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Hands-On Data Science for Marketing
Hands-On Data Science for Marketing

Hands-On Data Science for Marketing: Improve your marketing strategies with machine learning using Python and R

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Hands-On Data Science for Marketing

Section 1: Introduction and Environment Setup

This section will introduce you to data science for marketing and setting up Python and R environments for the upcoming projects.

This section consists of the following chapter:

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Key benefits

  • Understand how data science drives successful marketing campaigns
  • Use machine learning for better customer engagement, retention, and product recommendations
  • Extract insights from your data to optimize marketing strategies and increase profitability

Description

Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies. This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R. By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business.

Who is this book for?

If you are a marketing professional, data scientist, engineer, or a student keen to learn how to apply data science to marketing, this book is what you need! It will be beneficial to have some basic knowledge of either Python or R to work through the examples. This book will also be beneficial for beginners as it covers basic-to-advanced data science concepts and applications in marketing with real-life examples.

What you will learn

  • Learn how to compute and visualize marketing KPIs in Python and R
  • Master what drives successful marketing campaigns with data science
  • Use machine learning to predict customer engagement and lifetime value
  • Make product recommendations that customers are most likely to buy
  • Learn how to use A/B testing for better marketing decision making
  • Implement machine learning to understand different customer segments
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Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 29, 2019
Length: 464 pages
Edition : 1st
Language : English
ISBN-13 : 9781789346343
Category :
Languages :
Concepts :
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Product feature icon Download this book in EPUB and PDF formats
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Product feature icon AI Assistant (beta) to help accelerate your learning
Estimated delivery fee Deliver to Belgium

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Product Details

Publication date : Mar 29, 2019
Length: 464 pages
Edition : 1st
Language : English
ISBN-13 : 9781789346343
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Table of Contents

19 Chapters
Section 1: Introduction and Environment Setup Chevron down icon Chevron up icon
Data Science and Marketing Chevron down icon Chevron up icon
Section 2: Descriptive Versus Explanatory Analysis Chevron down icon Chevron up icon
Key Performance Indicators and Visualizations Chevron down icon Chevron up icon
Drivers behind Marketing Engagement Chevron down icon Chevron up icon
From Engagement to Conversion Chevron down icon Chevron up icon
Section 3: Product Visibility and Marketing Chevron down icon Chevron up icon
Product Analytics Chevron down icon Chevron up icon
Recommending the Right Products Chevron down icon Chevron up icon
Section 4: Personalized Marketing Chevron down icon Chevron up icon
Exploratory Analysis for Customer Behavior Chevron down icon Chevron up icon
Predicting the Likelihood of Marketing Engagement Chevron down icon Chevron up icon
Customer Lifetime Value Chevron down icon Chevron up icon
Data-Driven Customer Segmentation Chevron down icon Chevron up icon
Retaining Customers Chevron down icon Chevron up icon
Section 5: Better Decision Making Chevron down icon Chevron up icon
A/B Testing for Better Marketing Strategy Chevron down icon Chevron up icon
What's Next? Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.1
(14 Ratings)
5 star 64.3%
4 star 7.1%
3 star 7.1%
2 star 14.3%
1 star 7.1%
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Cliente Amazon May 12, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very practical book. Recommended marketers and data scientists working in marketing.
Amazon Verified review Amazon
IP May 18, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I am a data scientist at MBB and have done numerous marketing related projects. However, most of my team's approach was rather ad-hoc so I was looking for a structured way of looking at those problems. This book walked me through from start to end and covered most of the things that I needed to perform data science for marketing. I think this book will help data scientists in all experience levels; if you are new to data science, this book has a step-by-step setup and coding guide with examples. If you are an experienced data scientist, this book will help you to understand key concepts in marketing analytics as well as a general marketing strategy and know-how. All in all, I recommend this book to any data scientist who wants to learn more about both data science and marketing.
Amazon Verified review Amazon
jeeb Mar 29, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Perfect for someone who is looking for a data science starter kit in the field of marketing. Highly recommend.
Amazon Verified review Amazon
Tae Uk Apr 27, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
As a college senior who studies data science, I found this book is super useful. This book provides a variety of real-world use of data analysis in marketing, where you can apply your knowledge in theory, something that you can’t learn from class. With applications of basic simple regression analysis to advanced machine learning, this book will get you engaged to practice many techniques that are applied to key researches and analyses in marketing.Another huge thing about this book is that it is very engaging and comprehensible. With well-organized order in each chapter, the author guides you challenging materials with nice step by step explanation to almost effortlessly help you learn key functions in both Python and R languages. If you want to get your feet wet or brush up your data analytic expertise in marketing, I highly recommend this book!!
Amazon Verified review Amazon
James White Jul 30, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I bought this book having spent the last 5 years working in data analytics and it was good to see something specific to marketing. I enjoyed going through the coding examples (every chapter features code in both Python and R). The code was about 90 percent accurate with a few typos or misprints here and there. I would encourage you to download the answers and try out the examples in one or both programming languages. I certainly see where you could use these examples, learn and either put together something on your laptop or work on your favorite public cloud. You do need at least some understanding of programming and willingness and ability to debug coding mistakes. This was a great tutorial if you have the willingness to roll up your sleeves and write some code.
Amazon Verified review Amazon
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