Measurement underpins retail and commerce media, yet pinning down what to measure – and how to compare and contrast measurements – is getting harder to do.
According to the latest data from WARC in its The Future of Measurement 2026 report the shifting sands of marketing measurement have shifted once again and now focus on three ‘new’ key areas: the shift to outcomes measurement; how AI is moving measurement upstream; and the rise of creative intelligence.
These shifts have all taken place against a sea change in the retail media market itself. As explored in the latest RetailX Retail Media Landscape 2026 report, exposure happens in more places, attention is more fragmented, conversions may happen later or elsewhere. This shifts the question from “did this ad work?” to “what part of this system created incremental value and how do we prove it?” Measurement, in other words, is no longer just a reporting function, it is one of the main constraints on retail media’s next phase of growth.
So, what does this changed measurement landscape look like?
Outcomes measurement gathers pace
WARC’s report says that media is increasingly bought against outcomes, driven by greater access to data, digital platforms and ROI pressures. But the ability to measure and optimise against them is developing unevenly across the ecosystem.
Digital platforms are embedding real-time, outcome-based optimisation directly into their advertising systems, while legacy media are still evolving from an audience-based measurement towards proving their impact using experiments and advanced modelling techniques. The result is a two-speed measurement landscape converging on the same goal: incremental growth.
With no single system providing a complete picture, and a lack of trust and transparency in data and attribution, particularly within digital platforms, marketers are advised to make independent validations and take a cross-platform approach that combine multiple data sources and insights to support better marketing investment decisions.
AI moves measurement upstream
According to WARC, AI is primarily being used in measurement to automate data collection, cleaning and normalisation before human interpretation. It can also significantly increase the frequency of testing and modelling for advertisers.
AI promises to move marketing measurement upstream, from a reporting output into ‘decision system’ that supports more dynamic planning and optimisation.
Marketers are rightfully excited about its potential. However, without rigorous, independent validation, AI-driven measurement risks becoming a black box for budget allocation, producing outputs that may appear credible but are not transparent or reliably grounded in true causal signals.
The rise of creative intelligence
Creative quality is a key – and often overlooked – driver of advertising effectiveness, yet it remains undervalued and undermeasured by marketers making it harder to justify investment. This is changing thanks to advances in AI and machine learning, believes WARC.
Marketers are building creative intelligence capabilities, an integrated system that allows them to measure and optimise creative at scale. This enables them to forecast asset performance ahead of launch, continuously optimise creative assets in real time for engagement and effectiveness, and measure the true impact of creative on commercial outcomes.
However, creative intelligence faces several barriers to adoption, such as poor data quality and a lack of resources. It also demands a closer integration across people, processes and technology – particularly creative and media.
WARC is advising marketers to unify disciplines and workflows so creative and media work as one operating system. Investing in platforms that support end-to-end creative activation, optimisation, and measurement will be essential. Piloting is expected to begin with social channels, where creative data is easily accessible and closely linked to performance.
What brands want from measurement
This is all well and good, but what do brands who are advertising actually after from measurement? According to the RetailX Retail Media Landscape 2026 report, brands want more than a post-campaign sales number. What they increasingly want is a layered measurement framework that answers different questions at different stages of the journey.
At the most basic level, they still want accountability: did the campaign drive sales and what was the return? That is why ROAS remains so important. But that is only the starting point. They also want transparency into how those outcomes were achieved, how metrics were calculated, what audiences were reached, whether the result was genuinely incremental, and how retail media performed relative to other channels competing for the same budget.
According to IAB Europe’s 2025 Attitudes to Retail Media report study, buyers rank transparency and reporting ahead of almost everything else when assessing networks, which suggests that measurement is as much about trust as it is about optimisation. They also want integrated online/offline reporting, which reflects the reality that retail media is no longer confined to ecommerce alone.
In practice, that means the ideal retail media measurement stack now includes several layers: delivery metrics, commerce outcomes, customer outcomes such as new-to-brand, causal measurement such as incrementality, and increasingly cross-channel modelling such as MMM or other forms of portfolio analysis.
