MQL vs SQL: the line marketing and sales never agree on
MQL and SQL are two stages of the same lead, but the line between them is where marketing and sales argue most. We explain how to define it well.
Few acronyms generate as much friction between marketing and sales as MQL and SQL. Not because they are complex, but because the line between them is almost never well defined, and that is where conflicts about lead quality are born.
What each one is
An MQL (Marketing Qualified Lead) is a lead that, by marketing criteria, shows enough interest and fit to pass to sales. An SQL (Sales Qualified Lead) is a lead that sales has validated as a real opportunity worth active follow-up. The difference is who validates and by what criteria.
Where the conflict is
The problem appears when marketing passes MQLs that sales rejects as not ready. If there is no joint definition of what makes an MQL acceptable as an SQL, each team uses its own yardstick and the argument is endless. The solution is not more leads: it is a clear agreement on criteria.
- Objective criteria shared by both teams
- Fit (ICP) and minimum signals to pass to sales
- An SLA: sales commits to follow up every SQL
- Sales feedback that adjusts the MQL definition
The loop that fixes it
The line is sharpened with data: sales returns to marketing which MQLs became SQLs and which did not, and marketing adjusts its criteria. Without that loop, marketing optimizes for MQL volume and sales complains. With it, both teams look at the same goal: opportunities that close.
Where lead buying fits
Buying qualified leads with agreed objective criteria reduces MQL/SQL friction, because the lead arrives already filtered by fit and intent. The conversation about what a good lead is happens before buying, which forces both teams to align from the start.