Effective B2B marketing measurement in a changing media landscape

As a CMO or Marketing Director, you’re no stranger to the mounting pressure to prove the ROI of your marketing spend. Fragmented, disconnected data sources and longer, more complex sales cycles only add to the challenge. How do you ensure your marketing drives growth when traditional attribution models fall short and some brands even struggle with getting any view (last click or otherwise) of attribution in the first place?

To tackle these challenges, it’s important to first understand how buyer behaviour has evolved and why it’s made effective measurement so much harder.

How changing buyer journeys affect effective measurement

In B2B, the days of single decision-makers are long gone. Buying decisions now involve larger, more diverse teams, with extended scrutiny and a growing need for self-serve information. Buyers expect greater access to detailed, in-depth resources that allow them to evaluate solutions independently before engaging with a vendor. As a result, buyer journeys are more intricate than ever, with the average buying cycle growing from 17 to 27 interactions (Source: The Demise of Dead-End Demand). This shift necessitates a more nuanced approach to demand generation.

Additionally, much of this activity happens “in the dark.” Buyers conduct months of in-depth research incognito before even engaging with a vendor. This behaviour makes it harder for marketers to track and influence their journeys effectively.

Traditional, lead-focused methods of measurement fall short in this environment as they fail to account for the collective behaviour of buying teams, missing the wider context of interactions that drive decisions. To address these complexities, many B2B marketers are turning to intent data. By identifying the signals from specific buying teams, intent data provides a clearer picture of which accounts are actively researching solutions and how best to engage them.

Still, long sales cycles with scattered touchpoints across weeks or months make it challenging to connect marketing activities to outcomes. This isn’t entirely new; traditional attribution models, which often rely on cookies or individual lead tracking, have always struggled to capture the full scope of a customer’s journey – especially when offline or multi-channel interactions are involved. But as buyer journeys become even more fragmented, these limitations are becoming increasingly apparent.

Attribution vs. incrementality

When it comes to measuring marketing effectiveness, we need to be clear on what it is we’re actually measuring. This is where the distinction between attribution and incrementality becomes so important, and yet, it’s a distinction that’s often misunderstood.

Attribution is about distributing credit for a conversion across the various touchpoints in a buyer’s journey. It helps you identify which channels, campaigns, and content assets played a role in driving a sale. This makes attribution valuable for understanding how marketing efforts contribute to conversions.

Incrementality, on the other hand, answers a different question: Would those conversions have happened without your marketing interventions? It measures the true lift generated by your marketing activities, isolating the impact of your campaigns from conversions that would have occurred anyway.

The problem is that many businesses conflate these two approaches, mistakenly assuming that attribution reveals the true value of their marketing. The reality is that a significant number of conversions attributed to paid media, for example, might have happened regardless of those campaigns.

Failing to distinguish between attribution and incrementality can lead to skewed perceptions of performance and, ultimately, to poor decisions like over-investing in channels that appear more effective than they truly are. By understanding and applying both concepts correctly, marketers can gain a more accurate view of their efforts and allocate budgets with greater confidence.

Marketing Mix Modelling and incrementality

Marketing Mix Modelling (MMM) has gained traction in the B2C world as a method for measuring the impact of various channels on sales. It’s no surprise that many agencies are talking about it; it offers a data-driven approach to understanding channel effectiveness.

However, what works well in B2C doesn’t always translate to B2B. The unique dynamics of B2B marketing make applying MMM a much more complex task. Long sales cycles, smaller and highly targeted audiences, and high consideration purchases make it difficult to apply MMM effectively.

In B2B, conversions are rarely the result of straightforward, channel-driven interactions. Instead, they often hinge on personal relationships, sales team efforts, and non-marketing touchpoints. All these factors play an important role in influencing decisions but are difficult to capture within the MMM framework.

Incrementality testing, too, is similarly more challenging in the B2B space. The multi-stage customer journeys and relatively low frequency of sales make it harder to isolate the impact of individual marketing activities. Unlike B2C, where large data volumes and frequent transactions can provide clearer insights, B2B marketers operate in a more nuanced environment.

To address these challenges, B2B marketers need to rethink what they measure and why. There’s a growing shift towards rethinking what constitutes a meaningful metric.

While traditional short-term metrics such as lead volume or immediate sales opportunities have their place, they often reflect a narrow view of marketing’s true value. Instead, campaigns should align with broader strategic goals and focus on metrics that capture the bigger picture.

This shift requires clarity about the purpose of each marketing activity: how it connects to solving critical business challenges, even if it doesn’t directly generate leads. Measurement strategies that integrate intent data, account-level insights, and qualitative feedback are far better suited to uncovering the true impact of marketing, allowing marketers to demonstrate value beyond immediate results.