MKT42400 Consumer Insights & Analytics

Academic Year 2023/2024

Marketers can now utilise a fast-growing volume of customer data to generate insights and make better decisions. Yet, data is not information, and information is not insight. Data is only of value when it is collected rigorously, analysed correctly, and more importantly, when it is translated into insights that help marketers to make better decisions. This course aims to highlight latest advances in customer insights and analytics and to understand the benefits and limitations of various approches. You’ll learn how to translate business problems into research questions, and how to evaluate and implement appropriate research designs, and how to generate marketing insights from online and offline data.

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Curricular information is subject to change

Learning Outcomes:

Learning Objectives
Understand how to read and intepret customer data
Learn how to collect, clean, analyse and interpret data from sources such as surveys, websites, apps, or geo-tracking.
Learn about various methods to analyse customer data
Comprehend the difference between correlation and causation
Understand the basic concepts of predictive analytics
Learn about key (customer) metrics like ROI and CLV

Indicative Module Content:

Analytical Techniques every marketer needs to know;
Descriptive statistics
Sampling & Inferential statististics
Analysis of independent groups (e.g., T-Tests)
Correlation and regression
Marketing experiments
Calculating ROI and other KPIs
Predictive Analytics
Customer Lifetime Value

Student Effort Type Hours


Small Group




Requirements, Exclusions and Recommendations

Not applicable to this module.

Module Requisites and Incompatibles
Not applicable to this module.
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: AB Testing Simulation Unspecified n/a Graded No


Continuous Assessment: Weekly presentations and questions Throughout the Trimester n/a Graded No


Multiple Choice Questionnaire: Online Quizzes Unspecified n/a Graded No


Carry forward of passed components
Resit In Terminal Exam
Spring No
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Online automated feedback
• Peer review activities

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Dr David DeFranza Lecturer / Co-Lecturer
Tutorial Offering 1 Week(s) - 6, 7, 8, 9, 10, 11, 12 Thurs 12:00 - 12:50
Lecture Offering 1 Week(s) - Autumn: All Weeks Tues 09:00 - 11:50
Tutorial Offering 1 Week(s) - 2, 3 Wed 12:30 - 13:30
Tutorial Offering 2 Week(s) - 6, 7, 8, 9, 10, 11, 12 Thurs 12:00 - 12:50
Lecture Offering 2 Week(s) - Autumn: All Weeks Tues 14:00 - 16:50
Tutorial Offering 2 Week(s) - 2, 3 Wed 12:30 - 13:30
Tutorial Offering 3 Week(s) - 6, 7, 8, 9, 10, 11, 12 Thurs 12:00 - 12:50
Lecture Offering 3 Week(s) - Autumn: All Weeks Wed 09:00 - 11:50
Tutorial Offering 3 Week(s) - 2, 3 Wed 12:30 - 13:30

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