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Professor Geoff Webb
Phone: +61 3 990 53296
Fax: +61 3 990 55159

Contact hours: Tuesday 1-2pm - email for other times/appointment

Lecturer(s) / Leader(s):


Professor Geoff Webb
Phone: +61 3 990 53296
Fax: +61 3 990 55159

Contact hours: Tuesday 1-2pm - email for other times/appointment


Professor Geoff Webb
Phone: +61 3 990 53296
Fax: +61 3 990 55159

Contact hours: Tuesday 1-2pm - email for other times/appointment

Additional communication information:

Professor Geoff Webb
Clayton School of Information Technology
Faculty of Information Technology
Monash University, Clayton Vic 3800
Email webb@infotech.monash.edu.au


Room 220, Building 63 Clayton

Room 6.45, Building H, Caulfield


Welcome to FIT5158 Customer Relationship Management and Data Mining. This 6 point unit belongs to the Business Systems track in the Master of Business Information Systems degree. The unit fits in well with other business intelligence units such as Data Warehousing and Business Intelligence. FIT5158 focuses on business data analysis in a customer relationship management context highlighting the importance of building a customer centric organization.

Unit synopsis

This unit provides an understanding of the business value of customer relationship management and how data mining technology can be used to improve organizational interaction with customers. Building a business around the customer relationship is the aspiration of many modern organizations. Customer relationship management and data mining has been combined together to provide the required concepts, techniques, technology and tools to achieve this goal. The unit discuss how IT and IT based techniques can be used for customer segmentation, clustering and classification, market basket analysis and association rule mining in addition to traditional CRM.

Learning outcomes

At the completion of this unit students will be able to:
  • use software tools and techniques for identifying business opportunities;
  • plan direct marketing campaigns and product introductions;
  • analyse and understand customer churn with data mining tools;
  • create stable and accurate predictive models and interpret results;
  • provide advise to management on CRM;
  • advise management on data mining techniques and tools.

Contact hours

2 hrs lectures/wk, 1 hr laboratory/wk


* two-hour lecture and
* one-hour tutorial (or laboratory) (requiring advance preparation)
* a minimum of 2-3 hours of personal study per one hour of contact time in order to satisfy the reading and assignment expectations.
* You will need to allocate up to 5 hours per week in some weeks, for use of a computer, including time for newsgroups/discussion groups.

Unit relationships



Teaching and learning method

Teaching approach

The unit will be delivered via lectures and laboratories.
Lecture: During the lecture, your lecturer will introduce key theoretical concepts and demonstrate various approaches to database tasks. The time in lectures is quite brief, please ensure you gain the best advantage from this time by:
• Prior to the lecture
o downloading and reading the lecture notes,
• During the lecture
o annotate a printed set of lecture notes as the lecture proceeds, and
o participate, question, seek clarification
• After the lecture
o read over you notes and make sure you understand the concepts
o seek help if you are unsure

Timetable information

For information on timetabling for on-campus classes please refer to MUTTS, http://mutts.monash.edu.au/MUTTS/

Tutorial allocation

On-campus students should register for tutorials/laboratories using the Allocate+ system: http://allocate.its.monash.edu.au/

Unit Schedule

Week Date* Topic Key dates
1 01/03/10 CRM and Customer Intelligence  
2 08/03/10 Storing Data for Customer Intelligence  
3 15/03/10 Data Warehousing with SQL Server 2005  
4 22/03/10 Dimensional Modeling  
5 29/03/10 Data Warehouse and Analytical CRM  
Mid semester break
6 12/04/10 Online Analytical Processing  
7 19/04/10 Introduction to Business Data Mining  
8 26/04/10 Customer Relationship Management Assignment 1 due - Friday - 30/4/10, Week 8
9 03/05/10 Decision Trees  
10 10/05/10 Neural Networks  
11 17/05/10 Collaborative Filtering and User Profiling  
12 24/05/10 Customer Life Cycle and Data Mining Assignment 2 due - Friday - 28/5/10, Week 12
13 31/05/10 Revision  

*Please note that these dates may only apply to Australian campuses of Monash University. Off-shore students need to check the dates with their unit leader.

Improvements to this unit

More practical tutorial and examples in lectures will be introduced

Unit Resources

Prescribed text(s) and readings

Data Mining Techniques for Marketing, Sales and CRM, M. Berry and G. Linoff, Wiley, 2004

Text books are available from the Monash University Book Shops. Availability from other suppliers cannot be assured. The Bookshop orders texts in specifically for this unit. You are advised to purchase your text book early.

Recommended text(s) and readings

• Practical Business Intelligence with SQL Server 2005 by John C. Hancock and Roger Toren, Addison Wesley, 2006
• The Microsoft Data Warehousing Toolkit by Joy Mundy and Warren Thornthwaite, John Wiley & Sons, 2006

Required software and/or hardware

WEKA Data Mining software

SQL Server 2008

Equipment and consumables required or provided

Students studying off-campus are required to have the minimum system configuration specified by the Faculty as a condition of accepting admission, and regular Internet access. On-campus students, and those studying at supported study locations may use the facilities available in the computing labs. Information about computer use for students is available from the ITS Student Resource Guide in the Monash University Handbook. You will need to allocate up to 5 hours per week for use of a computer, including time for newsgroups/discussion groups.

Study resources

Study resources we will provide for your study are:

* Weekly detailed lecture notes outlining the learning objectives, discussion of the content, required readings and exercises;
* Weekly tutorial or laboratory tasks and exercises with sample solutions provided one to two weeks later;
* Assignment specifications;
* A sample examination and suggested solution;
* This Unit Guide outlining the administrative information for the unit;
* The unit web site on MUSO, where resources outlined above will be made available.



Examination (3 hours): 60%; In-semester assessment: 40%

Faculty assessment policy

To pass a unit which includes an examination as part of the assessment a student must obtain:

  • 40% or more in the unit's examination, and
  • 40% or more in the unit's total non-examination assessment, and
  • an overall unit mark of 50% or more.

If a student does not achieve 40% or more in the unit examination or the unit non-examination total assessment, and the total mark for the unit is greater than 50% then a mark of no greater than 49-N will be recorded for the unit.

Assignment tasks

Assignment coversheets

Assignment coversheets are available via "Student Forms" on the Faculty website: http://www.infotech.monash.edu.au/resources/student/forms/
You MUST submit a completed coversheet with all assignments, ensuring that the plagiarism declaration section is signed.

Assignment submission and return procedures, and assessment criteria will be specified with each assignment.

  • Assignment task 1
    Assignment 1 - SQL Server and Data Warehousing
    Due date:
    Friday - 30/4/10, Week 8
  • Assignment task 2
    Assignment 2 - Data Mining
    Due date:
    Friday - 28/5/10, Week 12


  • Weighting: 60%
    Length: 3 hours
    Type (open/closed book): Closed book

See Appendix for End of semester special consideration / deferred exams process.

Due dates and extensions

Please make every effort to submit work by the due dates. It is your responsibility to structure your study program around assignment deadlines, family, work and other commitments. Factors such as normal work pressures, vacations, etc. are not regarded as appropriate reasons for granting extensions. Students are advised to NOT assume that granting of an extension is a matter of course.

Students requesting an extension for any assessment during semester (eg. Assignments, tests or presentations) are required to submit a Special Consideration application form (in-semester exam/assessment task), along with original copies of supporting documentation, directly to their lecturer within two working days before the assessment submission deadline. Lecturers will provide specific outcomes directly to students via email within 2 working days. The lecturer reserves the right to refuse late applications.

A copy of the email or other written communication of an extension must be attached to the assignment submission.

Refer to the Faculty Special consideration webpage or further details and to access application forms: http://www.infotech.monash.edu.au/resources/student/equity/special-consideration.html

Late assignment

Assignments received after the due date will be subject to a penalty of 5% per day, including weekends. Assignments received later than one week (seven days) after the due date will not normally be accepted. In some cases, this period may be shorter if there is a need to release sample solutions.

This policy is strict because comments or guidance will be given on assignments as they are returned, and sample solutions may also be published and distributed, after assignment marking or with the returned assignment.

Return dates

Students can expect assignments to be returned within two weeks of the submission date or after receipt, whichever is later.


Please visit the following URL: http://www.infotech.monash.edu.au/units/appendix.html for further information about:

  • Continuous improvement
  • Unit evaluations
  • Communication, participation and feedback
  • Library access
  • Monash University Studies Online (MUSO)
  • Plagiarism, cheating and collusion
  • Register of counselling about plagiarism
  • Non-discriminatory language
  • Students with disability
  • End of semester special consideration / deferred exams
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