In this chart, we observe the top 5 churn reasons. Among them, the most prevalent reason, occurring 313 times, is related to competitor devices outperforming ours. This suggests that our current offers may not be as compelling as those offered by competitors. Additionally, it highlights a need for proactive customer query resolution to enhance overall satisfaction.
We've enhanced our analysis by introducing location-baseds Segmentation to identify churn patterns. Upon closer examination,
San Diego emerges as the location with the highest churn rate, accounting for 185 customers (64% of total churn). Following closely is Los Angeles, where 78 customers (26%) have shown comparatively higher churn rates than other locations. Delving further into our customer base, we've categorized churn based on contract durations. Our data reveals that month-to-month contract customers constitute the highest churn rate, representing 45.84% of total churn. In contrast, one-year contract customers experience a lower churn rate at 10.71%, while two-year contract customers have the lowest churn rate, standing at 2.55%. This data underscores the importance of understanding contract dynamics in addressing churn. To facilitate data exploration and analysis, we've introduced a question and answer bot within Power BI. This tool empowers users to ask questions about our datasets and receive instant insights,enhancing our ability to uncover actionable insights and make data-driven decisions
In the Age/Demographic/Detailed section, our in-depth analysis of customer churn has yielded several key findings. We've introduced a Customer Headcount (HC) with churned rate breakdown by age,which has uncovered an intriguing trend. Specifically, we've observed that customers aged 60 and above exhibit a gradual increase in churn rates, indicating a distinct upward trend. Moving on to the Churn Reason analysis, we've identified significant factors contributing to churn. Notably, the competition is luring customers away with compelling offers, as evidenced by the high churn rate associated with 'Competitor Offers' (841 instances).Additionally, 'Customer Service Dissatisfaction' (321 instances) has emerged as a critical issue. This points to a need for improvement in representative interactions, as clearly indicated by the graph.In our examination of customer plan types, we've detected a subtle difference in churn rates between 'No' (32.90%) and 'Yes' (31.65%) for customers on unlimited data plans. While the distinction is slight, it's worth exploring further to mitigate attrition among specific plan segments. One intriguing segment of our analysis pertains to 'Offer Reasons.'We've singled out this category due to a notable trend: a significant proportion of churn is associated with 'Offer E.' This indicates a critical area for improvement, as customers are evidently finding our competitors' offers more enticing. We've also dissected this data by gender to gain a clearer perspective on customer churn dynamics. These insights collectively provide us with a comprehensive understanding of customer churn patterns, enabling us to devise targeted strategies for improvement and retention.
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