What Is the Difference Between MQL and SQL?
Tom Regan
Founder & GTM Strategist, Artemis GTM
Former Apollo.io SDR Leader (152% of quota) | Scaled ARR from $800K to $50M
Last updated: 2026-04-12
An MQL (Marketing Qualified Lead) has shown engagement interest — content downloads, webinar attendance, return website visits. An SQL (Sales Qualified Lead) has been verified by sales as having budget, authority, need, and timeline to buy. The handoff between them is where 23% of B2B pipeline leaks.
23% of B2B pipeline is lost at the MQL-to-SQL handoff. Only 32% of companies have a shared definition of what qualifies a lead. The average MQL sits for 14 days before being actioned by sales, according to Artemis GTM's 2026 Benchmark Study of 127 SaaS companies. (Artemis GTM 2026 Benchmark Study (n=127))
The Full Picture
An MQL is scored by marketing based on two dimensions: fit (does the person match your ICP?) and intent (have they taken actions that suggest buying interest?). Typical MQL triggers include downloading a whitepaper, attending a webinar, visiting the pricing page multiple times, or requesting a demo. An SQL has passed an additional sales validation step. A sales rep has confirmed the prospect has a real problem, budget to solve it, authority to make a decision, and a timeline to act. This validation usually happens via a discovery call. The gap between MQL and SQL is the highest-friction handoff in B2B. When marketing and sales use different definitions of "qualified," leads fall into a black hole between the two stages.
The Data
| Metric | Value |
|---|---|
| Pipeline lost at MQL-to-SQL handoff | 23% |
| Companies with a shared MQL/SQL definition | 32% |
| Average time lead sits in MQL before action | 14 days |
| Average sales acceptance rate of MQLs | 44% |