Customer Analytics is a research-oriented class that examines how firms can use analytics to gain actionable insights about customers both internal to the firm (employees) and external to the firm (consumers) to create, manage, and grow their business and brands. The class gives students the analytical tools to develop and operationally execute strategies that enhance customer engagement and loyalty.
M.S. in Commerce | Academics
Business Analytics Track
Here you’ll learn the skills, technologies, and practices necessary to design, create, and analyze datasets as well as report meaningful insights to diverse audiences. Coursework includes case studies, labs, seminars with industry leaders, and team projects for corporate sponsors. We give students the key frameworks, technologies, and functional skills employers are seeking. You’ll learn to:
Employ a consulting-style approach to identify a client business problem/opportunity, apply data preparation methods, develop predictive models, and use descriptive analytics to deliver a proposed solution (including strategy and recommendations) for a client
Develop and execute strategies that build customer engagement, loyalty, and brand by utilizing customer analytics to gain actionable insights about customers both internal (employees) and external (customers) to an organization
Use multivariate statistics to analyze “big data” for improved decision making
Work within teams to leverage web and search analytics to bolster the online presence for a small business or nonprofit
Derive business insights from large quantities of search, clickstream, and social media content using Hadoop-based software packages
Advanced Quantitative Analysis
Advanced Quantitative Analytics provides students with multivariate statistics training to analyze “big data” sets. The course covers discrete choice modeling (logistic and probit models), classification techniques (discriminant and cluster analyses), data reduction techniques (factor analysis), and advanced predictive techniques (regression models with interactions and curvilinear effects, structural equation modeling, and factorial ANOVA). The course also trains students on three widely-used statistical packages, IBM-SPSS, SAS, and R.
Data Management for Decision Making
This course provides an overview of the concepts, technologies, and tools necessary to support and improve electronic commerce, with emphasis on tools and methodologies for measuring and enhancing digital presence. The two major areas covered are web analytics and search analytics. Through a semesterlong group project, the course focuses on how these concepts can be used to measure, analyze, and improve user experience, web traffic, and conversion rates.
Predictive Analytics with Low Code Technology
Business analytics leverages the vast data resources available today to identify trends and patterns that are critical to enhancing business performance. This course introduces students to contemporary business analytics methods, including predictive and descriptive analytics techniques, and demonstrates how to practically apply analytics to real-world business decisions.
Managerial View of AI
This course aims to provide students with a practical understanding of AI technology. It covers key factors for the successful development, deployment, and management of AI; machine learning; and other algorithmic approaches to automated decision making. Students will better understand the societal impacts of AI, ethical considerations in the use of AI, the limitations of AI, and approaches to balance AI risks and benefits.
Unstructured Data Analytics
This course is focused on harnessing the power of unstructured data to perform advanced analytical techniques. Students will be exposed to big data technologies (NoSQL, Hadoop, etc.) to understand how to manage and interact with large, complex data sets. We will also cover various analytical and machine learning techniques that can apply to these data, with particular attention to text data from reports, articles, and social media.
Python for Data Science
The course provides an overview of the fundamentals necessary to conduct data analytics with Python, including understanding Python objects, data types, structures, packages, and data flow statements and, reading, writing, manipulating, and plotting data. Students will perform predictive analytics via machine learning using industry-standard packages.
Essentials of Project Management
This course provides students with an introduction to how to effectively fill the role of project manager. It covers a blend of conceptual knowledge and practical skills necessary for the effective management of complex projects.
This course is designed to provide a broad overview of management consulting and other related advisory services professions while also helping students develop skills that are broadly applicable in these professions as well as in other fields (business, politics, not-for-profit, etc.). Working both individually and in teams, students will gain an appreciation of what makes consulting and advisory services unique from other areas of business.
Bain & Company
Booz Allen Hamilton Inc.
Boston Consulting Group
The Coca-Cola Company
McKinsey & Company
Business Analytics Track
Omar Amer (M.S. in Commerce '18)
"The real-life consulting projects I faced in the program built a foundation of skills that easily translated to my current job in consulting. The rigorous problems we encountered in some of the courses, along with the people skills that we gained while interviewing some of our clients, definitely gave me a better edge to kick off my career."
Roy Masha (M.S. in Commerce '19)
"Commerce Career Services was super helpful in preparing me for consulting season and eventually my job offer with Bain. They connected me with alumni at the company and even helped guide me through the negotiation process. They were always supportive and there when I needed them."
Rosemary O'Hagan (M.S. in Commerce '18)
"I gained an affinity for storytelling through my History major and translation skills with my French major. The M.S. in Commerce gave me the tools I needed to tailor those skills to the world of business."
Jack Whitson (M.S. in Commerce '17)
"The M.S. in Commerce really stood out to me as an opportunity to bridge the gap between what I had learned in undergrad and where I wanted to be after graduate school. The Business Analytics Track in particular helped me a great deal with polishing my technical skills. I also really improved my presentation skills—I felt like we were constantly giving presentations and working in teams, and a lot of great communication skills came out of that."