications, it is imperative to understand trends, and patterns in a quick and efficient way to keep up with the evolving market dynamics. The location information is not just assisting the businesses with their business challenges, but are also driving new opportunities for telecom operators and enterprises to easily utilize infrastructure to support intelligent positioning services.
With data that is available from multiple sources, (network, services, social media, customers and others), telcos should aim at creating a 360-degree view of customers and extract actionable insights from the data to increase loyalty, create targeted marketing campaigns and to develop new services.
mViva leverages HBase, a distributed, scalable big data store backed by class-leading Hadoop map-reduce framework with robust HDFS(Hadoop Distributed File System) as the data storage layer to enable analysis of large, diverse and ever-increasing customer data to reveal patterns, trends, associations and key behavioral traits and put them to effective use by channelizing the right offer to the right customer at the right time and leverage the overall CX.
