To the best of our knowledge, this is one of the few college courses designed specifically to the unique subject matter of eCommerce. This fast-moving space requires a true interdisciplinary approach spanning marketing, finance, and operations. The course material was based on our industry experience working across eCommerce brands like Kickstarter, Jackson Hole Resort, Caterpillar, Vivint, DonorsChoose.org and others ranging from $1M to $1B in annual revenue. While the scale varies tremendously, the most profitable enterprises consistently leverage diverse datasets spanning marketing campaigns with customer data and operations in real-time.
For our purposes we use Python and Jupyter notebooks for our analysis with open datasets from Kaggle, UC, Irvine, and Google Merchandise Store. In addition, we’ll use Google Analytics for exploratory analysis and Data Studio for visualizing data from a real live eCommerce store.
Please email us with any ideas or questions and we’ll do our best to respond at [email protected]
eCommerce Course Description
This course covers eCommerce fundamentals including how to generate traffic for an e-commerce website, identify and segment the best customers for increasing the business valuation, and leverage operations data to make smarter financial decisions for the profitability of the business based on inventory.And there’s no better time than right now given the explosion of eCommerce during the COVID pandemic…
Given this growth, we’re seeing how digital disruption is transforming how consumers connect with brands today and technology has allowed even the smallest mom and pop business to build a direct-to-consumer online channel. This presents a unique conundrum in that many business management fundamentals still apply for producing results. However, the individual skills for leaders to manage e-commerce businesses requires a wide range of interdisciplinary skills.We will seek to explore both sides of this challenge in the followings ways:Working with a sample dataset from the Google Merchandise Store and Kaggle, students will explore the following:
Understanding marketing campaigns and how the best customers shop as measured by the Customer Lifetime Value (CLV).
Allocating and pricing for inventory based on variables like seasonality, margin, and geography.
Building basic growth forecasts against constraints like capital and CLV.
Creating an executive level dashboard for visualizing the above data in Google Data Studio.
Borrowing from such diverse fields as design thinking, operations, digital marketing, and data science, students will come away with a solid understanding of how to plan, execute, and iterate modern online businesses for predictable and profitable long-term growth.In addition, students will be exposed to a systematic framework for building successful e-commerce businesses with an appreciation for how finance and operations influence growth and profitability.Pre-reqs: Graduate students enrolled in the MBA, MSBA, or MACC programs or upper-division students in good standing in the Computer Science department at Montana State University.
What Students Learn
The eCommerce space moves fast but also contains much hype which we will seek to dispel with real-world examples and case studies throughout the course.
Students will be exposed to the three key pillars for building a profitable eCommerce store: customer acquisition & retention, effective digital marketing campaigns, and ongoing operations efficiency with particular focus on inventory optimizations and capital needs.How We’ll Do This
By working with real-time eCommerce datasets, students will explore how to:
Drive the right traffic to a website
What products produce the most profit
Which customers are worth the most over their lifetime and which marketing campaign they came from.
Through blending diverse datasets across the entire enterprise, students will come away with a strong appreciation for the nuanced difficulty of running a profitable eCommerce store that extends beyond just the basic technology needs.
The course will include multiple anecdotes from in-the-trenches eCommerce practitioners who have worked with businesses ranging from $1M to $1B in scale, all of which face the same common optimization challenges as mentioned above. Understanding the interplay, regardless of top line revenue, will equip students to be successful leaders in direct-to-consumer business models.
At the conclusion of the course, students will approach digital business problems with a set of tools for going beyond the vanity metrics of site visitors or Instagram likes and instead be able to dissect the true variables of an online store that drive growth and true profit.
To get a sense of some of the exciting analysis we can do once we have good clean data, you can take a peek at this sample eCommerce data science notebook that looks at a few variables to predict what will most likely boost revenue (hint: Length of Membership or Time on Site?).
This also shows a very basic machine learning exercise to see how well our variables predict what will boost revenue.
Explore a sample eCommerce Jupyter Notebook on Google Colab to see what generated this plot:
The unifying framework behind all our will be basic web analytics using the Google Analytics platform and the demo account for Google’s Merchandise Store.
This is an incredible opportunity to work with real data to validate hypotheses in real-time for an e-commerce store. Google Analytics is overwhelming for new users, so we’ll play with this tool early and often throughout the semester. Students are encouraged to also download the mobile app of this tool for daily updates via iOS or Android.
Customer Data Analytics
Here, we’ll start to blend things like customer behavioral data with sales orders to get a sense of who are best customers are based on their lifetime with a brand. We’ll also explore emerging tools like Natural Language Processing (NLP) and sentiment analysis to comb through product reviews or site feedback to learn what customers are really thinking.
Next, we’ll begin building some basic predictive models to figure what which variables can help us boost our overall revenue.
Digital Marketing Campaign Data
Users come to an eCommerce store via a variety of channels like search engines and YouTube. Or ads like on Instagram and Facebook. Sometimes they remember a brand and come directly to the website itself. Some choose to subscribe to an email newsletter or SMS.
All these different paths possess a fascinating insight into user behavior in a digital realm and provide real clues on where best a company should focus its efforts.
We’ll dig in a bit on what the right “recipe” is for growing profitable revenue by acquiring and retaining our best traffic.
Often the lurking variable in eCommerce – the bottom line. Knowing what it costs to make a product and adding in the cost to acquire and retain a customer (yes, there is a cost here), we can begin to make smart guesses on which products we should keep or discard.
The Operations data for margins, inventory turns, and price are often ignored. Here, we’ll look at some demand forecasting and play with some pricing scenarios to help further optimize our site’s traffic for profitability.
Finally, we’ll move beyond just crunching numbers to data-visualization for crafting custom dashboards that help our key stakeholders see the important numbers and what that means for boosting their store’s profitability. For presentation viz, we’ll rely on Google Data Studio to sync various datasets across Google Analytics, BigQuery, or whatever dataset you like.
Inline analysis will be done with handy Python libraries listed below.
(Bonus points here for providing context around the data and making it actionable)
Optional: Tableau or data-viz tools of student’s choice
Learning Objectives and Assessment
Working with a open dataset from the Google Merchandise Store and Kaggle, students will work to build skills for the following:
Understanding marketing campaigns and how the best customers shop as measured by the Customer Lifetime Value (CLV) and cross-channel touchpoints from search engines, paid media, email and social.
Allocating and pricing for inventory based on variables like seasonality, margins, and geography.
Building basic growth forecasts against constraints like capital and customer lifetime value using the tools of their choice (Excel, R/Python) by asking smart questions of the available data, performing appropriate analysis with statistical acumen, and communicating the results against the overall profitability objective of the case study.
Creating an executive level dashboard for visualizing the above data in Google Data Studio (or their Data-Viz tool of choice)
Emphasis on Real-World Applications
To supplement the concepts, various leading online marketers, experience designers, and content strategists from industry will address special topics such as email marketing, user experience design, search engine optimization (SEO), building online communities, geo and mobile marketing.
Students will also have the opportunity to examine these topics firsthand through group projects and exercises ranging from getting a project funded on Kickstarter, building out a personal site in WordPress, to working with a real e-commerce company on the final.
Participants will exit the course with a solid understanding of digital marketing tactics, tools, and resources available for ongoing education.
Course Prerequisite: TBD (BUS 341–Principles of Marketing)
Required Text & Readings
Textbook: “The Flywheel of Profitable eCommerce – Mastering the 4Cs for Remarkable Success“
Assigned readings from the following outlets and blogs:
Harvard Business Review
You will be assigned various readings from the text and also handouts for wrestling with real-world problems. Not preparing for class will show in the discussions in front of your peers and in your analysis. Participation is graded upon attendance, leading class discussions on your assigned case study day, and asking smart questions of your colleagues.
Your final grade will be determined by your understanding of the course materials, case study analysis, and ability to creatively apply the concepts in real world scenarios via the final group project.
Particular emphasis is placed on having a solid foundation of qualitative and quantitative data to back up your recommendations and clean data visualizations that a non-technical audience can appreciate and make critical decisions from.
Course Alumni: Where Are They Now?
I am very pleased to report that alumni from this course have gone on to do incredible things. Ben and Carlee work embedded at Google as part of an agency relationship with R/GA in San Francisco and Tokyo. Scott was rookie of the year of R/GA global in the NYC office. Mary has become a digital analyst of supreme skill leading C-Suite executives through a variety of digital initiatives. Abby works with the Fortune 50 on customer experience management software implementations. Chris leads the direct to consumer website for Caterpillar.
And the list goes on and on.
And that’s our one goal as professors – to ensure you are getting the most relevant skills and mindsets to make you competitive for digital jobs upon graduation.
I’ve been working in the technology space since 2006 and have had the fortune to serve clients such as Microsoft, The Webby Awards, MailChimp, The Lowline NYC, Google, Caterpillar, Children’s Miracle Network, DonorsChoose.org and Kickstarter along with a host of others.
One of my biggest passions is creating courses and teaching emerging subjects. With that I’ve been blessed to serve as an adjunct professor since 2007 at Montana State University, American College, University of Montana, and Minneapolis College of Art & Design spanning innovation, digital marketing, data science and early-stage entrepreneurship.
At Montana State, I served as the Academic Director for Digital Marketing & Analytics program in Executive Education and was a cofounder of the Design Sandbox for Engaged Learning (DSEL) which is an interdisciplinary effort across colleges at MSU designed in collaboration with Stanford’s Dr. Jim Patell.
Our “Innovative Ideation” class teaches the principles of design thinking to engineering, business, and design students. I also get to work on outreach efforts with organizations like IDEO, Stanford d.school, R/GA, Havas, Google, and IBM.
More recently, I created and co-taught the first graduate class designed exclusively for the unique challenges of direct to consumer e-commerce called “Ecommerce Pillars of Profitability” at the University of Montana’s MS program in Business Analytics. We are also piloting this course with upper-division computer science students at the Gianforte School of Computing at Montana State University with a focus on data science basics.
My day job is that of a co-founder and CEO at Tadpull with a focus on building digital marketing and analytics software with a user-first approach. Currently, we are solving the data explosion for businesses around the globe by combining insights ranging from SEO, Social, Email, Paid, ERP, and Site Analytics to be crunched in real-time for driving more effective online campaigns.
My undergraduate degree is in Physics via a swimming scholarship (I’ve since sworn off Speedos forever) and I stuck around for an MA in Marketing from a liberal arts college called Drury University in Springfield, Missouri.
Currently, I blog on occasion for Forbes, FastCompany.com, Behance’s 99U, Smashing Magazine, and Startup Nation.
I split my spare team between trying to learn how to cook better, writing code, reading the latest biz marketing or analytics book, building Jupyter notebooks in Python and getting outside as much as possible in southwest Montana with my lovely wife, business partner, and co-professor, Dr. Eulalie Cook.