Data Science for Digital Marketing

Why this course?

This course will teach you how to gain deeper marketing insights through the power of data science and enable you to become a better digital marketer.

Key benefits:

  • Tutor-led - University of Southampton academics will guide you through the content and answer your questions, unlike other online courses where you're left to your own devices
  • Continuing Professional Development (CPD) accredited, helping you demonstrate your commitment to upskilling at your next appraisal
  • Hands-on - learn how to use data science to better understand your organisation's customers. 

Developed by the pioneering Data Science team at the University of Southampton – ranked among the top 100 universities globally – this course will teach you how to effectively use data science techniques to improve your marketing insights, better understand your customers, and manage customer interaction in web-based environments.

Taught by industry-leading experts in data science using a practical approach to learning data skills and real-life business examples, this 6-week flexible online course will enable you to interpret how your customers engage and interact with your digital marketing efforts – helping you to become a more effective digital marketer.

The course runs over 6 weeks and is broken down into manageable weekly topics:

Week 1: Introduction to common web analytics tools

  • Googleverse
  • How people interact with sites
  • Setting goals
  • Basic site design – what Google wants
  • Google Analytics and search console
  • Facebook advertising

Week 2: Analytics for digital marketing

  • A/B testing
  • Reporting
  • Traffic and site journeys
  • Sources and conversations
  • Reporting dashboards
  • Integrating traffic with other business metrics

Week 3: Social network analysis

  • The role of social networks
  • Facebook advertising campaigns
  • Micro-segmentation
  • Graph theory
  • Tools for social media analytics
  • Content analysis methods

Week 4: Machine-learning

  • Definitions of data science
  • What is machine learning?
  • Different types of machine learning methods and models for marketers
  • Decision trees
  • Cluster analysis
  • How machine learning can be applied to website data
  • How to choose training data and evaluate the effectiveness of machine learning

Week 5: Application of machine learning in marketing

  • Using machine learning for attention, persuasion and retention
  • Your strategic role in applying machine learning to your work
  • Limitations of Artificial Intelligence (AI) and ethical considerations

Week 6: Big data and future applications

  • What is big data?
  • Volume, variety, velocity, and veracity dimensions and how they apply to marketing data sources
  • Cloud computing and distributed computing architectures
  • Data analysis in the cloud
  • Novel visualisations and applications
  • Future technological directions

After successfully completing the course, you’ll be able to:

  • Understand the role data science plays in digital marketing
  • Describe tools for web analytics and understand how customer journeys and sources can be tracked using these tools
  • Describe different ways in which social network analysis can be used to gain marketing insights
  • Apply content analysis methods to gain insights into your customer base
  • Explain what machine learning is and what it can be used for
  • Understand what big data is and how it applies to your business problems
  • Identify what data needs to be collected to ensure your digital marketing process is optimised


Les Carr

Les is Professor of Web Science at the University of Southampton’s School of Electronics and Computer Science. He’s also a Director of the Web Science Institute and former Director of the Web Science Centre for Doctoral Training. His research on Open Access and Open Data led to the establishment of Eprints – offering Open Access publication and data services, training and support to the research industry.


Gary Willis

Gary is an Associate Professor in Computer Science at the University of Southampton. He graduated from the University of Southampton with an Honours degree in Electromechanical Engineering, followed by a PhD in Industrial Hypermedia Systems. Gary is a Chartered Engineer, a member of the Institute of Engineering Technology, and a Principal Fellow of the Higher Educational Academy. He is also a visiting Associate Professor at University of Cape Town and a research professor at RLabs.


Rob Blair

Rob is Visiting Fellow at the University of Southampton’s School of Electronics and Computer Science. He holds an MSc Information Systems from the University of East Anglia and an MSc Web Science from the University of Southampton. Qualified to teach Physics, Mathematics and Computer Science, Rob is a highly-experienced classroom teacher and online tutor specialising in data science.


David Millard

Dave is Associate Professor of Computer and Web Science at the University of Southampton, David is a founding member of the Web and Internet Science research group within the School of Electronics and Computer Science (ECS). He represents ECS on the steering group for the Web Science Centre for Doctoral Training. David is currently Vice-Chair for ACM SIGWEB.


Manuel León Urrutia

Dr. Manuel León Urrutia is Research Fellow in the Web and Internet Science research group of the Electronics and Computer Science department of the University of Southampton. Manuel is specialised in learning technologies, with experience in learning design and research interests in MOOCs and learning analytics. Prior to joining the Computer Science department in 2012, he worked for 6 years as an editor in a publishing company, and 6 more years as a language teacher in the University of Southampton. Manuel currently has an academic, senior tutoring and learning design role in the Southampton Data Science Academy.

How you'll learn

Guidance thoughout the course

A key benefit of choosing Southampton Data Science Academy over some of the other online courses available is that our courses are tutor-led. A tutor is just as important with an online course as it is in a physical classroom. A good tutor’s passion for the subject will motivate you and inspire you, making the content stick in your mind.

Our tutors are data science experts who can make complex ideas accessible. If you don’t understand the course material right away they can provide an alternative explanation or use a different example. If you have a question about the content, our tutors are available to answer it. They will work with you to make sure you understand the subject fully and are on track to complete the course successfully.

Hands-on learning that you can immediately apply to your work

Learning is hands-on, using real-life business examples to demonstrate how you can immediately harness and apply the power of data science to your work. Our online learning platform is easy to access via smartphone, tablet or desktop – anytime and from anywhere in the world. You’ll join a global online network of like-minded professionals and take part in group discussions, Q&A sessions and video tutorials.

Our courses are also CPD-accredited. Many employers will ask you at appraisals to show evidence of the impact of Continual Professional Development (CPD) on your professional work. A CPD-accredited Southampton Data Science course is a great way to demonstrate your commitment to upskilling, especially as you will learn practical techniques and tools that you can immediately apply to your workplace.

Find out more about how you'll learn with Southampton Data Science Academy.

Ready to boost your data literacy?

Take our flexible online course and learn how to leverage data to achieve your business goals.

Apply now