Database Management and Modeling
INTG1-GC1025
Credit:
Marketing, Advertising, and Public Relations
Students will learn the basic of database set up and management, as well as the analytical techniques and tools used in direct and digital marketing to assess, enhance, and profit from customer-relationship management. In particular, this course will cover the following:
Building a customer database ¿ why, how, and types
Defining customer data requirements ¿ short- and long-term needs, considerations by division, off- and online data-integration issues, and special considerations
Maintenance of the database ¿ NCOA processing, address standardization, deduping, and other methods for cost efficiency and accuracy
Database technology, organization and planning- technology needs and outsourcing considerations
Sampling techniques ¿ nth selects and frozen files
Creating powerful predictor variables - univariate and cross tabulations, ratios, time series variables, and other measures
Segmenting the customer file - cross-tabulations, RFM analysis, CHAID, factor analysis and cluster analysis
Predicting customer actions - using multiple linear regression and logistic regression to model response, payment, attrition, churn, and other factors
Outside list selection options - best customer models, response models, manual selects
Gains charts and expected profit calculations - selecting the best customer for promotion based on profitability
Introduction to mining with SAS - an introduction to the use of SAS, the most widely used software available today for database mining and modeling.
To register for this course you must be an admitted student in an NYU credit or degree program or have special student status.
Admitted NYU credit or degree students may visit NYUHome to register through ALBERT.
To apply to an NYU-SCPS credit or degree program, call (212) 998-7100.
