The Anti-Playbook, Part 4: Kill the MQL
This is Part 4 of The Anti-Playbook, a series on how I’d actually build demand gen at an early-stage B2B SaaS company in 2026. Parts 1-3 covered the setup, the inverted roadmap, and the outbound stack. This one comes for a sacred cow.
The MQL — marketing qualified lead — is the most successful concept marketing operations has ever produced.
It gave marketing a way to prove it was generating value. It gave sales a queue of warmed-up prospects to call. It gave executives a number to put on a slide. For about a decade, it was the right abstraction.
It is no longer the right abstraction.
The MQL Was Built for a World That No Longer Exists
The MQL was invented in the mid-2000s, productized by Marketo and Eloqua, and codified by every marketing automation platform that came after. The economics that made it work were specific to that era:
Leads were scarce. Most companies had no functional way to generate inbound demand, so any lead with a valid email address was worth scoring.
SDRs were expensive and slow. A human had to call every lead, so you needed a system to tell them which ones to call first.
Buyer research happened in dark corners. A prospect downloaded a whitepaper, disappeared for six months, then showed up to a webinar. Lead scoring was the only way to track that engagement over time and decide when they were “ready.”
The handoff between marketing and sales was a meaningful event. It happened at one moment in time, when a lead crossed a threshold, and it required a formal process.
Look at how many of those conditions still hold in 2026.
None of them do.
Leads aren’t scarce — AI enrichment and outbound tooling can produce 500 high-fit accounts in an afternoon. SDRs aren’t the only way to engage a lead. Buyer research doesn’t happen in dark corners — intent platforms like 6sense, Demandbase, and Common Room surface buying signals in near real time. And the marketing-to-sale handoff is no longer a moment. It’s a continuous flow of signals, contexts, and conversations.
What’s Actually Wrong With Lead Scoring
Beyond the era mismatch, there are three specific operational problems with traditional MQL scoring at an early-stage company.
It optimizes for the wrong metric
Lead scoring rewards engagement — opens, clicks, downloads, page views. But engagement isn’t a buying signal. It’s an interest signal.
A prospect can be highly engaged and never buy. Another prospect can have zero engagement, then walk into a Zoom and sign a six-figure contract because their CFO told them to find a solution by Friday. Scoring engagement systematically misses the second prospect and over-invests in the first.
It introduces latency exactly where speed matters most
A lead becomes an MQL when their score crosses a threshold. The threshold check runs on a schedule. The handoff to sales happens via a workflow. The SDR sees the lead in their queue. The SDR decides when to reach out.
Total elapsed time from “buyer is ready” to “buyer hears from us” is often measured in days. The companies winning in 2026 measure it in minutes. Scoring is a structural cause of the latency.
It creates the illusion of objectivity for what is actually a guess
Every lead score is a model. Every model has assumptions baked into it. A score that says “this prospect is a 73” sound quantitative — but the 73 is the output of a series of judgement calls about how much a webinar attendance is worth versus a pricing page visit.
When the model is wrong — and it’s always wrong about something — the score makes it harder to spot, because the number feels like data instead of opinion. This is how marketing teams end up defending a lead scoring model that hasn’t generated a closed-won deal in six quarters. The dashboard still produces a number, the number still goes up and to the right, and nobody wants to be the person who admits the whole apparatus was theater.
What Replaces It
Killing the MQL doesn’t mean abandoning prioritization. It means replacing a single composite score with three separable judgements, made continuously rather than at a threshold.
Fit: Is this account in our ICP? This is binary. An account either matches the ICP of it doesn’t. Fit doesn’t get a score — it gets a tier: ICP, adjacent, or out. Out-of-ICP accounts get suppressed. Adjacent accounts get lower-touch motions. ICP accounts move to the next layer.
Intent: Is there a buying signal right now? Intent comes from behavioral signals on owned properties, third-party intent data, trigger events like funding or leadership changes, and outbound reply signals. (A positive reply to a cold sequence is a stronger intent signal than any inbound form fill.) Intent is binary and evaluated continuously — signals decay. A pricing page visit from 90 days ago is not a current signal. The system tracks freshness, not cumulative score.
Speed: How fast can we engage when fit and intent both hit? When an ICP-fit account shows current intent, what’s the latency between signal and human contact? In the MQL world, days. In the model that replaces it, the only acceptable answer is minutes.
There is no MQL. There is no SQL. There are accounts with active buying signals, and accounts without them. The marketing-sales handoff stops being a threshold event and becomes a continuous flow of signals into a single shared queue.
The Strongest Argument for Keeping It
The best case for lead scoring is that it forces marketing and sales to agree on what “qualified” means. The artifact of agreement matters, even if the score itself is imperfect.
This is a real concern. But the answer isn’t to keep scoring — it’s to replace the agreement artifact with something better.
The fit and intent definitions are the agreement artifact. Marketing and sales sit down together and define: who is in our ICP, what counts as an active buying signal, and what response speed we’re committing to. That document — three pages, max — does the work lead scoring was attempting to do, without the latency and false objectivity of a points-based model.
Lead scoring was a workaround for a problem that’s now solvable directly. Workarounds outlive their reason for existing because nobody wants to dismantle them. That’s the actual reason most companies still run scoring — not because it works, but because removing it requires a conversation nobody wants to have.
Why This Matters More for Early-Stage
If you’re at a late-stage company with established scoring infrastructure, replacing it is real organizational change — educating executives, rebuilding reporting, retraining sales. That’s a high cost.
But if you’re at an early-stage company that hasn’t built the scoring infrastructure yet — the company this whole series is written for — there’s no reason to build it in the first place.
Building lead scoring in 2026 is like building a fax workflow into a new product. It will function. It will produce outputs. And it will tie the company to an operating model the rest of the market is actively moving away from.
Skip the step entirely.
What’s Next
Part 5: The Channel Bet — why “a balanced multi-channel approach” is what you say when you don’t want to commit to anything, and the one channel I’d actually bet on
This one’s going to be divisive — lead scoring has a lot of defenders, and a lot of careers built on it. If you think I’m wrong, I genuinely want to hear it. Tell me what the score is doing that fit, intent, and speed can’t.
