MKT6450
Competitive Marketing Analytics
This course applies data analytics to problems in marketing to better understand customer needs and preferences; and to help organizations accomplish their strategic goals and objectives. Special emphasis will be placed on summarizing marketing data, forecasting new products, pricing strategies, estimating demand, market segmentation, calculating customer lifetime value, retailing, advertising, and internet and social marketing. Students will also learn how to construct models to support decisions in the areas of customer acquisition, engagement, satisfaction, and retention. This course will integrate the fundamentals of marketing analytics with research design best practices related to survey design, execution, and analysis; and qualitative methods including focus groups, case studies, and interviews.
UPON COMPLETION OF THE COURSE, THE STUDENT WILL BE COMPETENT IN:
- Collecting, storing, cleaning and managing data.
- Summarizing marketing data using descriptive statistics and graphical techniques.
- Examining marketing data for missing information, outliers, normality, homoskedasticity and linearity.
- Specifying marketing models in consideration of data availability and limitations.
- Exploring the structure of data using principal component, confirmatory, and exploratory factor analysis.
- Constructing marketing models using binary and multiple regression analysis.
- Segmenting markets using hierarchical and nonhierarchical cluster analysis.
- Implementing the marketing research process including constructing a problem statement, performing data analysis, and interpreting results.
- Utilizing a statistical processing software package to collect, organize, and analyze marketing data.
- Utilizing data obtained from multiple sources including customer surveys, focus groups, case studies, and questionnaires.
- Applying regression analysis to problems in marketing.
- Applying analysis of variance, multiple analysis of variance, and discriminant analysis to problems in marketing.
- Applying structural equation modeling to problems in marketing.
- Identifying the most appropriate marketing model in consideration of research design, sampling, and measurement issues.
- Integrating quantitative analysis with qualitative techniques including focus group, case studies, and survey analysis best practices.
- Synthesizing and applying universal ethical principles to competitive marketing analytics in modern organizations.