Executive Summary

• Analyzed 30K+ customer service interactions to identify the operational factors influencing customer satisfaction and retention across Flipkart’s customer support ecosystem.
• Cleaned and transformed customer call data using Excel by handling missing values, removing duplicates, standardizing formats, and engineering analytical fields for response time, call duration, weekdays, and sentiment analysis.
• Designed a business KPI framework and metrics tree to monitor CSAT, Response Time, Call Duration, Sentiment Score, First Contact Resolution, Queue Waiting Time, and Churn Rate, translating business objectives into measurable performance indicators.
• Applied Exploratory Data Analysis (EDA), descriptive statistics, pivot table analysis, correlation analysis, and hypothesis testing to evaluate customer service performance across call centers, support channels, weekdays, and issue categories.
• Identified a strong positive correlation (r ≈ 0.89) between customer sentiment and CSAT, establishing service experience as the strongest predictor of customer satisfaction.
• Found that Billing-related issues accounted for approximately 71.37% of total support tickets, making them the largest contributor to customer dissatisfaction and operational workload.
• Discovered that response time and call duration had minimal impact on customer satisfaction, indicating that resolution quality matters more than handling speed.
• Revealed that chatbot support delivered comparatively lower customer satisfaction, while Fridays experienced the highest operational load and reduced CSAT, highlighting opportunities for channel optimization and workforce planning.
• Developed an interactive Excel dashboard featuring KPI scorecards, pivot charts, and operational insights, delivering actionable recommendations to improve customer experience, service quality, issue resolution, and long-term customer retention.