5 ways Telecom sector is leveraging Data Science

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New-age technologies are rapidly disrupting the landscape of almost every industry and the telecom sector is fast embracing these changes for business growth and customer delight. The advancement of technology is making the world a global village. Thanks to these disruptive technologies we feel connected to our loved ones even if they are miles apart. With the increasing connectivity, the data generated each is on a rise and needs to be handled smartly. 

By using Data Science, telecommunication companies are improving five crucial areas of their services. 

  1. Product development
  2. Predictive analytics
  3. Price optimization
  4. Fraud detection
  5. Targeted marketing

Product development

Product development is very complex and crucial for the Telecom industry and it needs data-driven management from concept development to ongoing life-cycle management and maintenance. Telecom companies use smart data solutions to ensure the quality of the product according to the customer’s requirement. Data-driven product development processes are being used to meet the customer needs and to implement digital analytics, internal feedback and marketing intelligence.

5 ways Telecom sectorPredictive analytics

Telecom industry performs predictive analytics on the data collected to gain the insights which help them become faster and better. It also helps the industry to take data-driven decisions. Predictive analytics uses historical data to predict customer behaviour which is crucial for the better understanding of customer preferences.

Price optimization

Price optimization is a crucial factor for companies in the Telecom sector as the competition is increasing by the day. Right pricing plays an important role when it comes to increasing and retaining users. Advanced Data Science solutions are being used for the real-time analysis of various aspects which helps them in setting the optimal price of products according to their customer preferences.

Fraud detection

The Telecom industry is prone to fraudulent activities which has a direct impact on the service provider and customer relationship. The most common fraudulent activities in the Telecom industry are unauthorized access, fake profiles, misuse of credit/debit card information, etc. It is crucial for the industry to use fraud detection systems, tools and techniques in order to keep fraudulent activities at bay. The industry is using various machine learning algorithms and fraud analytics for detecting unusual user activities.

Targeted marketing

The Telecom industry is leveraging Data Science to a greater extent to predict the customer behaviour and to know their preferences for targeted marketing. Targeted marketing is essential when it comes to maximize customer satisfaction and revenue generation. Telecom companies also do location-based promotions with the use of Data Science. The companies detect the real time location of their customers and send them promotional texts.

The huge amount of data available in the Telecom industry is being used to get valuable insights with the intervention of Data Science technologies and solutions. The insights are used for various purposes such as:

  • Revenue generation and maximizing the profit
  • Planning efficient business and market strategies which are more personalized
  • Data visualization and performing data transmission
  • Maximizing the customer satisfaction

Also read:4 Reasons: Why a career in Data Science is very lucrative  https://www.nationalskillsnetwork.in/4-reasons-why-a-career-in-data-science-is-very-lucrative/

Telecom industry serves billions of people each day generating massive amounts of data. Data Science is providing humongous opportunities for the industry to smartly use the huge amount of data that is available. The industry is in demand of certified and skilled Data Science experts who will be able to handle the massive amount of data properly. 

Author: Purvi Shah | Senior Director | Talent Sprint | For more information please visit: https://talentsprint.com/

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