School of Management                                                                                                         Spring Semester 2004

University of Texas at Dallas                                                       Monday 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:                                         Tuesday – 4-6pm or by appointment                                

 

Texts:

 

(I)                 The New Direct Marketing – David Shepard Associates (Not Required)

 

 

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

         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 3rd week and the other due in the 5th week.  The assignments will require students to interpret the output and make inferences/decisions based on the results.  I will post the output of the analysis on my website.   

 

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.

 

Exam:

 The exam will be conducted in the final session and will test students on material covered in the 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 exam, 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 7th 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.

March 15

Course Introduction

Review of Regression Analysis

 

 

Introduction to SAS

2.

March 22

Factor Analysis

 

 

Data Reduction Technique

3.

March 29

Cluster Analysis  (First Assignment Due)

 

 

Segmentation Technique

4.

April 5

Discriminant Analysis

 

 

Response Analysis Technique

5.

April 12

Logit Analysis (Second Assignment Due)

 

 

Response Analysis Technique

6.

April 19

Project Presentations

 

 

 

7.

April  26

Final Exam