Free vs Paid Plan Retention Comparison

Segmented retention analysis comparing free and paid plans with statistical significance testing, effect size calculations, retention curve shape analysis, and strategic recommendations for improving free tier conversion.

Input

What you provide to the skill

I have 8 months of user data with 500+ signups. Need monthly cohort analysis comparing free vs paid plans. Also track login retention to see which segment has better engagement.

Output

What the skill generates for you

SaaS Retention Cohort Analysis Report

Analysis Date: 2024-12-15
Data Period: May 2024 - December 2024 (8 months)
Total Users Analyzed: 550
Retention Definition: Login activity

Executive Summary

This analysis examines monthly retention cohorts comparing free plan (55% of users, n=303) vs paid plan (45% of users, n=247) subscribers across 8 months of user data. Key findings reveal paid users demonstrate 2.4x better 3-month retention and 3.1x better 6-month retention compared to free users, with statistically significant differences indicating plan type as a strong predictor of long-term engagement.

Critical Insights:

Paid users show 82% Month-1 retention vs 55% for free users (27pp difference, p<0.001)
Largest retention cliff occurs Month 0→1 for free users (45pp drop)
Paid cohort retention stabilizes around 52-55% after Month 6
Free cohort retention continues declining, reaching 10% by Month 7

Segment Comparison: Free vs Paid Plans

Free Plan Average Retention:

M1: 55.1% (95% CI: 50.2% - 60.0%)
M3: 28.2% (95% CI: 23.1% - 33.3%)
M6: 12.5% (95% CI: 8.4% - 16.6%)

Paid Plan Average Retention:

M1: 82.1% (95% CI: 77.8% - 86.4%)
M3: 68.2% (95% CI: 63.2% - 73.2%)
M6: 55.5% (95% CI: 49.4% - 61.6%)

Statistical Significance Testing

Two-Proportion Z-Tests (Free vs Paid)

| Period | Free Retention | Paid Retention | Difference | p-value | Significant? |
|––––|––––––––|––––––––|————|———|–––––––||
| Month 1 | 55.1% | 82.1% | 27.0pp | <0.0001 | Yes |
| Month 3 | 28.2% | 68.2% | 40.0pp | <0.0001 | Yes |
| Month 6 | 12.5% | 55.5% | 43.0pp | <0.0001 | Yes |

Effect Size:

Month 1: Paid users are 1.49x more likely to be retained
Month 3: Paid users are 2.42x more likely to be retained
Month 6: Paid users are 4.44x more likely to be retained

Retention Curve Analysis

Free Plan Pattern: Exponential decay

Steep initial drop, continues declining without stabilization
Classic “leaky bucket” pattern indicating onboarding/value realization issues

Paid Plan Pattern: Power law decay approaching plateau

Moderate initial drop, then gradual decline
Appears to stabilize around 52-55% after Month 6
Healthier retention curve suggesting strong product-market fit

Industry Benchmark Comparison

Metric	Your Free Plan	Your Paid Plan	Industry Standard	Assessment
M1 Retention	55.1%	82.1%	60-80%	Free: Below avg / Paid: Excellent
M3 Retention	28.2%	68.2%	40-55%	Free: Poor / Paid: Excellent
M6 Retention	12.5%	55.5%	30-45%	Free: Critical / Paid: Excellent

Actionable Recommendations

Priority 1: Address Free Plan Month 0→1 Cliff (45pp drop)

Immediate Actions:

Implement targeted onboarding intervention within first 7 days
Offer 1:1 onboarding call for users who haven’t logged in within 3 days
Create interactive product tour for first-time users

Success Metric: Increase free M1 retention from 55% to 65%

Priority 2: Convert High-Engagement Free Users Earlier

Recommended Approach:

Implement usage-based conversion triggers at power user thresholds
Show targeted upgrade prompts when users hit usage thresholds
Test “freemium+” tier to reduce friction

Success Metric: Convert 15% of M2 free users to paid within 30 days

Reproducible Analysis

uv run analyze_cohorts.py your_data.csv \
  --cohort-period monthly \
  --retention-event login \
  --segment-col plan_type

Report Generated: 2024-12-15
Model Used: Statistical cohort analysis with Wilson confidence intervals and two-proportion z-tests