Community Analytics and Growth

What Gets Measured Gets Managed

🔄 Quick Recall: In the previous lesson, you learned to handle community crises — from member conflicts to public PR situations — with the inside-out communication principle and escalation protocols. Now you’ll build the analytics system that detects problems early, measures what’s working, and proves your community’s value with data.

Most community managers rely on gut feeling: “The community feels active” or “Engagement seems down this week.” AI-powered analytics replace gut feeling with data — and data tells you not just what happened, but why and what to do about it.

The Community Health Dashboard

Help me design a community health dashboard.

My community:
- Platform: [Discord/Slack/Circle/other]
- Size: [X] members
- Age: [how long has the community existed?]
- Business goal: [what should the community accomplish?]

Design a dashboard with these metric categories:

GROWTH METRICS:
- New members per week/month
- Member source (where are they coming from?)
- Onboarding completion rate

ENGAGEMENT METRICS:
- DAU/MAU ratio (daily active / monthly active users)
- Posts per active member per week
- Contribution ratio (what % of members post vs. lurk?)
- Average response time (how fast do posts get replies?)

RETENTION METRICS:
- 7-day, 30-day, 90-day retention rates
- Churn rate and churn reasons (if available)
- At-risk member identification

HEALTH METRICS:
- Sentiment score (overall community mood)
- Guideline violations per week
- Member satisfaction (survey-based)

For each metric:
- How to calculate it
- What's a healthy benchmark
- What to do if it's declining

Key Metrics and Benchmarks

Metric	Healthy Range	Warning Sign	Action
DAU/MAU ratio	15-30%	<10%	Improve daily content variety; check notification settings
Contribution ratio	10-20% contributors	<5%	Add low-barrier engagement formats (polls, reactions)
Response time	<4 hours	>24 hours	Assign conversation starters; use AI to draft initial responses
7-day retention	60-75%	<40%	Overhaul onboarding flow
30-day retention	40-55%	<25%	Audit content quality and member value delivery
Sentiment score	Positive/Neutral 85%+	<70% positive	Investigate recent conflicts; check moderation logs

✅ Quick Check: Why is the DAU/MAU ratio more useful than either number alone? Because MAU tells you how many members exist, and DAU tells you how many showed up today — but neither reveals the community’s daily “pull.” The ratio (DAU ÷ MAU) measures what percentage of your monthly audience engages on any given day. A community with 1,000 MAU and 200 DAU (20% ratio) has strong daily pull. A community with 10,000 MAU and 200 DAU (2% ratio) has a massive lurker problem despite technically having the same daily activity.

AI-Powered Sentiment Analysis

Help me set up sentiment tracking for my community.

I want to monitor the overall emotional tone of my community
over time. Design a system that:

1. Samples [X] posts per week from key channels
2. Classifies each as positive, negative, neutral, or mixed
3. Identifies trending topics in negative sentiment
4. Flags sentiment shifts (e.g., sentiment dropped 15% this week)
5. Connects sentiment changes to events (new feature launch,
   guideline change, community incident)

Create a weekly sentiment report template I can generate using AI:
- Overall sentiment score
- Top positive themes this week
- Emerging negative themes
- Recommended actions

Cohort Analysis for Retention

Help me design a cohort analysis for my community.

I want to compare member groups by when they joined:
- January cohort: How many are still active? What's their engagement?
- February cohort: Same analysis
- And so on...

For each cohort, track:
1. 7-day activation rate (did they engage in first week?)
2. 30-day retention rate
3. 90-day retention rate
4. Current activity level

This helps me answer:
- Are newer members retaining better than older ones? (Onboarding improved?)
- Was there a specific month where retention dropped? (What changed?)
- Which cohort has the highest contribution rate? (What did they experience?)

Show me how to visualize this as a retention curve and
identify the biggest improvement opportunity.

Proving Community ROI

Help me build a business case for my community using data.

Available data:
- Community members vs. non-member customers: [any data?]
- Support tickets: community self-service vs. staff-handled
- Product feedback: ideas that originated in the community
- Retention: member vs. non-member churn rates
- Revenue: spend of community members vs. non-members (if available)

Build a quarterly business report that shows:
1. COST SAVINGS: Support deflection (member-answered questions × avg
   ticket cost), reduced onboarding support for product
2. REVENUE IMPACT: CLV difference between community members and
   non-members, upsell/cross-sell from community engagement
3. PRODUCT VALUE: Feature requests sourced from community,
   beta testing participation, NPS comparison
4. GROWTH CONTRIBUTION: Referrals from community members,
   content generated by members (SEO value)

Present each as a dollar figure or clear percentage improvement.

✅ Quick Check: Why present community ROI as dollar figures, not engagement metrics? Because executives make decisions based on revenue impact, not activity metrics. “Our community has 30% DAU/MAU ratio” means nothing to a CFO. “Community members have 2.4x higher customer lifetime value, saving $120,000/year in support costs and generating $340,000 in additional revenue” justifies the next budget request. AI helps you translate community metrics into business language.

Key Takeaways

Fix retention before pursuing growth — adding members to a community with low engagement makes the problem worse, not better
DAU/MAU ratio (daily active ÷ monthly active) measures your community’s daily “pull” better than either number alone; target 15-30%
Predictive churn analysis identifies at-risk members before they leave — personal outreach based on their specific contribution history re-activates 30%+
Cohort analysis (comparing member groups by join date) reveals whether your onboarding and content improvements are actually working
Prove community ROI in dollar figures: CLV comparison, support deflection savings, and revenue impact — not engagement metrics

Up Next: You’ll assemble everything into a sustainable community management system — with daily, weekly, and monthly workflows that keep your community thriving without burning you out.