Introduction to Algorithmic Marketing is a comprehensive guide to advanced marketing automation for marketing strategists, data scientists, product managers, and software engineers. It summarizes various techniques tested by major technology, advertising, and retail companies, and it glues these methods together with economic theory and machine learning. The book covers the main areas of marketing that require programmatic micro-decisioning targeted promotions and advertisements, eCommerce search, recommendations, pricing, and assortment optimization.
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good basic intro to application of models (optimization, causal inference, Markov Chain, regression, NBayes, LSA, etc) in the context of marketing, relevant marketing metrics, etc // needs digging into details, papers and models // tech side too general and out-dated..
评分good basic intro to application of models (optimization, causal inference, Markov Chain, regression, NBayes, LSA, etc) in the context of marketing, relevant marketing metrics, etc // needs digging into details, papers and models // tech side too general and out-dated..
评分非常好的入门介绍，对于promotion, ads 有了全新的认识。不足之处是没有实际案例支持，难以上手
评分good basic intro to application of models (optimization, causal inference, Markov Chain, regression, NBayes, LSA, etc) in the context of marketing, relevant marketing metrics, etc // needs digging into details, papers and models // tech side too general and out-dated..
评分good basic intro to application of models (optimization, causal inference, Markov Chain, regression, NBayes, LSA, etc) in the context of marketing, relevant marketing metrics, etc // needs digging into details, papers and models // tech side too general and out-dated..
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