To prepare your content for generative search in 2026, you need to structure it around real user questions, provide clear answers upfront, organise information so it can be easily extracted, and demonstrate credible, experience-based insight. Content that is vague, generic, or poorly structured is far less likely to be cited by AI systems, regardless of how well it ranks in traditional search.

Key Takeaways: What to Do Differently To Improve GEO Visibility in 2026

If you are adapting your content for generative search, the shift is less about doing more and more about doing things differently. You need to focus on clarity, structure, and credibility at every stage of content creation.

• Start with real questions, not keywords
  Build content around what your audience is actually asking across search, sales, and support.
• Answer clearly and early
  Lead with the answer, then explain, rather than burying key information deeper in the content.
• Organise content so it is easy to follow and reuse
  Use clear sections, simple language, and logical flow so parts of your content make sense on their own.
• Prioritise expertise over generic content
  Include real examples, practical insight, and clear methods based on actual experience.
• Think beyond the article as a whole
  Make sure your content includes explanations, definitions, and processes that can stand alone.
• Keep content current and accurate
  Regular updates improve trust and increase the chances of your content being used.

Read on to understand exactly why this shift is happening.

Why Traditional SEO is No Longer Enough

Imagine a potential client searches for exactly the kind of question your organisation is best placed to answer. Whether they are asking ChatGPT and Gemini, or turning to Google — where AI Overviews now surface a response before the results even appear — the AI generates an answer that doesn’t cite you. It cites someone else. To prevent this and prepare your content for generative search in 2026, you must structure your content around real questions, format it for AI extraction, and lead with credible, experience-based insight.

When a competitor gets cited instead of you, you might assume this is a ranking problem. It isn’t. The reality is that the AI didn’t just answer what was asked. It invisibly expanded that question, factoring in context, intent, and industry before choosing a source.

Generative search has fundamentally changed how people find and trust information. Instead of scanning a page of links, users now ask questions inside AI-powered tools such as Google’s AI Overviews, ChatGPT, Perplexity, and Microsoft Copilot. These tools interpret information from multiple sources and present a single, clear response, often without requiring users to visit several websites. 

Content that is unclear, difficult to interpret, or lacking real expertise is unlikely to be used in AI-generated answers, regardless of how well it ranks in traditional search. Unfortunately,  most content being published today falls into this category because it is too generic, too loosely organised, or too difficult for systems to confidently understand and reuse.

Simply put: It is no longer enough for your content to rank. It needs to be clear enough to be used as part of an answer. 

Traditional search engine optimisation still plays an important role in helping search engines discover and index your content. However, as outlined in SEO vs. AI SEO: How to Get Found and Chosen in Generative Search, optimising for algorithms alone does not fully prepare content for how AI systems evaluate and use information. Generative Engine Optimisation (GEO) addresses this gap by focusing on making content clear, well organised, and trustworthy so it can be selected and included in AI-generated answers.

Here is a detailed look at how to practically apply these steps to your content:

1. Start With Real Questions to Drive Your AI SEO Strategy

One of the biggest changes in generative search is how people ask for information. As we explored in Search Behaviour 2025: How Artificial Intelligence Is Redefining the Customer Journey, users are moving away from browsing and toward asking. Instead of typing short keyword phrases, they now ask complete questions that reflect what they are actually trying to understand or solve. This changes the starting point for content strategy in a meaningful way, requiring a shift in how topics are identified and prioritised.

For example, traditional SEO often begins with terms such as “SEO audit services” or “senior care marketing.” In contrast, generative search begins with questions like “What does a proper SEO audit include?” or “How can I improve visibility in AI search results?” These questions are more specific, more intent-driven, and require more complete answers than keyword-based content typically provides.

Because of this shift,  if your content does not clearly answer these types of questions, it is unlikely to be used by AI systems. Fortunately,  most organisations already have access to these questions, as they appear in search queries, internal site search, customer support emails, sales calls, proposal documents, and onboarding conversations. These sources reflect how real people think and what they want to know, making them far more valuable than abstract keyword lists.

By gathering and grouping these real-world questions into themes, you can build a content plan that reflects real needs instead of relying only on keyword tools. Once the right questions are identified, the focus shifts to how they are answered. AI systems favour answers that are clear, direct, and easy to understand, which means stating the answer early, using plain language, and avoiding unnecessary filler.

Ultimately,  content that genuinely helps someone understand a topic will consistently perform better than content written mainly to rank. This shift in strategy also means rethinking how you measure success. As discussed in From SEO Reports to Artificial Intelligence Visibility Metrics: What To Track in 2026, visibility is increasingly tied to whether content is used, cited, and trusted, not just whether it is clicked.

2. Organise Content for Generative Engine Optimisation (GEO)

In a generative search environment, how your content is organised matters just as much as what it says. According to Google’s documentation on AI Overviews, AI systems rely on clear, well-structured information to determine what content to include in generated answers.

This is because AI systems do not read content in the same way people do; instead, they analyse how information is structured before deciding how to use it. When content is unclear, overly dense, or loosely organised, it becomes harder for these systems to identify and reuse the most relevant parts. Think of it like a well-organised filing cabinet: everything has a clear place, and anyone who needs something specific can find it quickly and confidently. AI systems work the exact same way.

Well-organised content makes this process easier by clearly separating ideas, showing how concepts relate to each other, and allowing specific pieces of information to stand on their own without losing meaning. This is why clear headings and well-developed paragraphs are important, as they help both readers and AI systems understand what each section is about and how it connects to the overall topic.

In fact, foundational research on Generative Engine Optimization (GEO) by Princeton and Georgia Tech supports this, showing that structuring content with clear formatting and distinct concepts can boost a website’s visibility in AI-driven search responses by up to 40%.

Beyond basic formatting,  the way information is presented also plays a key role. Clear definitions, simple explanations, and step-by-step guidance are easier to understand and reuse. For example, defining a term in plain language before expanding on it helps build clarity, while explaining a process in a logical order makes it easier to follow and apply.

At the same time, it is important not to over-simplify or break content into too many small pieces. Too many short fragments can remove context and make the content harder to follow. Instead,  each paragraph should communicate a complete idea so that it makes sense on its own while still contributing to the overall narrative.

3. Lead With Real Expertise, Not Generic Content

As generative search evolves, the quality of content matters more than ever because AI systems are more likely to use content that shows clear expertise and avoid content that feels generic or repetitive. Basic explanations are no longer enough, as many AI tools can already generate these independently.

In fact, research from Gartner predicts a massive shift toward AI for everyday information gathering by 2026. As these tools drive up the volume of generic, synthetic content, it makes relying on real, experience-driven differentiation more important than ever before.

What these systems cannot easily replicate is real-world experience, practical examples, and clearly explained methods. This creates an opportunity for organisations to stand out by going beyond surface-level content and providing insight that reflects actual work and experience.

Including examples from your work, describing common challenges, or explaining how you approach a problem adds depth and credibility. These details show that your content is based on experience rather than theory,  helping to build trust with both readers and AI systems.

It is also important to show who created the content. Including the author’s name and experience helps establish credibility, particularly in industries where trust is essential. In some cases, adding a reviewer with relevant qualifications can strengthen this further.

Finally,  explaining your own processes or frameworks is another effective way to demonstrate expertise, as it makes your content more distinctive and useful. Referencing reliable external sources, such as the Government of Canada Digital Standards, can also support your points and  solidify that trust.

4. Format Content to Capture ChatGPT Citations

Your content no longer appears in just one place. It can be used in summaries, direct answers, follow-up questions, comparisons, and step-by-step explanations across different AI tools. Because of this, it is important to think of your content as more than a single article, but rather  as something that can be used in multiple ways.

Within a well-written piece, there are usually several parts that can stand on their own, such as a clear answer to a question, a short definition, or a simple explanation of a process. These elements increase the likelihood that your content will be selected and reused in different types of responses.

The goal is not to artificially break content into pieces, but to ensure that these clear and useful sections exist naturally. For example, an article might begin with a direct answer, followed by a more detailed explanation, then include clearly defined terms and a section that explains a process step by step.

For lean teams, this is a meaningful advantage. Rather than producing large volumes of content to cover every possible question, a single, well-structured article can support multiple uses without requiring additional content creation.

5. Strengthen Trust Signals to Optimize for AI Overviews

Trust plays a central role in whether your content is used by AI systems, as outlined in Google’s guidance on creating helpful, reliable content. These systems compare information across multiple sources and favour content that appears accurate, consistent, and transparent. Maintaining that trust requires attention at every level of your content, starting with how current your information is.

Keeping your content up to date is one of the simplest ways to maintain credibility. For AI engines, freshness is increasingly tied to whether content is surfaced at all. Even if your core message remains valid, outdated statistics, broken links, or old terminology act as immediate red flags that reduce trust.

However, freshness alone isn’t enough; who stands behind the content matters just as much. Transparency is crucial here. Providing clear contact details, author information, and visible,  organised information signals to AI systems that there is a legitimate, accountable source driving the content. This goes hand-in-hand with accuracy, as unsupported claims or exaggerated statements are quickly filtered out by AI cross-referencing.

Finally, this commitment to trust must extend beyond the words on the page to the platform itself. Technical quality, like having a secure, fast, and well-maintained website, cements your overall credibility.

Ultimately, these layers of optimization determine whether AI systems view you as a reliable source worth citing. In the age of AI search, trust is no longer just a brand value; it is a technical and structural commitment that dictates every decision you make about your content.

FAQ: Preparing Content for Generative Search

What is generative search?

Generative search refers to AI-driven systems that answer questions directly by synthesising information from multiple sources, rather than simply listing links. Examples include Google AI Overviews, ChatGPT, and Perplexity AI.

How is generative search different from traditional SEO?

Traditional SEO focuses on ranking web pages in search results. Generative search focuses on whether your content is selected, summarised, and cited within AI-generated answers.

What is Generative Engine Optimisation (GEO)?

GEO is the practice of structuring and writing content so it can be clearly understood, extracted, and reused by AI systems in generated responses.

Why isn’t my high-ranking content being cited?

Because ranking is no longer the only factor. If your content is unclear, generic, or poorly structured, AI systems may ignore it in favour of more usable sources.

About the Author

Mhairi Petrovic is the founder of Out-Smarts Marketing, a digital marketing agency that helps purpose-driven organisations improve their visibility through ethical, transparent, and practical strategies. With more than twenty years of experience in digital marketing, search engine optimisation, online advertising, and content strategy, Mhairi specialises in supporting healthcare, senior care, and community-focused organisations. She believes in clarity over complexity, and in building marketing systems that serve real humans first.

The post Generative Search Content Strategy: How to Optimize for AI Overviews in 2026 appeared first on Out-Smarts.

• Discovery has moved upstream: most journeys start on social media, move to AI for validation, and only then reach Google.
  
• Volume down, quality up: organic sessions may dip while direct, branded, and LLM-referral traffic rise. Visitors are more qualified.
  
• Measure beyond rankings: track AI citations, entity/brand strength, question-led queries, recency, and E-E-A-T signals alongside classic SEO.
  
• Report outcomes, not just clicks: frame visibility as trust and recognition across social → AI → search, not only position.
  

The Ground Has Shifted

For years, marketing leaders equated visibility with neat charts: rankings, impressions, organic sessions. Those reports haven’t vanished, but the meaning behind them has. Discovery now begins before search. People encounter brands through social posts or videos, validate what they’ve seen in AI tools like ChatGPT or Perplexity, and only use Google if they still need to compare, confirm, or act.

This layered path means the traditional SEO dashboard captures only a fraction of reality. The clicks that reach your site tell just the final chapter, not the story that made the visit possible. (For a behaviour primer, see our companion piece: How People Search and Engage Online in 2025.)

The Limits of Traditional SEO Metrics

Classic SEO metrics were designed for a linear experience: query → click → visit → convert. That model collapses when information is summarised and amplified upstream. In healthcare, senior care, and other regulated sectors, where credibility is non-negotiable, your brand may be referenced in AI summaries, discussed on LinkedIn, or understood via expert round-ups well before the first click. Yet attribution lags; dashboards look flat because the middle of the journey is invisible.

The New Data Reality

Across Out-Smarts’ client analytics, we’re seeing the same pattern:

• Organic traffic trends down. Social content and AI answers often satisfy early curiosity before a click.
  
• Direct traffic trends up. After seeing your brand cited in an AI response or social thread, people skip search and type your URL or brand name.
  
• Referrals from large language models (LLMs), AI chat platforms like ChatGPT and Perplexity, are emerging in GA4. Some visits are clearly tracked, while others appear as ‘unassigned’ sessions but show high engagement and behaviour specific to your brand.
  

The key advantage is the quality of these visitors. They often come already familiar with your brand and closer to making a decision. Engagement deepens; conversion paths shorten. As Search Engine Land notes in its overview of generative engine optimisation (GEO), visibility in AI-mediated discovery behaves more like earned media rather than simple rank-and-click acquisition (open access).

Redefining Visibility

In 2025, visibility is no longer just about ranking; it’s about being recognized and cited, both by humans and algorithms. The journey now moves through three layers:

1. Social discovery: Interest begins. Credibility grows through association and engagement.
   
2. AI exploration: Understanding develops. Clear, well-sourced content and topical authority are rewarded.
   
3. Search validation: Intent leads to action. Technical strength and structured content become critical.

Measurement should follow the full journey, not just the landing page, to capture real impact.

What to Measure Now

AI Citations and Mentions

Generative systems increasingly cite their sources, and that’s becoming a measurable visibility signal. Start monitoring how often your website appears in AI-generated answers. Perplexity.ai makes this easy because it lists its citations directly. For models that don’t fully expose sources (like ChatGPT), run manual checks on key queries to see whether your content is being referenced or summarised.

Industry analysts are already pointing to AI-citation visibility as the next major reporting metric. In other words, it’s not just about ranking pages anymore; it’s about how often AI systems use your content to construct their answers.

Entity and Brand Strength

To get noticed by AI and search engines, your data needs to be structured and consistent. That means using schema for your business, articles, FAQs, and authors, keeping bios and credentials accurate, and making sure your name, address, and phone number match everywhere. Google has confirmed that when your business information is clearly defined, it’s more likely to appear in AI-generated summaries.

Question-Led QueriesLLM 

Generative discovery starts with questions. In tools like Search Console and GA4, track natural language queries such as “how,” “what,” and “why.” These queries indicate where users and AI are looking for answers and context.

Freshness and Recency

AI tools pay attention to currency, meaning that newer information carries more weight. Updating key pages every few months, showing when they were last updated, and keeping short change logs can improve your visibility. Studies like Ahrefs SEO & AI Search Checklist confirm that recent content is more likely to appear in AI-generated responses.

E-E-A-T and Transparency

Experience, Expertise, Authoritativeness, and Trustworthiness remain foundational. Make author credentials visible, cite primary sources, and link to reputable organisations (e.g., Government of Canada Open Data; sector regulators). Transparent sourcing increases perceived authority (see Harvard Business Review coverage on trust signals; public pieces are available, avoid paywalled items).

Building a Multi-Layer Visibility Dashboard

We recommend combining classic SEO with AI-era visibility in one view:

• Keep your baseline: organic impressions, rankings, backlink quality, conversions.
  
• Layer in AI visibility: citations/mentions, branded query growth, structured-data health, freshness cadence, and LLM referral patterns.
  
• Track the social → AI → search flow: correlate social engagement spikes with subsequent branded/direct visits and AI citations.
  

This dual model captures what conventional SEO misses: the trust your content earns upstream. For a strategic foundation, see our anchor piece: SEO vs AI SEO: How to Get Found in the Age of Generative Search.

Reporting to Leadership

Executives care less about rank and more about reputation, recognition, and results. Reframe reports to emphasise:

• Inclusion in AI Overviews or LLM answers as evidence of third-party trust.
  
• Growth in branded search and direct sessions as recognition signals.
  
• Higher conversion rates from LLM-referred and direct cohorts as proof of quality over volume.
  

What Comes Next

Analytics platforms are moving toward metrics like AI citation tracking, entity confidence, and brand trust indices. Expect dashboards that look more like media monitoring than keyword sheets: where you were quoted, by which engines, and with what sentiment. The organisations that adapt now will read their pipelines more accurately – and fund content that compounds trust.

The Out-Smarts Perspective

We don’t view the drop in organic volume as a loss; we view it as refinement. Clients in healthcare, senior care, and other purpose-led sectors are attracting more qualified visitors – people who encountered their expertise upstream (social or AI), then arrived with intent. The journey has lengthened, but the signal has sharpened. Visibility today isn’t just about being found; it’s about being trusted before the click – and that trust converts.

Coming Up Next (Internal Link Preview)

We’ll publish a hands-on companion to this piece:
How to Prepare Your Content for GEO (Generative Engine Optimisation) in 2026 – A Practical Framework for Lean Marketing Teams.
(We’ll link it here once live.)

About the Author

By Mhairi Petrovic, Founder, Out-Smarts Marketing
Published: 19 November 2025

Mhairi Petrovic (pronounced Va-ri) is the founder of Out-Smarts Marketing, a digital agency helping healthcare, senior-care, and purpose-driven organisations strengthen online visibility through ethical, transparent, and results-focused strategies. With more than two decades in SEO, advertising, and content strategy, she and the Out-Smarts team guide brands through the evolving landscape of AI-driven discovery.
Connect with Mhairi on LinkedIn

The post From SEO Reports to AI Visibility Metrics: What to Track in 2026 appeared first on Out-Smarts.

Key Takeaways

Search isn’t linear anymore. In 2025, people discover problems on social media, research with AI tools, and validate through Google and peer networks.

• Discovery starts before intent. Social and AI reveal needs people didn’t know they had.
  
• AI tools shape visibility. Clear, structured content gets cited and surfaced in AI summaries.
  
• SEO spans multiple platforms. Visibility depends on being findable, credible, and consistent across touchpoints.
  
• Measurement is evolving. Focus on brand visibility and engagement, not just last-click attribution.
  

Businesses that adapt early, optimising for both humans and AI, will build trust faster and stay discoverable wherever their audiences actually search.

The Biggest Shift in Search Behaviour Yet

I’ve seen many evolutions in digital marketing over the past two decades, but it’s evolving faster and more dramatically than anything I’ve ever seen. Previous SEO updates were small and easier for organizations to adapt. 

The recent addition of AI in search is having a big impact on many businesses, including healthcare and purpose-led organisations. Many organizations seem unsure of how to make their websites appeal to both humans, AI, and traditional SEO. Is AI-search a temporary trend or something long-term that needs our marketing attention now? 

When it comes to search, people increasingly start their journeys on social platforms like TikTok, Instagram, and LinkedIn rather than on Google (HubSpot, 2024). At the same time, AI tools such as ChatGPT, Claude, and Gemini are becoming part of early-stage research to compare products, interpret data, or clarify jargon before traditional searching begins (Statista, 2025).

While Google still matters for validation and comparison, it’s no longer the default starting point for SEO, as it has been for the past 20+ years.

Today’s buyer might encounter a pain point on social media, ask AI for context, watch reviews on YouTube, check Reddit for unfiltered opinions, and only then visit a company website. That’s not a funnel. It’s a pinball machine. In this article, I’ll explore how organizations can tailor their content and SEO strategies for this new way of searching.

How Customers Buy: Then vs. Now

It’s long been understood that a customer needs multiple touchpoints with your brand before making a buying decision. In the past, these were usually touchpoints that you controlled (your website, social media account, ads, and other owned content. Today, this single “should I buy” decision may lead them through multiple channels (not necessarily content you control): a TikTok spark, ChatGPT research, a Google search, a LinkedIn scroll, a Reddit review, a YouTube demo. 

For small and mid-sized marketing teams, it can feel impossible to get your content on all these platforms. Instead, look at it as a chance to simplify. You don’t have to be everywhere; you just have to show up where your audience actually makes sense of problems. Wherever you decide to create content, you need to create content that is human and user-friendly.

The Problem Discovery Stage (Where Google Isn’t Dominant Anymore)

In the past, many businesses focused most of their SEO and content efforts on creating content for people who already know what they need, not those still naming their problem. While this is still true today, a growing audience is still naming their problem, and that’s where AI meets SEO. Businesses need to shift their SEO and content strategy to cater to the problem discovery phase in AI search. 

For example, instead of targeting SEO keyword phrases like “best telehealth platforms,” a healthcare tech company could write articles about “why patients skip follow-ups” or “hidden admin inefficiencies costing clinics revenue.” These topics address the pain points people are researching on AI platforms, rather than the solution (at least to start). This kind of content educates before it sells, positioning your brand as a trusted expert before the buyer is even in-market. It’s this kind of content that AI search is more likely to include in its responses to queries. 

Research Mode (Platform Hopping Goes Wild)

As people learn more about their pain point, and see your organisation mentioned in AI search results or social media, they switch to research mode to learn more about you. This part of SEO and traditional marketing strategies hasn’t changed as much: building credibility and trust.

As they research, they may explore content on platforms and tools like: 

• Google (still the go-to for detailed answers).
  
• LinkedIn (builds credibility and peer trust).
  
• Reddit (provides real-world experiences and third-party opinions).
  
• YouTube (shows proof in action).
  
• AI tools (to synthesise their research into shortlists, comparisons, and summaries.
  

As searchers land on AI search tools, you want your content to be quoted and referenced. This only happens when it’s structured and clear. AI can only summarise what it can understand. Humans can only trust what feels genuine. Aim for both, starting with the strategies in the next section.

Platform Strategies That Work

Your SEO and content strategy on each platform will be slightly different. Here’s our top, high-level strategies for popular online channels to help guide users through their discovery phases as they use traditional search and AI tools:

• Google: Focus your keywords SEO phrases for people who know what they’re looking for. Prioritise optimizing content for Google algorithms that are in-depth, E-E-A-T, and intent-based. 
• AI Tools: To get referenced in AI search results, structure your content for visibility. Use headers, bullets, and FAQs to make your expertise easy for AI and humans to read. 
• TikTok: This channel is becoming a fast-rising star as a search engine for younger audiences. On this platform, create content that skips the sales pitch and focuses on quick, useful, authentic insights.
• YouTube: Continue using video and shots to build authority through tutorials, walk-throughs, and case studies.
• LinkedIn: Let team members speak. Authentic, personal posts often outperform polished corporate updates.
• Instagram: Think “visual storytelling with substance.” Use Instagram for carousel posts, quick insights, or behind-the-scenes content and stories.

The AI Integration Reality

AI is now the first research stop for millions of users (Pew Research, 2024). People ask tools like ChatGPT for summaries, comparisons, or industry snapshots before ever visiting a brand’s site.

Use this as an opportunity to get discovered by your target audience early in their research phase. To do this, make your content AI-friendly:

• Use structured formatting (headers and bullet lists).
• Keep paragraphs concise.
• Focus on clarity and context over keyword stuffing.
• Add an FAQ section for related, commonly searched questions
• Don’t forget to write descriptive meta titles and descriptions (AI looks for these).
• Add author bios and credentials to build credibility 
• Add publish and update dates to content (so AI can assess recency)

SEO and AI are merging. SEO ensures your content is found. AI ensures it’s understood and reused. When your brand can master both, you’ll increase your visibility in our evolving world of online search. 

What AI SEO Means for Your Business

SEO has long been a necessity for businesses to establish and grow their online visibility. Now organizations must add an AI layer to their strategy to cater to the new way people discover and search online. 

To help you get started, here’s my recommended first four steps:

1. Map your real customer journey. Ask recent customers what influenced them (don’t guess).
   
2. Pick your platform focus. Instead of spreading yourself too thin, choose two or three platforms to focus on (base these on where your customers spend their time online).
   
3. Create structured, layered content. Create content that acknowledges a problem and creates awareness, compares solutions, and offers solution guidance.
   
4. Prepare for longer sales cycles. More research means slower conversions. Prepare for a longer sales cycle, but potentially stronger commitment from those who eventually choose your solution.
   

The Challenge of Modern Search Measurement 

Like any marketing strategy, you need to measure its effectiveness. Unfortunately, AI SEO is a non-linear path, making it hard for traditional analytics to provide accurate measurements. Someone might discover you on social media, research via AI, visit through search, and convert after a retargeting ad weeks later. Currently analytics can’t track this multi-platform navigational path, so you may never know where your customers come from. 

Shift your analytics strategy from chasing attribution perfection to monitoring brand strength indicators:

• Branded search volume
  
• Direct traffic
  
• Engagement and mentions across platforms
  

These brand indicators show whether your audience is recognising and remembering you. (Of course, you can still use traditional metrics like click-through-rates to measure the effectiveness of individual campaign paths)

My Take

It’s been fascinating to watch how SEO has evolved over the past 20+ years. I believe that AI-search isn’t a passing phase. It’s forever going to change the landscape of digital marketing.

Yes, it’s more complex, but it’s also more human. Today’s buyers are curious, cautious, and connected. The brands that meet them with transparency and clarity will win loyalty long before conversion. This can be your brand!

To achieve this brand trust, show up consistently and conversationally across multiple platforms to educate, without shouting or tooting your own horn too loud. This is how you’ll become the trusted voice that helps people make sense of their challenge.

At Out-Smarts Marketing, this is our focus: helping the care sector and purpose-led organisations adapt to how people actually search, decide, and buy today. From SEO and AI-ready content to transparent reporting, our work centres on clarity, credibility, and results.

Let’s chat more about how you can adapt your traditional SEO strategy to make it appealing for the future of AI-search. Book a free discovery call today to ask your questions. 

Mhairi Petrovic (pronounced [ˈvaːrɪ]) is the founder of Out-Smarts Marketing and specialises in search behaviour and digital strategy. She helps organisations understand how customers discover and evaluate products across platforms, and turn those insights into ethical, effective marketing strategies.

Connect with Mhairi on LinkedIn

The post Search Behaviour 2025: How AI Is Redefining the Customer Journey appeared first on Out-Smarts.

TL;DR

Search isn’t dying; it’s rewriting its own rules. Generative AI platforms like ChatGPT, Perplexity, and Google’s AI Overviews have shifted discovery from lists of links to synthesized, conversational answers.

For healthcare care, and purpose-led organisations, this means visibility now depends on being cited as the trusted source, not just ranking well.

Winning in this new landscape means:

• Keeping SEO fundamentals: Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T); structured content; and technical hygiene.
  
• Creating content with clear, verifiable answers.
  
• Maintaining accuracy, recency, and trust signals that AI engines can verify.
  
• Tracking new KPIs like citations in AI Overviews and question-led engagement.
  

SEO hasn’t been replaced by AI SEO optimization; it’s expanded to include it.

From Found to Chosen: Understanding the New Search Ecosystem

For decades, SEO worked like a library: you searched for a keyword, and Google handed you a tidy stack of results. Strong keywords, credible backlinks, and technical consistency helped you climb that stack.

AI search has evolved that model. SEO is now like talking to an expert: you ask a question, and an answer appears in a conversational, summarized form, based by sources hidden behind the synthesis.

It’s powerful for users, but presents some high-stakes challenges for organisations. If your content isn’t chosen or cited by another source or page, you risk being written out of the digital conversation entirely.

Gartner estimates organic traffic could drop by 25% by 2026 as AI-driven search absorbs more queries into direct answers.  Google’s rollout of Google AI Overviews confirms that discovery now happens within AI responses, not just on result pages.

Regardless, being found still matters. But being chosen, trusted, cited, and surfaced as the source, matters more. 

The Common Ground: What Still Works Everywhere

Despite the changes, the foundations of search haven’t vanished. Both traditional SEO and AI SEO depend on:

1. Content quality and E-E-A-T: Experience, Expertise, Authoritativeness, and Trustworthiness remain non-negotiable. It’s still important to demonstrate your qualifications, cite credible data, and publish transparent editorial policies. (Google Search Central)

2. Structured content and schema: Use clear headings, consistent hierarchies, and schema markup (FAQ, Article, Organisation) to help crawlers and AI understand context and relationships.

3. Internal linking and topical depth: Build internal networks of content to prove subject mastery — this improves answer extraction and user navigation alike.

4. Credible citations: Link to reputable, verifiable sources. For example, a healthcare provider might link to Health Canada, Statistics Canada, and The Canadian Institute for Health Information (CIHI). Outgoing links strengthen your perceived authority in both human and AI evaluation.

Where Paths Split: SEO vs AI SEO

Traditional SEO Still Matters

Even as AI-driven discovery changes how people find information, strong SEO fundamentals remain the foundation for effective online presence. The tactics below still contribute to being seen, trusted, and technically sound enough for both search engines and AI systems to reference.

• Keyword strategy: Align content around search intent, with natural inclusion of primary and secondary keyword phrases that match what users are actually looking for.
  
• Technical excellence: Core Web Vitals, mobile responsiveness, indexability, and canonicalisation (choosing the preferred URL of a webpage for search engines to crawl and rank) remain key.
  
• Backlink authority: Quality mentions on third-party sites and digital PR still correlate strongly with rankings.
  
• Analytics: Track impressions, clicks, click-through rate (CTR), and conversions via Search Console and Google Analytics 4.
  

AI SEO Requires New Thinking

AI SEO calls for a shift in mindset, from optimising for algorithms to communicating with machines that think more like people. With the rise of generative search, The focus now is on clarity, credibility, and conversation: creating content that answers questions directly, proves its claims, and stays fresh enough to be trusted as a reliable source. Be sure to consider:

• Answer-first design: Lead each key page with a concise, direct answer. Then expand into proof, data, and examples.
  
• Conversational tone: Optimise for how real people ask questions — “How do I choose a safe care home?” not “senior care options BC.”
  
• Data integrity: Cite verifiable, localised data (e.g. Government of Canada Open Data) and update regularly.
  
• Recency signals: Add visible timestamps and change logs; freshness now outweighs static authority.
  

For example, a patient safety organisation could improve visibility in AI-generated results by refreshing FAQs with current incident data and linking to trusted sources such as Healthcare Excellence Canada. 

Why Care and Purpose-Led Organisations Need a Different Playbook

Care and purpose-led organisations operate in a space where trust is everything. People turn to them for reliable guidance on health, safety, and wellbeing, so every word published carries weight. That’s why these sectors need a more deliberate approach to SEO and AI visibility: one that treats accuracy, transparency, and accountability as non-negotiable parts of the strategy. This includes: 

• Compliance and accuracy: Content must align with current standards and regulations such as PIPEDA and provincial health privacy frameworks.
  
• Source transparency: Make author credentials, publication dates, and updates visible.
  
• Ethical communication: Clarity, empathy, and transparency matter. Avoid jargon, always disclose sources, and explain limitations where appropriate.
  
• Trust signals: Prominently display author bios, credentials, and review cycles. Include a “last updated” date and brief note on the relevant review processes.
  

These cues help AI systems and humans alike assess reliability, and reward it by using it in AI search results.

The Out-Smarts Dual-Optimisation Framework

The Out-Smarts Dual-Optimisation Framework is a practical roadmap for balancing traditional SEO with emerging AI search demands. It’s designed to help care and purpose-led organisations strengthen visibility, credibility, and compliance across both SEO ecosystems. Each phase builds on the last, from strengthening technical foundations to refining content, enhancing accessibility, and optimizing the right mix of SEO and AI-era performance metrics.

Here are a few activities we typically include in each phase of a Dual-Optimisation Framework project:

Phase 1 — Foundation Building

• Audit content for keyword gaps and unanswered questions
  
• Implement schema for Organisation, FAQ, and Article pages
  
• Standardise architecture and fix technical errors
  
• Publish E-E-A-T assets: bios, editorial policy, and review notes
  

Phase 2 – Content Evolution

• Rewrite high-intent pages with an answer-first intro, followed by context and examples
  
• Build FAQ clusters from site search data and “People Also Ask”
  
• Add concise, citable definitions and sector data from sources
  

Phase 3- Technical and Accessibility Optimisation

• Improve Core Web Vitals and ensure pages are scannable (short paragraphs, bullets, headings)
  
• Include transcribed videos or downloadable summaries where relevant
  
• Optimise for voice and assistive interfaces using clear Q&A blocks and pronounceable phrasing
  

Phase 4 – Monitoring and Adaptation

• Continue tracking traditional SEO metrics (rankings, traffic, conversions)
  
• Add new AI SEO metrics:
  
  • Citations in Google AI Overviews and Perplexity
    
  • Question-led traffic
    
  • Engagement with FAQs and informational resources
    
• Conduct quarterly content freshness checks and publish change logs to maintain authority and trust
  

Process in Practice: Building Sustainable SEO + AI Workflows

Sustainable SEO and AI optimisation rely on consistency, not one-off fixes. The process below outlines how to weave AI tools and traditional SEO practices into a single, repeatable workflow  to keep your content accurate, empathetic, and visible across both human and machine audiences.

1. Plan: Map key customer journeys, from awareness to returning visitors,and identify what content each audience needs based on their search intent at different stages.
2. Draft: Use AI tools for ideation and outline support only. Keep all final writing and editing human-led to ensure tone, compliance, and empathy.
3. Review: Cross-check every fact, citation, and claim against credible Canadian sources. Maintain a reviewer-of-record system for document oversight.
4. Update: Schedule quarterly reviews for top pages. Replace outdated stats or guidance as soon as possible and update change logs publicly.
5. Measure: Use dashboards to track both classic SEO and new AI indicators — including brand mentions in AI platforms and referral patterns from answer engines.

This process shifts your SEO from a “set-and-forget” strategy to a live, measurable trust engine to be reviewed more often.

Measuring What Matters in the AI Era

Traditional metrics (impressions, click-through rate, rankings, and conversions) remain core indicators of reach and performance. But, AI-driven search introduces a new layer of visibility measured by trust and citation.

Measuring what matters for AI search includes: 

• Citations in AI results: Track how often your brand or content is referenced in AI Overviews or platforms like Perplexity. (This is currently a manual process, but one day it may be automated).
  
• Referral traffic from AI tools: Use UTM parameters or referral data to identify visits originating from AI interfaces (like Chat GPT)
  
• Question-led engagement: Monitor (via Search Console and GA4) which pages draw visitors through natural-language or voice-style queries.
  
• Brand trust signals: Measure mentions and backlinks from credible publications; they reinforce authority in both human and AI evaluations.

In our evolving AI era, success isn’t just about clicks; it’s about being recognised as the source worth quoting.

Practical Checklist: Turning SEO and AI Uncertainty into Action

The gap between knowing what’s changing and actually doing something about it is where most organisations stall. To help, we’ve created this checklist to turn the shifting landscape of SEO and AI search into concrete, manageable steps, the kind your team can act on without overhauling everything at once. Each action strengthens visibility, accuracy, and trust, one update at a time:

• Identify 10 top-performing pages to convert into answer-first format
  
• Update schema (FAQ, Article, Organisation) and resolve any technical issues
  
• Add visible author credentials and update stamps
  
• Refresh data quarterly with relevant stats and link to current sources
  
• Track both search visibility and AI citations
  
• Document updates and keep a public change log
  

SEO Hasn’t Been Replaced

SEO hasn’t been replaced; it has evolved. In the age of generative search, clarity, transparency, and recency are what help healthcare, senior care, and patient safety organisations get found and chosen by both humans and AI.

What’s next for your organization? Keep your SEO fundamentals sharp. Lead with clear answers. Refresh often. Cite everything.

Do this well and your organisation won’t just stay visible; it’ll stay trusted.

Author: Mhairi Petrovic
Founder, Out-Smarts Marketing

Mhairi Petrovic is the founder of Out-Smarts Marketing, a digital marketing agency that helps care, senior care, and purpose-led organisations strengthen their online visibility with ethical, transparent strategies. With over 20 years of experience in SEO, online advertising, and digital strategy, she helps teams navigate the shift toward AI-informed marketing, ensuring their work remains discoverable, credible, and trusted in the age of generative search. Connect with her on LinkedIn.

Learn more about Out-Smarts Marketing

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In truth, email marketing has many benefits over social media marketing if you do it the right way. While social media is effective at blasting your messaging and content to everyone, email marketing allows you to target your audience and messaging to better cater to your subscribers’ needs, potentially increasing your ROI. 

Keep reading to learn how to create an email marketing strategy that “delivers” (sorry for the pun). We’ll discuss common email marketing mistakes (and fixes) and actionable strategies you can start implementing today. 

Why email is a preferred marketing channel for organizations in 2025 

Email marketing is a great channel to create personalised content for your audience. You can send targeted messaging to customers based on many characteristics or demographics, such as:

• City or region
• Buying or engagement history
• Opt-in preferences
• Marketing funnel stage
• Activity on your website
• Industry and role

To segment your email subscriber audience, your email marketing program will have a feature called “tags,” “lists,” or something similar. You can customise these tags depending on the segmentation that matters most to you. 

Bonus tip: Email marketing is about quality over quantity. Starting an email marketing campaign doesn’t mean creating endless emails. In fact, when you use automation tools, you can automatically send emails to subscribers when they perform specific actions (like making a purchase or signing up for your list). 

Read more about using email marketing as a small business. 

5 ways you’re doing email marketing wrong (and how to fix them) 

Some organisations tell us that email marketing hasn’t been effective for them in the past. In many cases, email marketing isn’t working because their strategy wasn’t optimised for their target customers. 

Here are the five reasons email marketing strategies fail organizations and how you can fix each one:

1. Everyone gets the same content

If everyone wanted to read generic, impersonal content, they’d go to your social media feeds. Email is meant to cater to the specific needs of individual users (or at least by their preferences or demographics as closely as possible). Sending emails to segmented lists can drive as much as 30% more opens and 50% more clickthroughs. 

To fix: Add tags or create groups in your email list to cater to unique demographics such as recent purchasers, new customers, VIP customers, and where they live. Then, send unique content and messaging that relates to that segment (for example, sending “here’s a 10% discount code to come back” or emailing those who haven’t made a recent purchase to entice them back)./

2. Your subject lines are spammy or not engaging enough

Your audience may confuse your email with spam. Make sure your email subject lines don’t contain spammy language and are written in your brand voice. Use the recommended 30-50 characters (or first 4-7 words) to create intrigue so people want to open your email and engage with its contents. 

To fix: Test your email subject lines for effectiveness using this email subject line tester tool from CoSchedule.

3. Your emails are hard to read or navigate on mobile

How often do you read emails on your mobile device? 41% of your email views are viewed on mobile devices, and 20% are on tablets. If your subscribers can’t read your emails, or the design is distracting or not optimized for small screens, they can’t read or click on links in your emails. 

To fix: Keep your email designs simple to avoid display problems and to make optimising for mobile layouts simpler. 

4. You’re sending too many (or too few) emails. 

Did you know that receiving too many emails is a top reason people unsubscribe from email lists? For many organizations, sending daily emails may be too much. For example, if you’re a promotional products company and know your customers only purchase once or twice a year, you can stay top of mind (and not annoy them) with monthly emails rather than daily or weekly ones. 

To fix: Try sending emails less frequently or replacing frequent, general emails with fewer but more targeted emails to segmented lists. Always make sure your content is relevant and worth opening. 

5. You’re not tracking your success and improving results 

You can’t effectively understand the success of your email marketing without looking at your KPIs. To know if your content is effective, your sending frequency is just right, and your campaigns are converting or meeting your goals, you need to track and look at your email analytics. 

Standard metrics to track include clickthrough rate, open rate, leads or conversions, traffic from email campaigns, and click rate.

To fix: Easy! Start tracking KPIs relevant to your goals and use that information to change future emails and campaigns to improve your results next time.

How email can outperform social media

In digital marketing, social media can seem like the easiest way to focus your marketing efforts. However, you’re not fully controlling who (and how many) people see your content. That critical factor is left to the algorithms, and while you can play its game to increase your chances of visibility, it’s not a guarantee. 

With email marketing, everyone opts in to receive messages from you. When you send an email, it will land in everyone’s inbox. No more hoping the algorithm places your content on your follower’s screens.

How are you collecting emails and opt-ins?

Of course, an email marketing strategy won’t be helpful if you don’t have subscribers. In many regions, Canada included, it’s a legal requirement that subscribers opt-in to receive communications from you. You can’t purchase email lists or add customers without their permission. 

How can you grow your email list and get new subscribers?

• Add a “subscribe” link on your website, email footer, and business cards
• Offer a free gift (freebie) in exchange for their email and consent. 
• Collect email addresses and consent during online checkout (or in-store point-of-purchase)
• Collect email addresses on a sign-up sheet at trade show booths or speaking events (where you’re a speaker). 

No matter how you receive email addresses for your list, be transparent and ensure they understand that they’re opting in to receive email communications from your brand. 

Email isn’t dead—if you do it right

Email marketing can be an effective digital strategy to complement your other online activities. You can repurpose (share again) content you’ve posted to your social media, your blog, and other channels for your email list to nurture leads and customers. 

A social media post can be easily missed (especially with social media’s changing algorithm that controls what posts you see). Email marketing goes directly to your prospective and current customers who have subscribed to your list. 

We challenge you to look at your email marketing strategy this month. Make sure you’re not making any of the mistakes we mentioned above, and that your email marketing strategy fits within your marketing funnel and content strategy. 

Sometimes, you may need an outsider’s perspective because you’re too deeply entrenched in your current email marketing activities to see what’s not working. That’s why meeting with a digital marketing agency like Out-Smarts Marketing can provide valuable insights. 

Our team of senior digital markers can help you look at your email marketing strategy and how it fits into your marketing plan and meets (or doesn’t meet) your organization’s goals. We can help you reach the right people with the right message – at the right time through email. 

From setting up your account and building your list to crafting engaging content and tracking results, we handle the details so you can focus on what matters. We can also create lead funnels that use your email marketing strategy to its fullest potential. How can we help you harness the power of email marketing and make it relevant and effective for your organisation? Start by booking a discovery call with our team today

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