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

Yoon Hyup Hwang

AU$53.99

4.1 (14 Ratings)

eBook Mar 2019 464 pages 1st Edition

Renews at AU$24.99p/m

Yoon Hyup Hwang

AU$53.99

4.1 (14 Ratings)

eBook Mar 2019 464 pages 1st Edition

Renews at AU$24.99p/m

Renews at AU$24.99p/m

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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

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Product Details

Publication date : Mar 29, 2019

Length: 464 pages

Edition : 1st

Language : English

ISBN-13 : 9781789348828

Category :

Data

Languages :

Python

Concepts :

Data Science

Tools :

TensorFlow

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19 Chapters

Section 1: Introduction and Environment Setup

Data Science and Marketing

Technical requirements

Trends in marketing

Applications of data science in marketing

Setting up the Python environment

Setting up the R environment

Summary

Section 2: Descriptive Versus Explanatory Analysis

Key Performance Indicators and Visualizations

KPIs to measure performances of different marketing efforts

Computing and visualizing KPIs using Python

Computing and visualizing KPIs using R

Summary

Drivers behind Marketing Engagement

Using regression analysis for explanatory analysis

Regression analysis with Python

Regression analysis with R

Summary

From Engagement to Conversion

Decision trees

Decision trees and interpretations with Python

Decision trees and interpretations with R

Summary

Section 3: Product Visibility and Marketing

Product Analytics

The importance of product analytics

Product analytics using Python

Product analytics using R

Summary

Recommending the Right Products

Collaborative filtering and product recommendation

Building a product recommendation algorithm with Python

Building a product recommendation algorithm with R

Summary

Section 4: Personalized Marketing

Exploratory Analysis for Customer Behavior

Customer analytics – understanding customer behavior

Conducting customer analytics with Python

Conducting customer analytics with R

Summary

Predicting the Likelihood of Marketing Engagement

Predictive analytics in marketing

Evaluating classification models

Predicting the likelihood of marketing engagement with Python

Predicting the likelihood of marketing engagement with R

Summary

Customer Lifetime Value

CLV

Evaluating regression models

Predicting the 3 month CLV with Python

Predicting the 3 month CLV with R

Summary

Data-Driven Customer Segmentation

Customer segmentation

Clustering algorithms

Segmenting customers with Python

Segmenting customers with R

Summary

Retaining Customers

Customer churn and retention

Artificial neural networks

Predicting customer churn with Python

Predicting customer churn with R

Summary

Section 5: Better Decision Making

A/B Testing for Better Marketing Strategy

A/B testing for marketing

Statistical hypothesis testing

Evaluating A/B testing results with Python

Evaluating A/B testing results with R

Summary

What's Next?

Recap of the topics covered in this book

Real-life data science challenges

More machine learning models and packages

Summary

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About the author

Yoon Hyup Hwang

Yoon Hyup Hwang is a seasoned data scientist in the marketing and financial sectors with expertise in predictive modeling, machine learning, statistical analysis, and data engineering. He has 8+ years' experience of building numerous machine learning models and data products using Python and R. He holds an MSE in computer and information technology from the University of Pennsylvania and a BA in economics from the University of Chicago. In his spare time, he enjoys practicing various martial arts, snowboarding, and roasting coffee. Born and raised in Busan, South Korea, he currently works in New York and lives in New Jersey with his artist wife, Sunyoung, and a playful dog, Dali (named after Salvador Dali).

See other products by Yoon Hyup Hwang

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

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