The three stages in order
| Stage | Full name | Who decides | The decision |
|---|---|---|---|
| MQL | Marketing Qualified Lead | Marketing | Fit and behavior clear the scoring threshold |
| SAL | Sales Accepted Lead | Sales | The record is worth a rep's time, accepted at intake |
| SQL | Sales Qualified Lead | Sales | Contact made, qualification passed, worth an opportunity |
Why SAL is the stage teams skip
Most funnels jump from MQL straight to SQL, and the acceptance step disappears into an implicit assumption that sales works whatever marketing sends. That assumption fails quietly.
When MQL-to-SQL conversion drops, the two teams argue. Marketing says the leads were fine and sales did not follow up. Sales says the leads were unqualified. Neither claim is checkable without a SAL step, because the data does not separate leads that were rejected on sight from leads that were called and failed qualification.
Adding SAL splits one ambiguous number into two clear ones. A low MQL-to-SAL rate is a criteria problem, because sales is refusing the records marketing considers ready. A healthy MQL-to-SAL rate with a low SAL-to-SQL rate is an execution or fit-depth problem, because sales accepted the leads and could not advance them.
Write the definitions down
Each stage needs criteria specific enough that two people scoring the same record reach the same answer. Vague definitions produce drift, and drift is invisible until conversion rates move.
- MQL criteria. The scoring threshold plus any hard fit gates such as company size or excluded industries. - SAL criteria. The rejection reasons a rep is allowed to use, and the window they have to use them before acceptance is automatic. - SQL criteria. The qualification framework and the specific evidence required, such as a confirmed problem, a named decision path, and a timeline.
What the stage counts feed
These three numbers set the top of the funnel that everything downstream inherits. SQL volume drives opportunity creation, and opportunity creation drives pipeline coverage for the quarter after this one, which is the input most revenue forecasts lean on hardest. A stage definition that loosens by a few percent this month shows up as a coverage gap two quarters later, long after anyone connects the two. Reviewing the three counts together each month, rather than reviewing MQL volume alone, catches the drift while it is still cheap to correct.
Frequently Asked Questions
What is the difference between an MQL and a SAL?
An MQL is marketing's judgment that a lead is ready for sales contact, usually based on fit attributes plus behavior. A SAL is sales agreeing with that judgment. The gap between the two counts is the clearest measure of whether the two teams share a definition of qualified, because it isolates rejection at intake from failure after outreach.
What is the difference between a SAL and an SQL?
A SAL has been accepted but not yet worked. An SQL has been worked and confirmed, meaning the rep made contact, ran qualification, and validated that there is a real need, a plausible budget, and a path to a decision. SAL is an intake decision made on the record. SQL is a decision made after talking to a human.
Do you need all three stages?
You need SAL if you want to diagnose the handoff. Without it, a falling MQL-to-SQL rate has two possible causes and no way to tell them apart: sales rejected the leads on sight, or sales worked them and they failed qualification. Those problems have different fixes, so collapsing the stages hides the one piece of information the metric was supposed to give you.
Who owns each stage?
Marketing owns MQL definition and volume. Sales owns the SAL acceptance decision and the SQL qualification decision. The definitions themselves belong to both teams jointly and should be written down, because a stage definition that only one team agreed to gets ignored the first time volume gets tight.
Put these metrics to work
ORM builds custom revenue forecast models that turn concepts like mql vs sal vs sql into prescriptive action for your team.
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