Correlated subqueries power complex analytics when each row needs custom calculation: employees above their specific department average (not company average), products priced higher than their category median, customers spending more than their cohort average, sales reps exceeding their regional quota, students with GPA above their major average. They enable row-specific comparisons that simple aggregates cannot provide.

E-commerce: Customer Dashboard Performance Crisis

Marketing dashboard with 4 correlated subqueries per customer. 50K customers, 12 second query time.

E-commerce

-- Slow: 4 correlated subqueries, 12000ms

-- Fast: JOIN + GROUP BY, 850ms (14x faster)

Reduced query time 14x. Database CPU from 85% to 12%. Generated $2.3M revenue from VIP program.

PostgreSQL