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Marketing analytics : essential tools for data-driven decisions / Rajkumar Venkatesan, Paul W. Farris, and Ronald T. Wilcox.

By: Venkatesan, Rajkumar [author.]Contributor(s): Farris, Paul W [author.] | Wilcox, Ronald T [author.]Material type: TextTextSeries: Darden business publishingPublisher: Charlottesville : Darden Business Publishing, University of Virginia Press, 2021Description: x, 294 pages : illustrations ; 24 cmContent type: text Media type: unmediated Carrier type: volumeISBN: 9780813945156Subject(s): Marketing -- Management | Marketing -- Statistical methods | Marketing researchAdditional physical formats: Online version:: Marketing analyticsDDC classification: 658.8/3 LOC classification: HF5415.127 | .V453 2021
Contents:
Resource Allocation -- Cluster Analysis -- Conjoint Analysis -- Linear Regression -- Customer Lifetime Value -- Marketing Experiments -- Paid Search Advertising -- Text Analytics -- Logistic Regression -- Recommendation Systems -- Automation of Marketing Models -- Implementing Marketing Analytics.
Summary: "A textbook on marketing analytics, this book provides practical predictive models in marketing. It strives to strike a balance between highly sophisticated models and managerial relevance. Through the diverse business cases in the book, readers learn how to connect marketing inputs to customer behavior and how to use historic information, experiments, or heuristics to develop forward-looking what-if scenarios and predictive models. The real-life cases include real data, enabling readers to take a hands-on approach to the analysis"-- Provided by publisher.
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Includes bibliographical references and index.

Resource Allocation -- Cluster Analysis -- Conjoint Analysis -- Linear Regression -- Customer Lifetime Value -- Marketing Experiments -- Paid Search Advertising -- Text Analytics -- Logistic Regression -- Recommendation Systems -- Automation of Marketing Models -- Implementing Marketing Analytics.

"A textbook on marketing analytics, this book provides practical predictive models in marketing. It strives to strike a balance between highly sophisticated models and managerial relevance. Through the diverse business cases in the book, readers learn how to connect marketing inputs to customer behavior and how to use historic information, experiments, or heuristics to develop forward-looking what-if scenarios and predictive models. The real-life cases include real data, enabling readers to take a hands-on approach to the analysis"-- Provided by publisher.

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