PolyAnalyst PRO for Windows NT is being used as the main data mining tool for the course Marketing Intelligence Management (M549) taught by Prof. Raymond R. Burke to the second year MBA students of Kelley School of Business at Indiana University. The students are using PolyAnalyst PRO installed in Kelley School of Business on 75 PC’s for in-class workshops and individual data analysis. The main projects carried out during the course include the analysis of:
- Marsh Superstudy program performed by Marsh Supermarkets, Inc.
- The effectiveness of the Anheuser-Busch beer promotion program over a retailing chain in a particular city.
- Possible ways to improve the Rodale Press’ cross-selling initiative.
- Design and effectiveness of the Simon DeBartolo Group’s MALLPeRKS program. MALLPeRKS is a proprietary customer incentive program that targets high-dollar, high-volume shoppers to encourage customer loyalty, stimulate sales, and create a valuable database of customer information.
I am very enthusiastic about the PolyAnalyst package for both education and commercial research. The software provides a unique and powerful set of tools for data mining applications, including promotion response analysis, customer segmentation and profiling, and cross-selling analysis. Students find the object-oriented interface to be easy to learn and use. This is especially important in business classes where the focus is on data analysis and interpretation rather than on programming.
Raymond R. Burke
E.W. Kelley Professor of BA
Kelley School of Business at Indiana University
Bloomington, IN, USA
Marketing Intelligence Management Course Description
Marketing research is in a state of transition. New technologies including point-of-sale UPC scanners, frequent shopper programs, credit/debit cards, in-store tracking, caller-id systems, and electronic shopping interfaces have created an explosion of data on customers and their purchase behavior. The Internet and online retrieval systems have opened the door to volumes of secondary research on market trends and the competitive environment. Syndicated databases provide detailed information on the buying habits of individual households. The task of analyzing marketing data is no longer relegated to research specialists. Managers are now using networked, desktop computers to process this information. However, more computing power and data will not necessarily lead to better decisions. Managers must understand what research is available, what assumptions underlie the research methods, how to analyze and interpret the data, and how to apply the results in a business context.
The goals of this course are to introduce students to the emerging field of marketing intelligence management. The course will discuss three major types of customer and competitor databases: geodemographic information systems, point-of-sale scanner databases, and catalog and frequent shopper databases. We will review existing data analysis tools used to manage the data explosion, track sales and market share, and diagnose changes in product performance. We will apply data-mining software to profile customer segments, analyze promotion effectiveness, and identify cross-selling opportunities. We will discuss recent innovations in tracking customer behavior and measuring customer value. The course concludes with a discussion of how to create a “knowledge-based organization” which incorporates marketing research into a firm’s ongoing operations to build a closer relationship with customers.