Churn Analysis & Retention

Monthly Churn Rate

8.2%

↓ -1.3% from last month

Avg Customer LTV

₹18,500

↗ +₹2,100 from last quarter

High-Risk Users

2,847

↗ +12% this week

90-Day Retention

74.3%

↗ +2.1% from last quarter

AI Churn Prediction Model

91.2% Accuracy

Top Churn Indicators

Low engagement (7+ days) 87%
No profile updates 72%
Limited interactions 65%
Subscription near expiry 58%

Retention Factors

Successful matches 92%
Family involvement 78%
Regular communication 71%
Premium features usage 68%

Critical At-Risk Users

Priya Sharma (UUID: 018bfa...)

Last active: 14 days ago • Churn probability: 89%

Arjun Patel (UUID: 018bfb...)

Last active: 8 days ago • Churn probability: 74%

Kavya Reddy (UUID: 018bfc...)

Last active: 6 days ago • Churn probability: 68%

Active Retention Campaigns

Win-Back Email Series

Active

Personalized re-engagement emails

Target: 1,234 users Success: 23%

Premium Feature Trial

Scheduled

Free premium access for at-risk users

Launches: Tomorrow Target: 567 users

Personal Matchmaker

Active

Dedicated relationship consultant

Target: 89 VIP users Success: 67%

Family Engagement

Active

Family member involvement program

Target: 456 families Success: 41%

Cohort Retention Analysis

Cohort
Month 1
Month 2
Month 3
Month 6
Month 9
Month 12
Month 18
Jan 2024
85%
72%
68%
61%
58%
52%
48%
Mar 2024
88%
76%
71%
65%
61%
56%
-
Jun 2024
91%
79%
74%
68%
-
-
-
Sep 2024
93%
82%
77%
-
-
-
-

Key Insight: Recent cohorts show improved retention, likely due to enhanced onboarding and AI matching improvements.

Top Churn Reasons

Poor Match Quality

Incompatible suggestions

34%

2,890 users

High Subscription Cost

Price sensitivity

27%

2,301 users

Limited Communication

Few profile interactions

18%

1,532 users

App Usability Issues

Technical difficulties

13%

1,107 users

Time Constraints

Too busy to engage

8%

681 users

Action Required: Focus on improving AI matching algorithms and creating flexible pricing tiers.

Retention Action Center