As a data analytics and finance expert, Core financiero would advise against calculating a moving average for cumulative Net Revenue Retention (NRR). Here's why:
Understanding NRR and Its Cumulative Nature
Net Revenue Retention (NRR): Measures the percentage of recurring revenue retained from existing customers over a specific period, accounting for upgrades, downgrades, and churn.
Cumulative NRR: Aggregates NRR over multiple periods, resulting in a naturally increasing metric (assuming positive revenue).
Issues with Moving Averages on Cumulative Metrics
Distortion of Trends:
Cumulative Metrics: By their nature, cumulative metrics increase over time, even if the underlying performance is declining.
Moving Averages: Designed to smooth out short-term fluctuations in stationary data to reveal underlying trends.
Applying to Cumulative Data: Leads to misleading interpretations, as the moving average may suggest a flattening or declining trend when, in fact, the cumulative metric is inherently increasing.
Mathematical Redundancy:
Averaging Cumulative Values: When you average values that are already cumulative sums, you effectively dilute the information about the rate of change.
Loss of Granularity: Important fluctuations and inflection points in the data can be obscured.
Misinterpretation Risks:
False Signals: The moving average of cumulative NRR might indicate stability or decline where none exists.
Decision-Making Impact: Relying on such misleading trends can lead to incorrect strategic decisions.
Recommended Approach
Instead of applying a moving average to the cumulative NRR, consider the following:
1. Use Moving Average on Non-Cumulative NRR
Calculate Periodic NRR:
Determine NRR for each individual period (e.g., monthly or quarterly), not the cumulative sum.
Apply Moving Average:
Smooth out short-term volatility by calculating the moving average over these periodic NRR values.
Benefits:
Trend Visibility: Provides a clearer picture of how NRR is changing over time.
Actionable Insights: Helps identify underlying trends in customer retention and revenue growth.
2. Analyze NRR Increments or Growth Rates
NRR Increments:
Calculate the change in NRR from one period to the next.
Growth Rates:
Determine the percentage change in NRR between periods.
Apply Moving Average:
Smooth these incremental changes to understand the trend in growth rates.
Benefits:
Sensitivity to Changes: Highlights acceleration or deceleration in revenue retention.
Strategic Value: Enables proactive responses to improving or declining retention rates.
Why This Approach Is Better
Accuracy in Trend Analysis:
Reflects the true performance and health of customer retention efforts.
Enhanced Decision-Making:
Provides reliable data to inform strategies for customer success, marketing, and sales.
Avoids Misleading Conclusions:
Prevents the distortion of trends that can occur when averaging cumulative data.
Practical Implementation
Adjust Your Measures:
Modify your DAX measures to focus on periodic NRR and its increments.
Visualizations:
Use line charts to plot the moving average of periodic NRR or its growth rates.
Contextual Analysis:
Combine quantitative insights with qualitative factors (e.g., market conditions, customer feedback) for comprehensive understanding.
Conclusion
Calculating a moving average of cumulative NRR is not advisable due to the inherent issues it presents in trend analysis and interpretation. Instead, focusing on moving averages of non-cumulative, periodic NRR metrics will provide more meaningful insights into your business's revenue retention performance.
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