What is sql vs mql?
An MQL is a lead marketing scored as worth contacting; an SQL is one sales has accepted as worth selling to — the handoff between teams.
| Letter | Meaning | What it actually means |
|---|---|---|
| MQL | Marketing Qualified Lead | Behavioural + firmographic score above a threshold. |
| SQL | Sales Qualified Lead | An MQL that an SDR or AE has confirmed is worth pursuing. |
What is SQL vs MQL?
MQL and SQL mark two points on the journey from anonymous visitor to real opportunity. A Marketing Qualified Lead has shown enough interest — a demo request, a pricing page visit, a high-intent download — that marketing believes sales should look. A Sales Qualified Lead has been spoken to and passes an agreed bar: they fit the ideal customer profile, they have a problem worth solving, and there is a plausible path to a decision. The gap between the two is where most revenue teams quietly break. Marketing reports MQL volume, sales says the leads are unusable, and nobody has written down what qualified actually means. The fix is dull and effective: a single documented definition both teams sign, a service-level agreement on follow-up time, and a monthly review of MQL-to-SQL conversion. Healthy conversion sits somewhere between 15% and 30%; below that, the MQL bar is too low.
When to use SQL vs MQL
- Defining handoff criteria between marketing and sales
- Diagnosing why sales rejects marketing's leads
- Building a lead scoring model or routing rules
Real examples
- MQL trigger: requested a demo, or visited pricing three times in a week from a target-account domain.
- SQL bar: spoke to a human, matches ICP, named a problem, and a decision path exists.
- SLA: every MQL contacted within 30 minutes during business hours.
Common mistakes
- Two definitions — one in marketing's dashboard, one in sales' head.
- Scoring on content downloads, which measures curiosity rather than intent.
- No follow-up SLA, so genuinely hot leads cool before anyone calls.
- Judging marketing on MQL volume instead of on SQLs and pipeline created.
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This page is maintained by the LemCoach product team. Definitions are validated against how reps actually deploy SQL vs MQL inside our practice scenarios — the same framework powers our in-app coaching rubric, so changes here roll forward into how we score live calls.
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