How an MQL actually works
An MQL is the point where marketing decides a lead is warm enough to pass to sales. Most teams reach it with lead scoring: points for fit, meaning the lead matches the target company size, industry, and role, and points for behaviour, meaning they downloaded a buying-stage asset, visited pricing, or requested a demo. Cross a threshold and the lead becomes an MQL. The mechanism is simple; the discipline is in the threshold, because the label is only useful if it reliably predicts that sales time spent on the lead is time well spent.
Why the MQL definition governs your ad spend
In paid acquisition the MQL is often the conversion you optimise toward, which means its definition silently steers your budget. Set the bar too low and you generate cheap MQLs that never convert, and the bidding model, rewarded for volume, doubles down on the audiences producing junk. Set it too high and you starve sales of pipeline. iClick treats the MQL definition as a shared agreement between marketing and sales, revisited with real close-rate data, because optimising ads to a badly defined MQL is optimising toward the wrong outcome with real money.
MQL vs SQL vs PQL
These three mark different points in the funnel. An MQL is marketing's judgement that a lead is ready for sales contact. An SQL is sales accepting that judgement and confirming the lead is a real opportunity. A PQL, a product qualified lead, has actually used the product, often via a free trial, and shown value from it. The three are not interchangeable: a business running product-led growth may lean on PQLs and barely use MQLs, while a traditional sales-led motion runs MQL to SQL as its spine.
Feeding MQL quality back into the ads
The advanced practice is to stop optimising to raw MQLs and start optimising to the MQLs that become opportunities. By importing which MQLs progressed to SQL and closed revenue back into the ad platform as offline conversions, you let bidding chase quality, not just quantity. iClick treats a B2B account without this loop as optimising blind, because until the CRM tells the ad platform which MQLs were real, the algorithm cannot tell a valuable lead from a form-fill and will happily buy more of the wrong one.
