MRR
vs last month
Active subs
vs last month
Trial → paid
Churn
vs last month
What to improve
Ranked from your metrics — most urgent first
Health score
93/100
A·HealthyChurn is eating revenue
Top priorityAdd a cancel-flow save offer and target the stale-subscriber reminder toggle at drop-off cohorts.
Paywall reach below target
Cut friction at "Completed onboarding" — it's the single step holding paywall reach under target.
United Kingdom converts below the rest
Tailor onboarding/pricing for United Kingdom — localized pricing or a platform-specific flow often closes a gap this size.
Churn concentrates on Android
Dig into why Android users leave — a cohort this far above baseline usually shares one fixable pain point.
Low daily stickiness
Add a habit loop (streaks, a daily reason to return, or a well-timed notification) tied to the core value.
Unit economics
What each subscriber is worth
Subscriber LTV
$91.27
~15 mo lifetime
ARPPU
$5.93
per paying sub / mo
ARPU
$0.73
per active user / 30d
AI cost share
9%
of revenue
Trends
Momentum over the last six months
MRR
0.7%$5.6K
Users
0.7%14.3K
Churn
3.4%6.5%
Paywall reach
3.4%70.5%
Activation & retention
Where new users convert, and how the active base sticks
Onboarding → paywall funnel
70.5% reach paywall/ 75% aim- Opened app5,353 · 100%
- Started onboarding4,764 · 89%
↓ 17.2% drop-off
- Completed onboarding3,945 · 74%
↓ 4.3% drop-off
- Reached paywall3,774 · 71%
↓ 78.5% drop-off
- Purchased811 · 15%
Users & engagement
DAU
1.4K
WAU
3.7K
MAU
7.5K
New users
1.4K
Stickiness
18%
DAU / MAU
Retention
Revenue
Subscription revenue and how it breaks down
Last 30 days
$5.5K
This month
$4.6K
New subs (30d)
190
Churned (30d)
61
By plan
Segments
Where churn and conversion concentrate
Coloured vs blended baseline (churn 6.5% · conv. 52%) — worse / better.
Audience & growth
Who's using it, and where the top of funnel stands
Audience
Countries
- United States34%
- Netherlands16%
- United Kingdom12%
- Germany9%
- Other29%
Devices
OS
Growth
Waitlist signups
3,607
Registered users
14,254
AI costs
Model spend against the value it supports
Spend (30d)
$513
Tokens (30d)
15.2M
Cost / user
—
needs per-user data
By model