Data Science for Marketing Analytics : Achieve Your Marketing Goals with the Data Analytics Power of Python [Repost]

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

The book will start 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 advance, 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 the techniques you’ve learned to create a churn model for modeling customer product choices.

By the end of this book, you’ll 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 choices
Optimize classification algorithms to extract maximal information

This book is designed for developers and marketing analysts who are looking to use new, more sophisticated tools in their marketing analytics efforts. Prior experience of coding in Python and knowledge of high school level mathematics will be helpful. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.


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