XeNoX36/MTN_Site.github.io

This app analyzes MTN customer churn in the first quarter of 2025 in Nigeria **click link to view the Dashboard App:** mtnchurnapp.streamlit.app This app analyzes MTN customer churn in the first quarter of 2025 in Nigeria # Data Analysis and Insights **A. Demographics and Churn Behavior** The churn rate metric dynamically revealed customer loss patterns across gender and age groups. Younger customers (18–34) exhibited higher churn tendencies, potentially due to competitive pricing or dissatisfaction with network coverage. Gender analysis using sunburst and histogram visualizations showed that male customers churned slightly more frequently than females in most regions. **B. Geographic Insights** Top 10 states by revenue were visualized using bar charts, indicating concentration of high-value customers in metropolitan areas such as Lagos, Abuja, and Port Harcourt. State-wise churn distribution identified specific regions with elevated churn rates, signaling areas for improved network quality or targeted retention campaigns. **C. Revenue Analysis** The total and average revenue KPIs helped quantify the financial impact of churn. Seasonal trends were detected through monthly revenue patterns, showing fluctuations aligned with billing cycles and promotional periods. Subscription-based analysis revealed which plans generated the most revenue and which were prone to higher churn. **D. Customer Behavior** Device-type analysis showed that smartphone users dominated the customer base but also accounted for a larger proportion of churners — possibly linked to faster switching behavior among digitally active users. Reasons for churn, captured and visualized, included issues such as poor network service, pricing dissatisfaction, or customer support challenges. The relationship between customer reviews and purchase frequency indicated that higher satisfaction ratings correlated with repeat purchases and longer tenures. # Business Implications and Recommendations **Targeted Retention Campaigns**: Implement predictive churn modeling to proactiv …