Module manager: Verdiana Giannetti
Email: v.giannetti@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2025/26
| LUBS2840 | Marketing Research |
| LUBS3845 | Marketing Strategy |
This module is not approved as a discovery module
In an increasingly competitive and data-driven marketplace, a company’s success is increasingly dependent on its ability to understand customer behaviour, preferences, and lifetime value so to build sustainable relationships and drive long-term profitability. This module aims to provide students with a comprehensive overview of Customer Relationship Management (CRM) and customer analytics, equipping them with both strategic and data-driven approaches to managing customer relationships. The module integrates key concepts from marketing strategy, marketing analytics, data science, and behavioural marketing to provide students with the necessary skills to analyse and optimize customer interactions. Through the application of analytical tools and techniques, students will learn how to interpret customer segmentation, design effective retention strategies, and evaluate customer lifetime value (CLV), among other things. These insights will enable them to enhance customer experiences, improve engagement, and maximize revenue potential. By bridging theory with practical application, this module prepares students to navigate real-world challenges in customer management, making data-informed decisions that align with business objectives. The module is particularly relevant for students interested in marketing, business analytics, and customer-centric strategy development.
This module aims to equip students with the knowledge, skills, and analytical techniques required to manage customer relationships effectively in a data-driven business environment.
By integrating strategic and data-driven approaches, students will learn how businesses can leverage customer data to improve engagement, retention, and profitability. The module combines key concepts from marketing strategy, analytics, data science, and behavioural marketing to provide students with essential skills in customer segmentation, retention strategies, and customer lifetime value (CLV), among others.
Through a blend of theoretical foundations and hands-on application, students will develop a deep understanding of CRM, customer analytics techniques, and the role of data-driven decision-making in optimizing customer experiences. Additionally, the module emphasizes ethical considerations and compliance with data privacy regulations, ensuring that students are equipped to apply CRM strategies responsibly.
Upon completion, students will be able to:
1. Understand CRM Fundamentals
- Define and explain the core principles of Customer Relationship Management (CRM).
- Analyse CRM’s role in business strategy and its impact on competitive advantage.
- Examine how traditional CRM has evolved into digital and AI-driven systems.
2. Apply Customer Analytics Techniques
- Identify key customer data sources and data collection methods.
- Use customer segmentation, predictive analytics, and machine learning models for customer insights.
- Apply data visualisation and reporting techniques to support business decisions.
3. Develop Customer Engagement Strategies
- Design and evaluate customer engagement strategies to enhance satisfaction.
- Assess the effectiveness of CRM strategies.
4. Enhance Customer Retention and Loyalty
- Measure customer lifetime value (CLV) and predict customer churn.
- Analyse loyalty programs, retention techniques, and relationship marketing strategies.
- Evaluate case studies of successful CRM implementations in leading organisations.
5. Analyse Ethical and Legal Aspects of CRM
- Understand key data privacy laws such as GDPR.
- Discuss ethical challenges in collecting, storing, and using customer data.
- Develop strategies to ensure compliance and responsible CRM practices.
Learning Activities to Achieve These Aims and Objectives
To help students meet these objectives, the module includes:
- Lectures and Readings: Cover fundamental and advanced CRM concepts.
- Case Studies and Industry Examples: Offer real-world insights into CRM applications.
- Data Analysis Workshops: Provide hands-on experience with customer data analytics.
- Group Discussions and Debates: Encourage critical thinking on CRM strategies and ethical issues.
By combining theory with practical application, this module prepares students to manage customer relationships effectively, make data-driven marketing decisions, and implement customer-centric strategies in competitive business environments.
Upon successful completion of the module, students will be able to:
- Critically evaluate customer relationship management (CRM) frameworks and analyse their impact on business performance.
- Apply and adapt customer analytics techniques, including segmentation, predictive modelling, and churn analysis, to improve customer engagement strategies.
- Design and implement data-driven CRM strategies that enhance customer retention, loyalty, and satisfaction across different industries.
- Recognise and apply ethical considerations, data privacy regulations (e.g., GDPR), and corporate social responsibility principles in CRM practices.
On successful completion of the module students will have demonstrated the following skills learning outcomes:
1. Work-ready skills
- Critical thinking
2. Digital skills
- Information, Media, and Digital Literacies
3. Enterprise skills
- Applying Creativity and Innovation
- Working and Communicating with Others
4. Academic skills
- Problem solving
5. Sustainability skills
- Ethical and Strategic Practice
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lecture | 10 | 1 | 10 |
| Seminar | 5 | 1 | 5 |
| Private study hours | 85 | ||
| Total Contact hours | 15 | ||
| Total hours (100hr per 10 credits) | 100 | ||
Throughout the module, students' progress will be actively monitored through in-class exercises, unassessed pop quizzes, and interactive discussions during lectures. The practical sessions will encourage the students to engage with the material before class and apply their knowledge during hands-on exercises.
For the statistical modelling component, students will work individually on computer-based exercises, applying the models learned in lectures to solve marketing problems. Immediate feedback will be provided to enhance understanding and application. Various exercises will be used to illustrate how different analytical models can be applied to tackle different marketing challenges effectively.
Students will have multiple opportunities for formative feedback throughout the module. Individual meetings can be booked during weekly office hours to discuss progress, seek clarification, and address any areas of difficulty. Additionally, a dedicated discussion forum on Minerva will be available, allowing students to ask questions, engage with peers, and receive further support.
To assist with the individual report preparation, students will have the opportunity to receive written feedback on their outline plans before submission, helping them refine their approach. This structured support system ensures that students receive continuous guidance and constructive feedback to maximise their learning experience.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Coursework | 2,000 word Individual Report | 100 |
| Total percentage (Assessment Coursework) | 100 | |
The resit for this module will be 100% by 2,000 word individual report.
The reading list is available from the Library website
Last updated: 30/04/2025
Errors, omissions, failed links etc should be notified to the Catalogue Team