What is MQL?
A lead that meets criteria suggesting they're worth sales follow-up, eventually.
MQL stands for marketing qualified lead, a person who has shown enough interest through their behaviour, such as downloading a guide or attending a webinar, that marketing judges them worth passing to sales for follow-up. It sits between an anonymous website visitor and a sales qualified lead who a salesperson has actively vetted.
Why MQL matters
Not every lead deserves a salesperson's time, and not every sales team trusts every lead marketing sends over. Defining what counts as an MQL creates a shared, agreed bar so sales spends time on people genuinely more likely to buy rather than chasing every form fill. Without this agreement, sales often ignores marketing leads entirely, assuming they are low quality, which wastes the effort marketing put into generating them in the first place.
Getting the MQL definition right also shapes what marketing optimises for. If the bar is too low, sales drowns in leads that go nowhere and stops trusting marketing's output. If it is too high, genuinely promising prospects get missed because they have not ticked every box yet. A well-calibrated definition, reviewed against actual sales outcomes, keeps both teams pulling in the same direction.
How MQL works in practice
- 01Agree the MQL definition jointly with sales, based on actions that have historically led to closed deals.
- 02Score behaviours such as pricing page visits, content downloads, and email engagement rather than relying on one signal alone.
- 03Set a threshold score that triggers the MQL status and route it automatically into the sales team's workflow.
- 04Review closed-won and closed-lost deals quarterly to check the scoring criteria still predicts real buying intent.
- 05Give sales a fast, simple way to flag MQLs that turn out to be poor quality, then adjust the model.
Common mistakes
- ·Setting the bar so low that sales receives leads with no real buying intent and stops trusting the label.
- ·Never revisiting the definition after it is set, even as the product, market, or buyer behaviour changes.
- ·Scoring based only on demographic fit, such as company size, and ignoring actual engagement behaviour.
- ·Letting marketing and sales use different definitions of MQL, which causes disputes over lead quality.
How to measure MQL
Track MQL to sales qualified lead conversion rate and MQL to closed-won rate, since these show whether the definition is actually predictive. A healthy pipeline usually sees a meaningful share of MQLs accepted by sales rather than rejected outright, and a visible improvement in win rate for leads that passed through the MQL stage. Reviewing these rates monthly with sales keeps the definition honest rather than theoretical.
What good looks like
A good MQL definition is specific, based on real behavioural data rather than guesswork, and agreed jointly by marketing and sales so nobody disputes it after the fact. It gets reviewed regularly against actual deal outcomes and adjusted when it stops predicting well. MarketJargon agents can build and refine lead scoring models as part of an ongoing marketing operation.
The agent that runs MQL
MQL questions, answered
What is the difference between an MQL and an SQL?
An MQL has shown interest through behaviour marketing tracks, such as content downloads. An SQL, or sales qualified lead, has been reviewed and accepted by a salesperson as genuinely worth pursuing, usually after a conversation confirming budget and need.
How many points should trigger MQL status?
There is no universal number, since it depends entirely on your scoring model and sales cycle. The right threshold is whichever one, tested against actual closed deals, correlates most closely with leads that go on to buy.
Should every MQL get a phone call?
Not necessarily. Some businesses route higher-scoring MQLs to a call and lower-scoring ones into nurture email sequences. The right approach depends on sales capacity and average deal value.
Why do sales teams sometimes distrust MQLs?
Usually because the definition was set without their input and does not match what actually converts in their experience. Involving sales in setting and reviewing the definition largely resolves this.
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