AI for Search and Content Strategy

How search actually works today

• Understanding why Google and AI answer engines interpret the intent behind a query rather than matching keywords - and why this changes everything about how content needs to be written
• Recognising the three discovery channels every content strategy must address: organic search, AI answer engines and generative engine citation
• Understanding what E-E-A-T means and how search engines use it to judge whether content deserves to rank or be cited
• Seeing why zero-click search is growing and how to position content to be the source that gets cited rather than the one that gets bypassed

What your audience is actually searching for

• Understanding the four types of search intent - informational, navigational, commercial investigation and transactional - and what each one means for the content you need to create
• Using Google Keyword Planner and Search Console to see what real people actually type, rather than guessing
• Applying intent mapping to a real business or brand using AI tools including ChatGPT and Perplexity

Assessing what your website is doing well and where it falls short

• Auditing an existing website to identify which intent types are well served and which are missing entirely
• Using Google search and AI assistants to see how competitor content is currently being surfaced
• Building a gap analysis that prioritises where new content will have the greatest impact on visibility and commercial performance

Choosing the right type of page for the right purpose

• Understanding why different content goals require different page structures - and why the wrong structure reduces both ranking and AI citation
• Mapping the core page types to their intent types: overview pages, insight articles, learning path pages, glossary pages, free resource pages, capability pages and conversion pages
• Applying page type thinking to the course's through-line business and beginning a PageType inventory

The methodology: why keyword-first planning fails - and what works instead

• Understanding the domain-in, cluster-out approach: why describing your domain, audience and purpose produces better content architecture than starting with keywords
• Recognising why building content from a course agenda, service description or product feature list is the wrong starting point - and what to do instead
• Applying the methodology to any sector: commercial, academic, charitable or public

Planning content that covers your topic completely

• Understanding how topic clusters work and why grouped, interconnected content outperforms isolated pages
• Designing non-overlapping, intent-aligned clusters using AI tools - and testing them against the cluster design rules
• Avoiding the most common cluster planning mistakes: overlap, duplication and building clusters where genuine search demand does not exist

Turning clusters into specific content ideas

• Understanding the difference between a topic cluster and a search topic - and why this distinction matters
• Generating focused, independently searchable content ideas using AI tools and natural query patterns
• Applying the one-topic rule: ensuring each piece of content targets a single, distinct query and does not compete with other pages on the same site
• Prioritising a content list by search demand, business value and competitive opportunity

Writing content that search engines and AI assistants want to cite

• Structuring every page so the opening paragraph can be extracted as a standalone AI response
• Adapting tone, structure and depth to the requirements of each page type
• Using ChatGPT and Copilot to draft, structure and improve content aligned to a specific search query
• Reviewing AI-generated content for accuracy, tone, expertise and professional credibility

Making commercial pages work harder

• Understanding why commercial pages need a fundamentally different approach from informational content
• Building a commercial query set using Google autocomplete, Search Console and keyword tools
• Embedding commercial queries naturally into page titles, opening paragraphs and meta descriptions

Knowing whether the strategy is working

• Using Google Search Console to identify which pages are being seen but not clicked - and what to do about it
• Tracking AI citation: how to test whether your content is being surfaced by AI answer engines
• Building a simple measurement framework that turns content activity into actionable learning

Keeping content accurate, relevant and effective over time

• Setting a practical review schedule based on how fast your topic area changes
• Knowing when to refresh, consolidate or retire existing pages
• Building the minimum governance habits that keep a content strategy working without constant management

The wider landscape and next steps

• A rapid overview of the topics that sit around this course and that every content strategist needs to be aware of: technical SEO, backlinks, structured data, paid search and voice search
• Reviewing the complete content planning chain from intent mapping through to measurement
• Identifying the highest-priority actions to take in the two weeks after the course
• Understanding how to use AI tools as an ongoing strategic thinking partner - and what to learn next