Interviewers who hire for B2B SaaS rarely want you to recite GROUP BY . They put a subscriptions , events or invoices table in front of you and ask for retention, ranked plans or day-over-day active users. Window functions are the difference between a brittle subquery nest and a readable answer that looks like production analytics SQL.

I run Loop Origin , a software company that builds custom web applications for product teams. I wrote this with help from AI tools and checked every command and claim myself. The examples below use PostgreSQL shapes I see in real multi-tenant apps: tenant_id , subscription periods and product analytics events.

Which SQL window functions should you know for SaaS metrics interviews?

Direct answer: Master ROW_NUMBER , RANK / DENSE_RANK , LAG / LEAD , running aggregates with SUM() OVER , and partitioned frames for per-tenant or per-cohort metrics.…