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Clustering and Segmentation - Green, Paul E.

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    Brand new, In English, Fast shipping from London, UK; Tout neuf, en anglais, expédition rapide depuis Londres, Royaume-Uni;ria9781636514673_dbm

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        Avis sur Clustering And Segmentation Format Relié  - Livre Économie

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        Présentation Clustering And Segmentation Format Relié

         - Livre Économie

        Livre Économie - Green, Paul E. - 01/05/2025 - Relié - Langue : Anglais

        . .

      • Auteur(s) : Green, Paul E. - Publishers, Vibrant
      • Editeur : Vibrant Publishers
      • Langue : Anglais
      • Parution : 01/05/2025
      • Format : Moyen, de 350g à 1kg
      • Nombre de pages : 444.0
      • ISBN : 1636514677



      • Résumé :
        Clustering and Segmentation by Paul Green offers a rigorous yet practical exploration of how marketers and analysts can discover meaningful groups within customer data. This book demystifies the statistical techniques behind cluster analysis and market segmentation, equipping readers with the tools to identify patterns in consumer behavior, preferences, and needs. With applications ranging from customer profiling to product customization, the book emphasizes the importance of using segmentation to guide targeted marketing strategies. Green breaks down complex algorithms such as hierarchical, k-means, and latent class clustering with real-world examples, while also addressing validation methods and common pitfalls. Emphasizing interpretability and actionability, the book shows how segmentation outputs can be translated into clear business strategies and messaging. Whether you're a marketing researcher, data analyst, or business strategist, this book provides a strong foundation in customer segmentation and its relevance in today's data-driven landscape. It's a vital reference for anyone looking to enhance personalization, improve targeting, and drive market success through analytical precision....

        Biographie:
        Paul E. Green was Emeritus Professor of Marketing at The Wharton School, The University of Pennsylvania. Prof. Green was often called the father of conjoint analysis, the powerful predictive statistical technique and backbone of market research. Conjoint analysis allows marketing managers to make accurate decisions about what products and services to sell-and helped make Green marketing's most cited author. The marketing discipline's familiarity with the utilization of Bayesian statistics, multidimensional scaling, clustering, and analysis of qualitative data are due in part to the pioneering works of Prof. Green. The most prolific of marketing scholars with 16 books and over 200 articles, his influence on the marketing discipline ranges far beyond his ground breaking inspired writings. As a creative researcher, he stimulated the design and implementation of numerous innovative studies for the solution of real-world problems. Prof. Green received all of the major marketing awards, including the Parlin Award for Advancement of Science in Marketing, the AMA/Irwin Marketing Educator of the Year Award, The Outstanding Marketing Educator Award, and the Lifetime Achievement in Marketing Research Award. In 1996 the Journal of Marketing Research established the Paul E. Green Award for the best article in the Journal of Marketing Research that demonstrates the greatest potential to contribute significantly to the practice of marketing research. He passed away on September 21, 2012....

        Sommaire:
        Clustering and Segmentation by Paul Green offers a rigorous yet practical exploration of how marketers and analysts can discover meaningful groups within customer data. This book demystifies the statistical techniques behind cluster analysis and market segmentation, equipping readers with the tools to identify patterns in consumer behavior, preferences, and needs. With applications ranging from customer profiling to product customization, the book emphasizes the importance of using segmentation to guide targeted marketing strategies. Green breaks down complex algorithms such as hierarchical, k-means, and latent class clustering with real-world examples, while also addressing validation methods and common pitfalls. Emphasizing interpretability and actionability, the book shows how segmentation outputs can be translated into clear business strategies and messaging. Whether you're a marketing researcher, data analyst, or business strategist, this book provides a strong foundation in customer segmentation and its relevance in today's data-driven landscape. It's a vital reference for anyone looking to enhance personalization, improve targeting, and drive market success through analytical precision....

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