Why teams can’t agree on what “good” looks like in digital media

Digital media rarely lacks data, but what it often lacks is confidence in what the data means.

Digital marketing teams look at platform performance and efficiency; Finance focuses on revenue, margin, and return; and Trading looks at demand, stock, and pricing. Each of these perspectives is valid, yet in practice, they bring different levels of knowledge into a technically complex media environment. What I’ve seen repeatedly is that there are still plenty of retailers that don’t have a structure or process in place to create a shared understanding across those perspectives and functions.

Digital media performance is measured in increasingly granular ways using multiple tools and is now fundamental to the business's success. So when the question arises whether digital activity is genuinely working, the answer often shifts depending on who’s ‘in the room’ and which system of record they are referencing. There follows a ‘rush for data’ to prove a particular point of view; this campaign is generating ‘x’ return for ‘y’ investment, and it is due to this channel and that campaign. Unfortunately, other tools can equally persuasively demonstrate media mix, attribution and an alternative customer journey. A single version of the ‘truth’ that prevents this scenario is desperately needed.

Search, Shopping and Paid Social now operate at a significant pace. Budgets change daily, performance shifts while activity is still live, and in an AI-led media environment, any crack in how performance is defined or trusted becomes immediately obvious.

The speed with which media metrics feed back performance today increases scrutiny across the retailer, particularly as the budget sums involved are now significant and have a direct bearing on the bottom line. Over time, I’ve often seen one team recognise an opportunity, another focus on inefficiency, and another concentrate on risk, with conversations not moving towards clear decisions on how to respond to what’s happening in the media and the market.

Often, the response is to add more reporting and different metrics, on the assumption that greater visibility will create clarity. In practice, this rarely occurs; especially when success remains ill-defined, and measurement frameworks are not designed to inform decision-making.

The pattern is very clear. Teams bring different levels of knowledge into a complex and technically demanding media environment, which leads to different interpretations of what the same performance metrics actually mean. Confidence in the evidence weakens, and a disproportionate amount of time is spent explaining performance rather than acting on it. When this happens, the issue isn’t access to information, but agreement on what that information can be trusted to inform and decide.

That lack of agreement carries a cost, as it’s shaping budgets and targets around reassurance rather than the opportunity present in the media and the market. This rarely shows up as a single failure. My view is that it accumulates gradually through small delays and missed decisions over months and quarters.

I’ve seen many cases where digital media has been optimised relentlessly and where it’s clear that it is contributing real value, yet the black-box nature of algorithms and machine learning means activity is neither understood, measured, nor managed in a way that fully exploits the market opportunity.

Retailers do not lack measurement tools and techniques. What’s missing is agreement on what performance means in the context of the business, expressed clearly in revenue, margin and growth, and understood consistently across teams with very different levels of technical knowledge.

Until that agreement exists, digital media will continue to miss its full potential and feel harder than it should. Teams will either stick with the status quo and continue debating numbers instead of using them, while the digital media team remains constrained by an outdated operating model. One that was never designed to support AI-led media or the decisions CMOs, CFOs and CEOs are now expected to make.

In the next piece, I’ll share how alignment can actually be achieved, what needs to be measured, and why increasing understanding is the real objective.