Advanced Marketing Analytics Sequence

Course of Study for Advanced Marketing Analytics

The Marketing faculty have designed the Advanced Marketing Analytics (AMA) Sequence to allow Marketing Majors to concentrate their coursework in preparation for marketing roles that require more analytical skills, such as statistical analyses, data visualization, data cleaning and handling, data mining, predictive analytics, etc. The use of analytics is expected to continue growing rapidly.

Through our curriculum you will acquire techniques that improve marketing decisions. It aims to optimize marketing tactics, budget allocation, return on investment (ROI), and revenue prediction. We also partner with SAS to provide our students with the SAS Joint Academic Program certificate. Other tools we teach include R, Tableau, IBM SPSS Statistics, as well as digital marketing tools such as Google Analytics and SEO and SEM programs to optmize marketing investments and efforts to reach and covert the right target audience.

Advanced Marketing Analytics Sequence

As a marketing major, it is strongly recommended that you take MKT 190 (counts as MKT 230) in your sophomore year and declare the Advanced Marketing Analytics (AMA) Sequence by your Junior year, as some of our courses may be "major blocked" unless you are declared AMA Sequence.

Listen to students share their thoughts about the Advanced Marketing Analytics Sequence.

The following lists a brief description of the marketing courses offered as part of the Advanced Marketing Analytics (AMA) Sequence. For additional details, please also consult the “ MARKETING Major Checklist for Advanced Marketing Analytics” document.

Introduction to Marketing Analytics MKT 245: This course introduces you to the tools and techniques of data mining and predictive analytics, with the goal of using analytical techniques to derive actionable intelligence from marketing data to drive measureable improvements in marketing performance.

Advanced Marketing Analytics MKT 345: This is a quantitatively oriented course that is intended to explore concepts, tools, and methods of customer relationship management (CRM) in addition to more specialized and important contemporary business tools. Since data analysis is an important first step in developing a CRM program, a focus of the course will be placed upon techniques, and terminology associated with data analysis.

Brand Management & Analytics MKT 339.13: This course will provide students with advanced knowledge and practical skills necessary to make day-to-day and long-term brand related decisions. The course focuses on important issues in planning, implementing, and evaluating brand strategies based on the relevant theories, models, and the latest analytics tools available in brand management.

Marketing and Sales Forecasting MKT 311: This course develops an understanding of forecasting concepts and builds skills in performing a variety of qualitative and quantitative analysis methods. Applications include determining market and sales potential, estimating future sales, determining territory assignments and target markets. This is a highly interactive class, emphasizing actual forecasting applications through real-world exercises and projects.

Introduction to Databases for Business Analytics (New in Spring 2021) MKT 312: This course provides a comprehensive introduction to the language of relational databases: Structured Query Language (SQL), as well as the fundamentals of database management and data integration and warehousing. Knowledge in SQL and database management is helpful not only for data scientists, but also marketing analytics professionals who wish to explore customer and other pertinent business data.

Information on other courses in the sequence is provided below.

Introduction to Business Analytics ACC 271 / Introduction to Business Intelligence IT244: This course enables the student to become aware, comprehend, explore and manage significant issues confronting the field of Business Intelligence and Analytics from a multi-disciplinary perspective. Students can expect to be “immersed” in Business Intelligence analyses, research, resources, cases, tools, and techniques from industry and academia alike.

Accounting Information Systems ACC 263: This course provides students with advanced spreadsheet skills and familiarity with an accounting software package.

Advanced Business Data Management ACC 366: This course covers advanced study in computer storage techniques required for business information systems. Techniques are developed for both enterprise and desktop applications.

Data Mining IT 344: This course enables students to discover knowledge from data by applying data mining tools and techniques. It will emphasize preparing data, application of data mining techniques, interpreting the results and devising action plans based on the discovered knowledge. Students will be equipped with theoretical foundations to engage in algorithmic and optimization exercises.

Geographic Information Systems GEO 303: In this course students create effective visual presentations of spatial data. Students obtain datasets for GIS analysis, assess the suitability of the dataset to a given problem, and evaluate the associated uncertainties. Students will also independently analyze spatially referenced data, interpret results, and apply these skills to a decision-making process.