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The University of Southampton

MANG2043 Analytics for Marketing

Module Overview

This module introduces some key concepts about the use of some basic statistical and analytical techniques within the marketing context. Students will learn through a combination of lectures, group work, practical (computer-lab) sessions (where needed), and self-study. After studying this module, students will be able to apply these techniques to analyse data in practice.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

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

  • how to use analytic techniques to evaluate the quality of data for supporting marketing decisions;
  • how to apply standard analytical tools to support marketing decisions.
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • differentiate suitable approaches for a range of analytics tasks;
  • implement analytic models to support marketing decision making.
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • explain concepts clearly and critically apply findings.
Subject Specific Practical Skills

Having successfully completed this module you will be able to:

  • apply and critically evaluate marketing intelligence techniques and use them to draw practical recommendations;
  • apply marketing concepts and evaluate them by using marketing intelligence techniques.


• Data types and their sources • Univariate/Descriptive statistics • Probability, cross tabulation and chi square • Discrete, Continuous and Sampling distributions • Interval estimation • Hypothesis testing • Comparisons of means • Correlation and linear regression

Learning and Teaching

Teaching and learning methods

The basic principal of the teaching and learning strategy for this unit is to encourage you to actively engage in the subject matter through guided self-discovery of the material which will include: Reading; lecture slides; case studies; discussion and debate.

Wider reading or practice15
Follow-up work32
Practical classes and workshops10
Completion of assessment task28
Preparation for scheduled sessions11
Total study time150

Resources & Reading list

Cortinhas, C. and Black, K. (2012). Statistics for Business and Economics. 

Burns, A. C., Veeck, A. and Bush. R. F. (2016). Marketing Research. 

Jelen, Bill, and Alexander, M. (2016). Excel 2016 Pivot Table Data Crunching. 

Middleton, Michael R. (2004). Data Analysis Using Microsoft Excel. 

McGivern, Yvonne (2013). The Practice of Market Research. An Introduction. 

McDaniel, Carl, and Gates, R. (2015). Marketing Research. 

McFedries (2013). Excel Data Analysis, Visual Blueprint. 

Winston, W. L (2014). Marketing Analytics: Data-Driven Techniques with Microsoft Excel. 



Class Exercise


MethodPercentage contribution
Essay  (3000 words) 100%


MethodPercentage contribution
Essay  (3000 words) 100%


MethodPercentage contribution
Essay  (3000 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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