Observed Signal · May 4, 2026 · Panel Discussion · Source: Adweek · Impact: 2/5 · Sentiment: Positive

Marketers Seek Clean Incrementality Measurements

Executive Signal Summary

An ADWEEK House panel co-hosted with Fetch examined the challenges brands face when measuring incremental impact from marketing. Panelists from CAVA, Nestlé, The Hershey Company, Haleon, Digitas and Fetch emphasized that incrementality is contested because consumer behavior is fragmented, teams often claim the same outcomes, and measurement signals from partners can conflict. Speakers argued randomized controlled trials remain the most reliable method but require discipline and time (brands may need six to eight months to see impact). Melissa Berger noted only about 8% of brands have formal incrementality programs. The discussion stressed the need for honest communication between brands and partners, careful experimental design, aligned timelines and realistic expectations about what measurement can prove.

Polaris7 AgentPolaris7 Strategic Assessment
High Confidence

Incrementality measurement affects how brands allocate media budgets and validate campaign effectiveness; the discussion highlights practical measurement constraints (RCTs, timelines, partner alignment) but does not announce major platform or policy changes.

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Key Takeaways & Evidence Grounding

  • ADWEEK House hosted a group chat on incrementality co-hosted with Fetch.
  • Melissa Berger (Digitas) said only 8% of brands have a formal incrementality program.
  • Geoff Matthews (Fetch) stated randomized control trials are the most reliable way to isolate marketing impact.
  • Sandra Abla (CAVA) said brands often need six to eight months to determine whether marketing drives impact.
  • Panelists included representatives from Fetch, CAVA, Nestlé, The Hershey Company, Digitas, Haleon and ADWEEK.
Primary Source Grounding & Direct Attribution
Direct Origin Attribution
Primary Reporting: Adweek•Published: May 4, 2026
Original Coverage Title: “How Marketers Can Get Clean Incrementality Measurements in a Messy World”

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