Neuware -Marketing paradigm is becoming customer centric. Every day billions of interactions and transactions occur, generating huge quantities of data. Customers are analysed though the lenses of marketing, with the data that those organizations record, integrate and manage. Today analytical tools include new statistical learning developments, such as machine learning, to generate new models gaining customer insights and supporting marketing decisions. A review of recent research in marketing showed a wide variety of case studies using machine learning methods from customer acquisition analysis, to customer development and customer retention issues. Machine learning models are able to process large data sets, including structured and unstructured data, for prediction and feature extraction models. In an environment where Artificial Intelligence is taking on a large part of the analytical work, companies should consider integrating these methodologies and tools into their marketing teams.Books on Demand GmbH, �berseering 33, 22297 Hamburg 96 pp. Englisch.

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Titel: Machine Learning in Marketing
Verlag: LAP LAMBERT Academic Publishing Jan 2021
Ver�ffentlichungsdatum: 2021
Sprache: Englisch
ISBN-10: 6203202010
ISBN-13: 9786203202014
Bindung: Taschenbuch
Zustand: Neu

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Marketing paradigm is becoming customer centric. Every day billions of interactions and transactions occur, generating huge quantities of data. Customers are analysed though the lenses of marketing, with the data that those organizations record, integrate and manage. Today analytical tools include new statistical learning developments, such as machine learning, to generate new models gaining customer insights and supporting marketing decisions. A review of recent research in marketing showed a wide variety of case studies using machine learning methods from customer acquisition analysis, to customer development and customer retention issues. Machine learning models are able to process large data sets, including structured and unstructured data, for prediction and feature extraction models. In an environment where Artificial Intelligence is taking on a large part of the analytical work, companies should consider integrating these methodologies and tools into their marketing teams.

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