The Difference in One Line
An MQL is a marketing judgment about interest. An SQL is a sales judgment about readiness to buy. The label changes when a lead crosses from "worth nurturing" to "worth a rep's time." Get the boundary wrong and one of two things happens: sales drowns in leads that will never close, or marketing starves the pipeline by holding leads too long. Both wreck pipeline coverage planning.MQL vs SQL: Side by Side
| MQL | SQL | |
|---|---|---|
| Owned by | Marketing | Sales (accepted) |
| Judged on | Engagement and behavior | Fit, intent, and buying readiness |
| Typical trigger | Content downloads, demo-page visits, email engagement, lead score threshold | Discovery call confirms need, authority, and timeline |
| Question it answers | "Is this contact interested?" | "Is this a real opportunity?" |
| Next step | Nurture or route to sales | Enter the active pipeline |
Where the Handoff Breaks
The MQL-to-SQL transition is the single most contested line in the revenue funnel. Marketing is measured on MQL volume, so the incentive is to pass more. Sales is measured on closed revenue, so the incentive is to reject anything that is not obviously ready. Without a shared definition, the two teams argue about lead quality instead of fixing it.
The leak is measurable. Track the MQL-to-SQL conversion rate by source, by segment, and by rep. A source that produces high MQL volume but low SQL conversion is generating activity, not opportunity. That is a budget reallocation signal, not a sales-effort problem.
How to Define the Threshold
The threshold that works blends two dimensions, not one:
- Fit. Does the contact match your ideal customer profile on company size, industry, and role? A perfect-fit account with light engagement often outperforms a heavy-engagement contact at the wrong company. - Intent. Has the contact shown recent buying behavior, not just content curiosity? Pricing-page visits, repeat demo requests, and multiple engaged stakeholders signal intent.
Write the definition down, agree it across both teams, and enforce it in the lead scoring model. Then set a service-level agreement: how many MQLs marketing commits to deliver, and how fast sales commits to work them. The definition plus the SLA is what turns a recurring argument into a measurable, improvable process. For the broader system this sits inside, see the revenue operations guide.
Frequently Asked Questions
What is the difference between an MQL and an SQL?
An MQL has engaged enough to justify marketing follow-up, judged on behavior like content downloads, demo-page visits, and email engagement. An SQL has been reviewed against fit and intent criteria and accepted by sales as a real opportunity. MQL is a marketing judgment about interest; SQL is a sales judgment about readiness to buy.
Who owns the MQL to SQL handoff?
Both teams own it together, which is why it breaks. The durable fix is a written, mutually agreed definition of what qualifies as an SQL and a service-level agreement on how fast sales works an MQL. RevOps owns the system that enforces both.
Why do MQLs fail to convert to SQLs?
Usually because the MQL bar measures activity, not fit. A contact who downloads three ebooks looks engaged but may never have buying authority or budget. Scoring that blends fit (right company, right role) with intent (recent buying behavior) converts far better than activity alone.
Put these metrics to work
ORM builds custom revenue forecast models that turn concepts like mql vs sql into prescriptive action for your team.
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