5 Reasons how Data Science is enhancing Telecom Sector

Data Science is no longer surrounded to only typical research firms. And, for the Telecom Sector, it is emerging as a gold mine with endless opportunities to dig and make the profit. Whether it is to understand the new data pack offers or forecast the bandwidth and capacity of a network, Data Science is helping Telecom companies to make the best data sets for the right customers at right time.

In the recent few years, Data Science works in the following domains in the Telecom Sector-

Customer Demand Identification- Data Science gives the exact results in terms of Searching patterns of websites, the duration analysis of browsing the websites, past records of purchasing, social media activity track records, data packs and SMS success patterns, usage history of services.This makes the Telecom Companies offer their services in a more customized way at the right broadcasting channels.

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Analysis of KPI- The extracted data gives the accurate results to track the experience a customer from his/her pre-purchase interaction with a vendor to the post-purchase feedback. Along with this lifetime behaviour tracking of the customer, extracted data also provides the values of the Key Performance Index such as Customer Churn Prevention, Brand Improvement idea generations, Cross-Channel Strategy Information.behaviour tracking of the customer, extracted data also provides the values of the Key Performance Index such as Customer Churn Prevention, Brand Improvement idea generations, Cross-Channel Strategy Information.

Sentiment Analysis in Telecom- Data Science provides the reviews and news feed from Social Media to Telecom Companies that help them to use this information for the analysis of the customer’s sentiment. The harvested data gives a close insight to improve any Brand Image, identify a new revenue segment, monitoring of the social campaigns, tracking the Feedback of any new product and offer, to manage data of potential customers and their concerns.

Churn Prevention of a Telecom Customer- At present, one of the biggest challenges in the Telecom Sector is to restrain the customers from jumping to new networks from the existing network. It turns to be more expensive for a telecom company to maintain the existing customers rather than adding new customers to its network. The common factors for churning include low prices of competitor network, poor connection quality, expensive data and service packs and useless offers.

For this, Data Analysis assists the Telecom Companies in following ways-

Prediction of the call bills, the number of messages sent and received, data of time spent on the calls.

Knowledge of when the customers change his/her SIM and when they are visiting competitor’s websites.

Use of Social Media Data to detect the behavior changes of the customers.

Optimization of the Network by Predictive Data Analysis- In the previous years, for the problem of the network down and overtaxed or unutilized data capacity, the telecom companies used to handle these issues by implementing unique Pricing Models for each network capacity management.But by using Predictive Analysis, companies are now managing the network usage policies by predicting the subscriber actions, seasonal data trends, customer marketing initiatives and redirecting the offers towards active hot spots of a network.

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