Data Analytics Portfolio Project: What is Driving SaaS Recurring Revenue at Risk? with Churn Performance
Overview of SaaS Churn & Retention Dashboard
The churn and retention dashboard is based on fictional SaaS subscription business data during the period from January 2024 to December 2025. It presents insights in a bird’s-eye view of the business performance, showing recurring revenue lost to churn across segments, primary churn drivers, and the association between product adoption and churn.
From a SaaS business perspective, the insights indicate growing pressure on recurring revenue from the existing customer base. Revenue churn exceeds logo churn, suggesting that lost customers carry above-average revenue value. A GRR of 94.04% and NRR of 95.97%, both under 100%, which means that the existing customer base is contracting because churn and downgrades outweigh expansion.
Enterprise accounts represent the greatest financial risk. However, results by industry, region, acquisition channel, and billing frequency show that the highest churn rates do not always align with the largest MRR losses.
Meanwhile, competition, pricing, and low product adoption emerged as the leading churn drivers. Also, the last bar chart illustrates that product adoption and seat utilization alone do not consistently explain churn, suggesting that retention risk is influenced by multiple factors. Overall, stakeholders should focus on protecting high-value accounts and coordinating cross-functional retention initiatives across customer success, product, sales, and finance.
Breakdown of the Churn & Retention Analysis
Objectives for the Dashboard
- Define KPIs to monitor and evaluate churn performance
- Shows whether the business is losing more customers or recurring revenue over time
- Presents GRR and NRR trends to assess the recurring revenue performance
- Identifies which customer segment generates the largest financial loss
- Performs why customers churn and what the main drivers are
- Validates whether product adoption or seat utilization is associated with higher churn.
Dataset Background & Methodology
The data is synthetic, mimicking a real-world B2B SaaS subscription business dataset for the period January 2024 to December 2025. The dataset covers the complete customer lifecycle, including customer acquisition, onboarding, subscriptions, recurring revenue, billing payments, product usage, feature adoption, expansion, contraction, churn, and account health. It consists of 12 tables.
Based on the SaaS data, it offers KPI-building aligned with the SaaS business’s primary goals, which increase user retention, optimize service adoption, and prioritize recurring revenue growth and profitability. Also, the SaaS data enables various analytical approaches to support executive, finance, revenue operations, customer success, product, sales and marketing teams by tracking, monitoring, and evaluating.
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This project aims to translate raw data into analytics-driven actions for SaaS business success. Before analyzing and visualizing data, tables are cleaned, validated, transformed, and joined to ensure data integrity and present reliable analyses.
Key Performance Indicator (KPI) Definitions
- Logo Churn Rate: The percentage of customers lost divided by total distinct customers. It measures customer retention performance and indicates whether the company is maintaining a stable customer base.
- Revenue Churn Rate: The percentage of recurring revenue lost through cancellations.
- Gross Revenue Retention (GRR): The percentage of beginning recurring revenue retained from existing customers after subtracting churn and contraction, excluding expansion and reactivation revenue. GRR reveals the strength of the company’s core revenue base and whether existing customer revenue is being protected before upsells are considered.
- Net Revenue Retention (NRR): Measures how effectively the company retains and expands recurring revenue from existing customers. It includes expansion, contraction, reactivation, and churn but excludes new-customer revenue. NRR is calculated as Beginning MRR plus Expansion MRR and Reactivation MRR, minus Contraction MRR and Churned MRR. Then, dividing the result by the Beginning MRR. It is formatted as a percentage.
- Churned MRR: Total recurring revenue lost, calculated as the sum of churned Mrr divided by the sum of Mrr beginning
- Churned Accounts: Number of customers lost due to churn
SaaS Churn and Retention Performance Dashboard
Deep Dive Insights
- Retention is weakening despite continued recurring revenue. November’s 4.91% logo churn and 5.51% revenue churn indicate that churned customers generate above-average revenue. With GRR at 94.04% and NRR at 95.97%, the existing customer base is shrinking rather than supporting growth. Stakeholders should prioritize retention and expansion within high-value accounts.
- Enterprise churn presents the greatest financial exposure. Enterprise customers recorded the highest churn rate at 6.4% and the largest segment-level MRR loss of approximately $65K. Customer Success and account management teams should strengthen executive engagement, renewal planning, product-value reviews, and early-risk intervention for enterprise accounts.
- Churn rate and revenue impact require different prioritization. Real estate had the highest industry churn rate at 6.16% but only about $5K in lost MRR, while financial services and technology produced substantially greater revenue losses at lower churn rates. Stakeholders should evaluate both churn frequency and financial impact when allocating retention resources.
- Contract and acquisition patterns reveal targeted risks. Annual subscriptions showed the highest billing-frequency churn rate, while monthly subscriptions generated the greatest lost MRR. Event-acquired customers experienced the highest acquisition-channel churn rate, whereas outbound sales produced the largest MRR loss. Sales and marketing teams should review customer fit, onboarding quality, contract expectations, and channel economics.
- Churn is driven by competitive, pricing, adoption, and payment issues. Competition was the leading churn reason, followed by pricing and low product adoption. However, adoption and seat-utilization categories did not show a consistent relationship with churn, suggesting that simple usage levels may not reliably predict customer health. Stakeholders should combine product usage with support interactions, payment behaviour, contract status, and account-level risk indicators.
Recommendations & Next Steps
- Protect high-value and enterprise revenue. Establish a risk-based retention program for Enterprise accounts and other high-MRR segments. Assign executive sponsors, conduct regular value reviews, and trigger proactive outreach before renewal when health scores, payment behaviour, or engagement indicators deteriorate.
- Strengthen renewal and contract strategies. Investigate why annual contracts have the highest churn rate and why monthly subscriptions generate the greatest MRR loss. Introduce earlier renewal discussions, targeted retention offers, flexible contract options, and structured onboarding for customers acquired through events and outbound sales.
- Address the root causes of churn with cross-functional action. Product, Customer Success, Sales, and Finance teams should coordinate responses to competition, pricing concerns, low adoption, and payment failures. Improve competitive positioning, demonstrate measurable product value, support adoption of high-impact features, and automate payment-recovery workflows to reduce voluntary, non-renewal, and involuntary churn.
Appendix
Caveats and Assumptions
- The dataset is synthetic and does not represent an actual company.
- Gross margin and customer-acquisition cost are unavailable due to insufficient data.
- Revenue recognition may differ from subscription MRR.
- Predicting historical customer behaviour patterns may not be enough for future outcomes due to a lack of data.
Tech Stack Used
- Data Preparation: SQLite, Python, VS Code
- BI tool: Tableau
- AI-assisted: ChatGPT, Gemini
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👉This is a part of my data analytics project, and I’d love to hear your constructive feedback, ideas, or suggestions for improvement. 🧐
