The key word is both. Fit without intent is a tyre-kicker. Intent without fit is someone who will never buy. An MQL needs the two together and the bar you set decides whether sales trusts your leads or ignores them.
There is no universal formula. The point is to write the definition down, agree it with sales and hold the line, see SQL for the next stage.
There is no magic number but a useful sanity check is the MQL to SQL acceptance rate. If sales accepts well under half your MQLs, the bar is too loose and you are passing noise.
Acceptance rates vary a lot by motion and ACV. The trend that matters is your own over time, on a definition both teams agreed, not a benchmark borrowed from a company at a different stage.
Score them on two axes so a high-intent bad-fit lead never sneaks through as an MQL.
An MQL definition marketing sets alone is one sales will ignore. Write it together.
Track how many MQLs sales accepts. A falling rate means the definition drifted.
An ebook download is not intent. Tie MQL status to actions that actually predict a buy.
A lead that fits your ideal customer profile and has shown enough buying intent that marketing decides it is worth passing to sales.
An MQL is marketing's judgment that a lead is worth sales time. An SQL is sales accepting that judgment after its own review.
On two axes, fit (does it match your ICP) and intent (has it taken actions that predict a purchase). A lead needs both.
Because they count low-intent actions like content downloads. That floods sales with leads that never buy and erodes trust in marketing.
The 30-minute audit includes whether your MQL definition is passing pipeline or noise. No sales sequence.
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