AI Digital Marketing: SEO, Google Ads & Email Automation

AI Digital Marketing: SEO, Google Ads & Email Automation
Marketing/Digital Marketing
English

Course Details

AI Digital Marketing: SEO, Google Ads & Email Automation

Artificial intelligence is changing how digital marketing is planned, executed, measured, and optimised.

But using AI effectively in marketing is not simply about generating content with ChatGPT or adding AI to individual tasks. The real opportunity is understanding where AI can improve the marketing process — from research and planning to execution, analysis, and optimisation.

This course provides a practical introduction to AI-powered digital marketing, covering SEO, content, Google Ads, email marketing, analytics, and marketing performance.

You will explore how AI can support different stages of the digital marketing workflow and how these applications fit together.

What you will learn

AI and Digital Marketing Strategy

Understand how AI is changing digital marketing and explore how it can support strategic planning, audience analysis, competitor research, and marketing decision-making.

You will also be introduced to AI prompt engineering for marketing, helping you work more effectively with generative AI tools.

AI for SEO and Content Marketing

Learn how AI can support:

  • Keyword research and SEO strategy

  • Content planning and development

  • Search-focused content creation

  • Technical SEO and website optimisation

  • Identifying opportunities for improving organic visibility

The focus is on using AI as part of the SEO process rather than treating AI-generated content as a substitute for SEO knowledge and human judgement.

Google Ads and PPC with AI

Explore how AI is being integrated into paid search advertising, including:

  • Google Ads fundamentals

  • Audience targeting and expansion

  • AI-assisted ad copy and creative optimisation

  • Smart Bidding

  • Budget optimisation

You will develop a clearer understanding of where AI can support paid advertising decisions and campaign optimisation.

AI for Email Marketing and Automation

Learn how AI can support email marketing through:

  • Customer and audience segmentation

  • Personalised email content

  • Campaign optimisation

  • Email automation

  • More efficient marketing workflows

The goal is to understand how AI can enhance email marketing without losing sight of audience needs and marketing objectives.

AI for Marketing Analytics and Performance

Data is essential to understanding whether marketing activity is working.

You will explore how AI can support:

  • Marketing performance measurement

  • KPI analysis

  • Predictive analytics

  • Attribution

  • Automated reporting

  • Continuous campaign optimisation

You will also consider the limitations of AI-generated analysis and the importance of human judgement when interpreting marketing data.

Why this course?

Many AI marketing courses focus on individual tools or isolated prompts.

This course takes a broader view.

You will see how AI can be integrated across several connected areas of digital marketing:

Research → Strategy → Content → SEO → Advertising → Email → Analytics → Optimisation

This helps you understand not just what AI tools can do, but where they fit within a real marketing workflow.

Who is this course for?

This course is suitable for:

  • Digital marketing professionals

  • SEO and content professionals

  • Google Ads and PPC professionals

  • Email and CRM marketers

  • Entrepreneurs and small-business owners

  • Freelancers and marketing consultants

  • Students and career changers

  • Professionals who want to understand practical applications of AI in marketing

No programming experience is required, and no prior AI expertise is necessary.

Basic familiarity with digital marketing concepts is helpful but not essential.

A practical approach to AI marketing

AI can make marketing work faster and more scalable, but faster does not automatically mean better.

Effective AI-supported marketing still requires clear objectives, good data, critical thinking, and human judgement.

Throughout the course, the emphasis is therefore on understanding how to use AI thoughtfully and effectively, rather than simply generating more content or automating more tasks.

By the end of the course, you will have a structured understanding of how AI can be applied across SEO, Google Ads, content marketing, email automation, and marketing analytics, and where these capabilities fit within the wider digital marketing process.


Course Author

Alex Amoroso, PhD
Senior UX Researcher | Product, Behavioural & Data Research

Alex Amoroso is a researcher, educator, and course designer with more than 10 years of experience across UX and product research, behavioural research, data, analytics, customer experience, strategy, and professional education.

Her work focuses on understanding behaviour, analysing evidence, identifying patterns, and turning complex information into clearer decisions.

She has conducted research across B2B and B2C environments, working with qualitative and quantitative data to investigate customer and user behaviour, evaluate digital products and experiences, identify problems, and support product and business decisions.

This background informs her approach to AI and digital marketing: AI can accelerate research, analysis, content development, and optimisation, but effective marketing still depends on understanding the audience, asking the right questions, evaluating evidence, and applying human judgement.

Alongside her professional research work, Alex teaches doctoral-level research design and methodologies, supervises and assesses research projects, and has developed approximately 30 online courses across research, UX, product, data, analytics, customer experience, business, and decision-making. Selected courses are also available through Udemy Business.

She holds a PhD in Health Anthropology, with research focused on human behaviour, environmental stress, and quantitative data analysis, and has published research in peer-reviewed journals.

Her teaching approach combines:

  • Research-based thinking

  • Practical frameworks and methods

  • Real-world applications

  • Clear explanations of complex subjects

  • A focus on turning information into better decisions

Her goal is simple: to help professionals understand complex subjects and use what they learn more effectively in practice.