MQL
Also: MQL, Marketing Qualified Lead, Marketing-Qualified Lead, Lead qualifie par le marketing, Prospect qualifie marketing
Marketing Qualified Lead: a prospect deemed ready to be handed off to sales, based on pre-agreed qualification criteria.
What it is
An MQL (Marketing Qualified Lead) is a prospect that marketing has judged ready to be passed to sales, based on qualification criteria agreed in advance between the two teams. It sits between a raw lead (any contact who entered the funnel) and an SQL (Sales Qualified Lead) that sales has accepted and is actively working.
The MQL is a shared definition, not a marketing opinion. It typically combines:
- Fit: does the contact match the ideal customer profile (industry, company size, role, geography)?
- Engagement / intent: behavioral signals such as pricing page visits, demo requests, content downloads, or repeat sessions.
- Data quality: enough valid contact information to act on the lead.
Why it matters
The MQL exists to protect two scarce resources: sales time and marketing credibility. Without a clear threshold, sales gets flooded with low-value contacts and starts ignoring marketing entirely.
- For marketing, MQL volume and MQL-to-SQL conversion measure lead quality, not just quantity.
- For sales, a consistent MQL definition means every handoff is worth a call.
- For finance and leadership, MQLs anchor pipeline forecasting and cost-per-lead economics.
How it is used in practice
1. Define the criteria jointly (marketing plus sales) and write them into a Service Level Agreement.
2. Score leads, often via a points model (fit points plus behavior points) or explicit rules.
3. Trigger handoff when the threshold is crossed: the lead is routed to sales in the CRM.
4. Track downstream: what share of MQLs become SQLs, opportunities, and closed deals.
5. Recalibrate the threshold periodically as data accumulates.
A warning: a high MQL count is a vanity metric if those leads never convert. Always read MQL volume alongside conversion rates.
Worked example
A B2B software vendor uses a 100 point model. Fit: correct industry (+20), 200+ employees (+15), VP or C-level title (+15). Behavior: pricing page view (+20), demo request (+30), webinar attendance (+10).
- A junior analyst downloads one ebook: 10 points, stays a lead.
- A VP of Operations at a 500 person firm views pricing and requests a demo: 20 + 15 + 15 + 20 + 30 = 100 points, becomes an MQL and is routed to an account executive.
Over a quarter, 1,000 MQLs yield 250 SQLs (25 percent) and 40 closed deals. That conversion chain, not the raw 1,000, tells the real story.
See also
Frequently asked questions
What is an MQL?
An MQL (Marketing Qualified Lead) is a prospect that marketing has judged ready to hand off to sales, based on qualification criteria agreed in advance by both teams. It sits between a raw lead, meaning any contact who entered the funnel, and an SQL (Sales Qualified Lead) that sales has accepted and is actively working. The criteria usually combine fit with the ideal customer profile, engagement signals, and enough valid contact data to act on.
What is the difference between a lead, an MQL and an SQL?
A lead is any contact who entered the funnel, an MQL is a lead that crossed the qualification threshold agreed between marketing and sales, and an SQL is an MQL that sales has accepted and is actively working. The distinction matters because it locates responsibility: marketing owns the volume and quality of MQLs, sales owns what happens after acceptance. MQL-to-SQL conversion is the metric that reveals whether the threshold is set correctly.
Who needs to care about MQL definitions beyond the marketing team?
Sales and finance both do. Sales relies on a consistent MQL definition so that every handoff is worth a call, and finance uses MQL volume together with downstream conversion to anchor pipeline forecasting and cost-per-lead economics. That is why the MQL threshold should be a shared definition written into a service level agreement between marketing and sales, not a marketing opinion.
How do you build an MQL scoring model?
Most teams use a points model that adds fit points and behavior points, then set a handoff threshold. A typical B2B software example on a 100 point scale: correct industry +20, 200 or more employees +15, VP or C-level title +15, pricing page view +20, demo request +30, webinar attendance +10. A junior analyst downloading one ebook lands at 10 points and stays a lead, while a VP of Operations at a 500 person firm who views pricing and requests a demo reaches 100 and becomes an MQL routed to an account executive.
Why is MQL volume considered a vanity metric?
Because a high MQL count means nothing if those leads never convert. MQL volume should always be read alongside the conversion chain: 1,000 MQLs producing 250 SQLs (25 percent) and 40 closed deals tells the real story, not the raw 1,000. If conversion drops as volume rises, the qualification threshold is too low and needs recalibrating.