By Seb Joseph  •  December 18, 2025  •

Ivy Liu

In practical terms, Pugh’s job is about tapping into that shift. His focus will be on helping advertisers decide earlier what success could look like and which signals should actually guide decisions. That means stress-testing channels for incrementality, shrinking bloated metric frameworks into tighter scorecards tied to business outcomes and comparing performance across markets to shape future spend. A growing share of that will land in the U.S. where Ebiquity is looking to expand its effectiveness business and where advertisers are confronting the same measurement problems — just at a much larger scale. 

“We’ve heard of advertisers looking at 50-plus metrics in one particular campaign,” said Pugh. “Not all of them are doing something.”

In many ways, Pugh’s career is a reflection of all that — it’s unfolded alongside marketing’s shifting relationship with measurement, and in some ways, ahead of it. 

Before entering advertising, he trained as an academic in mathematical and computational optimization of real-work problems. One of the models he worked with drew on the behavior of ants: how simple, local decisions made independently can, over time, produce an efficient system. It shows how outcomes emerge over time, rather than being precisely engineered from the outset.

“When the first batch leaves the nest they go off in a fairly random scatter,” said Pugh. “That ground biases the decisions of the next batch.”

He arrived in marketing in the early 2000s, when that kind of thinking was still peripheral. Measurement was limited, data sets were narrow and effectiveness work largely focused on establishing basic accountability. The central question was whether marketing worked at all, not how or why.

As the industry’s tools expanded, the question got more complicated. Digital channels multiplied. Data volumes grew. Expectations calcified. Proving that marketing worked stopped being enough. Marketers were expected to explain how it worked — to separate cause from coincidence in environments awash in signals but short on clarity. Different systems told different stories. Metrics piled up. The connection between activity and outcome didn’t get cleaner, it got more difficult to pin down.

“A lot of what we’re doing is trying to align cause and effect,” Pugh said. “Not just to look at what’s happened but to understand what actually drove it.”

As Pugh prepares to step into his new role, that capability is gaining more prominence. Automation and artificial intelligence are reshaping how media is planned and bought, reducing the labor involved in execution. What remains unresolved is how success should be defined, evaluated and, in some cases, paid for. 

Those questions have become more pressing as advertisers reconsider long-standing agency arrangements and explore compensation models tied more closely to outcomes. Such models depend on agreement about which measures matter and how they should be weighted — a task that requires judgment as much as analysis. It also requires commitment. Many advertisers are still early in the process. Data infrastructures are uneven and measurement systems do not always align. Progress can be incremental. 

Even so, the direction of travel is unmistakable. There’s a growing insistence among CMOs that advertising should be judged less by activity and more by what it actually delivers.

“We’re at the start of the journey with this,” said Pugh. 

Some Ebiquity clients, at least, appear ready to take it. 

“Working with Nick has had a major impact on the effectiveness of my marketing budgets over the years,” said Emma Colquhoun, chief marketing and commercial officer at Wagamama. “His ability to turn complex data into clear, actionable strategy helped achieve measurable business gains. He is one of the most effective marketing leaders I’ve partnered with.”

The same goes for insurance firm Direct Line Group.

“Nick brings a rare combination of strategic vision and hands-on partnership. He has been able to challenge our thinking in the best way and consistently help us deliver stronger, smarter, more effective work and outputs,” said Carl Bratton, head of marketing effectiveness at Direct Line Group. “His leadership has elevated how we approach marketing effectiveness, and the effectiveness culture we have within the business”

Pugh is measured about what lies ahead. He expects automation to accelerate much of the technical work involved in effectiveness, from data processing to modeling and reporting. Insights that once took weeks to generate can now be surfaced far more quickly.  

What cannot be automated, he suggested, is the work of deciding what to do with those insights. Someone still has to interpret results in context, weigh trade-offs and make choices that extend beyond the net campaign. As marketing systems grow more complex that role is becoming more visible — and more consequential. As Pugh explained: “Once you get all the answers out, you then get into the ‘what does it mean for them’ phase and the scenario planning.”

Pugh’s upcoming move does not resolve the industry’s uncertainties. It signals where companies are beginning to place responsibility for them.