Observed Signal · Sep 30, 2026 · Opinion · Source: AdExchanger · Impact: 2/5 · Sentiment: Neutral
MMMs Can Tell You If CTV Worked.
Marketing mix models (MMMs) are gaining attention as an alternative to click-centric measurement, particularly for Connected TV (CTV). They can indicate whether CTV contributed to growth, but a channel-level readout often hides significant operational complexity and can be misleading. A campaign may run across numerous networks, segments, and devices, and the same channel label can encompass very different executions. Using MMMs as arbiters of judgment rather than calibration tools can lead to wrong budget decisions, especially when geo-tests are contaminated by imperfect location signals. The article argues that MMMs are a valuable counterweight to platform-reported attribution but should be sequenced with more granular diagnostics to understand why performance occurred, looking at network mix, audience, frequency, and creative. The goal is to use MMMs to sharpen questions rather than end them.
The article provides an opinion on the limitations of MMMs for CTV, which is relevant for measurement discussions but does not announce a new product or major industry shift.
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Key Takeaways & Evidence Grounding
- MMMs are increasingly used to measure CTV effectiveness.
- MMMs can indicate whether a channel worked but not why.
- CTV campaigns often run across many networks, segments, and devices.
- Geo-testing can be contaminated by imperfect location signals.
- MMMs serve as calibration tools, not arbiters of judgment.
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Five Lessons from Marketing Mix Modelling for Marketers
An opinion piece by Tobin Thomas (CEO & Founder, Lifesight) published on VideoWeek argues that modern marketing mix modelling (MMM) corrects common measurement biases by capturing brand and cross-media effects that last-click attribution misses. The article lists five core insights: brand effects (TV/video/audio) are measurable via MMM; high ROAS channels can have low incremental value; channels interact as a system rather than acting independently; overspending can reduce marginal returns; and contemporary MMM is sufficiently advanced to support cross-media decision-making across CTV, video, social, retail media, search and offline channels. The author emphasizes acting on model outputs — including defunding beloved channels when models indicate low contribution — rather than simply decorating dashboards.
MMM and MTA Both Needed for 2026 Budgets
A MarTech contributor (via MarTechBot Q&A) argues that as third-party cookies disappear and B2B buyer journeys shift into private channels, marketers should use both Multi-Touch Attribution (MTA) and Marketing Mix Modeling (MMM) in 2026. The piece positions MTA as a tactical “microscope” for short-term campaign optimization and MMM as a strategic “telescope” for privacy-safe, top-down budget allocation that captures untrackable channels (podcasts, events, brand). It recommends a unified measurement framework or “triangulation” that compares MMM and MTA outputs, and advises supplementing quantitative models with qualitative inputs such as “How did you hear about us?” self-reported attribution to account for the “dark funnel.” The article was published on 2026-06-15 and notes MarTech is owned by Semrush.
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