The Death of MQLs and What Replaces Them

Marketing-qualified leads were a useful construct for a different era. They gave marketing teams a clean handoff metric and gave sales teams something to accept or reject. The whole system created a tidy workflow on paper.

In practice, it created a perverse incentive: marketing optimized for volume of form fills, and sales complained about quality. Both sides had data to support their position. Neither side was focused on what actually mattered, which is whether a real buying group at a real company was actively considering a purchase.

I've managed pipeline engines that generated $280M+ in attributable revenue across global markets. The shift away from MQL-centric thinking was one of the highest-impact changes I made at every company.

Three structural changes have made MQLs increasingly unreliable as a primary metric.

Buying is a group activity, not an individual one. Enterprise B2B purchases involve 6 to 10 decision-makers on average. A single person downloading a whitepaper tells you almost nothing about whether their organization is ready to buy. MQLs count individuals. Buying happens in groups.

Signal quality has surpassed form-fill data. Intent data, product usage signals, engagement patterns, and account-level behavior provide a richer picture of buying readiness than whether someone filled out a gated form.

Self-service and PLG motions have changed the funnel shape. In product-led environments, prospects are often deep into evaluation before they ever talk to sales. The traditional MQL sits at the wrong point in that journey.

The companies I've seen get this right have moved to a signal-based model that evaluates buying readiness at the account level rather than scoring individual leads.

From lead scoring to account engagement scoring. Instead of "did this person hit a point threshold," the question becomes "is this account showing a cluster of behaviors that indicate active evaluation?"

From marketing-qualified to sales-ready opportunities. The handoff point moves from "this person filled out a form" to "this account is showing buying signals that match our ideal customer profile and engagement threshold."

From volume metrics to pipeline quality metrics. Instead of tracking MQL volume, track opportunity creation rate, pipeline velocity, and conversion rates at each stage.

This isn't a "flip the switch" change. It requires alignment between marketing, sales, and revenue operations on what constitutes a buying signal, how signals get scored, and when accounts move from marketing nurture to sales engagement.

At Sumo Logic, building this kind of measurement rigor was critical for IPO readiness. The board didn't care about MQL volume. They cared about pipeline predictability, cost-per-opportunity, and conversion rates.

The practical starting point is simple: pick your top 10 closed-won deals from the last two quarters. Map every signal and touchpoint from those accounts backward. You'll quickly see that the buying journey looks nothing like a linear MQL funnel. Use that map to build your new signal model.