MQL vs. SQL (MQL / SQL) (MQL / SQL)
MQL (Marketing Qualified Lead) is a lead that marketing has determined meets defined criteria for sales readiness, while SQL (Sales Qualified Lead) is a lead that sales has confirmed through…
MQL (Marketing Qualified Lead) is a lead that marketing has determined meets defined criteria for sales readiness, while SQL (Sales Qualified Lead) is a lead that sales has confirmed through direct interaction as a viable opportunity worth pursuing.
What Are MQL and SQL?
MQL and SQL are two stages in the lead qualification process used by B2B revenue teams.
MQL (Marketing Qualified Lead): a contact that marketing has assessed as meeting a defined threshold of fit and engagement. The MQL designation means marketing believes this lead is worth sales' time — they've demonstrated interest and match the target customer profile. MQLs are passed from marketing to sales for follow-up.
SQL (Sales Qualified Lead): a contact that a sales representative has directly assessed — typically through a discovery call or meeting — and confirmed meets the criteria to enter the active sales pipeline as a viable opportunity. SQLs have confirmed budget access, decision-making authority, a genuine need, and a timeline.
Why the MQL-to-SQL Distinction Matters
The handoff between MQL and SQL is the most contested boundary in B2B revenue operations. When it's well-defined and consistently applied, marketing and sales work from shared data. When it's ambiguous, you get:
A clear, agreed-upon MQL definition — what specific behaviors and fit criteria qualify a lead — and a clear SQL definition — what specific outcomes from sales interaction confirm viability — resolves this operationally rather than through ongoing debate.
How MQL and SQL Are Defined in Practice
MQL definition components:
SQL definition components (BANT or equivalent):
The definitions should be documented in the CRM as configured logic, not only in a shared document.
| MQL | SQL | SAL | PQL | |
|---|---|---|---|---|
| Qualified by | Marketing (automated + human) | Sales (direct interaction) | Sales (acceptance) | Product usage data |
| Method | Scoring + fit criteria | Discovery call / meeting | Acknowledgment | In-product behavior |
| Used in | All B2B models | All B2B models | Complex sales orgs | PLG companies |
| CRM stage | Lifecycle Stage | Lifecycle Stage | Custom stage | Custom stage |
MQL and SQL at Dbugger
Dbugger implements HubSpot lead qualification workflows for enterprise revenue teams — including lead scoring models, MQL automation, MQL-to-SQL handoff workflows, disqualification reason tracking, and the feedback loop reporting that improves MQL definition over time.
Related terms: CRM Pipeline · Lifecycle Stage · Lead Scoring · HubSpot · BANT · RevOps
Frequently asked questions
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