What Is an MQL?
Definition
An MQL (marketing qualified lead) is a lead that marketing has scored as ready for a salesperson to contact, based on how well the company fits your ideal customer and how the person has behaved.
The score combines two separate things: fit, meaning who the company is, and behaviour, meaning what the person did. An MQL is a prediction that the pairing is worth a rep’s time, and only the rep can confirm it.
What Makes a Lead an MQL
Two inputs, and keeping them apart is what makes a model readable six months later.
- Fit is who they are: industry, headcount, revenue, country, job title. It comes from your data rather than anything they did, and it answers one question. Could this company ever buy from us?
- Behaviour is what they did: requested a demo, read pricing twice, replied to a sequence, returned three times in a week. It answers the other question. Are they thinking about it now?
Score them separately and the failure modes become obvious. High fit with no behaviour belongs in outbound, not a rep’s inbound queue. High behaviour with poor fit is usually a student, a competitor, or someone who will never have budget. Merge both into one number and those very different leads score the same, which is how a model that looks tuned produces a queue nobody trusts.
MQL vs SAL vs SQL vs PQL
The stage most teams are missing sits in the middle. In the demand waterfall that SiriusDecisions made popular, and which Forrester now publishes, a lead passes through acceptance before it is ever qualified.
| Stage | Who decides | What it means | Failure it exposes |
|---|---|---|---|
| Inquiry | Nobody | Someone gave you their details | Traffic without intent |
| MQL | Marketing | Scored as worth contacting | Scoring model is too loose |
| SAL | Sales | Accepted as worth a rep’s time | Teams disagree on what fit means |
| SQL | Sales | Vetted on a call, treated as an opportunity | Interest was shallow |
| PQL | Product usage | Hit a usage milestone in a trial | Activation, not marketing |
Add that acceptance step even informally. Leads rejected before anyone calls mean your scoring is wrong. Leads accepted then failing qualification mean your content attracts the right companies at the wrong moment. Without the stage, both look like one number.
MQL Scoring Model in Practice
Scoring ships as a feature in most lead generation tools, and the defaults they arrive with are almost never right for your business. Vague advice about scoring is easy to agree with and hard to use. Here is a starting model for a B2B software company selling to mid-market operations teams, with a threshold of 60.
| Signal | Type | Points |
|---|---|---|
| Headcount 50 to 500 | Fit | +20 |
| Target industry | Fit | +15 |
| Operations or revenue-ops title | Fit | +15 |
| Director level or above | Fit | +10 |
| Demo or pricing enquiry | Behaviour | +40 |
| Pricing page, twice in a week | Behaviour | +25 |
| Replied to an outbound sequence | Behaviour | +25 |
| Blog visit | Behaviour | +2 |
| Free-mail domain | Negative | -15 |
| Competitor domain | Negative | -40 |
| No activity in 90 days | Decay | -20 |
Run three realistic leads through it. An operations director at a 200-person target-industry company who asked for pricing scores 100 and should be called today. A junior analyst at the same company who read two blog posts scores 39 and stays in nurture. A perfect-fit VP who has done nothing scores 60 on fit alone, which is why fit-only leads should route to outbound rather than the inbound queue.
The exact numbers matter far less than the gaps between them. A demo request has to outweigh any amount of passive reading, or a determined blog reader eventually outranks a buyer. Decay matters too: without it, scores only ever rise and the queue fills with enthusiasm that expired a year ago.
How Fast To Follow Up on an MQL
This matters more than any refinement you will make to the weights.
Research by James Oldroyd with MIT and InsideSales, covering six companies, more than fifteen thousand leads and over a hundred thousand call attempts, found that contacting a web lead after thirty minutes rather than five cut the odds of making contact by roughly a hundred times and the odds of qualifying by around twenty-one times.
Two honest limits. It studied callbacks to web form fills, so it applies to inbound enquiries rather than cold outbound. And it is old enough that the exact numbers deserve some doubt, even though the direction has been repeated many times since.
You will also find published statistics claiming some large share of leads are never followed up at all. Treat those carefully, because many trace back to sources that cannot be verified. The number that matters is your own rate of leads nobody worked, which your CRM can tell you this afternoon.
MQL agreement to adapt and sign
- Definition. A lead becomes an MQL at 60 points or above, combining company fit and recorded behaviour, unless excluded by a negative rule.
- Marketing commits to. Routing within five minutes of the threshold being crossed, with the triggering behaviour visible on the record.
- Sales commits to. First contact attempt within five minutes in business hours, and a logged accept or reject within one working day.
- Rejection. Every rejected MQL carries a reason code. Fit rejections go back to marketing; timing rejections return to nurture with a date.
Why it works: every clause names an owner and a number, so disagreements become questions of fact rather than opinion.
Bottom Line
An MQL is a shared definition with a score attached, and its value lies entirely in whether marketing and sales agree on the sentence. Build fit from deals you actually won, rank behaviour by proximity to a purchase, score the two axes separately, and set the threshold to match how many leads your team can genuinely work.
Then move faster than you tune. The evidence on response speed is far stronger than anything another round of weight changes will buy you.
One last warning about the number itself. MQL volume is the wrong thing to chase: reward the count and the threshold quietly loosens until the queue is full and useless. Reward the pipeline that survives sales acceptance instead.
FAQs
1- What does MQL stand for?
Marketing qualified lead. It marks a lead that marketing has scored as ready for sales contact, combining how well the company fits your ideal customer with how the person has engaged.
2- What is the difference between an MQL and an SQL?
Marketing decides the first, sales decides the second. An MQL is a prediction that someone is worth contacting; a sales qualified lead has been vetted in a real conversation and judged a genuine opportunity.
3- What is a good MQL to SQL conversion rate?
There is no portable answer, because every company draws the stage boundaries differently. Compare against your own previous quarters and watch the direction rather than chasing a published figure.
4- What score should make someone an MQL?
Whatever score produces the number of leads your reps can actually work each week. Capacity sets the threshold; the points are just a way of ranking who gets in.
5- How quickly should an MQL be contacted?
Minutes rather than hours for inbound enquiries. Research on web leads found the odds of qualifying fell sharply between a five minute and a thirty minute response, and no amount of scoring accuracy makes up for a slow reply.
6- What is the difference between an MQL and a PQL?
A product qualified lead earns its status through usage, by hitting a meaningful milestone in a free trial or free tier. An MQL earns it through fit and marketing engagement, before any product use.