School of Management Fall Semester 2003

University of Texas at Dallas TUESDAY 6:00-10:00 p.m.

DataBase Marketing (MKT 6223)

Professor: Nanda Kumar

Room SM 3.702

Tel: (972) 883-6426

Fax: (972) 883-2799

E-mail: nkumar@utdallas.edu

URL: http://www.utdallas.edu/~nkumar

Office Hours: Mon 2:00 - 4:00pm; or by appointment.

Teaching Assistant: Howard Dover

Room SM 3.618

Tel: (972) 883 4418

howard.dover@student.utdallas.edu

Office Hours: Tu/R – Times to be announced later

Texts:

(I) The New Direct Marketing – David Shepard Associates (Recommended)

course description

The last two decades have witnessed a tremendous explosion in ways that firms use to track consumer behavior. This was aided considerably by the precipitous fall in the price of electronic storage media as well as computing power. Despite access to valuable data on purchase behavior and consumer characteristics, very few firms actually condition their strategies on the data they have. This may be attributed to at least two factors. First, firms now have so much information that it is often very costly for them to get to the data that can be meaningfully used to devise their strategies. Second, many firms just don’t know what to do with the data.

The course addresses both these issues. The course will introduce students to analytical techniques that will assist in data reduction and consumer segmentation. Additional techniques to uncover the characteristics of the different consumer segments will be developed. The latter half of the course will apply these techniques to some marketing problems – devising communication strategies, catalog marketing etc.

While the thrust of the course will be in developing analytical techniques that will eventually aid managers in devising strategies, the course will require students to work with different data sets and estimate various models with a software package such as SAS. The Unix/Windows version of SAS is available on the university computers and all registered students will have access to this version. In addition, PC based versions of the software may be purchased at a student discount

evaluation of student's performance

Each student's grade will be based on the following:

Basis of Evaluation % of Total Grade

Individual Component

· Final Exam 40%

Group Component

· Assignments (2´15%) 30%

· Term Project (Report + Presentation) 30%

Total 100%

Group Assignments:

There will be two assignments: one due in the 3^rd week and the other due in the 5^th week. Each assignment has two parts – the first part, involves running the analysis. This part is relatively straight forward since I will provide the SAS code for each assignment (on my website). The students are simply required to run this program and turn in the output. This helps achieve a small but important objective of this course – expose and make students conversant in a statistical package (SAS) that can help them conduct sophisticated analyses. This part of the assignment will be due, the Thursday (5pm) following the day when the assignments are handed out. The second part of the assignment will require students to interpret the output and make inferences/decisions based on the results. I will post the output of the program on Thursday evening, to assist you in this part (just in case you are unable to get the program to work). The second part of assignments I and II will be due in the 3^rd week and the 5^th Week respectively.

Term Project:

The term project is a group assignment, in which each group will work on a database-marketing problem of its choice. This enables students to apply the techniques discussed in class in developing a database marketing solution. Each group will turn in a report and present their findings to the class.

Mid-term Exam:

The exam will be conducted in the 5^th session and will test students on material covered in the first four sessions. The exam will be in-class and closed book. Students can expect multiple-choice and short questions on this exam.

Peer Evaluation:

With the exception of the mid-term, students will work on the assignments and the term project in groups. Since, individual group members may not all contribute equally to the task at hand, I seek your assistance in rating your group members (including yourself) on their contribution to the groups’ overall output. Rate each member of your group starting with yourself on 20 points, with 0 depicting that the particular member provided little or no input and with 20 depicting very valuable contribution. Your peer evaluation score will be the average of your groups’ rating of your contributions. I will provide the peer evaluation forms in the 7^th week. Bear in mind that you will be doing yourself (and other members of your group) a disservice if your rating of your contribution and/or the contribution of other group members is inaccurate. These evaluations are confidential and your ratings should not be shared with your group members. I reserve the right to discard valuations that are suspect.

Tentative Schedule

Week	Date	Topic
1.	October 21	Course Introduction Review of Regression Analysis
		Introduction to SAS
2.	October 28	Factor Analysis
		Data Reduction Technique
3.	November 4	Cluster Analysis (First Assignment Due)
		Segmentation Technique
4.	November 11	Discriminant Analysis
		Response Analysis Technique
5.	November 18	Logit Analysis (Second Assignment Due)
		Response Analysis Technique
6.	November 25	Project Presentations
7.	December 2	Final Exam
8.	December 8	Discussion