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A large amount of commercial data is being generated on a daily basis due to huge amount of transactions taken place in service industry particularly in the telecom industry due to large number of customers. Because of large number of service providers available in the telecom industry, the competition in the B2B telecom sector is high and the churning of customer leads to significant threat to branding, revenue and profitability. Preventing B2B customer churning is cheaper than adding a new customer. Knowing well ahead of churning of customers can help the service providers to plan and arrest the attrition process. Also, proactively identifying customers at risk of churning allows businesses to implement retention strategies, minimizing losses and fostering long-term relationships. This document outlines innovative approaches to churn analysis for B2B telecom customer leveraging the power of AI/ML techniques for the best model selection for prediction using aggregation.

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Real-Time Churn Analysis Using AI/ML for Predicting Attrition of B2B Telecom Customers for Operational Efficiency

  • 会议论文

  • 发表日期：

    2026年

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  • Gourkishore Tripathy,
  • Manoj Choudhury

摘要

A large amount of commercial data is being generated on a daily basis due to huge amount of transactions taken place in service industry particularly in the telecom industry due to large number of customers. Because of large number of service providers available in the telecom industry, the competition in the B2B telecom sector is high and the churning of customer leads to significant threat to branding, revenue and profitability. Preventing B2B customer churning is cheaper than adding a new customer. Knowing well ahead of churning of customers can help the service providers to plan and arrest the attrition process. Also, proactively identifying customers at risk of churning allows businesses to implement retention strategies, minimizing losses and fostering long-term relationships. This document outlines innovative approaches to churn analysis for B2B telecom customer leveraging the power of AI/ML techniques for the best model selection for prediction using aggregation.