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MKT46150

Academic Year 2024/2025

Consumer Insights & Analytics (MKT46150)

Subject:
Marketing
College:
Business
School:
Business
Level:
4 (Masters)
Credits:
7.5
Module Coordinator:
Dr David DeFranza
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

Marketers today have unprecedented access to a rapidly expanding volume of customer data, offering a unique opportunity to derive actionable insights that drive impactful marketing strategies. However, raw data alone holds little value until it is meticulously collected, accurately analysed, and, most crucially, transformed into insights that directly inform and enhance marketing decisions. This course focuses on empowering marketers with the latest advances in customer insights and analytics, equipping them to leverage these insights for strategic advantage. You’ll explore how to customer insights play a critical role in addressing marketing challenges, how to evaluate and implement effective research designs, and how to generate marketing insights from both online and offline data. By doing so, you’ll learn to craft data-driven marketing actions that not only meet business objectives but also foster long-term customer engagement and growth.

About this Module

Learning Outcomes:

1. Understand how customer insights and the use of analytics can help marketers achieve strategic business objectives.
2. Assess different analysis methodologies and choose the most suitable design for specific marketing problems
3. Transform raw data into meaningful information and actionable insights that can inform and enhance marketing strategies and decisions
4. Develop a critical understanding of various customer analytics tools and methods, recognizing their potential benefits and limitations in different marketing contexts

Indicative Module Content:

Customer segmentation
Customer lifetime value
A-B testing
Marketing experiments
Campaign analytics and ROI
Text analysis
AI for marketing analytics
(Big &) Complex marketing data

Student Effort Hours:
Student Effort Type Hours
Lectures

24
Autonomous Student Learning

144
Total

168

Approaches to Teaching and Learning:
This is a fast-paced class that will be delivered through a combination of lectures, case discussions and in-class exercises. The class heavily depends on students' preparation. It is vital to have read the cases and assigned materials prior to the class.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Exam (In-person): The final exam will be one hour long and consist of 30 case-based multiple-choice questions. The exam will be held at the Blackrock Exam Centre. End of trimester
Duration:
1 hr(s)
 Alternative linear conversion grade scale 40% No
40
 No
Individual Project: Students in this course will participate in a simulation. Week 6, Week 7 Alternative linear conversion grade scale 40% No
40
 No
Quizzes/Short Exercises: Before each case discussion, students are required to submit a short analysis of the case, answering question provided in class. Week 2, Week 3, Week 4, Week 5, Week 6, Week 7, Week 8, Week 9, Week 10, Week 11, Week 12, Week 14, Week 15 Pass/Fail Grade Scale No
20
 No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Assoc Professor Marius Claudy Lecturer / Co-Lecturer

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Exam Offering 1 Week(s) - 12 Fri 10:00 - 11:50
Autumn Lecture Offering 1 Week(s) - Autumn: All Weeks Tues 11:30 - 13:20
Autumn Exam Offering 2 Week(s) - 12 Fri 10:00 - 11:50
Autumn Lecture Offering 2 Week(s) - Autumn: All Weeks Tues 09:00 - 10:50
Autumn Exam Offering 3 Week(s) - 12 Fri 10:00 - 11:50
Autumn Lecture Offering 3 Week(s) - Autumn: All Weeks Wed 10:00 - 11:50
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