This guest blog post is brought to you by Nadia Davis, VP of Marketing at CaliberMind. See her bio at the end of the article for more details.
“To MQL or not to MQL. That is the question.”
Even without a Hamlet-worthy skull to hold for Shakespearean-style drama and flare, the dilemma still stands: Do we ditch the MQL or redefine it?
For years, marketers have argued over the value of the MQL. Some say it’s outdated, a relic from a lead-gen playbook that no longer fits today’s buying journey. Others argue for its evolution. But what if the solution isn’t to do away with the MQL at all but instead to stop treating it like the beginning and end of marketing’s hand-off to sales, or the centerpiece of every external-facing performance dashboard… and instead use it as an internal signal, a leading indicator, that flags which accounts are actively looking and are in need of additional marketing & sales’ attention?
In the discussion that follows, I want to touch on why MQLs drew the short stick, the operational challenges of blending MQLs with account-based reporting, change management strategies, and practical adjustments that can transform MQLs into a valuable signal, without letting them take marketing center stage.
My perspective - often labeled as unique, though hardly unprecedented - on the still-relevant role of MQLs in 2025, was born out of several from-scratch instrumentations of B2B account-based marketing (ABM) motions across various SaaS businesses. The topic of measuring what matters and reporting on it, storytelling-style, became personal for me back when I built my first ABM program that captured digital insights of account-level performance but didn’t actually tell the full story of how the marketing department was doing. That’s where I had to take a stand on how we tiered marketing metrics: team-level metrics for ICs to track monthly output, business-level metrics tied to department OKRs, and board-level metrics - the kind that fit on a single slide and still tell the story of marketing’s short- and long-term impact. I realized that if I could isolate the right insights to tell the marketing story at each level - the sky would be the limit for how far I would go as a marketer.
So passionate was I about creating the right measurement and attribution frameworks to tell the full marketing story, that I staked my career on it: I left the brand side after a decade and a half in demand gen, revenue marketing, and MOps roles across multiple SaaS, DaaS and Iaas orgs - and joined the solution provider I had been a customer of, the one that helped me actually track and measure those three tiers of marketing performance. And this is a story about recognizing the right insights & marketing performance building blocks that can, if done correctly, supercharge your career, as well. And yes, MQLs were part of that story.
So where did this whole MQL thing even come from? Like most legacy frameworks that outlived their prime, it was born out of a need to bring order to chaos. Back in the early 2000s, SiriusDecisions coined the term “Marketing Qualified Lead” as part of their Demand Waterfall framework. The intent wasn’t to set up future marketers for failure. It was actually kind of genius for the time. Marketers needed a way to say, “Hey Sales, we did our part. Here’s a lead that’s been nurtured, engaged, and fits the profile.” Boom! Out of nowhere, we had marketing and sales alignment and marketing deliverables at scale, at least on paper. A white paper download form fill - an MQL! A webinar registrant - another MQL! A demo request - absolutely! Live event attendees - we like them all!
Forrester later acquired SiriusDecisions and doubled down on the framework, pushing it into the executive stratosphere. Suddenly, board decks had MQL charts, CFOs started quoting conversion rates, and nobody - not even the non-marketers - could imagine a funnel without them. The MQL as a metric stuck not because it was perfect, but because it was easy to explain, easy to report on, and universally recognized. No one ever asked, “What really makes an MQL?”. Everyone just assumed someone else had figured that part out. This was not a widely popular question or the bull’s eye of scientific inquiry for marketers. All that mattered was that it had a name and it was a means to an end. And it worked. For a while. The model gained traction, got operationalized everywhere, and became the gospel for B2B marketing. And strangely, everyone was OK that the bottom of the funnel conversion rates from a proverbial MQL to an opportunity were in the single digits… Nobody had any ideas of how to improve it, so the loosely defined MQL lived on.
Eventually, a few clever sales reps figured out that to get the most opportunities out of the needless MQLlists assigned to them automatically, all they needed to do is to look at the MQL titles, then their account (is it even the right org that we can sell into?!) - and, finally, multi-thread into that company by finding other relevant titles and reaching out to those as well to increase their chances of success. I diagramed this process as a prospecting lifecycle circle shown below:
Ironically, these clever sales people were not the only ones who had this awakening. So did a few early ABM proponents. About the same time, Jon Miller, Co-Founder and CEO of Engagio, uttered his famous quote about inefficiency of fishing with nets (lead-centric motion) and the need for laser-focused targeting equal to fishing with spears. From there on, the lead-centric world of marketing as we know it was no more.
Now, it was a new day of ABM - supercharged by MQAs - that had risen to GTM prominence with yet another silver bullet promise - to shorten your sales cycles once adoption across the org. This message flooded all marketing channels, thanks to well-funded ABM platforms, and got all of us convinced and converted. “Death to MQL,” shouted excited marketers on the streets of New York and captured the moment on LinkedIn. For many newly-minted proponents of this add-water-and-stir euphoria approach to marketing in these ABM-frenzied orgs, MQLs became hate-on & throw-away vanity metrics sacrificed on the public altar of the ABM bliss (that never came, by the way).
Most ABM-platforms called for all MQLs to be tossed aside. And this public MQL execution allowed ABM tools to build a strong and popular business model by banishing MQLs, while actually standing on the shoulders of what I call an ICP-qualified MQL.
But have we ever considered that if we take the same prospecting life cycle circle I described earlier - and travel it backwards, what we will have is exactly what the best sales people had figured out earlier?
You start at the account level (your TAL), engage it, get to an MQA point, then have sales people jump in and do account research, identify the buying group and start multithreading into the account from the key persona titles. Research account engagements and figure out who the most actively engaged people are in that account. Wait?! Aren’t those yesterday’s MQLs?
So you see, dear reader, if you flip the script and start with your ICP as one of the MQL qualifying criteria, drill down to the right personas - and only then consider the actions that indicate genuine buying signals; you begin to see MQLs not as a definitive sale indicator, but as a valuable signal that merits further investigation. Why didn’t we all do it in the first place?
Because no one wanted to think that hard about MQLs and their role. Too often, they were just the sales hand-off metric. No journey. No signal. No story. So tossed MQLs got, as baby Yoda would put it.
I often compare the MQL definitions to the concept of burden of proof in the US legal system. My first degree was in the legal world, and I once envisioned myself as a lawyer. In my mind, the MQL is a metric on trial, with the prosecutor applying the highest legal burden of proof that fits a criminal trial - “beyond reasonable doubt”. When in reality, MQLs committed no crime - it is a civil matter and a civil court and perhaps it should only meet a “preponderance of the evidence.” MQLs show interest signals; it’s up to the human in the loop (a BDR or an AE) to investigate further and apply human judgment.
This approach to MQLs, in my mind, fosters trust and collaboration, ensuring that sales aren’t just order takers but critical investigators who add value. MQLs are mile markers along the road traveled along the buyer’s journey. They are beacons of interest within an account.
“Flip my funnel” is a cool phrase that my friend Sangram Vajre, a co-founder of Terminus coined back in the day to illustrate how reversing the prospecting lifecycle circle made all the difference. Today, I am re-defining what that means.
I’ve been a hands-on practitioner of ABM go-to-market motions for a long time. And I quickly realized that MQAs alone don’t paint the full picture of all the things that Marketing departments do to help advance their businesses forward. You can’t build a marketing story from a siloed view of the ABM tool analytics module that only reports on what it can track through reverse IP identification or device ID lookup, especially when a true MQA takes months to materialize under tight definitions. You also can’t convince Sales to start working an account where you don’t have a single name of contacts that got engaged. What, they only got ad clicks?
That’s where the flipped-MQL approach comes in. In this scenario, a sales person would still start prospecting with the account, assess engagement at the account level, qualify the right personas, then look at the actions they’ve taken. That MQL? It’s not your starting point—it’s your signal to act within an MQA (engaged) account.
I’ve used this model to train new sales teams. When I frame it as “everything you already do, just in reverse,” they get it. No glazed-over eyes. No rolling their eyes at “Marketing 101.” It’s not radical. It’s just re-sequenced.
This “reverse engineering” of the MQL process allowed my sales teams to prioritize their actions and work with a smaller, more meaningful subset of accounts. Every time I explained it to new salespeople joining our account-based marketing efforts, I watched it landing SO WELL with the sales teams. They didn’t feel like marketing was rewriting their world. They just saw the logic. It was the same playbook -just backwards.
And that leads to trust. To collaboration. And to better conversion.
Sometimes, an MQL even saves you. You build your TAM list, lock it down, align across functions just to realize mid-quarter you missed something. That’s when an out-of-TAL MQL shows up and says, "Hey, look at me." It might be the signal to revisit that list and add this new account with a visiting MQL. Because a good TAM list is never static - and neither is your funnel.
The general problem with MQLs is two fold: first, defining what makes an MQL and socializing this across all relevant parties for alignment - and knowing what to do with MQLs once we got them and making the most out of them. What led businesses to give up on them was the poor definition, poor qualification, and incomplete or biased instrumentation of the MQL lead lifecycle stage.
Well, an MQL definition is in order, would you agree? While it may have different flavors for each business, the general similarities for any org around what makes an MQL could be:
OR
Notice that instrumentation of what determines “high engagement” and having ICP (ideal customer profile) requirement for an MQL make it an argument-proof metric to monitor.
Too many orgs gave up on MQLs because they never defined them well to begin with. They blamed the metric instead of the instrumentation. It’s not the MQL’s fault if your scoring model is broken, if your definition of engagement is garbage, or if your BDR team never bought into what the number is supposed to mean.
The message that I have for all of my marketing colleges is this: MQLs have a purpose. They fold into your account scoring. They can signal offline conversions. They just shouldn’t be the centerpiece. If your board-level conversation starts with “how many MQLs,” something is broken.
If we burn MQLs down without giving Demand Generation and Revenue Marketing departments something clear and credible to replace it with to add to their real-time performance monitoring or use as an early indicator of an opportunity, we leave a gap. What will take its place?
In addition to being sales signals, MQLs serve as benchmarks for marketing department leaders needing to set short-term goals for their individual contributors. As a practitioner leading a team many times I found myself facing the question: what do I track our performance week to week? People need to know how they are pacing towards a goal!
How do my A-type goal-oriented, numbers-chasing demand marketers and performance marketers benchmark their performance?
How do I and my team monitor channel performance, persona engagement, or campaign velocity?
Bringing back the MQLs was the answer. When instrumented and defined correctly, MQLs serve as leading indicators of quarterly performance and help orient revenue and demand marketers for daily or weekly monitoring of their performance:
Fellow marketers, we must reassess our approach! Instead of mindlessly chasing higher MQL numbers, we need to analyze the stories our data is already telling us. Look at the signals, connect the dots, and let the data inform your strategy. Let’s stop worshiping or crucifying MQLs as the ultimate metric and start using them as a tool, as a way to spark deeper insights and better collaboration between marketing and sales.
MQLs are not dead. They’re merely in need of a revival through a more analytical, thoughtful, and collaborative approach. Let’s redesign how we define them, the purpose they serve, and the way we measure them. Because at the end of the day, if you’re chasing some other vanity metrics, you’re missing the real story that lies beneath.
Because in the end, we weren’t wrong for adopting MQLs. We were wrong for oversimplifying them. For letting methodology replace strategy. For skipping the operational complexity it takes to actually make ABM work.
Tracking MQLs and MQAs can feel like a forced choice: you’re either all-in on lead gen or fully committed to ABM, with no in-between. But that binary thinking is outdated. CaliberMind’s dual-funnel framework gives you the ability to track both people and accounts in parallel without mixing signals or muddying the metrics. You can still define and operationalize MQLs at the individual level, while also tracking account-level progression toward your target list. The ultimate goal behind this functionality is to allow marketing teams to gain clear visibility into individual lead activity alongside account-level progression, all in the same place.
We believe that tracking marketing performance shouldn’t be about choosing sides. It’s about giving your team the full picture so you can prioritize the right actions, tell better stories, and show real marketing impact. In a dual-funnel world, MQLs and MQAs can coexist. CaliberMind just makes it make sense.
Nadia Davis is the VP of Marketing at CaliberMind, where she’s on a mission to help marketing leaders unlock insights from the data they already have and the metrics they’re already tracking—often across way too many disconnected systems. With a background in demand gen, revenue marketing, and marketing operations on the brand side, Nadia has built and instrumented account-based programs from scratch at multiple SaaS and data companies. She believes no two go-to-market strategies are the same, and your measurement framework shouldn’t be either. Whether it’s a custom funnel, dual funnel (people and accounts), or account funnel, what matters is proving marketing’s impact on revenue - and telling that story in a clear, compelling, and consistent way that gets buy-in across the business.
