A new Winterberry Group survey puts a hard number on a familiar frustration: 83% of senior US marketers call cross-channel spend optimization a leading priority, but only 9% say they can do unified marketing measurement “extremely well.”
The study, sponsored by Lifesight and fielded in July and August 2026, reached 121 US executives at VP level or above across retail, finance, CPG, travel, auto and consumer tech.
The priority-ability gap
The 9% figure translates to roughly 11 executives. The 83% is based on a 6 or 7 on a seven-point priority scale. A sharper question found 40% of respondents name unified measurement as their top measurement priority, ahead of higher-quality data sources at 33% and better incrementality testing at 31%.
Winterberry defines unified marketing measurement as an approach that integrates multiple methodologies and data sources into one calibrated, cross-channel view. But brands are still running a crowded toolkit: 93% use platform-native reporting, 71% use marketing mix modeling, 69% multi-touch attribution, 62% data-driven attribution and 52% incrementality testing. That averages nearly five methods per brand, and reconciliation often falls on marketing teams.
Why the gap matters
Platform-native numbers are the default referee. Google, Meta and Amazon now take about 59% of trackable US ad spend, up from 47% in 2020, according to the report. When each media seller also grades its own homework, budgets can move on numbers that were never designed to agree.
Lifesight CEO Tobin Thomas put it bluntly in the announcement: “Every platform grades its own homework.” That matters because only 18% of brands say they have all the people and skills they need, and 74% say they need outside help to interpret results and turn them into budget decisions.
AI is widespread but rarely central. 79% of brands use AI for measurement, mostly for summarizing results and forecasting; only 16% say AI plays a central role. The real blockers are data quality at 55%, integration with decision systems at 50% and trust in results at 40%. An AI agent summarizing platform-reported ROAS just summarizes the overcount faster.
What to do about it
Unification is not about pulling every number into one dashboard. It means calibration: causal marketing mix modeling, geo-based incrementality tests and incrementality-adjusted attribution should tell the same story. Otherwise, you are just looking at conflicting numbers side by side.
Three places to start:
- Audit platform ROAS against incremental ROAS. Ask for iROAS, not just last-click or reported returns, before you move budget.
- Run one geo lift test on a high-spend channel before the next budget cycle.
- Align marketing and finance on one cross-channel metric and definition, so both teams plan from the same evidence.
The sponsor context matters: Lifesight sells independent measurement, and its own client claims in the report come without published methodology. The survey fieldwork, though, was run by Winterberry Group and describes a real, senior sample.
Source: PPC Land
