Introductory description

This module provides an in-depth exploration of eCommerce operations and optimisation techniques, integrating data science methodologies with operational management principles. Designed for postgraduate students in the Data Science and Operations specialism, it offers a comprehensive understanding of the technological and strategic aspects driving modern eCommerce businesses.

Module aims

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.

Data-Driven Decision Making in eCommerce

• Big data analytics for eCommerce
• Customer behaviour analysis and segmentation
• Predictive modelling for demand forecasting

Supply Chain and Inventory Management

• Digital supply chain optimisation
• Inventory management systems and strategies
• Last-mile delivery optimisation

Pricing and Revenue Management

• Dynamic pricing models
• Revenue optimisation techniques
• Competitive pricing strategies

Customer Experience and Personalisation

• User experience (UX) design principles for eCommerce
• Recommendation systems and collaborative filtering

eCommerce Platform Technologies

• eCommerce platform architectures
• Integration of payment gateways and security measures
• Mobile commerce and progressive web apps

Marketing Analytics and Customer Acquisition

• Search engine optimisation (SEO) for eCommerce
• Pay-per-click (PPC) advertising and conversion rate optimisation
• Social media marketing analytics

Fraud Detection and Risk Management

• Machine learning for fraud detection
• Risk assessment models in eCommerce
• Cybersecurity best practices for online retail

Emerging Technologies in eCommerce

• Artificial Intelligence and chatbots in customer service
• Augmented and Virtual Reality in online shopping experiences
• Blockchain applications in eCommerce

Ethics and Compliance in eCommerce

• Data privacy regulations and compliance (GDPR, CCPA)
• Ethical considerations in data utilisation
• Sustainable and responsible eCommerce practices

Learning outcomes

By the end of the module, students should be able to:

• Collaboratively analyse digital business requirements and practically implement an eCommerce website in a real-world setting
• Demonstrate a comprehensive understanding of the key eCommerce technologies to determine an appropriate solution for given use-cases
• Critically evaluate the systematic and operational risks associated with eCommerce implementations to develop comprehensive mitigation strategies
• Critically evaluate data science techniques to optimise key eCommerce operations.

Indicative reading list

Chaffey, D., Hemphill, T. and Edmundson-Bird, D., 2019. Digital Business and E-Commerce Management. 7th ed. Harlow: Pearson.
Krug, S., 2015. Don't Make Me Think, Revisited: A Common Sense Approach to Web Usability. 3rd ed. Berkeley: New Riders.
Qin, Z., Dr, Shuai, Q., Wang, G., Zhang, P., Cao, M. & Chen, M. 2022, E-commerce: concepts, principles, and application, Springer, Singapore;Xi'an;.
Laudon, K.C. & Traver, C.G. 2021, E-commerce: business, technology, society, Global;Sixteenth; edn, Pearson, New York;Harlow, England;.
Cao, J. 2023, E-commerce big data mining and analytics, Springer, China;Singapore;.

View reading list on Talis Aspire

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