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: Text

TextSeries: 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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Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Books	KsTU Library Reference	HF5415.127 .V453 2021 (Browse shelf(Opens below))	1	Available		112720
Books	KsTU Library General Stacks	HF5415.127 .V453 2021 (Browse shelf(Opens below))	2	Available		113786

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Includes bibliographical references and index.

"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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