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AI-Enabled Pattern Recognition: Enhancing Customer Continuity for a Leading Telecom Provider​

Telecom
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Business Situation

  • A leading global telecom operator faced significant challenges in optimizing customer acquisition & retention strategies. ​
  • The existing systems were unable to provide real-time insights, so area managers spent excessive time on manual data analysis rather than focusing on customer engagement. ​
  • Additionally, the company’s inability to effectively analyze recharge behavior hindered its ability to enhance customer continuity and loyalty.

SGA Approach

  • Implemented static and dynamic thresholds to flag unusual changes in customer continuity patterns​
  • Monitored deviations from expected trends while accounting for periodic patterns to detect anomalies​
  • Used Bayesian networks to identify the root causes of anomalies in recharge behavior​
  • Developed AI models to prioritize issues based on their potential impact on customer retention and acquisition​
  • Leveraged Gen AI to compile detailed reports with actionable insights and strategic recommendations for retention and acquisition efforts​
  • Enabled operators to interact with the system through a conversational interface for customized insights and follow-up questions using Gen AI

Key Takeways

  • Created a comprehensive data integration strategy, combining first-party, third-party, and survey data​
  • Developed a sophisticated ML-based targeting model to predict purchase propensity across various insurance offerings​
    • Implemented explainable AI frameworks (SHAP and LIME) to provide transparency in decision-making​
    • 20% reduction in the manager’s time spent on decision-making​
    • CSat increased by 10%​
  • Enhanced competitive positioning through optimized engagement strategies

Related Tags

AI - Artificial Intelligence Data Research Services Tech Telecom TMT

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Besides being recognized by analyst firms such as Gartner, Everest Group, and ISG, SGA has been part of the elite Deloitte Technology Fast 50 India 2024 and APAC (Asia Pacific) 2025 High Growth Companies by the Financial Times & Statista.

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