Skip to the content | Change text size
PDF unit guide

FIT5158 Customer relationship management and data mining - Semester 1, 2011

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.

Mode of Delivery

Caulfield (Evening)

Contact Hours

2 hrs lectures/wk, 1 hr laboratory/wk

Workload

Students will be expected to spend a total of 12 hours per week during semester on this unit.
This will include:

  • two-hour lecture and
  • one-hour tutorial (or laboratory) (requiring advance preparation)
  • a minimum of 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

Prerequisites

FIT9004 or FIT9017

Chief Examiner

David Dowe

Campus Lecturer

Caulfield

David Dowe

Contact hours: To Be Confirmed - e-mail for other times/appointment

Clayton

David Dowe

Contact hours: To Be Confirmed - e-mail for other times/appointment

Tutors

Caulfield

Sumith Matharage

Asanka Fonseka

Learning Objectives

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.

Graduate Attributes

Monash prepares its graduates to be:
  1. responsible and effective global citizens who:
    1. engage in an internationalised world
    2. exhibit cross-cultural competence
    3. demonstrate ethical values
  2. critical and creative scholars who:
    1. produce innovative solutions to problems
    2. apply research skills to a range of challenges
    3. communicate perceptively and effectively

    Assessment Summary

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

    Assessment Task Value Due Date
    Assignment 1 - SQL Server and Data Warehousing 20% Week 7, Friday 15 April 2011
    Assignment 2 - Data Mining 20% Week 11, Friday 20 May 2011
    Examination 1 60% To be advised

    Teaching Approach

    Lecture and tutorials or problem classes
    This teaching and learning approach provides facilitated learning, practical exploration and peer learning.

    Feedback

    Our feedback to You

    Types of feedback you can expect to receive in this unit are:
    • Informal feedback on progress in labs/tutes
    • Graded assignments without comments

    Your feedback to Us

    Monash is committed to excellence in education and regularly seeks feedback from students, employers and staff. One of the key formal ways students have to provide feedback is through SETU, Student Evaluation of Teacher and Unit. The University's student evaluation policy requires that every unit is evaluated each year. Students are strongly encouraged to complete the surveys. The feedback is anonymous and provides the Faculty with evidence of aspects that students are satisfied and areas for improvement.

    For more information on Monash's educational strategy, and on student evaluations, see:
    http://www.monash.edu.au/about/monash-directions/directions.html
    http://www.policy.monash.edu/policy-bank/academic/education/quality/student-evaluation-policy.html

    Previous Student Evaluations of this unit

    If you wish to view how previous students rated this unit, please go to
    https://emuapps.monash.edu.au/unitevaluations/index.jsp

    Required Resources

    WEKA Data Mining software
    SQL Server (2008)
    This and other any software needed will be made available or provided.

    Unit Schedule

    Week Date* Activities Assessment
    0 21/02/11   No formal assessment or activities are undertaken in week 0
    1 28/02/11 CRM and Customer Intelligence  
    2 07/03/11 Storing Data for Customer Intelligence  
    3 14/03/11 Data Warehousing with SQL Server 2005  
    4 21/03/11 Dimensional Modeling  
    5 28/03/11 Data Warehouse and Analytical CRM  
    6 04/04/11 Online Analytical Processing  
    7 11/04/11 Introduction to Business Data Mining Assignment 1 due Week 7, Friday 15 April 2011
    8 18/04/11 Customer Relationship Management (CRM)  
    Mid semester break
    9 02/05/11 Decision Trees  
    10 09/05/11 Neural Networks  
    11 16/05/11 Collaborative Filtering and User Profiling Assignment 2 due Week 11, Friday 20 May 2011
    12 23/05/11 Customer Life Cycle and Data Mining  
      30/05/11 SWOT VAC No formal assessment is undertaken SWOT VAC

    *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.

    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

    Assessment Tasks

    Participation

    • Assessment task 1
      Title:
      Assignment 1 - SQL Server and Data Warehousing
      Description:
      Details will be provided.
      Weighting:
      20%
      Criteria for assessment:

      Details will be provided.

      Due date:
      Week 7, Friday 15 April 2011
    • Assessment task 2
      Title:
      Assignment 2 - Data Mining
      Description:
      Details will be provided.
      Weighting:
      20%
      Criteria for assessment:

      Details will be provided.

      Due date:
      Week 11, Friday 20 May 2011

    Examinations

    • Examination 1
      Weighting:
      60%
      Length:
      3 hours
      Type (open/closed book):
      Closed book
      Electronic devices allowed in the exam:
      None

    Assignment submission

    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.

    Extensions and penalties

    Returning assignments

    Policies

    Monash has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University's academic standards, and to provide advice on how they might uphold them. You can find Monash's Education Policies at:
    http://policy.monash.edu.au/policy-bank/academic/education/index.html

    Key educational policies include:

    Student services

    The University provides many different kinds of support services for you. Contact your tutor if you need advice and see the range of services available at www.monash.edu.au/students The Monash University Library provides a range of services and resources that enable you to save time and be more effective in your learning and research. Go to http://www.lib.monash.edu.au or the library tab in my.monash portal for more information. Students who have a disability or medical condition are welcome to contact the Disability Liaison Unit to discuss academic support services. Disability Liaison Officers (DLOs) visit all Victorian campuses on a regular basis

    Reading List

    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