Purpose

Current MRR: $2,901.75 with 0% month-over-month growth\u2014indicating plateau after sustained expansion
Active Subscribers: 41 customers generating $70.77 average revenue per user (ARPU)
Growth Trajectory: MRR grew 549% from $447 (Jan) to peak of $2,901.75 (Oct), then stalled in November
Churn Rate: 1.69% average monthly churn, with early months (Jan\u2013May) showing zero churn before stabilizing at ~2.4\u20133.3%
Plan Distribution: Enterprise tier dominates at 64% of MRR ($1,641.75) with 11 subscribers; Pro and Basic contribute 28.6% and 7.4% respectively

This section documents the data cleaning process applied to the raw Stripe subscription dataset before MRR analysis. A 92% retention rate indicates selective but conservative filtering, which is critical for ensuring the reliability of subscription metrics like churn rate, ARPU, and revenue trends that directly inform business health assessment.

Key Findings

Retention Rate: 92% (46 of 50 rows retained) - A healthy threshold suggesting minimal data loss while removing problematic records
Rows Removed: 4 observations excluded based on documented criteria (trialing subscriptions and invalid records)
Train/Test Split: Not applicable - This is descriptive analytics rather than predictive modeling, appropriate for subscription monitoring

Interpretation

The preprocessing strategy prioritizes data integrity over volume by excluding trialing subscriptions, which would artificially inflate subscriber counts and distort churn calculations. This decision directly supports the MRR analysis objective by ensuring that only active, revenue-generating subscriptions contribute to metrics like the current $2,901.75 MRR and 1.69% average churn rate. The 8% removal rate is proportional and justified.

Context

The documented assumptions (plan amounts in cents, annual-to-monthly conversion, trialing exclusion) are essential for interpreting downstream metrics. However, the small dataset size (46 final rows) may ampl