The concept exists to solve a real problem: sales can't work every inbound contact, so someone has to filter. Where it goes wrong is when MQL count becomes marketing's primary reported metric, because the definition is set by marketing and the consequences land on sales.
The structural issue is that MQL criteria usually measure engagement, not intent. Downloading a whitepaper, attending a webinar, and visiting a pricing page score similarly in many models, and only one of them indicates someone might buy.
The symptom is universally recognisable: marketing reports growing MQL volume while sales says the leads are worthless. Both are usually telling the truth. The leads meet the definition and the definition doesn't predict revenue.
Formula
MQL → SQL conversion rate = Sales Accepted Leads ÷ MQLs
If this sits below roughly 20%, the MQL definition is measuring the wrong thing. Fix the definition instead of generating more volume.
Why MQL matters
MQL volume is one of the few marketing metrics that can grow while the business gets worse. Optimizing acquisition toward it produces more people who behave like leads and fewer who behave like buyers, and it's a common reason ad platforms are trained on the wrong signal.
What to report instead
Qualified pipeline created, opportunity conversion rate by source, and closed-won revenue with the acquisition channel attached. For account-based motions, target account engagement depth is more predictive than any lead count. One industrial client stopped reporting MQLs entirely and closed $8.4M over sixteen months from 120 named accounts.
Benchmarks
- Healthy MQL → SQL conversion
- above 25%
- Definition likely broken below
- 20%
Ranges drawn from Digital Squad client accounts and published industry data. Treat them as orientation, not targets. Your category may differ substantially.
Common mistakes
Marketing defining MQL criteria alone
The definition should be agreed with sales and revisited quarterly against actual close data. Otherwise it drifts toward whatever is easiest to generate.
Scoring engagement instead of intent
Content downloads indicate curiosity. Pricing page visits, comparison page visits and demo requests indicate evaluation. Weighting them equally is why lead quality complaints persist.
Feeding MQLs to ad platforms as the conversion event
Platforms optimize toward whatever you send them. Send MQLs and you get more people who trigger MQL criteria, which isn't the same as more customers.
Keeping the metric because it's historical
If sales ignores your leads, MQL count is measuring something that doesn't matter. Changing it's uncomfortable because someone's target disappears, and it's usually correct.
Where we work on this