# Analytics Dashboard > User behavior tracking and analytics dashboards - Skill: `evezart/analytics-dashboard` (Agent Skill) - Install (CLI): `npx skillmds@latest add evezart/analytics-dashboard` - Raw SKILL.md: https://api.skillmd.com/api/skills/evezart/analytics-dashboard/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Data & Analytics - Author: EvezArt (https://skillmd.com/u/evezart) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/evezart/analytics-dashboard --- # Analytics Dashboard Skill Automate setup of analytics tracking and dashboard generation for web applications. --- ## Purpose This skill helps you implement comprehensive analytics tracking and create beautiful dashboards to understand user behavior, track conversions, and measure product success. --- ## When to Use - Adding analytics to a new application - Implementing event tracking for user actions - Creating analytics dashboards - Switching analytics providers - Setting up conversion tracking - Building admin analytics views --- ## What It Does 1. **Detects project type** (Next.js, React, Express, Python) 2. **Installs analytics dependencies** (PostHog, Mixpanel, Amplitude, Segment) 3. **Creates analytics configuration** with initialization code 4. **Generates dashboard components** with key metrics 5. **Provides tracking patterns** for common events 6. **Includes best practices** for performance and privacy --- ## Quick Start ### 1. Run Setup Script ```bash python3 /home/ubuntu/skills/analytics-dashboard/scripts/setup_analytics.py \ /path/to/your/project \ posthog \ YOUR_API_KEY ``` **Arguments**: - `project_dir`: Path to your project - `provider`: Analytics provider (posthog, mixpanel, amplitude, segment) - `api_key`: Your analytics API key --- ### 2. Initialize Analytics **Next.js** - Add to `app/layout.tsx`: ```typescript import { initAnalytics } from '@/lib/analytics' export default function RootLayout({ children }) { useEffect(() => { initAnalytics() }, []) return {children} } ``` **Python/Flask** - Add to app initialization: ```python from analytics import track_event, identify_user @app.before_request def track_page_view(): if current_user.is_authenticated: track_event(current_user.id, 'page_view', { 'path': request.path }) ``` --- ### 3. Track Events ```typescript import { trackEvent } from '@/lib/analytics' // Track button click // Track form submission const handleSubmit = (data) => { trackEvent('form_submitted', { form_name: 'contact', fields: Object.keys(data) }) } // Track conversion trackEvent('purchase_completed', { amount: 99.99, currency: 'USD', items: 3 }) ``` --- ### 4. Add Dashboard Copy the generated dashboard component: ```bash cp /home/ubuntu/skills/analytics-dashboard/templates/dashboard.tsx \ /path/to/your/project/components/ ``` Use in your app: ```typescript import AnalyticsDashboard from '@/components/AnalyticsDashboard' export default function AdminPage() { return } ``` --- ## Supported Providers ### PostHog (Recommended) - **Best for**: Startups, product analytics - **Features**: Session replay, feature flags, A/B testing - **Pricing**: Generous free tier - **Setup time**: 5 minutes ### Mixpanel - **Best for**: User behavior analysis - **Features**: Funnels, retention, cohorts - **Pricing**: Free up to 100k events/month - **Setup time**: 10 minutes ### Amplitude - **Best for**: Product-led growth - **Features**: Behavioral analytics, predictions - **Pricing**: Free up to 10M events/month - **Setup time**: 10 minutes ### Segment - **Best for**: Multiple analytics tools - **Features**: Single API for all providers - **Pricing**: Free up to 1k users/month - **Setup time**: 15 minutes --- ## Key Metrics to Track ### Engagement - Daily Active Users (DAU) - Weekly Active Users (WAU) - Monthly Active Users (MAU) - Session duration - Pages per session ### Conversion - Signup conversion rate - Trial-to-paid conversion - Purchase completion rate - Funnel drop-off points ### Retention - Day 1, 7, 30 retention - Churn rate - Cohort analysis ### Product - Feature adoption rate - User flows - A/B test results --- ## Event Tracking Patterns ### Page Views ```typescript useEffect(() => { trackEvent('page_view', { path: window.location.pathname, referrer: document.referrer }) }, [pathname]) ``` ### User Actions ```typescript trackEvent('button_clicked', { button_name: 'signup', location: 'homepage_hero' }) ``` ### User Identification ```typescript identifyUser(user.id, { email: user.email, plan: user.subscription_plan, signup_date: user.created_at }) ``` ### Conversions ```typescript trackEvent('purchase_completed', { amount: total, currency: 'USD', payment_method: 'stripe' }) ``` --- ## Dashboard Components The generated dashboard includes: 1. **Key Metrics Cards** - Total events - Unique users - Average session duration - Bounce rate 2. **Charts** - User growth (line chart) - Top events (bar chart) - Conversion funnel 3. **Tables** - Top pages by views - Top events by count - Recent user activity --- ## Best Practices ### Performance - ✅ Load analytics asynchronously - ✅ Batch events together - ✅ Debounce high-frequency events - ❌ Don't block page load ### Privacy - ✅ Get user consent (GDPR) - ✅ Provide opt-out mechanism - ✅ Anonymize sensitive data - ❌ Don't track PII without consent ### Data Quality - ✅ Include context with events - ✅ Use consistent naming - ✅ Test in development - ❌ Don't track too much --- ## Files Generated ### Scripts - `scripts/setup_analytics.py` - Automated setup script ### Templates - `templates/dashboard.tsx` - Analytics dashboard component ### References - `references/analytics_patterns.md` - Comprehensive guide (300+ lines) --- ## Workflow 1. **Setup** → Run script to install and configure 2. **Initialize** → Add analytics to app entry point 3. **Track** → Add event tracking throughout app 4. **Dashboard** → Add dashboard component for viewing 5. **Optimize** → Refine based on data --- ## Examples ### E-commerce Site ```typescript // Product viewed trackEvent('product_viewed', { product_id: product.id, category: product.category, price: product.price }) // Added to cart trackEvent('add_to_cart', { product_id: product.id, quantity: 1, cart_total: cart.total }) // Purchase completed trackEvent('purchase_completed', { order_id: order.id, total: order.total, items: order.items.length }) ``` ### SaaS Application ```typescript // Trial started trackEvent('trial_started', { plan: 'pro', trial_days: 14 }) // Feature used trackEvent('feature_used', { feature_name: 'export_data', usage_count: user.export_count }) // Subscription upgraded trackEvent('subscription_upgraded', { from_plan: 'basic', to_plan: 'pro', mrr_change: 20 }) ``` --- ## Troubleshooting ### Events not showing up - Check API key is correct - Verify analytics is initialized - Check browser console for errors - Test in production mode ### Dashboard not loading - Verify API endpoint exists - Check CORS settings - Ensure data is being tracked - Check network tab for errors ### Performance issues - Batch events together - Debounce high-frequency events - Load analytics asynchronously - Use sampling for high-volume --- ## Time Savings **Manual Setup**: 2-3 hours - Research providers: 30 min - Install dependencies: 15 min - Write configuration: 45 min - Create dashboard: 60 min - Test and debug: 30 min **With This Skill**: 15-20 minutes - Run setup script: 5 min - Configure API keys: 5 min - Add tracking: 5 min - Test: 5 min **Time Saved**: ~2 hours per project --- ## Related Skills - `deployment-automation` - Deploy with analytics configured - `user-authentication-system` - Identify users after login - `feature-flag-system` - Track feature flag usage - `error-monitoring-setup` - Combine with error tracking --- ## Resources - [PostHog Documentation](https://posthog.com/docs) - [Mixpanel Best Practices](https://mixpanel.com/blog) - [Amplitude Playbook](https://amplitude.com/blog) - [Analytics Patterns Reference](./references/analytics_patterns.md) --- *Built with best practices, privacy-conscious, performance-optimized.*