MQL

MQL became a standard term in the mid-2000s when SiriusDecisions (now part of Forrester) published its Demand Waterfall model. Before that, marketing handed every lead to sales, and sales spent most of its time complaining that 80% weren't worth a call. MQL drew the line — only leads passing both a fit test (close to your ICP) and an intent test (real engagement) get handed over.

The most common way to operationalise MQL is lead scoring. Marketing assigns fit points (company size, role, industry) and intent points (pricing-page visits, content downloads, email clicks), and a lead becomes an MQL when the total clears a threshold like 70. Some companies make a single demo request the entire definition; others require five pricing-page visits plus a whitepaper plus an ICP match. There is no universally right answer — there is only the definition that sales and marketing have agreed on.

The classic way MQL goes wrong is making it the only marketing KPI. Hit a quarterly MQL target of 1,000 by quietly nudging the threshold down, and sales is back to complaining that the leads aren't usable. The fix is to pair MQL volume with MQL-to-SQL conversion rate as a joint KPI. Healthy B2B SaaS typically shows 13-20% MQL-to-SQL conversion. Anything under 5% means the definition is too loose; anything above 40% probably means the bar is set so high that real opportunities are leaking past.

AI search is reshaping MQL behaviour in two ways. Buyers do more comparison and shortlist work inside ChatGPT before ever touching a vendor's site, so leads now arrive far later in their decision cycle and often request a demo on the first visit. Intent signals are shorter and stronger, which means many teams are loosening their MQL threshold while tightening response time on the front end. In Korea, AI-driven inbound is also showing up as a 'recommended by AI' source — and a growing number of teams are wiring 'AI referral' as a distinct lead source in their marketing automation stack.

One persistent misconception is treating MQL as marketing's final KPI. MQL is an intermediate metric. The real KPI is the rate at which MQLs become SQLs, opportunities and closed-won revenue. Teams where marketing reports only on MQLs while sales reports only on revenue end up with both functions hitting their numbers while the company misses on overall efficiency. Mature go-to-market teams co-own the MQL → SQL → Opportunity → Closed-Won conversion chain, and revisit the definitions together every quarter.