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Vijaya Chaitanya Palanki has successfully developed an advanced Consumer Churn Prediction Tool that has reduced first-year customer churn by 10% and long-term churn by 9%. This tool, along with an E-Commerce Conversion Optimization model, has significantly improved customer retention and increased conversion rates by 20%. The integration of advanced analytics into business processes has proven effective in enhancing overall e-commerce performance.
Palanki's initiatives have led to a remarkable increase in the e-commerce consumer database and revenue growth, demonstrating the power of data-driven strategies. The creation of a machine learning-based fraud detection system resulted in a 60% decrease in fraudulent transactions, showcasing the importance of AI in enhancing security. By fostering a data culture and implementing real-time analytics, Palanki has positioned the organization for future success in the evolving e-commerce landscape.
• Consumer Churn Prediction Tool reduced churn by 10% and increased retention.
• E-Commerce Conversion Optimization model improved conversion rates by 20%.
This tool predicts customer churn, helping businesses retain customers effectively.
This model enhances the conversion rate of online sales through targeted strategies.
Machine learning techniques were used to analyze customer behavior and improve retention.
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