Chapter 1 Preface

1.1 Welcome to MKTG 4060

Please be aware that these course notes are still in progress !!! This is an early draft. This mannual is copyrighted under Creative Commons Attribution-NonCommercial 4.0 International Public License. The mannual will continue to be updated in the future. Your feedback is highly appreciated!

The course notes serve as a companion resource to the following free textbooks and resources:

Retail Management,

Location Intelligence, Research and Applications, ((Must Complete Free Registration)

B2B Marketing Attribution,

The class is structured with the unity of theory and method in mind. In addition to the conceptual topics presented in each chapter, I also tried to include some additional technical resources (e.g., how to design a basic dashboard using Tableau) to help you learn about each topic. Remember that the course notes only serve as a starting point, explore the reading list, practical and lecture for more insights and ideas.

The course notes are proudly published with R (a statistics software) and Bookdown. The notes are designed to help students enrolled in CSUB Marketing Channel course led by Professor Jimmy “Zhenning” Xu.

Studies have shown that although each person has their own unique learning style, there are some aspects of learning commonalities that everyone of us will have in common (Knisley 2020). Based on these commonalities, I developed a model of how students learn marketing (Knisley 2020).

·Concepts should be introduced in as simple a setting as possible

·Definitions should be developed and utilized as soon as possible

·Concepts should be reinforced with recurring themes, written assignments, and technology

·Data-driven decision making and rigor are important goals in the learning of marketing decision-making

Tell me and I will forget, show me and I may remember; let me do it and I will understand. In a duration of 2 weeks time we remember only 90% of what we actually participate in. The more the involvement, the more we learn and remember in the long run. I hope that the course note will be a start-up point for you to take a deep dive into the art and science of marketing. If you have any suggestions for improvements, please get in touch with me.

The course notes are written using R (the most popular data analytics programming language) and Bookdown. Bookdown is a R package designed by Yihui Xie (2017) for generating html webpages and PDFLaTex files. Here is the website if you would like to publish your own book or project using R and Bookdown ( You might also think about writing your thesis using R and Bookdown.

“Differences of habit and language are nothing at all if our aims are identical and our hearts are open.”

— Albus Dumbledore

“When you visualize, then you materialize.”

—Denis Waitley

"our degrees aren’t as valuable as your skills.

— Richard Feynman

“If you want to master something, teach it.”

— Richard Feynman
“If you don’t make mistakes, you’re doing it wrong. If you don’t correct those mistakes, you’re doing it really wrong. If you can’t accept that you’re mistaken, you’re not doing it at all..”
— Richard Feynman
“If you thought that science was certain - well, that is just an error on your part.”
— Richard Feynman
“Learning is synthesizing seemingly divergent ideas and data.’ –Terry Heick.”
— Richard Feynman

1.2 Course schedule

Table 1.1:
Week 108.24-08.29Introductions / Team building activities/General principlesDiscussion 1
Week 208.31-09.05Search Engine Marketing (SEO)Discussion 2/have Excel & Tableau Installed
Week 309.07-09.12Google AnalyticsAssignment 1/Take the Google Analytics Certificate Test
Week 409.14-09.19Landing Page DesignDiscussion 3/Assignment 2
Week 509.21-09.26Last day to drop / Geodemographic market opportunity analysis / Project proposal (presentation)Discussion 4/Project Proposal PPT (presentation)
Week 609.28-10.03Geodemographic market opportunity analysisDiscussion 5/Assignment 3
Week 710.05-10.10Google AdWordsDiscussion 6/Take the Google Ads Certificate Test
Week 810.12-10.17Marketing Attribution ModelingDiscussion 7/Assignment 4
Week 910.19-10.24Merchandise ManagementDiscussion 8/Submit the Certificates (Google Ads & Google Analytics)
Week 1010.26-10.31Google AdWords recapDiscussion 9
Week 1111.02-11.07Trade Area Analysis and Site SelectionDiscussion 10/Assignment 5
Week 1211.09-11.14Retail Pricing and Sales Strategies / CRM software and Dashboard DesignDiscussion 11
Week 1311.16-11.21CRM software and Dashboard DesignDiscussion 12/Mid-term Project paper
Week 1411.23-11.25Group meeting with your instructor/ Happy Thanksgivingproject session/Group meeting with Dr. Xu
Week 1511.30-12.05Social Media AnalyticsDiscussion 13
Week 1612.07-12.10Work on your project paper & your self-reflectionProject presentation (PPT)/peer eval/self-reflection

1.3 Introduction

The course is designed to help business students understand the basic issues in marketing channel management from a strategic, analytical, and technological perspective.

Marketing channel is a diverse field, with both academic researchers and practitioners coming from different backgrounds including marketing, GIS, strategic management, operation management, logistics, management science, MIS, Industrial Engineering. The course notes provide an integrative review at the boundary of most of these areas. The aim of this course is to give students an opportunity to gain a broad view of the relevant areas and topics and to provide a starting point for future career growth.

The course content is benchmarked against similar courses offered at other leading schools including MIT, Columbia Business School, University of South Carolina’s Darla Moore School of Business, the College of Business at University of Rhode Island, the Jack Welch College of Business at Sacred Heart University, Daniels College of Business at the University of Denver, etc.


Seven majors that surprisingly use data and Tableau

1.4 Why a Strategic, Analytical and Technological perspective

“What gets measured, gets managed” - Peter Drucker

“Every day, three times per second, we produce the equivalent of the amount of data that the Library of Congress has in its entire print collection. Most of it is…irrelevant noise. So unless you have good techniques for filtering and processing the information, you’re going to get into trouble.” - Nate Silver

“We don’t have better algorithms. We just have more data.” - Google’s Research Director Peter Norvig

“All models are wrong and increasingly you can succeed without them.”- Google’s Research Director Peter Norvig

"“Retail is a very competitive environment. That’s why Coca-Cola and Walmart joined together via Tableau to share more data, build more trust, and strengthen the relationship.” - Tableau Software

Coca-Cola: Walmart and Coca-Cola Join Forces with Tableau as the Unifying Factor

Figure 1.1: Coca-Cola: Walmart and Coca-Cola Join Forces with Tableau as the Unifying Factor

For more details, you might want to watch “Coca-Cola: Walmart and Coca-Cola Join Forces with Tableau as the Unifying Factor”

In recent years, companies have become more proactive about their investment in Big Data Analytics (BDA) strategies. There are many BDA applications in strategic management, marketing channel decision-making, marketing research, advertising, social media management, new product development, etc. One of the basic features of BDA is its promise in delivering real-time automated recommendations or offering personalized marketing strategies. Definitely, there are many other fascinating areas like deep learning, AI applications, etc that use BDA extensively.

A recent report by Polovets found that high-performance firms tend to use more advanced analytic technologies (Asay, 2014). In the web 3.0 era, Big Data Analytics provides ways for companies to develop products that are more likely to be purchased by consumers. However, understanding the marketing environment and consumer appetites has been shown to be challenging since they are changing rapidly.

Matured Big Data Analytics provides new product, consumer, market, and competitor insights in a real-time fashion. In comparison to traditional marketing tools used for decision-making, Big Data Analytics has the potential to improve marketing channel decision-making due to improvements in the dimensions of volume, velocity, variety, veracity, and added value (IBM Big Data & Analytics Hub, 2015).

Even during this pademic, there were many analytics jobs in nearly all industries and related sub-industries (banking, finance, accounting, marketing, customer analytics, HR, etc.) need to be filled. If anyone can “help a company navigate a murky, uncertain future, it’s someone comfortable with and excited about working with data. Simply put, we need more analysts in companies that appreciate their skills” (Bordenave, 2020). Actually, Microsoft mentioned that we will need about more than 500 million tech-related talents by 2025.

To find out how different companies are using Tableau or analytics solutions to drive performance, please click on the links below:

There are at least 3 job categories that are closely business or marketing related:

Coca-Cola: Walmart and Coca-Cola Join Forces with Tableau as the Unifying Factor

Below is a list of companies hiring for business analytics / data analytics positions (actively updated):

Anheuser-Busch InBev
Daugherty Business Solutions
Stitch Fix
Weight Watchers
US Cellular
Walmart /
The Walt Disney Company

1.5 Why Tableau?

Tableau Desktop is the commercial visualization software we use for some of the major modules and topics. It is normally $1999 per user it is free to you for the duration of this class through the Tableau for teaching program.

Tableau became one of the most important business intelligence tools for bridging data, analytics, insights, and actions especially during the 2020 COVID (Paolin, 2020). For instance, the following interactive COVID-19 dashboard is created with Tableau Public (available at the CA government site:

CA COVID19 dashboard

Figure 1.2: CA COVID19 dashboard

“Demand for knowledgeable data analytics professionals currently outweighs the supply, meaning that companies are willing to pay a premium to fill their openings” (Dataquest, 2019). The lack of coverage of BI tools or big data analytics platforms in undergraduate education could be contributing to the mismatch between the supply and demand of data analysts. I am probably being a little bit too optimistic. However, I assume that think that through this work I’m helping to help you improve your critical thinking skills and quantitative reasoning skills that go beyond the subject matter of this course.

In order to accomplish these objectives, I finally choose Tableau software and hope you notice the usefulness of this popular BI tool. I could have used Excel instead of Tableau. However, I understand that Excel is usually covered in lower-level Stats courses. Tableau makes better visualizations than Excel and is widely used by big companies and organizations like Coca Cola, Walmart, Idexx, Walgreen’s, Grimmway Farms, the Wonderful Company, CSUB, etc.

Using Tableau, PepsiCo analyzes “inventory, logistical, and finance data from across the country” (Tableau, 2020). Tableau allows companies like PepsiCo, Walmart, Coca Cola, Walgreen’s to make sense of big data and empowers analysts to create supply chain and forecasting reports in real time(Tableau, 2020).

A sample CPFR dashboard from PepsiCo

Figure 1.3: A sample CPFR dashboard from PepsiCo

The 10 Technical Skills With Explosive Growth In Job Demand -

• Understand the basics for an internship position that requires BI or Tableau operations • Associate Analyst, Ranch Support - Wonderful Orchards Company Location Bakersfield, California Area - • Project Logistics Coordinator, Company NameFieldCore Company Location Bakersfield, CA, US -

According to a recent poll, 72 percent of organizations hired people in data analysis positions in 2016. Of those, 78 percent reported difficulty filling the positions.* It was ranked by Forbes in the top 10 technical skills to have for job growth in 2017. All businesses generate data from link clicks, email opens, customer information, sales and more. Data overload can lead to a loss of productivity, so it is important to know what data is meaningful and how to read it. Properly analyzed data brings a better understanding of your clients, customers and audience: who they are, where they are and what interests them.You can use this knowledge to make more focused decisions specific to your audience and business—with the data to back it up.


Tableau, 2020, PepsiCo cuts analysis time by up to 90% with Tableau + Trifacta

1.6 Acknowledgments

The content of this book was based on the current marketing technologies being used by marketers for developing marketing channel strategies.

There are about about 3 major textbooks for marketint channel. Most of these textbooks are remarkably expensive. That said, the use of technology is essential to the development of marketing channel strategies.

The development of this tutorial would not be possible without the feedback and suggestions offered by my colleagues and students. I am grateful for the support and encouragement of my supervisors, my colleagues, and most importantly, my students.

Jimmy “Zhenning” Xu, July 2020