Master of Science in Marketing Analytics
The Master of Science (M.S.) in Marketing Analytics is a 30-credit, online program providing students with strategic approaches to marketing decision-making within public and private institutions. These strategic approaches to marketing will be used to develop frameworks for solving analytical problems, decisions on which data needs to be collected, what information systems can be effectively used to collect the data, and what analyses should be performed in order to inform institutional decision-making.
Program Learning Objectives
This program provides students with the essential skills required in the field of marketing analytics.
Upon successful completion of this program, graduates should be able to:
- Leadership: Evaluate large stores of data as part of database design to discover patterns and trends that go beyond simple analysis to new and industry-leading insights.
- Problem Solving & Critical Thinking: Apply analytic tools such as machine learning and artificial intelligence to critically evaluate applied research, and develop meaningful insights.
- Disciplinary Knowledge: Analyze descriptive and inferential statistics and interpret the computer-generated statistical results with data visualization in marketing applications using programming languages such as R and Python.
- Ethical Reasoning: Develop ethical decision-making competencies through statistical methods and the application of analytical tools such as Microsoft Power BI.
- Strategic Thinking: Strategize how the issues facing leaders and decision makers, in the marketing field, can be resolved ethically.
- Managerial Communication: Analyze and present big data to make strategic decisions including resource allocation. Bridge the communication gap between technical and traditional marketing managers.
- Teamwork: Collaborate and contribute effectively to the achievement of organizational goals in a team environment.
Program Design
This 30-credit hour program is delivered through online instruction, providing flexibility and convenience for working professionals and adult learners. The program may be completed in as little as 15 months through full-time enrollment (typically 9 credits in fall and spring terms, 3-6 credits in summer terms). Part-time students may complete the program in two years. All students must complete the degree within six years of initial enrollment per the Graduate Time Limit for Program Completion Policy.
Prerequisites
In addition to a bachelor’s degree from a regionally accredited college/university, applicants must have undergraduate-level or graduate-level coursework in statistics (3 credits) and information technology (3 credits) to be considered for admission. Students who are missing one or both prerequisites, but are otherwise qualified and accepted into the program, will be required to take the missing prerequisites before starting the core classes.
Program Curriculum
Course Number | Course Title | Credits |
---|---|---|
INFT 6015 | Database Design and Management | 3 |
APAN 6015 | Data Models and Structured Analysis | 3 |
APAN 6010 | Computer Aided Multivariate Analytics | 3 |
APAN 6020 | Data Mining & Machine Learning for AI | 3 |
MGMT 6095 | E-Commerce Marketing Strategies | 3 |
MGMT 6185 | Quantitative Methods for Decision Making | 3 |
MGMT 6155 | Strategies for Marketing Research | 3 |
MGMT 7005 | Global Marketing Strategies | 3 |
MGMT 7030 | Marketing Analytics and Brand Management | 3 |
MKAN 7010 | Marketing Analytics Capstone | 3 |
Total Credits: 30
Marketing Analytics Capstone (MKAN 7010)
This capstone course focuses on students gaining real-world project experience in marketing analytics. Students will explore consumer data, market trends, and campaign efficacy. Students will be required to complete a capstone project. The emphasis of the project will be on leveraging data to inform marketing strategies, audience segmentation, and campaign performance evaluation.
Students can select their capstone project from one of the following options:
- Employer-based Project: Work on a data analytics project with their current employer that demonstrates mastery of the capstone learning outcomes.
- Self-Selected Specialization Project: Choose a project based on their specialization and personal interest. This should involve real-world data and be geared toward deriving real-world insights.
For more information about this program, its course sequencing and descriptions, please visit the Empire State University's Academic Catalog.