The 90s Called: They Want Their Metric Back
Did you know that the primary marketing metric used today is over 25 years old? While not every GTM metric needs to be new to be good, this one is definitely showing its age. Yet companies are still holding onto it like an old college hoodie: comfortable, familiar, embarrassing to wear out in public.
I’m talking about the MQL.
It was developed before LinkedIn existed, before third-party data, before buying committees were the norm. It was built for a world where one person could plausibly own an entire technology budget, and couldn't learn about your product without talking to a sales rep. It goes without saying, the world has changed significantly since then.
Selling to technical buyers in industrial verticals teaches you this fast. A plant manager running a 24-hour operation with two people out sick is not attending your webinar. They're researching on their own terms in places you don't control. And across every program I've built for those audiences, I've watched the same cycle play out: MQLs plateau. Someone tweaks the scoring model. Things improve for a few months. Then they tank again when marketing generated pipeline falls flat. And the same conversation happens over and over until someone cries or gets fired.
If your MQL-to-opportunity conversion rate is consistently under 20% and you've adjusted the scoring model more than twice in the past year, stop adjusting. The model isn't broken. The metric is. And here’s why:
You're scoring who is trackable, not who is buying.
Gartner's 2023/2024 research found that B2B buyers spend only 17% of their total buying time in direct contact with potential vendors, meaning roughly 80% of the journey is self-directed. By the time someone fills out your form, they've read the G2 comparisons, watched the competitor demos, and had the Slack conversation with three peers who've already implemented something in your category. None of that shows up in your CRM.
So your MQL model measures one thing with remarkable precision: willingness to exchange contact information for content. It mistakes visibility for intent and rewards whoever is most compliant with your tracking infrastructure.
There's real leverage in simply being present where your buyers research before they identify themselves: comparison sites, industry communities, public conversations where buyers are actively forming opinions. Paired with intent data platforms that can surface account-level research signals, and you get earlier visibility into which organizations are actively evaluating your space before anything hits your CRM.
But don’t take my word for it. Test it yourself. Set a baseline in an intent platform like a 6sense or a Bombora for how many ICP accounts are showing research activity in your category monthly, then cross-reference against your CRM. Accounts showing high external intent but zero CRM activity are your blind spot. That gap tells you exactly how much demand exists that your MQL model is completely missing.
A single lead has never closed an enterprise deal.
The average enterprise buying group now includes between 6 and 10 stakeholders, depending on deal size and category. The MQL was designed for one. That's a major structural mismatch between your measurement system and the reality of how your customers actually buy.
Buying group coverage, or the percentage of key roles showing meaningful engagement within a target account, tells you whether a real evaluation is forming. If three people from the same account research you or your competitors in the same month, that’s a categorically different signal than one person downloading three white papers.
Measuring buying group signals requires defining the group by role and title in your tech stack, then building an account-based engagement score that weighs activity accordingly. For large enterprises, score at the business unit or geo level, not the parent account to ensure you’re capturing the true nexus of intent.
MQLs make misalignment inevitable.
When MQLs aren't converting, the conversation gets uncomfortable fast. Marketing points to sales not following up. Sales points to lead quality. The cycle persists because MQLs keep marketing and sales optimizing for different things.
Two metrics worth building toward: marketing-sourced pipeline contribution (did any of the prospects associated with the opportunity originate from paid, organic, events, or third-party programs?); and marketing-sourced win rate, which tells you whether you have a quality problem or a volume problem.
———
Many companies still organize entire revenue operations around MQLs as though the metric was handed down from a marketing oracle on a misty mountaintop. But MQLs aren't sacred. They're just ancient. They optimize for visible, individual actions in a world where modern B2B buying is mostly invisible, non-linear, and distributed across multiple people.
That doesn't mean MQLs have no value. They can still be a useful leading indicator, helping us understand whether we're reaching the right audiences and generating interest. But somewhere along the way, we elevated them from an early signal to the ultimate measure of marketing success.
Hero image by https://unsplash.com/@busedoay
