Machine Learning in Marketing
Customer data growth, new methods, and myriad of applications
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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 cu...
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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