Customer Subscription Churn and Usage Patterns

By shrijeetverma13 · January 30, 2026

Data source :

The analysis reveals that the Premium plan has the highest customer attrition rate among all plan types. A detailed breakdown of churn rates has been calculated for each plan, showing both the percentage of customers who churned and the actual customer counts.

The total monthly revenue at risk from churned customers is $697,995. A bar chart has been generated showing how this revenue breaks down across different plan types, allowing you to see which customer segments represent the greatest financial risk.

The analysis reveals a clear relationship between payment failures and customer churn rates. A visualization and detailed breakdown show how churn rates vary across different levels of payment failures, helping identify which customer segments are most at risk.

Retained customers show significantly higher engagement with the service compared to churned customers. On average, retained customers use the service 13.75 hours per week, while churned customers only use it 12.25 hours per week - a difference of 1.49 hours or 12.2% more usage.

Retention rates across monthly signup cohorts in 2023-2024 averaged 42.5%, with significant variation between cohorts. The analysis tracked 24 monthly cohorts and reveals that March 2023 had the strongest retention at 48.5%, while February 2024 showed the lowest at 31.8%.

I've analyzed customer usage patterns across different plan types, breaking them into three segments: Low usage (under 8 hours per week), Medium usage (8-16 hours per week), and High usage (over 16 hours per week). The analysis includes a grouped bar chart showing the percentage distribution of customers in each usage segment for every plan type.

Last login recency shows a strong positive correlation with churn - the longer users stay inactive, the more likely they are to churn. The visualization clearly shows churn rates escalating as the days since last login increase.

Customers with more support tickets have higher churn rates. The analysis shows that churned customers averaged 4.22 support tickets compared to 3.44 for retained customers, indicating that support tickets are more often a sign of unresolved issues rather than successful retention efforts.

Customers most commonly churn at tenure month 16, with 57 customers leaving at that point. The analysis reveals a 57.3% overall churn rate (1,605 out of 2,800 customers). The visualizations show both the distribution of churn events across tenure months and how customer retention declines over time.

Customers who churned from the highest monthly fee plan ($699 Premium) show several distinct characteristics. Out of 548 churned customers on this premium tier, they averaged 11.8 hours of weekly usage, filed 4.2 support tickets, experienced 2.8 payment failures, and had been with the service for 18.1 months. Most notably, their last login was an average of 33.4 days ago, indicating significant disengagement before churning.

I've analyzed the average revenue per customer by plan type, calculated by multiplying monthly fees by tenure months. The analysis includes a bar chart showing how different plan types compare in terms of total revenue generated per customer.

There are 476 active customers who haven't logged in for 30 or more days and are at churn risk. This represents a significant portion—39.8%—of your total active customer base of 1,195 customers.

The analysis shows how different plan types are distributed across signup quarters. A grouped bar chart visualizes the number of users for each plan type in every quarter, making it easy to compare trends over time.

There are 245 low-tier customers with high usage that suggests upgrade potential. These customers are on the Basic plan ($199/month) but are using the service at levels comparable to higher-tier users, averaging 21.9 hours per week.

I've analyzed customer signups by month and their retention patterns. The visualization shows a dual-axis chart comparing the number of signups each month (blue bars) against the retention rate for each cohort (green line with markers).

Among customers who experienced payment failures, 60.6% eventually churned while 39.4% recovered and remained active. This analysis examined 2,358 customers who had at least one payment failure.

The combination of all three risk factors - low usage, high days since last login, and payment failures - is the strongest predictor of churn, with a 70.2% churn rate among the 588 customers who have all three characteristics.

Customers with 24+ months tenure who haven't churned represent a highly engaged segment of 436 customers (15.6% of the total customer base). These loyal customers demonstrate consistently positive patterns across all key metrics compared to other customers.