Sales-qualified lead (SQL)

A sales-qualified lead (SQL) is a contact that a salesperson, not marketing, has personally checked and accepted as a real buyer: the right kind of company and role, a clear need, budget, and a reason to buy soon. It sits after the marketing-qualified lead (MQL) stage and before a formal opportunity with a deal value attached.

What counts as an SQL

Definitions vary, so write yours down. In one version, an SQL is an MQL who has indicated that the product is desirable, within their budget, and is speaking with a salesperson. Another puts the decision with sales: a contact that sales has independently reviewed, confirmed matches your Ideal Customer Profile. That same guide uses BANT: Budget, Authority, Need, and Timeline as the check.

How to measure it

MQL to SQL rate = SQLs from a cohort of marketing-qualified leads (MQLs) / MQLs in that cohort x 100.

Match the cohorts in time. If your MQL-to-SQL cycle runs three months, compare month-three SQLs against month-one MQLs. For business-to-business software as a service (B2B SaaS), the most defensible published average is 13%.

Worked example

Chain the stages before you set a target. 100 MQLs at a 13% MQL to SQL rate produce 13 SQLs, roughly 5 to 6 opportunities, and one to two closed deals. Run your own rates backward from a revenue goal in the reverse funnel calculator.

Common mistakes

• Blending channels. Search engine optimization (SEO) and pay-per-click (PPC) leads differ: SEO-sourced MQLs converting to SQL at 51% against PPC at 26% in the same data. When paid volume grows faster than organic, every channel individually improved can still show up as a falling total.
• Treating activity as a stage change. If a rep moves a contact to SQL every time they send an email, your funnel reports will show inflated pipeline numbers.
• Passing contacts with no buying date. Contacts without a timeline belong in MQL, not SQL.

When it matters

The SQL stage is where marketing's count turns into sales capacity, so it drives coverage math in the pipeline coverage calculator. To test your definition, check SQL to opportunity conversion after your SQL definition has been live for 60 to 90 days. For calibration, B2B SaaS SQL to opportunity conversion runs 38% to 49% by channel. Compare against funnel conversion benchmarks.