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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…mehr

Produktbeschreibung
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.
Autorenporträt
José M. Ramos-Henríquez es Profesor Adjunto de Marketing, Departamento de Administración de Empresas e Historia Económica, Universidad de La Laguna. Es doctor en Marketing (Universidad de La Laguna), y máster en Ingeniería de Telecomunicación (Universidad Politécnica de Madrid). Trabajó durante una década en Accenture. Su investigación se centra en el marketing de servicios.