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The University of Southampton

MANG6230 Data Driven Marketing

Module Overview

In today’s data driven environment, it is essential for marketers to understand how data can be used to drive marketing decisions. The aim of this module is to provide an introduction to data driven marketing tools and techniques common within the discipline. After studying this module, students will develop a conceptual understanding of these tools and how they can be included to support and improve marketing activities. This module will particularly focus on Customer Relationship Marketing but will consider important related areas.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

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

  • the potential of data for gaining actionable insights and supporting marketing decisions;
  • the various possible sources of customer/campaign data and how data is stored;
  • the common types of data driven marketing activities.
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • make informed decisions on when to employ data based techniques, and understand the practical difficulties and other issues involved;
  • identify suitable approaches for incorporating insights into marketing tasks;
  • discuss the different types of software tools that are relevant to data driven marketing activities and understand the basics of how to apply them.
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • manage time and tasks effectively in the context of individual study;
  • explain concepts clearly and critically apply findings.


The topics covered include: • Sources of data; from traditional customer surveys to customer contact and behavioural data, past marketing campaigns, web and web 2.0 data • Data storage, extraction, integration and pre-processing • KDD process models • Exploring/visualising data using OLAP and dashboards • Common analytical CRM tasks: segmentation and profiling, response modelling, churn prediction, customer lifetime value and market basket analysis. The precise topics covered may change slightly in response to what is determined to be the most relevant based on academic and industry practice.

Learning and Teaching

Teaching and learning methods

Teaching methods include: • Lectures exploring the problems and concepts • Discussion sessions where the tools can be practiced and applied • Guided independent study Learning activities include: • An assignment • Laboratory work • Case study/problem solving activities • Private study

Independent Study63
Total study time75

Resources & Reading list

Provost, F., and Fawcett, T. (2013). Data science for business. 

Management Science. 

Expert Systems with Applications. 

Journal of Interactive Marketing. 

Marketing Analytics. 

SPSS/PASW software. Computer labs equipped with SPSS/PASW software

Library Support. Access to journal articles to supplement readings

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



Computer practicals


MethodPercentage contribution
Individual Coursework  (2000 words) 100%


MethodPercentage contribution
Individual Coursework  (2000 words) 100%


MethodPercentage contribution
Individual Coursework  (2000 words) 100%

Repeat Information

Repeat type: Internal & External


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:


Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase the mandatory/additional reading 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

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