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Tommy Blanchard - Data Science for Marketing Analytics: Achieve your marketing goals with the data analytics power of Python

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Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results

Key Features
  • Study new techniques for marketing analytics
  • Explore uses of machine learning to power your marketing analyses
  • Work through each stage of data analytics with the help of multiple examples and exercises
  • Book Description

    Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments.

    The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, youll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, youll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, youll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, youll apply these techniques to create a churn model for modeling customer product choices.

    By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions.

    What you will learn
  • Analyze and visualize data in Python using pandas and Matplotlib
  • Study clustering techniques, such as hierarchical and k-means clustering
  • Create customer segments based on manipulated data
  • Predict customer lifetime value using linear regression
  • Use classification algorithms to understand customer choice
  • Optimize classification algorithms to extract maximal information
  • Who this book is for

    Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. Itll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.

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    Data Science for Marketing Analytics

    Achieve your marketing goals with the data analytics power of Python

    Tommy Blanchard

    Debasish Behera

    Pranshu Bhatnagar

    Data Science for Marketing Analytics

    Copyright 2019 Packt Publishing

    All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

    Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

    Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

    Authors: Tommy Blanchard, Debasish Behera, Pranshu Bhatnagar

    Technical Reviewer: Dipankar Nath

    Managing Editor: Neha Nair

    Acquisitions Editor: Kunal Sawant

    Production Editor: Samita Warang

    Editorial Board: David Barnes, Ewan Buckingham, Shivangi Chatterji, Simon Cox, Manasa Kumar, Alex Mazonowicz, Douglas Paterson, Dominic Pereira, Shiny Poojary, Saman Siddiqui, Erol Staveley, Ankita Thakur, and Mohita Vyas

    First Published: March 2019

    Production Reference: 1290319

    ISBN: 978-1-78995-941-3

    Published by Packt Publishing Ltd.

    Livery Place, 35 Livery Street

    Birmingham B3 2PB, UK

    Table of Contents
    Chapter 1:
    Chapter 2:
    Chapter 3:
    Chapter 4:
    Chapter 5:
    Chapter 6:
    Chapter 7:
    Chapter 8:
    Chapter 9:
    Preface
    About

    This section briefly introduces the authors, the coverage of this book, the technical skills you'll need to get started, and the hardware and software requirements required to complete all of the included activities and exercises.

    About the Book

    Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of it based on the segments.

    The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices.

    By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions.

    About the Authors
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