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Advertising analytics is the study and practice of measuring, modeling, and optimizing the effectiveness of advertising across channels. Books in this category explain how to collect and connect campaign, audience, and customer-journey data; define and track KPIs such as reach, frequency, CTR, CPA, LTV, and ROAS; and build dashboards that translate metrics into decisions. They cover methods like A/B testing, incrementality and lift studies, attribution (rules-based and algorithmic), and media mix modeling, drawing on statistics, econometrics, and machine learning to forecast outcomes and allocate budgets. Additional topics include audience segmentation and targeting, creative performance measurement, spend optimization, experimentation design, and the data quality, governance, and privacy considerations of a post-cookie world. This category serves marketers, analysts, and students seeking practical frameworks and case studies for turning advertising data into measurable business results.

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