fewertools
๐ Growing Stage
The Growth
Dashboard
Measure what matters. Ignore the rest. Scale with clarity.
What's Inside
1
KPI Tracker
North Star metric, weekly dashboards, revenue breakdowns
2
User Feedback Log
Centralized inbox with categorization and sentiment
3
Funnel Metrics (AARRR)
Track every stage of your user journey
4
Experiment Tracker
Hypothesis-driven A/B testing with result logging
5
Customer Health Scorecard
Spot churn before it happens
SECTION 01
KPI Tracker
Define your North Star. Track what actually moves the needle.
North Star Metric
| Field | Your Answer |
|---|---|
| Metric | |
| Current Value | |
| Target (30 days) | |
| Target (90 days) | |
| How it's measured | |
| Why this metric |
Weekly Dashboard
| Metric | This Week | Last Week | ฮ Change | Target | Status |
|---|---|---|---|---|---|
| Revenue (MRR) | ๐ข ๐ก ๐ด | ||||
| New Signups | |||||
| Active Users (WAU) | |||||
| Churn Rate | |||||
| Activation Rate | |||||
| NPS Score | |||||
| Support Tickets | |||||
| Avg. Response Time |
Monthly Revenue
| Month | MRR | New MRR | Churned MRR | Net New | Customers | ARPU |
|---|---|---|---|---|---|---|
Cohort Retention
| Cohort | Week 0 | Week 1 | Week 2 | Week 4 | Week 8 | Week 12 |
|---|---|---|---|---|---|---|
| 100% | ||||||
| 100% | ||||||
| 100% | ||||||
| 100% |
๐ Focus
If you can only track one number, track Net Revenue Retention. It tells you if your existing customers are getting more value over time.
SECTION 02
User Feedback Log
Never lose a user insight. Centralize everything here.
Feedback Inbox
| # | Date | User | Channel | Feedback | Category | Sentiment | Status |
|---|---|---|---|---|---|---|---|
| 1 | Feature Request | ๐ | Open | ||||
| 2 | Chat | Bug | ๐ | Open | |||
| 3 | Praise | ๐ | Open | ||||
| 4 | |||||||
| 5 | |||||||
| 6 | |||||||
| 7 | |||||||
| 8 |
Top Requested Features
| Feature | # Requests | Revenue Impact | Effort | Decision |
|---|---|---|---|---|
| Build / Defer / Decline | ||||
User Quotes Worth Remembering
"[Exact quote from user]". Name, Date
๐ก Tip
Review this log weekly. Patterns emerge after 10+ entries. One complaint is an anecdote, five complaints about the same thing is a feature.
SECTION 03
Funnel Metrics (AARRR)
Track every stage of your user journey.
Acquisition. How do users find you?
| Channel | Visitors | Signups | Conversion | CAC | Notes |
|---|---|---|---|---|---|
| Organic Search | |||||
| Twitter/X | |||||
| Product Hunt | |||||
| Referral | |||||
| Direct | |||||
| Paid Ads | |||||
| Total |
Activation. Do they have an "aha" moment?
| Step | Users | Drop-off % | Notes |
|---|---|---|---|
| Signed up | - | ||
| Completed onboarding | |||
| Performed core action | |||
| Invited teammate | |||
| Activation rate | Target: 40%+ |
Retention. Do they come back?
| Timeframe | Retention Rate | Target | Status |
|---|---|---|---|
| Day 1 | 60% | ||
| Day 7 | 30% | ||
| Day 30 | 15% | ||
| Day 90 | 10% |
Revenue. Do they pay?
| Metric | Value | Target |
|---|---|---|
| Trial โ Paid conversion | 5-10% | |
| Free โ Paid conversion | 2-5% | |
| Average Revenue Per User | ||
| Lifetime Value (LTV) | ||
| LTV:CAC Ratio | >3:1 |
Referral. Do they tell others?
| Metric | Value | Target |
|---|---|---|
| Referral rate | 10%+ | |
| Viral coefficient (K) | >0.5 | |
| Avg. referrals per user |
SECTION 04
Experiment Tracker
Test hypotheses, not hunches. Run experiments properly.
Active Experiments
| ID | Name | Hypothesis | Primary Metric | Start | End | Result |
|---|---|---|---|---|---|---|
| EXP-001 | If we [change], then [metric] will [improve] because [reason] | |||||
| EXP-002 | ||||||
| EXP-003 |
Experiment Template
| Field | Details |
|---|---|
| Hypothesis | If we [do X], then [metric Y] will [change Z] because [reason] |
| Primary Metric | |
| Secondary Metrics | |
| Traffic Split | 50/50 |
| Min. Sample Size | |
| Duration | |
| Confidence Level | 95% |
Results Log
| Metric | Control | Variant | ฮ | Confidence | Winner |
|---|---|---|---|---|---|
Experiment Backlog
| Priority | Experiment | Expected Impact | Effort | Status |
|---|---|---|---|---|
| 1 | Queued | |||
| 2 | ||||
| 3 | ||||
| 4 | ||||
| 5 |
๐งช Rule of Thumb
Run one experiment at a time. Minimum 2 weeks per test. If you can't reach statistical significance, the difference probably doesn't matter.
SECTION 05
Customer Health Scorecard
Spot churn before it happens. Rescue at-risk customers.
Health Score Components
| Factor | Weight | Scoring (1-10) |
|---|---|---|
| Usage Frequency | 30% | Daily=10, Weekly=7, Monthly=4, Rare=1 |
| Feature Adoption | 20% | 80%+ features=10, 50%+=7, Core only=4, Minimal=1 |
| Support Interactions | 15% | Positive=10, Neutral=5, Frequent complaints=2 |
| Growth Signal | 15% | Added seats=10, Upgraded=8, Static=5, Downgraded=2 |
| Engagement Trend | 10% | Increasing=10, Stable=6, Declining=2 |
| Payment Health | 10% | On time=10, Late once=5, Multiple failures=1 |
Customer Dashboard
| Customer | Plan | MRR | Score | Health |
|---|---|---|---|---|
| /100 | ๐ข ๐ก ๐ด | |||
| /100 | ||||
| /100 | ||||
| /100 | ||||
| /100 |
๐ข Healthy (70-100)
Candidate for upsell, case study, referral ask.
๐ก At Risk (40-69)
Schedule check-in. Investigate usage drop.
๐ด Critical (0-39)
Immediate outreach. Offer help or discount.
Churn Risk Signals
Login frequency dropped >50% in last 30 days
Key feature usage stopped
Support ticket with negative sentiment
Downgraded plan
Payment failed 2+ times
Competitor mentioned in support conversation
Asked about data export or cancellation
Recommended Tool Stack
Product Analytics
PostHog
Feature flags, session replays, funnels. All-in-one.
Customer Messaging
Intercom
In-app messages, support, onboarding flows.
Error Monitoring
Sentry
Know about bugs before users report them.
Business Analytics
Metabase
SQL dashboards anyone on the team can read.
Email Marketing
Loops
Event-triggered emails that actually convert.
Build with fewer tools.
Curated stacks for every stage of building.
fewertools.com