Advanced User Analytics
Behavioral insights, cohorts, retention, and engagement metrics
User Cohorts
Size
45,230
Retention Rate
78%
Engagement Score
72/100
Behavior Patterns
Morning Shoppers (6-9am)
34%15,400 users
Evening Browsers (5-8pm)
42%18,980 users
Weekend Price Checkers
28%12,670 users
Receipt Reporters
18%8,150 users
Bulk Savers (shopping lists)
31%14,020 users
Feature Adoption Rates
Price Alerts
68%30,750 active users
Shopping Lists
72%32,550 active users
Store Comparison
54%24,420 active users
Receipt Scanning
22%9,950 active users
Community Validation
16%7,240 active users
Loyalty Rewards
41%18,540 active users
Retention Curve
Day 0
100%
Day 1
68%
Day 7
42%
Day 30
28%
Day 60
22%
Day 90
18%
Day 180
12%
Day 365
8%
Conversion Funnel (Sign-up to Reporter)
Sign-up Page
100%100,000
Create Account
68%68,000
Add First Store
50%34,000
Report Price
55%18,700
Enable Alerts
48%8,950
Become Reporter
20%1,790
Key Insights
- ✅ Strong evening engagement (42% of users active 5-8pm)
- ✅ Shopping lists are highest adoption feature (72%)
- ✅ New user retention at 68% (Day 1) – strong onboarding
- ✅ Long-term retention stable at 8-12% annual cohort
- ✅ Reporter conversion at 2% – opportunity for tier promotion
- ✅ Dormant users (12.5%) – re-engagement campaign recommended