Unlocking Customer Retention: Harnessing Automated Insights to Drive Success for a Leading Telecom Operator

SGA STRATEGIC APPROACH
 

To address these challenges, SGA implemented a comprehensive automated insights generation system. This approach was structured into several phases: 

Data Integration and Preprocessing: 

• Collected and integrated large datasets from various sources, including customer recharge data, transaction history, and customer interaction logs.
• Ensured data quality through cleaning, normalization, and preprocessing techniques to facilitate accurate analysis. 

Advanced Anomaly Detection: 

• Deployed machine learning models capable of dynamic thresholding, trend analysis, and seasonality adjustment. This enabled the system to identify unusual changes in customer continuity, both sudden and gradual. 
• Employed both supervised and unsupervised learning algorithms to detect anomalies, ensuring a robust detection mechanism.

Causal Graph Analysis: 

• Utilized Bayesian Networks to map relationships between different variables affecting customer continuity. This helped in understanding the root causes of anomalies. 
• Developed causal graphs to visualize these relationships, providing Area Managers with clear insights into factors driving customer behavior. 

Impact Scoring and Prioritization: 

• Implemented AI models to assess and prioritize detected issues based on their potential impact on customer continuity. 
• Developed scoring algorithms that considered factors such as the severity of anomalies, customer segment affected, and historical behavior patterns. 

Automated Report Generation: 

• Leveraged Large Language Models (LLMs) to generate detailed reports. These reports included actionable insights, strategic recommendations, and visualizations to aid in decision-making. 
• Enabled automated dissemination of these reports to relevant stakeholders, ensuring timely access to critical information. 

Generative AI Interaction: 

• Integrated a conversational AI interface, allowing Area Managers to interact with the system for customized insights and follow-up questions.
• Enabled natural language queries and responses, enhancing the usability and effectiveness of the system.
   

ENGAGEMENT

SGA's engagement involved a thorough analysis of the telecom operator's data infrastructure and customer behavior patterns. Key steps included: 

• Deploying machine learning models for dynamic thresholding, trend analysis, and seasonality adjustment.
• Utilizing Bayesian Networks for causal graph analysis to understand the root causes of anomalies.
• Implementing generative AI for automated report generation and interactive insights. 

BENEFITS & OUTCOME

• Operational Efficiency: Automation saved 20% of managers' time, allowing them to focus more on customer acquisition.

• Competitive Advantage: Insights-driven strategies kept the operator ahead of competitors. 

• Improved Customer Experience: Proactive insights increased customer satisfaction scores by 10%.
   

KEY TAKEAWAYS

• Automated insights significantly enhance operational efficiency and customer retention. 
• Combining advanced anomaly detection and causal analysis provides a deeper understanding of customer behavior. 
• Generative AI can transform data into actionable insights, improving strategic decision-making.