Big Data Analytics for Creative Marketers: Money Spinner

By Jieun Kang

This book is mainly for marketers who want to drive business growth using big data. Many people talk about big data analysis and many want to get strategic insight from data analysis, but it's not easy and not many best practices are introduced. In this situation, I dare say that I am the one who has been building a career in marketing analytics and want to share my experience.

• Language: English
• Publisher: Tellwell Talent
• Release date: Oct 12, 2021
• ISBN: 9780228850908

Jieun Kang

Jieun KangMarketing ScientistJieun Kang is a CRM expert and a marketing scientist who conducts marketing based on data analysis. She majored in atmospheric sciences in university and started to work as a dispatcher for Asiana Airlines. One day she told her friend to fly Asiana Airlines more frequently, but he refused, since he had more mileage with other airlines. This was a pivotal moment for her and began her passion for marketing. Then she studied marketing in graduate school and started career as a CRM specialist at LG Electronics. She has been building career in Samsung, Hyundai and so on.She creates marketing programs and analyzes data of various industries, such as retail, finance, and manufacturing. She provides special lectures regarding marketing analytics and career counselling in universities. She is the author of the book "To You Who Think of Changing Jobs".

Book preview

Big Data

Analytics

for

Creative

Marketers

Money Spinner

Jieun Kang

Big Data Analytics for Creative Marketers

Copyright © 2021 by Jieun Kang

All rights reserved. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the author, except in the case of brief quotations embodied in critical reviews and certain other non-commercial uses permitted by copyright law.

Tellwell Talent

www.tellwell.ca

ISBN

978-0-2288-5089-2 (Hardcover)

978-0-2288-5088-5 (Paperback)

978-0-2288-5090-8 (eBook)

To my international readers,

I am very happy to now have my book published in English. It has already been published in Korean, and I feel as if my dreams have come true. While I was studying data analysis in the United States, I realized that the data analytics I had practiced in Korea was going in the same direction as the global one. For this reason, I have decided to publish an English version of the book, as I wanted to share my invaluable experience with readers from around the world.

After publishing this book in Korea, I received a lot of feedback saying it is compact yet useful and informative. We hope this book will be handy to those who study or work in the field of data analytics in the United States and other English-speaking countries around the world.

September 2021

Contents

Prologue

01 Data Story

1. The Importance of Data Cannot Be Overstated

2. Moments When Data Is Valuable

3. How Data Tricks Us

4. History of Data Science

5. Current Level of Data Utilization

6. Data Reality Awareness Time

02 Data Analyst Story

1. The Role of Data Analysts and the Changing Trends

2. Essential Competencies of Data Analysts

3. Recruitment Status and Requirements Specification for Data Analysts in the Job Market

4. Popularity of Data Analysts

5. How to Become a Data Analyst that Everyone Wants

03 Customer Relationship Management (CRM) Story

1. The Evolution of CRM, Another Name for Big Data Analysis

2. CRM Big Picture and Strategy

3. Integration of All Customer Data—Building Customer Single View

4. CRM Strategy Differentiated According to Industry Characteristics

04 Everything in Data Analysis Practice

1. Identification of Data Analysis Objectives

2. Data Status Diagnosis and Acquisition Plan

3. Data Analysis Process

4. Data Analysis Tool

5. Deriving insights through data analysis

6. Creating Analysis Result Reports

05 From Marketing Program Design to Result Analysis

1. Marketing Programming and Implementation

2. Miscellaneous Issues Encountered in Marketing

3. Marketing Program Result Analysis

06 Marketing Cases through Data Analysis

1. Case 1 | (Finance) Customer Segmentation and Customer Retention Strategy for Re-contracting

2. Case 2 | (Manufacturing) Repurchase Program through Data Analysis

3. Case 3 | (Manufacturing/Financial Partnership Marketing) Co-target Marketing

4. Characteristics of Data Analysis Marketing Identified through Cases

5. Online vs. Offline from Data Analysis and Marketing Perspectives

6. Case 4 | (Online Retail) Real-time Personalized Recommendation Service

7. Case 5 | (Online Retail) Mobile Personalization

07 Challenges and Remaining Tasks of Big Data Analysis

Epilogue

For marketers who are struggling with data,

for marketers who want to do data analytics,

and for those who want to easily understand it.

Prologue

I call myself a marketing scientist or a customer relationship management (CRM) expert.

If you call me a data scientist, I will fix the issue as a marketing scientist. Often a person who simply pulls data from a tool is called a data scientist. Marketing specialist, CRM specialist, data marketing specialist, and big data analyst are used interchangeably.

If you look up data science on Wikipedia, you will read, Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data science is related to data mining and big data. In other words, data science is a field that involves extracting knowledge and insights from structured or unstructured data using scientific methods, processes, algorithms, and systems, and it is also related to data mining and big data. Therefore, if you call yourself a data scientist, you are a person who extracts knowledge and insights from data through a scientific method. This definition focuses on extracting knowledge and insights rather than simply extracting data from the system, but in reality, it is widely used to denote a person who simply connects to a data warehouse and knows how to extract data using an analysis tool.

Therefore, I define myself as a person who extracts knowledge and insights, which are unique areas and capabilities of analysts from the data, not simply a person who extracts data. That’s why I want to define it with the term marketing scientist rather than the name data scientist.

If I were to pick one word out of the term marketing scientist, I would focus on marketing. I use data to do marketing, and I use data scientifically for the process, which is the ultimate purpose for marketing. The ultimate purpose of marketing is to make money, after all. It uses data to conduct sophisticated marketing to make money scientifically and systematically. Marketing scientists make a remarkable contribution to business by professionally using data. Data has existed in the past and has been used in business, but few people have done it well or have succeeded. In the meantime, I write this book with pride that I have dared to do this kind of marketing properly.

Most of the big data-related books on the market tell developers how to analyze data using languages such as R and Python. Many books introduce actual cases of marketing by analyzing data. Why are there no books that discuss big data analysis from a marketer’s practical standpoint? I wish I could meet someone who wrote such a book. I’d like to have a passionate conversation with him or her, but I haven’t met such a person yet. So I am lonely. Having said that, I also know the reason why such a person is not around. Companies have a strong need to analyze data and execute marketing, but very few companies implement it consistently and steadily. Leaders are at risk if there is no performance in the short term because marketing is a product of constant activity. It is very difficult for big data marketing to achieve results in a short period. So while trying it, the person in charge changes, everything fizzles out, and this repetitive cycle continues. It is only possible to see results through data-based marketing when the leader’s philosophy and momentum for data marketing are present, because data marketing is more like herbal medicine than Western medicine.

In this climate, I have been working on marketing using data as a joke of my own choice or fate. After studying customer loyalty in graduate school, I started with CRM in manufacturing and then worked in finance, online retail, and IT services. I have been fiercely contemplating making money with data, and as an in-house CRM expert, I have provided special CRM lectures at seminars where I was invited by partner companies to train the employees preparing to become expatriates. I have also given special marketing lectures on CRM at Yonsei University and Duksung Women’s University. Now I would like to share these experiences with those who want to become big data analytics experts through this book. Therefore, the main contents of this book will also focus on the process of making and executing marketing programs and ultimately making money through data analytics rather than data analytics itself.

Earlier this year, Seoul National University established the Graduate School of Data Science. It was revealed that 257 people applied for the master’s program, which selects 40 people. That is when I realized its popularity. At the company I joined as an experienced employee, expressions such as I want to be a data scientist and I want to learn about the field and build a career were shared openly among colleagues who had a lot of experience in various positions in the group.

Many people want to be data scientists. In this challenging environment of data marketing, I would like to share my experiences and methods in my area of expertise with those who want to do data-based marketing from the standpoint of an extremely realistic marketing practitioner, not a developer. Specifically, I approach it from a pragmatic point of view to find the answer to how to start when a person in the field of work was suddenly instructed from above to conduct data analysis and marketing.

I would like to thank my seniors and colleagues at various companies for helping and teaching me to dig a single well called a CRM, for starting my career in manufacturing to finance, online retail, and IT service companies.

July 2020

Jieun Kang

01

Data Story

1. The Importance of Data Cannot Be Overstated

2. Moments When Data Is Valuable

3. How Data Tricks Us

4. Data Science History

5. Current Level of Data Utilization

6. Data Reality Awareness Time

1. The Importance of Data Cannot Be Overstated

  The power of data

Reviews for Big Data Analytics for Creative Marketers

[Tiffany Moonsammy · Rating: 3 out of 5 stars]

This books provide text book like information providing information on how to go about data analysis as a marketer. The flow charts were useful. However some concepts were introduced but only at a surface level leaving a lot of gaps making it difficult to follow.