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The Channels Marketers Cannot Measure Are the Ones They Are Starving

Marketers are systematically starving the channels they cannot measure, and new research suggests the bias is now large enough to distort entire budgets. A study by mobile measurement…

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Photo: Google Nexus S smartphone.jpg, CC BY 2.0, via Wikimedia Commons

Marketers are systematically starving the channels they cannot measure, and new research suggests the bias is now large enough to distort entire budgets. A study by mobile measurement company AppsFlyer with EMARKETER, surveying 157 U.S. agency and brand leaders in May 2026, found that 58.6 percent of marketers believe their organizations underinvest in channels they cannot adequately measure. Social media was named the worst attribution blind spot by half of respondents, and connected TV by nearly half.

The mechanism is pressure. As AI systems assume more control over budget decisions, the quality of measurement signals determines where money flows. Marketers under significant return-on-investment pressure withhold spend from channels they cannot prove work, leaving potential revenue unclaimed — while automated tools risk amplifying flawed data at scale, pouring budget into whatever happens to be trackable rather than whatever happens to be effective.

The context makes the trap deeper. Gartner’s 2026 marketing technology research found 73 percent of marketing leaders reporting low confidence in their attribution data, up from 54 percent in 2023, while industry estimates suggest roughly 61 percent of digital touchpoints are now “dark” or untrackable thanks to privacy tools, AI intermediaries and cross-device journeys. Traditional frameworks built on cookies, pixels and last-click logic were designed for a web that no longer exists: journeys now pass through AI assistants, retail shelves, creator content and televisions, few of which produce a click to count.

The industry’s answer is triangulation rather than a single successor metric. Multi-touch attribution remains useful for day-to-day optimization where user-level data exists. Marketing mix modeling — aggregate, privacy-safe and increasingly fast — is absorbing the strategic questions; modern AI-powered models run in weeks rather than the annual cycle of the past. Incrementality testing supplies the causal ground truth through holdouts and geographic experiments. Practitioners describe the three together as a measurement triangle, each method covering the others’ blind spots.

The newest attempt to keep measurement honest is structural: Google, Meta, Moloco and Unity have backed AppsFlyer in an investment designed to preserve an independent mobile attribution provider even as platforms grade their own homework. For brand teams, the practical takeaway is diagnostic. Pull your last budget and mark every channel by how confidently you can measure it. If the measurability ranking and the spending ranking look suspiciously alike, you have found the bias the research describes — and probably your largest pool of unclaimed growth.

Until the triangle is in place, treat every platform-reported return figure as a claim awaiting corroboration — including the flattering ones, which are precisely the figures most likely to be believed, budgeted and wrong.

Related reading: Three in Four Marketers Say Their Measurement Is Broken. The IAB Puts a Price on Fixing It. · AI Agents Move Into the Marketing Stack: Breeze, Agentforce and the End of the Blank Field

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