In this video, you will know how data science is transforming our lives through Telecom Industry.
The Telecom Industry utilizes the insights gained with the help of Data Science for different purposes like maximizing profit, Planning efficient business and market strategies, data visualization, performing data transmission, etc.
1. Customer Experience
Millions of client complaints are analyzed to understand common complaints and the types of solutions needed. The correct solution at the correct time for the specific problem will improve customer satisfaction. And Satisfied customers are loyal customers. On the internal front, how did a technician deal with a customer complaint, can also be a source for analyzing his performance. Customer calls are more likely to generate a great deal of unstructured data. Analyzing it will mean reduced truck roll costs.
2. Customer Segmentation
With the use of predictive analytics to the core, the industry can understand its clients well. Customer segmentation is one such application of the Telecom industry. If the telecom organizations can divide their market and then focus on the content, success isn't far away. Customer behavior segmentation, customer migration segmentation, customer value segmentation, and customer lifecycle segmentation are the 4 segmentation areas.
3. Product Development
Strategic and Careful planning continued throughout the product development lifecycle will improve a loyal customer base. By using the insights collected from data analysis and predictive analytics, targeted product development is feasible; your consumers will get what they like, with top quality. Predicting which product will be accepted nicely in the current market scenario and competition is a crucial point for the telecom sector.
4. Real-time Analytics
Real-time data is used to gather real-time issues, solve them and give responses. Real-time analytics collates information related to location, customer profiles, usage, traffic, and network. It then creates a comprehensive view of the service or product. When the response is real-time, changes occur within the blink of an eye, and the telecom market will flourish.
5. Customer Sentiment Analysis
A collection of techniques used to process information is called customer sentiment analysis. This process assesses the negative and positive feedback of the consumer for a product. When the collected information is analyzed properly, main insights and the newest trends are unearthed. A real-time solution to the issues experienced by clients is also possible. Text analysis techniques also enable customer sentiment analysis.