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New framework models business impact of generative AI marketing

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced Generative Marketing Mix Modeling (GMMM), a new framework designed to quantify the business impact of generative artificial intelligence in marketing. This model specifically addresses the challenge of measuring user exposure and notice of brand names within AI-generated content and sponsored placements. GMMM utilizes data on generated answers, user interactions, and advertising records to estimate causal effects, enabling firms to better understand the ROI of their generative AI marketing strategies. AI

IMPACT Provides a framework for measuring the ROI of generative AI in marketing campaigns.

RANK_REASON Academic paper introducing a new modeling framework. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework models business impact of generative AI marketing

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Academic paper introducing a new modeling framework. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Masahiro Kato, Daiki Honma, Taka Kato ·

    Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact

    arXiv:2609.11915v1 Announce Type: new Abstract: Generative artificial intelligence changes how firms reach customers, but standard marketing data do not record how often users see and notice a firm's name in generated answers. We develop Generative Marketing Mix Modeling (GMMM) t…

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