Credits and costs
Advanced Marketing Analytics for a Data-Driven World
The Master of Professional studies in Data Analytics with an option in Marketing Analytics delivers the knowledge to help you design, implement, and apply data analysis techniques to solve today's complex marketing challenges. You will learn to use and analyze data to address issues related to brand positioning and differentiation, pricing and product strategy, brand equity, marketing campaign performance, and customer satisfaction measuring campaign performance.
This program, delivered entirely online through Penn State World Campus, also provides you with a solid understanding of the broader mechanics involved in data analytics, including the computational statistics and machine learning options for processing and exploring datasets. Professionals in market research, brand management, and marketing analysis will find this degree particularly useful, as it empowers them to make effective data-driven decisions that impact the customer experience, overall marketing effectiveness, and an organization's future growth.
The Penn State Difference
Top Ranked. Penn State World Campus ranked in the top 10 of six categories in U.S. News & World Report’s 2019 Best Online Programs, the most of any institution in the country. You can feel confident knowing you are partnering with a proven leader in online education.
Expert Faculty. Delivered through a strong partnership between faculty from multiple departments across the University, the marketing analytics program offers you the opportunity to benefit from the expertise and unique perspectives of faculty with real-world marketing and data analytics experience.
Flexibility. This program allows for asynchronous learning. That means you can work at your own pace on assignments and not worry about being in class at a specific time. This flexibility makes the program great for working adults, military personnel, or anyone else with a busy lifestyle.
Skip the GMAT. This online program is temporarily waiving GRE/GMAT test scores for applicants who meet certain criteria.
Your Online Marketing Analytics Curriculum
This in-depth program strives to develop experts in the data sciences and the application of analytics techniques, with a specific focus on the discipline of marketing. Students will:
- learn how to apply data analytics, data mining techniques, and predictive analytics to meet business objectives and leverage competitive advantage.
- address challenges related to customer acquisition, management, and retention; brand evaluation and management; product and pricing assessment; digital marketing communications; and social media influence.
- demonstrate fundamental understanding of data mining principles as well as statistical techniques including hypothesis testing, estimation, confidence intervals, and regression.
- learn to effectively communicate data-driven findings to executive stakeholders.
- gain practical, hands-on experience with statistical software and database solutions.
This program can be completed entirely online and incorporates the contemporary principles of marketing analytics with the theories and methodologies associated with data science.
Courses are structured to allow you to complete assignments when and where it's most convenient for you. While courses are autonomous, you will have the opportunity to interact and engage with fellow classmates through integrated experiences. This peer-to-peer interaction enhances your learning experience while strengthening your professional network on a global scale.
You will take 9 credits in the program's core courses, 9 credits specific to the marketing analytics option, and 9 credits of electives in consultation with your program adviser. You will then complete your studies with the 3-credit culminating capstone experience.
Required Courses (9 credits)
Marketing Analytics Option Required Courses (9 credits)
Electives (select 9 credits)
Culminating Capstone Experience (3 credits)
All students will complete their program of study with the capstone course to give students an opportunity to apply their knowledge of the theories, methods, processes, and tools of data analytics, learned throughout their program, in a culminating and summative experience.
If you're ready to see when your courses will be offered, visit our public LionPATH course search (opens in new window) to start planning ahead.
Costs and Financial Aid
Graduate tuition is calculated based on the number of credits for which you register. Tuition is due shortly after each semester begins and rates are assessed every semester of enrollment.
|How many credits do you plan to take per semester?||Cost|
|11 or fewer||$1,056 per credit|
|12 or more||$12,678 per semester|
|How many credits do you plan to take per semester?||Cost|
|11 or fewer||$1,067 per credit|
|12 or more||$12,805 per semester|
Financial Aid and Military Benefits
Some students may qualify for financial aid. Take the time to research financial aid, scholarships, and payment options as you prepare to apply. Military service members, veterans, and their spouses or dependents should explore these potential military education benefits and financial aid opportunities, as well.
How to Apply
Deadlines and Important Dates
Your degree application, including receipt of all materials, must be received by the deadlines below to be considered complete. Space is limited, so you are encouraged to apply early.
- Summer Deadline: Apply by March 15 to start May 13
- Fall Deadline: Apply by July 15 to start August 26
- Spring Deadline: Apply by November 15, 2024, to start January 13, 2025
To help you manage the application process, our online application management system will provide you with complete details regarding the required elements of your application portfolio — and will even help you track your progress. You can also save your work and return to complete your application at any time.
If you have questions about the admissions process, contact our admissions counselors.
For admission to the Graduate School, an applicant must hold either (1) a baccalaureate degree from a regionally accredited U.S. institution or (2) a tertiary (postsecondary) degree that is deemed comparable to a four-year bachelor's degree from a regionally accredited U.S. institution. This degree must be from an officially recognized degree-granting institution in the country in which it operates.
Applicants with an undergraduate degree in a quantitative discipline such as science, engineering, or business will be given preferred consideration. Applicants from other disciplines will be considered based on prior coursework, professional work experience, and/or standardized test scores.
What You Need
Applications are submitted electronically and include a nonrefundable application fee. You will need to upload the following items as part of your application:
Official transcripts from each institution attended, regardless of the number of credits or semesters completed. Transcripts not in English must be accompanied by a certified translation. Penn State alumni do not need to request transcripts for credits earned at Penn State, but must list Penn State as part of your academic history. If you are admitted, you will be asked to send an additional official transcript. You will receive instructions at that time.
For questions about transcripts, contact:
Penn State Great Valley
GPA and Test Scores — Postsecondary (undergraduate), junior/senior (last two years) GPA of 3.0 or above on a 4.0 scale is required. GRE/GMAT scores are NOT required.
English Proficiency — The language of instruction at Penn State is English. With some exceptions, international applicants must take and submit scores for the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS). Minimum test scores and exceptions are found in the English Proficiency section on the Graduate School's "Requirements for Graduate Admission" page. Visit the TOEFL website for testing information. Penn State's institutional code is 2660.
References (2) — You will need to initiate the process through the online application by entering the names, email addresses, and mailing addresses of two references. Upon submission of your application, an email will be sent to each reference requesting that she or he complete a brief online recommendation regarding your professional and/or academic strengths and accomplishments, and your potential for success in an online program. The admissions committee prefers that all recommendations be written within the last six months and reference the applicant's current career goals. Please inform each reference that she or he must submit the form in order for your application to be complete.
Statement of Purpose — You should submit a personal statement not to exceed 2-3 paragraphs or 1 page, which should describe your specific career goals and objectives, prior experience relevant to the decision to pursue an advanced degree, and other information that may be useful to the admissions committee. Upload to the online application.
Vita or Résumé — A listing of your professional experience. Upload to the online application.
Start Your Application
You can begin your online application at any time. Your progress within the online application system will be saved as you go, allowing you to return at any point as you gather additional information and required materials.
- Choose Enrollment Type: "Degree Admission"
- Choose "WORLD CAMPUS" as the campus
Checking Your Status
You can check the status of your application by using the same login information established for the online application form.
Given the scale of data used in the data analytics program and the continuous advances in tools and platforms used in data science, students are urged to check individual course technical requirements vigilantly. At a minimum, students will need a PC that runs Windows 7 or higher with 8GB of RAM and 250GB of free space on the hard drive. Mac OS machines are not compatible for most courses in the program and are not recommended.
Start or Advance Your Career
Start or Advance Your Career
You can use the knowledge gained from this program and the support of Penn State career resources to pursue careers in a variety of fields, depending on your goals.
Earn a Valuable Credential along the Way
Earn a Valuable Credential along the Way
Show mastery of specific subjects before your degree is complete. Thanks to shared courses across programs, students can often earn a certificate along with their degree in less time than if they earned them separately.
To learn more about the Master of Professional Studies in Data Analytics – Marketing Analytics Option, follow the guidelines below.
For questions about the program and regarding how to apply, contact:
World Campus Admissions Counselors
Email: [email protected]
For general questions about the program, contact:
Dr. Amanda Neill
Email: [email protected]
Adrian S. Barb
DegreePh.D., Computer Science, University of Missouri
DegreeMBA, Finance and Management Information Systems, University of Missouri
DegreeB.S., Industrial Engineering, University of Bucharest
Dr. Adrian S. Barb, associate professor of information science, teaches databases, data mining, and big data courses. He has worked as a database programmer analyst as well as a web developer at University of Missouri. His research interests include data mining, knowledge discovery in databases, knowledge representation and exchange in content-based retrieval systems, semantic modeling and retrieval, conceptual change, ontology integration, and expert-in-the-loop knowledge generation and exchange.
DegreePh.D., Industrial and Systems Engineering, University of Oklahoma
DegreeM.S., Industrial Engineering, Tarbiat Modares University
DegreeB.S., Industrial Engineering, University of Tabriz
Dr. Mohamad Darayi, assistant professor of systems engineering, focuses his principal research and key publications on infrastructure network resilience and simulation modeling applications in health care, manufacturing, and supply chain management. He teaches courses in system simulation, risk analysis, network modeling, and data analytics.
DegreePh.D., Communication Science, University of Connecticut
DegreeM.L.S., Southern Connecticut State University
DegreeB.A., English, Philosophy, University of Connecticut
Dr. Chelsea Hammond is an assistant clinical professor of marketing and program director of the online marketing analytics certificate. Prior to joining the Penn State Smeal College of Business, she spent more than a decade in the market research and marketing analytics industry, where she helped the world's most iconic and well-known brands leverage data to drive business success.
DegreePh.D., Industrial and Systems Engineering, Auburn University
DegreeM.E., Industrial and Systems Engineering, Auburn University
DegreeB.S., Industrial and Systems Engineering, University of Tehran
Dr. Ashkan Negahban is an associate professor of engineering management. Prior to joining Penn State, he was an instructor at Auburn University, where he taught courses in simulation, probability theory, and statistics. His research interests include the application of different types of simulation (discrete event, agent-based, and Monte Carlo) in design and operation of complex systems. He has developed several e-learning modules that have received worldwide publicity and are used by faculty from leading institutions around the world.
DegreePh.D., Software and Systems Engineering, University of Wales Swansea
DegreeM.Sc., Communications Systems, University of Wales Swansea
DegreeB.Eng., Electrical Engineering, University of Wales Swansea
Dr. Colin Neill is a professor of software engineering and systems engineering. He teaches many courses in software and systems engineering and project management. He is the author of more than 80 articles on the development and evolution of complex software and systems and their management and governance. Dr. Neill is a senior member of the IEEE and a member of INCOSE, and he serves as associate editor-in-chief of Innovations in Systems and Software Engineering.
J. Andrew Petersen
DegreePh.D., Business Administration (Marketing), University of Connecticut
DegreeB.A., Economics, University of North Carolina at Chapel Hill
Dr. J. Andrew Petersen is an associate professor of marketing in the Smeal College of Business and program director of the online marketing analytics and insights master’s degree. His research interests include measuring and maximizing customer/donor lifetime value (CLV/DLV) and customer/donor equity, managing customer product return behavior, measuring the value of word-of-mouth, selling and sales management, and linking marketing metrics to financial performance. His research has been published in many top academic journals, including Journal of Marketing, Journal of Marketing Research, Harvard Business Review, MIT Sloan Management Review, and The Wall Street Journal.
Robin G. Qiu
DegreePh.D., Industrial Engineering, Penn State
DegreePh.D., (Minor), Computer Science, Penn State
DegreeM.S., Numerical Control, Beijing Institute of Technology, China
DegreeB.S., Mechanical Engineering, Beijing Institute of Technology, China
Dr. Robin G. Qiu is a professor of information science at Penn State. He teaches courses on data analytics, information science, software engineering, and cyber security. Dr. Qiu's research includes smart service systems, IoT, big data, data/business analytics, information systems and integration, supply chain and industrial systems, and analytics. He served as the editor-in-chief of INFORMS Service Science. He is an associate editor of IEEE Transactions on Systems, Man, and Cybernetics and IEEE Transactions on Industrial Informatics, and has more than 160 publications.
Raghvinder S. Sangwan
DegreePh.D., Computer and Information Sciences, Temple University
DegreeM.S., Computer Science, West Chester University
DegreeB.S., Genetics and Plant Breeding, Haryana Agricultural University
Dr. Raghvinder S. Sangwan is a professor of software engineering. His teaching and research involve analysis, design, and development of software-intensive systems and their architecture, and automatic/semi-automatic approaches to assessment of their design and code complexity. He actively consults for Siemens Corporate Technology in Princeton, New Jersey, and holds a visiting scientist appointment at the Software Engineering Institute at Carnegie Mellon University in Pittsburgh, Pennsylvania. He is a senior member of the IEEE and ACM.
DegreePh.D., Information Technology, University of Nebraska at Omaha
DegreeM.S., Industrial Engineering and Management, Indian Institute of Technology, Kharagpur
DegreeB.S., Information Technology, Bharathidasan University
Dr. Satish Srinivasan is an associate professor of information science in the engineering division at Penn State Great Valley. He teaches courses related to database design, data mining, data collection and cleaning, design and implementation of predictive analytics system, network and web securities, and business process management. His research interests include social network analysis, data mining, machine learning, big data and predictive analytics, and bioinformatics.