The University of Southampton
Courses

MANG3056 Data Mining for Marketing

Module Overview

Companies nowadays have collected a large volume of data from various sources. This module aims to introduce the key concepts of using ‘Big Data’ to improve marketing activities. Specifically, it focuses of the use of data mining techniques to manage customer relationships. Relevant marketing issues such as customer surveys, profiling/segmentation, communications, campaign measurement, satisfaction, loyalty, profitability, social media and other current topics will be discussed with regard to how data mining and analytical approaches can be used to improve marketing decision making. In this module, students will get hands-on experience and will be introduced to software commonly used in marketing departments and organisations. Thus, this module seeks to equip students with key skills needed to manage real marketing decisions based on marketing data.

Aims and Objectives

Module Aims

This module will introduce the key concepts of using and analysing data with a particular focus of their application to marketing problems. The issues of customer surveys, profiling/segmentation, communications, campaign measurement, satisfaction, loyalty, profitability, and social media will be discussed with regard to how data mining and analytical approaches can be used to improve decision making for marketing activities. Notably, students will get hands-on experience in using data analytic techniques and software to make marketing decisions based on data.

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • The potential of data mining for gaining actionable marketing insights and for supporting marketing decision making
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • Explain and evaluate concepts and tools needed to evaluate, analyse, and interpret marketing data
  • Plan the resources needed to evaluate and analyse data, critically apply findings, and disseminate the outcomes
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • Demonstrate the ability to persuade, convince and argue effectively.
  • Analyse datasets to provide insight into marketing activities
  • Manage yourself, time, and resources effectively
Subject Specific Practical Skills

Having successfully completed this module you will be able to:

  • Develop technical and analytical skills
  • Apply and critically evaluate marketing concepts by using marketing intelligence techniques to draw practical recommendations

Syllabus

Topics include: - Data preparation: Data storage, extraction, integration and pre-processing - Key marketing tasks, e.g., segmentation and profiling - Exploring/visualising data using software - Descriptive vs. predictive analytics: Application of analytical techniques to marketing decisions

Special Features

N/A

Learning and Teaching

Teaching and learning methods

Teaching methods include: The basic principle of the teaching and learning strategy for this module is to encourage you to actively engage in the subject matter through guided self-discovery of the material which will include: Reading; lecture slides; practical classes/computer lab sessions; exercises; discussion and debate. As with all programmes in the Faculty, student learning will also be supported by published course materials and the University's virtual learning environment (VLE).

TypeHours
Wider reading or practice20
Follow-up work24
Completion of assessment task54
Preparation for scheduled sessions18
Lecture24
Practical classes and workshops10
Total study time150

Resources & Reading list

Field, A. (2009). Discovering statistics using SPSS. 

Winston, W.L. (2014). Marketing Analytics: data driven techniques with Microsoft Excel. 

Linoff, G.S. and Berry, M.J.A. (2011). Data mining techniques: for marketing, sales and customer relationship management. 

Baesens, B. (2014). Analytics in a big data world. 

Davenport, T.H. & Harris, G. H. (2007). Competing on Analytics: the New Science of Winning. 

Assessment

Formative

In-class activities

Summative

MethodPercentage contribution
Individual project  (3000 words) 100%

Repeat

MethodPercentage contribution
Individual project  (3000 words) 100%

Referral

MethodPercentage contribution
Individual project  (3000 words) 100%

Repeat Information

Repeat type: Internal & External

Linked modules

Prerequisites: MANG1019 OR MANG1007

Pre-requisites

To study this module, you will need to have studied the following module(s):

CodeModule
MANG1007Management Analysis
MANG1019Foundations of Business Analytics

Costs

Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:

Textbooks

Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase the core/recommended text as appropriate.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at www.calendar.soton.ac.uk.

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