DataBase Marketing (MKT 6223)
Professor:
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
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 |
|
|
|
|