The MQL was never the problem

In that context, the MQL’s design and adoption were both rational and necessary. Marketing automation platforms built around scoring models made it possible to prioritise and route opportunities efficiently. Sales teams trusted that qualification signals would correlate, at least directionally, with readiness for conversation. Leadership teams measured it as an early pulse of interest.

However, the environment in which these models were constructed has since evolved, and with it the nature of modern B2B buying. Boards now assess pipeline health with scrutiny that goes well beyond activity counts. Finance leaders demand clearer linkage between investment and value creation. Revenue leaders focus increasingly on deal confidence and conversion quality rather than volume metrics alone. In this context, the traditional MQL framework is being asked to perform far more than it was originally designed to capture.

The issue is not that MQLs suddenly stopped working, nor that marketing teams misjudged their value. The challenge is that buyer behaviour has shifted more rapidly than the models used to measure it. When the underlying assumptions of a metric no longer align with real-world dynamics, the effects show up not just in measurement, but in pipeline outcomes.

Why the MQL was always a proxy, not a predictor

The MQL emerged at a time when buying journeys tended to follow a more orderly progression from awareness to engagement and, ultimately, conversation. In that era, observable engagement often corresponded reasonably with a prospect’s forward movement. Completing a form or interacting with content signalled interest, and interest was often predictive of further engagement.

As a structured approximation of buyer progression, the MQL introduced discipline, it created thresholds for action and facilitated measurement where previously there had been none. It helped organisations scale demand generation, prioritise follow-up and build a common language between functions.

What has changed is not the logic of using observable engagement as one input, but the nature of how buying actually unfolds.

Emerging research from 6sense underscores that modern B2B buying dynamics have shifted significantly. Their latest global 2025 Buyer Experience Report finds that buyers are making vendor choices long before traditional sales engagement begins, and that the balance between independent research and seller engagement has shifted, with the majority of evaluation happening before any direct contact with sales occurs.

This means that while engagement signals remain informative, they are no longer uniquely or reliably predictive on their own. A form fill or download signals interest, but it does not by itself confirm readiness to engage as a collective buying group or alignment with commercial criteria.

The MQL was therefore always a proxy, an approximation, not a definitive predictor of revenue outcomes. As buyer behaviour has become more distributed and less sequential, that proxy has naturally become less sufficient when viewed in isolation.

The buyer has outgrown the funnel

Current B2B buying is inherently more complex, iterative and consensus driven than the models that shaped earlier qualification frameworks assumed. According to the same 6sense research above, buyer behaviour now reflects significant independent evaluation before sellers enter the picture.

This evolution does not imply that marketing models failed. Rather, it reflects the reality that buyers now exercise a level of autonomy and self-direction that was uncommon when the MQL was invented. Modern buyers explore solutions across digital channels, compare alternatives, consult with peers and refine criteria before ever signalling their presence through a measurable action. In this environment, relying on a single individual’s interaction as a definitive indicator of a collective buying group’s intent becomes increasingly complex.

Research surrounding the timing and distribution of buyer engagement also aligns with long-standing findings from analysts such as Gartner, which report that buyers spend a relatively small proportion of their time meeting directly with potential suppliers compared with the total journey.

Within this context, treating early engagement alone as sufficient evidence of commercial progression is an incomplete interpretation of buyer behaviour rather than an indictment of the teams who built these models.

The disconnect between leads and revenue

The growing gap between traditional lead metrics and revenue outcomes reflects structural shifts in buying dynamics rather than deficiencies in marketing execution.

One of the clearest examples of this structural shift can be seen in how organisations interpret top-of-funnel engagement, particularly content syndication. Content syndication leads and Marketing Qualified Leads are frequently conflated, yet they represent different signals. A content syndication lead indicates that an individual has exchanged their details for access to information. An MQL typically applies an additional layer of scoring or qualification. In both cases, however, the signal is often misinterpreted.

Content syndication remains a valid and valuable mechanism for engaging buyers early in their journey. The challenge is not the tactic itself, but the expectations placed upon it. Historically, downloading an asset was often interpreted as an indication of readiness for vendor engagement. Today, it more accurately reflects independent research. Buyers are earlier in their evaluation process, gathering information on their own terms, often long before they are open to commercial conversation.

When organisations treat content syndication or early MQL signals as late-stage intent, a structural misalignment emerges. Marketing appears to be delivering “leads,” while sales experience a lack of readiness. The metric has not failed. The interpretation of what it represents has shifted.

Analysts report that modern buying journeys are non-linear and characterised by substantial independent research, internal consensus building and asynchronous evaluation across stakeholders, all of which precede formal engagement. As noted above, recent research finds that a significant portion of the buying cycle now unfolds before sales enters the conversation.

In parallel, organisations face heightened scrutiny around return on marketing investment. Senior leaders increasingly prioritise metrics that speak directly to pipeline quality, deal progression and revenue influence rather than raw engagement counts. This is not an indictment of engagement as a concept. Engagement remains vital. It is a reflection of how value is now articulated across revenue engines.

As the landscape has evolved, operating models that connect planning, execution and measurement across teams, channels and stages of the buying journey have grown in importance. Shared commercial objectives, account-level visibility and harmonised success metrics now play a central role in performance evaluation.

Attribution in a fragmented environment

Traditional multi-touch attribution models count interactions across touchpoints but are limited in their ability to discern whether those interactions reflect meaningful progression toward a purchase decision. When signals are optimised primarily for volume or frequency, teams can unintentionally prioritise signals that are easily measurable yet only loosely connected to revenue outcomes.

In a complex buying context, the challenge is to distinguish between activity, what can be observed and what actually moves a buying group closer to decision. As digital behaviours proliferate, measurement architectures that surface deeper context, behavioural patterns and progression across accounts gain importance.

From lead volume to lead value

If early engagement signals alone are no longer sufficient as predictors, the opportunity lies in integrating richer behavioural and contextual indicators into qualification frameworks. Forward-thinking organisations are investing in intent analytics and account-centric frameworks that align more closely with where buyers truly are in their evaluation process. Research from intent analytics providers and industry analysts highlights that applying intent signals strategically helps teams understand where prospects are in their decision journey and prioritise follow-up accordingly.

More nuanced qualification models consider behavioural evidence that indicates active evaluation, alignment with buying criteria and engagement across buying group stakeholders. Rather than abandoning the discipline of scoring signals, these approaches build upon it by introducing context and progression into qualification.

Simultaneously, organisations are redefining the transition point between marketing and sales, anchoring it not in a static score but in observable readiness for engagement, supported by behavioural evidence of momentum.

Reframing marketing’s role in growth

This evolution is not a rejection of measurement; it is an invitation to prioritise meaningful measurement. We now operate in a landscape defined by self-directed research journeys, complex buying groups and extended evaluation cycles, all of which demand metrics that reflect how revenue is created. Marketing’s role therefore extends beyond generating discrete leads to demonstrating influence across the entire revenue lifecycle, from expanding awareness and shaping perception, to influencing consensus and supporting qualified pipeline.

When marketing is accountable for measurable revenue contribution rather than activity alone, success is articulated through metrics that resonate with executive priorities- quality, velocity and confidence of pipeline, not simply counts of interactions.

The MQL is evolving

Declaring the death of the MQL makes for a compelling headline, but the empirical reality is more nuanced. The MQL was a transitional construct that introduced structure, discipline and shared language during a formative phase of digital adoption. It was never designed to be the sole arbiter of revenue outcomes in a world where buyers navigate independently across channels and consensus is distributed among multiple stakeholders.

Today’s organisations require qualification models that correlate with observable commercial behaviour and collective account progression. These models build on the foundations the MQL introduced, but extend them with deeper context, behavioural intent and account-level signals that align across functions.

This evolution is as much about operating models as it is about metrics. Buying journeys must be understood as they actually occur. Commercial goals must be aligned across teams. Engagement must be orchestrated across the full lifecycle. And progression must be captured at the account level rather than through isolated interactions.

This is also the thinking behind our solution; OrkestIQ, designed to reflect how B2B buying unfolds in today’s market- connected, self-directed and digitally enabled. By unifying planning, activation and reporting, such operating models create visibility across the full journey and surface account-level intent at pivotal moments.

Within this framework, qualification becomes grounded in observable behavioural signals and collective account momentum, and marketing performance is defined not by the quantity of leads captured, but by the quality and confidence of pipeline contribution.

In a market defined by scrutiny, attention alone is not a sufficient proxy for growth; what matters is demonstrable intent and its measurable connection to revenue outcomes.

For organisations questioning whether their current qualification model reflects how buyers actually buy, Gilroy offers a collaborative OrkestIQ Innovation Session.

In this working session, we’ll:

• Map your current buyer journeys
• Identify friction and misalignment
• Align your programmes to a connected buying framework
• Define a prioritised roadmap to improve pipeline quality and conversion

Book your OrkestIQ Innovation Session