Module Catalogue 2025/26

Pre Requisite Comment

Mathematics A-level recommended at grade B or above.

Co Requisite Comment

N/A

Aims

• Understand relevant core concepts and techniques used in marketing analytics.

• Critically apply marketing analytics to solve practical marketing problems in a variety of marketing areas and link them to a firm’s overall marketing strategy.

• Introduce software packages for developing analytical solutions to marketing problems.

• Equip students with basic skills to apply and interpret the results of different types of marketing analytical techniques for better decision-making.

Outline Of Syllabus

• Introduction to Marketing Analytics

• Customer Segmentation Techniques

• Predicting Customer Choice

• Understanding Customer Value I: Customer Lifetime Value

• Understanding Customer Value II: RFM Analysis

• Perceptual Maps.

• Optimising Products and Prices.

• Forecasting New Product Sales.

Intended Knowledge Outcomes

Upon successful completion of the module, students will able to:

• Understand the importance of marketing analytics in allocating marketing resources and developing marketing strategy.

• Critically evaluate a number of models and metrics that can be used to provide insight into common marketing issues.

• Conduct data analysis using advanced statistical techniques.

• Use modern computer software to solve common, practical marketing issues.

• Understand the limitations of marketing analytics and the importance of managerial judgement.

Intended Skill Outcomes

By participating in this module students are expected to enhance their skills as follows:

• Enhance analytical and written skills by completing the assessed work that consists of a proposal and a final assignment.

• Improve ability to identify relevant analytical techniques for common practical marketing problems.

• Advanced ability to use computer software to analyse business and customer data, interpret results, and derive meaningful recommendations.

Teaching Rationale And Relationship

The module involves a combination of pre-recorded lectures, online activities, and live computer laboratory sessions. Typically, theory and methods are learnt first in a lecture environment, intertwined with supporting online activities, which are then applied in the computer labs, using practical case examples using data and software.

The module applies flipped learning, whereby the lecture material is delivered asynchronously in blocks of approximately 20 minutes, punctuated by activities and readings to reinforce the learning. The face-to-face computer labs then allow the students to apply concepts and engage creatively with the subject matter.

Assessment Rationale And Relationship

The assessment will provide a semi-realistic case example and data for a company. The case will provide a brief background on the company, its plans and analytics needs. Students must use marketing analytical tools to aid in future decisions about the company. There are various problems and data that may be examined so they must be selective about the topic, techniques and data used.

To provide initial guidance to the students, an optional short (500-word) description and justification of their chosen marketing analytics data set, research problem and selected method of investigation may be submitted for formative assessment. Individual feedback will be provided which will facilitate the further development of the summative assessment. The summative assessment will consist of a final 2000-word report detailing the research problem, analysis, and results.

RESIT INFORMATION: If students are eligible to a second attempt resit will be an assignment and the resit calculation will be based 100% on the submission.

General Notes

N/A