Product / metrics
Product analytics translates usage events, funnels, activation, retention, churn, feature adoption, and cohorts into product decisions.
What this system does
Defines events and metrics around signup, activation, engagement, retention, churn, and feature adoption.
Uses funnels, cohorts, retention curves, A/B testing, and KPI dashboards to support product decisions.
Turns product usage evidence into roadmap input, stakeholder updates, and business tradeoff discussions.
How I use it
Portfolio SQL demo includes signup-to-paid conversion, churn rate, NPS, CSAT, event joins, and first-purchase logic.
Dashboard pages present executive-facing views for support, revenue/product mix, and KPI review.
Ghost-AI and Chorus are product concepts where event capture would support activation, collaboration, and learning progress analysis.
Related projects
Evidence or examples
Portfolio analytics SQL creates signups, subscriptions, events, purchases, and survey tables for KPI practice.
The SQL demo calculates signup-to-paid conversion, churn rate, event counts, first purchase ordering, NPS, and CSAT.
Existing dashboard assets support recruiter-readable KPI storytelling.
SELECT
COUNT(DISTINCT CASE WHEN event = 'signup' THEN user_id END) AS signups,
COUNT(DISTINCT CASE WHEN event = 'paid' THEN user_id END) AS paid_users,
ROUND(COUNT(DISTINCT CASE WHEN event = 'paid' THEN user_id END) * 1.0 /
NULLIF(COUNT(DISTINCT CASE WHEN event = 'signup' THEN user_id END), 0), 2) AS conversion_rate
FROM events;cohort_month + active_month + retained_users + cohort_size -> retention_rate by product segment.feature_used / eligible_users by account type, onboarding stage, and time since signup.