Definition
An SQL is a lead that sales has validated as qualified for a sales conversation (budget/need/timing or product fit).
Example
A lead confirms budget and timeline on a discovery call and meets ICP criteria.
How to use it
- Track MQL->SQL and SQL->Closed rates to find funnel bottlenecks.
- Segment by channel to identify high-quality sources.
- Document SQL criteria so marketing and sales use the same gate.
- Review SQL rate alongside response time and follow-up quality.
Common mistakes
- Labeling a lead as SQL without a real qualification step.
- Letting SQL definitions drift by rep or region.
- Treating all SQLs as equal quality without scoring.
Why this matters
This term matters because small changes compound in SaaS metrics. Use consistent definitions by cohort and segment so you can diagnose retention, payback, and growth quality.
Practical checklist
- Write a 1-line definition for "SQL (Sales-Qualified Lead)" that your team will use consistently.
- Keep the time window consistent (weekly/monthly/quarterly) when comparing trends.
- Segment results (channel/plan/cohort) before drawing big conclusions from blended averages.
- Use a calculator that references this term (e.g., Sales Funnel Targets Calculator) to sanity-check assumptions.
- Read the related guide (e.g., Sales funnel targets: leads -> MQL -> SQL -> opp -> win (how to plan)) for context and common pitfalls.
Where to use this on MetricKit
Calculators
- Sales Funnel Targets Calculator: Translate a revenue target into required wins, opportunities, SQLs, MQLs, and leads using funnel conversion rates.
Guides
- Sales funnel targets: leads -> MQL -> SQL -> opp -> win (how to plan): A practical guide to back-solving funnel volume targets from a revenue goal using conversion rates and average deal size.
- Sales ops metrics hub: quota, pipeline, win rate, and capacity planning: A practical hub for sales ops planning: quota attainment, pipeline coverage, required pipeline, sales capacity with ramp, and OTE math.