Product·Updated January 27, 2026

Launch Metrics Dashboard

Define key metrics to track for product launches and create a monitoring dashboard structure.

Use Case

Setting up launch tracking, defining success metrics, or monitoring product performance post-launch.

Prompt

Create a launch metrics dashboard for [product/feature name]. Include:

1. Success Criteria
   - What defines a successful launch?
   - Primary goals (adoption, revenue, engagement)
   - Secondary goals
   - Timeline for measuring success (Day 1, Week 1, Month 1, Quarter 1)

2. North Star Metric
   - The one metric that matters most
   - Why this metric
   - Target value
   - How to measure it

3. Adoption Metrics
   - Users who discover the feature
   - Users who try the feature
   - Users who adopt (use 3+ times)
   - Users who become power users
   - Adoption rate %
   - Time to first use
   - Activation rate

4. Engagement Metrics
   - Daily/Weekly/Monthly active users
   - Feature usage frequency
   - Session duration
   - Clicks or interactions
   - Retention (Day 1, Day 7, Day 30)
   - Stickiness ratio (DAU/MAU)

5. Quality Metrics
   - Error rate
   - Load time / Performance
   - Crashes or bugs reported
   - Support tickets related to feature
   - Customer satisfaction score
   - Net Promoter Score (NPS)

6. Business Impact Metrics
   - Revenue impact (if applicable)
   - Conversion rate changes
   - Upgrades or upsells
   - Churn rate changes
   - Customer lifetime value impact
   - Time saved or efficiency gains

7. User Sentiment Metrics
   - User feedback (positive/negative)
   - Social media mentions
   - App store reviews
   - Survey responses
   - Feature requests related to launch
   - Comparison to pre-launch sentiment

8. Competitive Metrics (if applicable)
   - Market share change
   - Feature parity with competitors
   - Win rate in competitive deals
   - Migration from competitors

9. Dashboard Structure
   **Real-Time View (Launch Day):**
   - Users who discovered feature
   - Users who tried feature
   - Error rate
   - Support tickets
   - Social sentiment
   
   **Weekly View:**
   - Adoption curve
   - Engagement trends
   - Quality metrics
   - Top user feedback themes
   
   **Monthly View:**
   - Retention cohorts
   - Business impact
   - Goal progress
   - Comparison to forecast

10. Data Sources & Tools
    - Analytics platform (Mixpanel, Amplitude, GA4)
    - Product analytics tool
    - Support ticket system
    - Survey tool
    - Social listening tool
    - How to access each source
    - Refresh frequency

11. Alerts & Thresholds
    - When to escalate issues
    - Threshold for each critical metric
    - Who gets alerted
    - Response protocol

12. Reporting Cadence
    - Daily standup (first week)
    - Weekly review
    - Monthly deep dive
    - Quarterly retrospective
    - Who reviews what metrics

Format as a complete dashboard specification with metrics definitions, targets, and monitoring plan.

How to use

1Replace [product/feature name] with what you launched. Example: "AI writing assistant feature"
2Define launch goals: Specify what success looks like. Example: "Goal: 30% of users try feature in first month, 15% become regular users"
3List available tools: Mention your analytics stack. Say "Tools: Mixpanel, Zendesk, Intercom, Google Analytics"
4Paste the prompt into your preferred AI tool, like ChatGPT or Claude
5Review metrics: Ensure metrics align with your goals
6Prioritize: Pick 5-7 metrics to monitor daily, others weekly
7Set up tracking: Implement events and dashboards based on the plan

Pro Tips

• Set up tracking before launch: Don't wait until launch day to instrument metrics
• Start with fewer metrics: Focus on 5-7 key metrics rather than tracking everything
• Compare to baseline: Know pre-launch metrics to measure impact
• Segment users: Compare new users vs existing users, power users vs casual users
• Watch for unintended consequences: Monitor negative metrics too (churn, errors)
• Share widely: Make dashboard accessible to whole team

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