WM9QW-15 eCommerce Operations and Optimisation
Introductory description
This module provides an in-depth exploration of both strategic and operational dimensions of modern eCommerce, combining design principles, data analytics, and operational management to optimise digital commerce performance. Students will learn to analyse eCommerce challenges, design user-centred solutions, and apply data-driven optimisation techniques across customer experience and digital operations. Through practical application of conversion rate optimisation (CRO) methodologies, A/B testing frameworks, and analytics tools, students will develop the skills to evaluate eCommerce platforms and propose evidence-based improvements. The module balances technical foundations with strategic thinking around customer segmentation, supply chain efficiency, and implementation planning.
Module aims
This module examines the advanced technologies, processes, and strategies that drive modern eCommerce operations and optimisation. It covers a comprehensive range of topics, balancing technical aspects such as data analytics, machine learning applications, and platform architectures with managerial considerations like supply chain optimisation and integration of eCommerce solutions with broader business operations.
The module develops both design thinking skills and analytical capabilities to optimise business performance. Students will learn to synthesise insights from customer behaviour data, operational metrics, and industry benchmarks to develop practical, evidence-based optimisation strategies.
Through collaborative projects and individual case analysis, students gain hands-on experience with industry-standard tools and methodologies applicable to eCommerce roles in retail, technology companies, and digital consultancy.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
eCommerce Foundations
- eCommerce Technology
- eCommerce Operations
- eCommerce Analytics
eCommerce Design & Conversion Rate Optimisation
- eCommerce Design Principles
- Wireframing and Prototyping
- CRO Key Concepts
- CRO Strategies and Theories
- Data-driven CRO: Testing Techniques
eCommerce Analytics for Operations & Optimisation
- Customer Analytics (Customer Segmentation, Customer Experience, Personalisation)
- Data-Driven Optimisation: Demand, Supply Chain, and Inventory
- AI and Machine Learning in eCommerce Operations
- Digital Marketing Analytics
- Risk Management, Security, and Ethical Data Practices
Learning outcomes
By the end of the module, students should be able to:
- Critically evaluate e-commerce design and user experience and propose design improvements applying CRO principles and industry best practices
- Critically analyse e-commerce operational practices and propose data-driven optimisation strategies
- Assess implementation feasibility of proposed e-commerce optimisation solutions, considering associated risks, resources, and business impact.
- Collaboratively analyse e-commerce business challenges and develop evidence-based optimisation strategies suitable for practical implementation
Indicative reading list
Reading lists can be found in Talis
Specific reading list for the module
Subject specific skills
Data analysis for ecommerce, ecommerce platform optimisation, supply chain analytics, web development, data science, pricing strategy development
Transferable skills
Data-driven decision making, presentation skills, research, teamwork, software development, critical thinking
Study time
| Type | Required |
|---|---|
| Lectures | 10 sessions of 1 hour (7%) |
| Seminars | 20 sessions of 1 hour (13%) |
| Online learning (independent) | 20 sessions of 1 hour (13%) |
| Private study | 40 hours (27%) |
| Assessment | 60 hours (40%) |
| Total | 150 hours |
Private study description
Private study will include preparing for lectures and seminars, reviewing lecture notes, and engaging with required readings and multimedia resources.
Costs
No further costs have been identified for this module.
You must pass all assessment components to pass the module.
Assessment group A
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
Assessment component |
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| Business Report | 70% | 42 hours | Yes (extension) |
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A business-style report critically evaluating and recommending data-driven strategies for eCommerce optimisation. Students will analyse a specified industry case and propose comprehensive optimisation strategies supported by relevant data science techniques and operational management principles. |
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Reassessment component |
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| Business Report | No | ||
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A business-style report critically evaluating and recommending data-driven strategies for eCommerce optimisation. Students will analyse a specified industry case and propose comprehensive optimisation strategies supported by relevant data science techniques and operational management principles. |
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Assessment component |
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| eCommerce optimisation challenge | 30% | 18 hours | No |
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Working in teams, students will analyse e-commerce business operation challenges, develop optimisation solutions using appropriate tools and methodologies, and evaluate potential outcomes. Teams will present findings and recommendations supported by evidence-based analysis. |
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Reassessment component |
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| eCommerce optimisation challenge - Individual Assessment | No | ||
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Students will individually analyse e-commerce business operation challenges, develop optimisation solutions using appropriate tools and methodologies, and evaluate potential outcomes. Students will submit a written report presenting findings and recommendations supported by evidence-based analysis. Students should also critically evaluate the principles and practices of collaborative working in eCommerce optimisation projects. |
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Feedback on assessment
Verbal and written feedback will be provided for the Group Project. Written feedback will be provided for the Business Report assignment.
Courses
This module is Optional for:
- Year 1 of TWMS-H1S4 Postgraduate Taught e-Business Management (Full-time)