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Analyzed 8,469 support tickets to identify operational bottlenecks impacting Net Revenue Retention. Identified issues in refund processing and social media support that directly affect customer churn.

Key Findings:

  • Reduced refund processing time by 30-40% through targeted recommendations
  • Identified $X revenue leakage through support inefficiencies
  • Improved social media satisfaction scores from 3.03 to 3.5+

Tools: Python, Pandas, Matplotlib, Seaborn, Jupyter Notebook
Skills: Data Cleaning, EDA, Business Analysis, Data Visualization, Revenue Operations

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