Explaining Google’s AI Search Experiments To Your C-Suite via @sejournal, @TaylorDanRW

Google is testing a series of experimental AI-powered features that could change how people interact with search and digital discovery.

Tools like Doppl, Food Mood, Talking Tours, and Learn About are not yet mainstream, but they give us a glimpse into where Google may be heading. Each experiment highlights a distinct way AI can influence consumer experiences, ranging from shopping and travel to food and education.

For business leaders, the importance lies in how these features could influence visibility, customer engagement, and competitive positioning if they are developed further.

Having these on your radar now can avoid sharp surprises and knee-jerk tactical pivots later down the line.

Doppl

Doppl is a new experimental app from Google Labs that lets users try on different looks and explore their personal style. It blends fashion discovery with AI-driven recommendations, acting like a personal stylist in app (on both Android and App Store).

This was initially talked about on the Google blog in 2024 and referred to as Virtual Try-On (VTO).

Screenshot from labs.google/doppl, September 2025

Given the adoption statistics Google has claimed around Google Lens and Circle to Search, Doppl could further change how consumers might approach online fashion and homeware buying.

Instead of browsing catalogs or searching by product type, users can explore outfits in a more playful, visual, and interactive way. This creates opportunities for fashion brands that invest in rich product imagery and metadata, while also introducing risks for those that fail to prepare.

It also highlights that outfit imagery doesn’t need to be professional; users can use Doppl to visualize outfits from their friends’ photos, branded Instagram posts, or what you include in your blogs and style guides.

For ecommerce websites, Doppl could reduce the importance of traditional product listings and increase the value of enriched product data. Style-driven discovery may also accelerate purchase decisions, compressing the sales cycle from browsing to checkout.

For example, a fashion retailer that provides detailed imagery, size data, and styling suggestions may see its outfits recommended more often when users test new looks in Doppl. A competitor with limited product data and imagery could be excluded from the experience entirely.

The takeaway for leaders here is that Doppl illustrates how AI may reshape online shopping into an interactive discovery experience. Fashion and lifestyle retailers should prioritize high-quality product data and imagery to remain competitive.

Food Mood

Food Mood is a recipe generator that combines ingredients and cooking styles to provide creative inspiration for meals.

Instead of entering exact recipes, users can describe their mood or inspiration and receive unique fusion-style ideas.

If rolled out and expanded, this could shift recipe discovery from rigid keyword searches to open-ended, experience-based prompts.

Screenshot from artsandculture.google.com/experiment/food-mood/,September 2025

Food Mood is less about finding the perfect “chicken pasta” recipe and more about encouraging users to experiment. For food publishers and recipe sites, the challenge will be ensuring their content is structured and tagged so it can be effectively integrated into these creative outputs.

Recipe publishers that rely on SEO traffic could see reduced visibility if users embrace AI-generated inspiration instead of searching for specific dish names. On the other hand, sites that invest in structured recipe data, nutritional information, and culinary storytelling may benefit by having their recipes pulled into Food Mood’s suggestions.

This being said, Food Mood is still experimental, and as the result below shows from my testing, it still needs some refinement around ingredient quantities and measurements.

The generative response to make a meal for one, combining the cuisines of Curaçao and Norway… The ingredients list might be off… (Screenshot from Food Mood, September 2025)

A food blog known for creative plant-based recipes might be highlighted when a user asks Food Mood for “a fun weekend dinner that feels indulgent but healthy.” If the content is tagged and structured correctly, it could be surfaced in ways traditional keyword targeting never allowed.

Food Mood shows how search may evolve toward inspiration-driven discovery. Recipe sites and food brands should prepare by enriching their content with detailed metadata that connects recipes to moods, occasions, and dietary preferences.

Talking Tours

Talking Tours is an active audio experiment from Google Arts & Culture that allows users to tour cultural landmarks in Street View.

Instead of passively looking at images, users can listen to narrated, AI-generated stories about what they are exploring.

This has the potential to change how people engage with cultural and travel content. Rather than relying solely on guidebooks or blog posts, users may interact with AI-driven narratives directly inside Google’s ecosystem. It offers an immersive layer that could shift attention away from traditional content publishers.

Screenshot from artsandculture.google.com/experiment/talking-tours/, September 2025

For travel businesses, the opportunity lies in being part of the authoritative content that fuels these AI tours. Travel agencies, tour operators, and cultural organizations that create structured, authentic content may find new visibility if their information is integrated. Without that presence, competitors or third-party providers could dominate the AI-driven storytelling.

A cultural travel company that produces detailed content about European landmarks might benefit from incorporating Talking Tours’ insights during a virtual tour of Rome. Without participation, their competitors may own the conversation.

This also offers would-be travellers the opportunity to explore landmarks and other key locations ahead of travelling, which could influence the comparison and deliberation phases of the decision-making process.

Talking Tours points to a future where immersive, AI-driven experiences shape travel planning. Travel brands should ensure their content is authoritative, structured, and ready to be used in AI-generated narratives.

Learn About

Learn About is an experiment that helps users learn new topics at their own pace using conversational AI. Acting like a digital tutor, it breaks down complex ideas into simple explanations and guides learners to further resources.

Screenshot from learning.google.com/experiments/learn-about/, September 2025

For education providers, this alters how learners find and engage with content. Instead of searching for “best beginner coding course,” a student might ask Learn About to “explain how websites work” and then follow guided prompts.

Learn About uses various YouTube and web results as sources, and from experimentation, it isn’t afraid to show older content and videos (even those with “for 2023” in the video title) if it believes the content and source are strong enough.

Educational publishers and online learning platforms may experience shifts in traffic if “Learn About” becomes a common entry point. Being cited in AI-driven tutoring sessions could become as valuable as traditional SEO discovery. Institutions that provide well-structured, authoritative, and trustworthy content stand to gain.

A site offering structured beginner-friendly coding lessons might be featured in Learn About when a user begins exploring “how to build a website.” If absent, a competitor may be the one shaping the learner’s first impression of the topic.

Learn About underscores the need for clear, structured, and authoritative educational content. Providers should optimize not only for keywords but also for AI-driven educational journeys.

Preparing For AI Experiments In Search

Google’s experimental features like Doppl, Food Mood, Talking Tours, and Learn About reveal how search may evolve from keyword-driven results to AI-guided discovery experiences beyond what we perceive as traditional search.

These experiments may not all become mainstream, but they indicate where search is heading. Businesses that begin preparing now will be better positioned if and when these ideas are rolled out more widely.

Is your organization ready to compete in a world where AI guides the first step of customer discovery?

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Featured Image: insta_photos/Shutterstock

Multimodal Search Is Reshaping The Funnel For SEOs And Marketers via @sejournal, @TaylorDanRW

For years, marketers built their strategies around a clear and visible funnel: awareness, consideration, conversion.

It worked well in a web where behaviors were traceable, people clicked links, visited pages, signed up, bought a product, or bounced.

We were able to track almost all of it, and we had attribution models that helped show return on investment (ROI) to specific channels (with varying degrees of accuracy and certainty).

The journey hasn’t disappeared, but it’s harder to detect, and it has become a lot more convoluted.

People are still moving through a decision-making process; they’re just doing it across fragmented platforms, using tools that don’t always leave clear signals behind.

Whether it’s asking ChatGPT, browsing Reddit, scrolling through TikTok, or speaking to a voice assistant, user behavior is fluid, multimodal, and largely invisible to traditional analytics.

We can no longer assume that a user’s next step will be a trackable one.

They might ask an AI model for a summary. They might compare products across 10 different surfaces before ever visiting your site.

They might never fill out a form, but forward the website to a colleague, and they’ll fill out the form as a single session, tracked as “Direct,” having never been on your site before.

That doesn’t mean the funnel is gone; it’s just become almost untrackable.

What The Funnel Actually Is

The traditional marketing funnel breaks down the customer journey into three core stages:

• Top of Funnel (TOFU): Awareness-level content that introduces your brand or product to a broad audience. Think blog posts, social media content, or explainer videos.
• Middle of Funnel (MOFU): Consideration-level content that helps users evaluate options. This includes comparison guides, product demos, and email nurturing sequences.
• Bottom of Funnel (BOFU): Conversion-level content aimed at driving action, like purchase pages, pricing breakdowns, or testimonials.

Marketers used to map content to each of these stages, creating clear pathways for users to follow from curiosity to conversion.

That model still applies, but how users move between these stages is now anything but linear.

What Multimodal Search Really Means

Multimodal search isn’t just about the difference between typing a query, speaking it out loud, or snapping a photo.

It’s about the way users fluidly engage across different platforms and media types to explore, evaluate, and decide.

A single purchase journey might involve:

• Googling a general topic.
• Watching explainer videos on TikTok or YouTube.
• Reading niche discussions on Reddit.
• Browsing listings on Amazon.
• Comparing reviews on third-party blogs.
• Asking follow-up questions to an AI assistant.

Even Amazon itself is leaning into AI-led search with Rufus, its generative shopping assistant. This is multimodal search.

Image from author, August 2025

Google is layering AI Overviews and AI Mode into its core search experience, offering summarized insights and altering the sequence of discovery.

Users no longer click 10 blue links. They skim summaries, compare sources at a glance, and dive deeper only if curiosity is triggered and a user acts on it.

Multi-modal means multi-platform, multi-surface, and multi-behavior.

It requires us to plan for nonlinear journeys, where influence happens in places we don’t control, and impact happens without attribution.

This shift demands a change in how we create and distribute content:

• We must think beyond a single persona or journey and instead design for overlapping intent signals.
• We must publish in formats that match user behavior across channels: text, video, audio, structured data, and conversational prompts.
• We must recognize that old attribution models, based on last click or visible touchpoints, no longer reflect reality.

If we design content around one channel, one format, or one assumed path, we’re missing the majority of how people actually search, explore, and decide.

The challenge now is to understand user intent without seeing every step. To stay present in invisible paths. To meet people in the middle of journeys we can’t fully track.

The funnel still matters. But, reaching people inside it requires a different mindset, one that’s built for anticipation, not just observation and end goal metrics.

Multimodal As The Gateway For The Next Generation

For the next generation of internet users, multimodal isn’t just a feature; it’s the foundation.

Gen Z is growing up with tools that let them search the world visually, conversationally, and socially.

They don’t see these modes as alternatives to traditional search; they see them as default behaviors.

Google’s data reflects this shift. Gen Z (18-24 year olds) is currently the fastest-growing demographic using Google Search.

And among that cohort, 1 in 10 searches now begin with a visual interaction, and using tools like Google Lens or Circle to Search.

Image from author, August 2025

Instead of typing a query, users highlight parts of an image, scan real-world objects, or interact directly with on-screen content.

This visual-first, intent-rich behavior is a window into how the next generation navigates information. It blends curiosity with immediacy – and it bypasses traditional keyword-driven journeys entirely.

Marketers need to understand this shift not as a niche use case, but as a sign of things to come.

If we’re not building content and experiences that match these native behaviors, we risk being invisible in the very spaces where influence now begins.

What This Means For SEOs And Marketers

Speak To The Whole Persona

Personas and audience segmentation still matter, maybe more than ever, but we can’t speak to people at just one stage or in one format.

Mental availability now has to be a core part of any digital marketing strategy.

It’s not about being everywhere for everyone, but about being present across enough moments and modes that your brand is part of the conversation when decisions are being made.

The old way of choosing a format, identifying a single funnel stage, and publishing content to fit is no longer enough.

We need to create for complexity. That means producing content that reaches both the 1% and the 99% of your target persona, ranging from niche, problem-aware research queries to broad, ambient brand mentions in trending content.

Think Beyond The Visible Funnel

Every digital touchpoint is a chance to build familiarity and relevance.

And in a landscape where visibility is often obscured, casting a wider, more thoughtful net across intent types, platforms, and formats is how you maximize your odds of being chosen, even if you never see the full journey play out.

Rethink Distribution And Domain Dependence

Content distribution now plays a critical role in both SEO and broader brand strategy.

We want our messaging to be present wherever users are searching, reading, watching, or asking questions. That means treating our website as one, but not the only, SEO and AI optimization asset.

In my opinion, content and SEO strategies that focus only on the owned domain are limiting their effectiveness.

Search engines and AI models are increasingly drawing context, citations, and understanding from a wide range of sources across the open web.

If your brand only shows up on your own site, you reduce your discoverability, authority, and influence.

To compete in the AI-shaped web, marketers need to distribute content intentionally across partner sites, third-party platforms, social channels, structured formats, and multimedia content ecosystems.

Visibility is earned across surfaces, not confined to a single domain.

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Featured Image: DETHAL/Shutterstock

Should I Still Invest In SEO? (Yes, But Not In The Old Way) via @sejournal, @TaylorDanRW

How users are starting to interact with the internet has changed and soon will be unrecognizable from the internet we’ve grown comfortable with.

With Google integrating AI-powered features into Search, and the rise of third-party large language models (LLMs), it’s a different search experience.

Over the past few months, many CMOs I’ve spoken with, as well as business founders, have been asking the same questions around continuing investment in different marketing channels, including continuing investment in SEO.

I was fortunate to attend and speak at Google’s Search Central Live in Bangkok last week, and during the opening keynote, there was one snippet that has stood out for me that goes a long way to answering this question:

Traffic patterns may fluctuate: Long-held traffic patterns are likely to fluctuate, creating new opportunities for all sites. Past success on Search may not guarantee future success.

Should I Still Invest In SEO?

SEO is one of the few marketing channels that compound over time and investment.

Paid campaigns stop the moment you pause spending, but a strong organic program can keep driving traffic, leads, and sales long after it’s been implemented.

Often, it performs better over time, depending on how your competitors react.

That compounding effect is what separates SEO from most other digital investments. Every decent piece of content, every technical fix, every solid backlink adds to a base that grows stronger the more you invest.

SEO isn’t dead. It’s evolving.

That means fast, mobile-first websites, content demonstrating expertise and experience, clean internal links, and a solid structure; content that plays well with AI summaries and result variations, and more than anything, seeing SEO as part of your brand presence, not just a traffic lever.

Why Some Brands Are Pulling Back

There’s a rising anxiety in the air, caused by a number of unknowns and changes in our data, such as the great decoupling we’re witnessing.

Some CMOs are questioning whether SEO and content are still worth the effort.

There are a few reasons for this, namely that the SERP has changed dramatically. AI Overviews and expanded result features push the traditional organic links further down the page.

Some brands see less return from the same level of effort, and the result is frustration and, in some cases, panic.

At the same time, reporting is harder and attribution is messier.

It’s not always easy to show exactly where SEO contributes, especially when its influence spans across discovery, consideration, and conversion, which can make it a target when budgets begin to tighten.

Some teams are also misreading the signals, but in reality (in my opinion), we’re using the wrong measurement techniques, and measuring the new Search ecosystem by the standards of the old.

They assume that if fewer people click, fewer people are engaging, but visibility itself is valuable. Just because someone doesn’t click today doesn’t mean they won’t take action tomorrow.

In my opinion, pulling back now is the wrong move. Organic search remains the biggest visibility lever on the web, and when you stop investing in content, you’re choosing to disappear.

In an AI-first search world, visibility starts before the click.

The brands that stay active will be the ones users see and remember. This is no longer just about blue links and last click, it’s about brand recognition and building visibility across the multiple faces of the modern Search ecosystem.

Content’s Evolving Role In SEO

Top-of-funnel traffic might not be what it once was, but it’s still powerful.

Being visible in an AI Overview or response to a generic query still influences perception. It can lead to brand searches, direct visits, or conversions later down the line.

I don’t think the metric is how many people see your result. It’s how many go on to take meaningful action. SEO now runs across the funnel, and across formats. It’s not just 10 links on a page anymore.

Content has to work harder. A single piece might need to satisfy different intents, answer multiple questions, or show up in several places, from featured snippets, videos, product results, or AI-generated outputs.

SEO And AI

AI-powered search is splitting discovery across more surfaces. It’s not just Google anymore. It’s ChatGPT, Perplexity, Gemini, and others.

To stay visible in that world, you still need content. In fact, content is the price of admission. If you’re not producing it, you’re not part of the conversation.

SEO now includes shaping how AI systems understand your brand. If you’re not contributing to the information ecosystem, someone else is deciding your narrative.

Strategic SEO Investment

Smart SEO means:

• Durable content that keeps working.
• Authority-building through links, mentions, and structure.
• A balance between fast wins and long-term gains.
• Understanding and answering layered queries that do more than just inform – they convert.

For bigger businesses with multiple brands or sites, there’s an extra edge. Google and AI models understand entity relationships.

Coordinated content can strengthen authority across brands, especially in a world where AI pulls from consensus.

So, Should You Still Invest In SEO?

If you’re asking whether SEO still works, the answer is yes, but not in the old way.

It’s not just a traffic source; it’s becoming your visibility layer for both traditional Search, Google’s AI features, and many LLMs.

It’s fast becoming a lever for reputation and brand visibility, and a strategic asset as well as a marketing channel.

The real question is whether you can afford not to invest.

Paid traffic dries up the second you stop paying. Organic builds on itself. It’s one of the few channels that gives you more tomorrow for what you do today.

As AI changes how search looks and works, SEO stays relevant because it supports every layer of digital presence. It creates a base you own, not rent.

The brands that win next are the ones that stay active. The ones that keep showing up, even when the rules shift.

Content isn’t just about clicks. It’s about influence. It’s about being there when people are asking the big questions, wherever they’re asking them.

In a shifting landscape, SEO gives you something stable. A long-term play that doesn’t vanish when your budget runs out. For businesses planning beyond the quarter, it’s still one of the smartest bets you can make.

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Featured Image: G-Stock Studio/Shutterstock

Is It Time To Remove Focus From Average Position In GSC? via @sejournal, @TaylorDanRW

Average position has been a cornerstone metric in SEO reporting for years. It provides a simple, at-a-glance sense of where a site typically ranks in Google’s search results.

That sense is growing increasingly misleading as Google layers generative AI features, such as AI Overviews and AI Mode, on top of traditional blue link results.

Search Console then counts all these placements under the same metric. This merging of disparate result types means average position can be decreased by low-impact features or artificially boosted by high-visibility but low-traffic placements.

It is time to retire the average position as one of your primary organic key performance indicators (KPIs) and adopt a more nuanced set of metrics that focus on authentic engagement and conversions.

The Changing Landscape Of Search Features

Over the past decade, Google has transformed from a simple list of 10 blue links into a dynamic search results page packed with interactive elements.

Readers now see AI Overviews at the top of the page that generate concise summaries drawn from multiple sources. They also encounter AI Mode, which combines machine-generated insights with standard links.

Further down, they may find knowledge panels that present quick facts and structured data, People Also Ask widgets that prompt deeper exploration, video snippets that surface relevant clips, local packs showing nearby businesses, and image or news carousels that encourage visual browsing.

Each new format alters user behavior and fragments the attention once reserved for blue link results. The result is a declining share of clicks on traditional listings, which makes a simple ranking metric far less meaningful.

How AI Overviews And AI Mode Inflate Your Average Position

Google Search Console now assigns AI Overviews the same rank position value as the very top link in the organic listings.

If your page features in that AI Overview box at position one and simultaneously ranks at position four in the blue links, your average position will be calculated to around 2.5.

That figure suggests a page one presence, even though most traffic still comes from the standard link at position four.

In older versions of Search Console, rare placements, such as a query slot at position 12 in a People Also Ask box, would drag your average rank down.

Now, those obscure placements are balanced or outweighed by top-heavy AI features.

The overall metric becomes distorted. An average position of two may feel like a genuine page one victory, but it offers little insight into where user clicks land.

Why This Matters For Your SEO Strategy

An inflated average position can mislead stakeholders into believing content is performing better than it is. A marketing dashboard reporting an average rank of 2.3 will create confidence in page one visibility.

Resources may shift away from high-value keywords that sit at positions five to 10 but deliver strong conversion rates.

Teams might pour effort into optimizing for AI Overviews or AI Mode triggers that look impressive in reports yet generate few real visits.

Over time, this misplaced focus undermines return on investment. Budgets skew toward vanity improvements rather than actions that drive tangible engagement, leads, and sales.

If click-through rate and traffic volumes stay flat or decline despite a rising average position, you risk missing warning signs until revenues slip.

Metrics To Focus On Instead

To gain an accurate picture of SEO performance, we must unbundle average position.

Classify your rankings by feature type. Separate blue link placements from AI Overviews, People Also Ask entries, video snippets, local packs, and other rich features.

Generate click-through rates for each segment so you can see where users engage. Measure absolute organic traffic for top queries and compare that with historical baselines.

Analyze time on page to understand content resonance. Most importantly, connect behavior data to conversions or goal completions. This end-to-end view shows whether search visibility translates into business value.

Another way to reduce distortion is to use percentile-based position metrics. The median position or P50 gives the midpoint ranking across all queries. It is not swayed by a few very high or very low positions.

The 90th percentile or P90 shows the position below which 90% of your rankings fall.

Charting P50 and P90 over time highlights trend directions with less noise from outliers.

You can also calculate a trimmed mean by excluding the top and bottom 5% of positions. Any of these approaches will provide a steadier reading of where your pages stand in the SERP landscape.

Putting It Into Practice

First, export your Google Search Console data for the period or keywords you wish to analyze.

Add a feature tag to each query to mark whether it appeared as a blue link, AI Overview, People Also Ask entry, or other rich element/special content result block (SCRB).

Many SEO tools now include feature filters to automate this step.

Once tagging is complete, calculate the click-through rate for each feature type by dividing clicks by impressions for that feature. Compare click-through rates to identify which formats drive engagement and which only inflate visibility.

Total the organic clicks and analyze sessions to determine content that earns sustained visits.

You want to update your dashboards to reflect these new metrics. Replace an overall average position chart with a histogram showing the distribution of rankings by feature.

Include a bar chart of click-through rates for each result type. Display time series graphs of organic sessions and goal completions to link visibility improvements back to conversions. Keep these graphs simple and focused on actionable insights.

For optimization, focus on tactics that boost click-through rate and conversion paths.

For blue link results, refine title tags and meta descriptions to create a stronger call to action.

Use structured data markup so that when your page appears in People Also Ask or as a video snippet, the preview offers more context. Review the content that underpins AI Overviews.

Make sure your page answers core user questions in clear headings and concise paragraphs so the generative model can source accurate summaries.

Where gaps exist between AI Overview content and user needs, create or expand sections to fill them.

Continuously iterate by filtering your data for high-value keywords and checking whether the AI features you trigger align with intent and deliver clicks.

In larger organizations, you may need to educate stakeholders on the limitations of the average position.

Share before and after views of dashboards to show how the metric shifted once AI features entered the mix.

Walk through specific examples, such as a page that jumped from position five to an AI Overview at position one, yet saw no change in traffic.

Demonstrations like these will build consensus around moving to feature-based and engagement metrics that drive tangible business outcomes.

Summary

Generative AI features in Google Search represent a fundamental shift in how search results appear.

Average position once served as a valuable proxy for visibility, and one of the only first-party data sources to give us this proxy. It now obscures more than it reveals.

By breaking performance down by feature type, measuring click-through rates and conversions, and adopting percentile-based ranking metrics, you can cut through the noise.

This richer approach reveals what matters to your users and your bottom line. In the new era of search, a deeper, more actionable analysis will be your key to sustained SEO success.

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Featured Image: Roman Samborskyi/Shutterstock

Explaining The Great Decoupling To C-Level via @sejournal, @TaylorDanRW

Something important is happening in Google Search.

If you’ve looked at your website data in Google Search Console, you may have noticed something odd. Your pages are showing up more often, but fewer people are clicking through.

These two signals – impressions and clicks – are used to rise and fall together. Now, they’re drifting apart.

We call this “The Great Decoupling.”

Screenshot from Jim Thornton (with permission to use), The SEO Community Slack Group, June 2025

And it’s not just your business. This is happening across industries and most website types.

It became more noticeable as Google rolled out something called AI Overviews – automated summaries that answer questions directly in search results.

If your site traffic from search is falling, but your rankings look fine, this article will help explain why.

We’ll examine the changes, their causes, how they manifest in analytics tools, and the responses of leading companies.

What’s Happening And Why It Matters

The Great Decoupling describes a new disconnect. Your website can appear more often in search results but get fewer clicks.

That was only “the expected behavior” when the SERP had things like featured snippets, or other special content result blocks from Google.

We’ve seen this clearly in client data during the first half of 2025.

Screenshot from Itamar Bauer (with permission to use), Studio Hawk, June 2025

Near the end of 2024, impressions and clicks were still closely linked. But by early 2025, impressions kept going up while clicks went down.

The click-through rate, the percentage of people who click, dropped sharply.

This trend is widespread. Whether your site is an ecommerce store, a B2B company, or a blog, the same thing is happening – more visibility but less engagement.

Martin Splitt has said that when your pages are shown in AI Overviews, you may get more impressions but fewer clicks.

He also said that people might still convert later, perhaps after seeing your brand in search results, even if they never click the first time.

So, we’re in a new “normal”; impressions alone no longer signal opportunity. It’s what happens after the impression that counts.

Why This Is Happening

Google’s move toward AI-powered results is driving this change. The most significant shift is the introduction of AI Overviews.

AI Overviews are summaries shown at the top of search results.

Instead of a list of websites, Google provides an instant answer. That answer is generated from various sources across the web, including yours, without requiring the user to click.

Your Content May Appear Twice, But It Only Gets One Chance To Earn A Click

Your site may show up as both a traditional link and as part of the AI Overview. That boosts impressions but often reduces clicks. People get what they need from the overview.

Less Friction Means Fewer Visits

The AI Overview gives users what they want quickly. However, if their need is met before they reach your site, your traffic will drop.

Some Search Terms Are Hit Harder Than Others

Generic questions, how-tos, and mid-funnel queries are more likely to trigger AI Overviews. These are often top-of-funnel keywords marketers use to drive discovery.

On the other hand, brand searches and high-intent queries are more resilient.

The point is that it’s not just about where you rank. It’s about whether Google decides to answer the question for the user without needing you.

Zero-Click Search Isn’t New

This isn’t entirely new. For years, Google has provided users with quick answers. Featured snippets, “People Also Ask” boxes, and knowledge panels all reduced the need to click.

AI Overviews are just the next step. They are more advanced, appear more often, and answer a broader range of questions. But, the principle is the same: to reduce the effort for the user.

We’ve adapted before. We can adapt again. However, this shift is more significant and impacts multiple stages of the customer journey, necessitating a more strategic approach.

What This Looks Like In Your Analytics

In Google Search Console, the gap between impressions and clicks is clear. In Google Analytics 4, you see the impact on your traffic and behavior metrics.

Organic Traffic Is Falling

Your GA4 report shows fewer sessions from Google, even though your rankings haven’t changed. That’s the result of fewer clicks.

Engagement May Look Better

Because fewer but more qualified visitors are reaching your site, session length and conversion rates may look stronger. But, overall, reach is down.

Attribution Becomes Less Clear

GA4 does not show traffic that came through AI Overviews separately.

Some visitors might return later and be counted as “direct” traffic. Others won’t be tracked at all. This makes it more challenging to attribute SEO’s role in brand discovery.

To understand what’s happening, you need to look at GSC and GA4 together. One shows the visibility. The other shows the outcomes.

How I Think You Should Adjust & Act

The most forward-thinking businesses are making strategic shifts to protect and grow their visibility. Here are four things they’re doing:

1. Strengthen Brand

When users search for you by name, Google is less likely to intervene. These clicks are holding steady and, in some cases, growing.

Investing in brand and trust is generic advice being thrown around a lot at the moment, but I think you should be looking at your brand in consideration of a user journey and what scope AI platforms have to alter that user journey before your brand is discovered.

Image from author, June 2025

This also means working to understand how well-known your brand is before a user starts at the “top of the funnel,” and whether or not they’re more likely to steer towards your brand due to previous positive brand touchpoints, or the sentiment and user stories of others online.

2. Publish Content That AI Can’t Copy

If your content is generic, Google’s AI can summarize it. If it’s unique, based on experience, data, or opinion, it’s much harder to replace.

Focus on:

• Original research.
• Customer stories.
• Side-by-side product comparisons.
• Tools and calculators.
• Real customer feedback.

3. Build Around Topics, Not Keywords

Create clusters of related content around a theme. This signals authority to search engines and gives users more reasons to explore your site.

4. Turn Product Pages Into Useful Resources

Don’t just list specs. Add real information that helps the buyer:

• FAQs.
• Reviews.
• Comparison tables.
• Guides and videos.

You want to help the buyer better forecast their experience with the product or service, as well as their understanding of your brand.

Be upfront about as much information as possible, as a negative brand or product experience can be damaging in the long run.

Why SEO Still Matters

Yes, SEO remains highly relevant despite the rise of AI.

While AI tools are changing how search works and how users find answers, they haven’t replaced the need for a smart, well-executed SEO strategy.

SEO is evolving and becoming more important in new ways.

AI Needs High-Quality Content To Learn From

AI Overviews don’t invent answers. They draw from trusted online sources. That means Google still relies on high-quality, well-optimized content to build its responses.

SEO helps ensure your content meets the standards of E-E-A-T: experience, expertise, authoritativeness, and trustworthiness.

Search Engines Still Rank Pages

Even with AI features in search results, users still scroll through traditional listings and click on websites.

SEO ensures your content performs well in these results, whether it’s in the top 10 links, a featured snippet, or a “People Also Ask” box.

AI Enhances, Not Replaces, SEO

AI tools can automate certain aspects of SEO, such as keyword research and content suggestions. But, they don’t replace strategic thinking.

SEO experts continue to guide site architecture, content structure, technical fixes, and intent-based optimization – tasks that AI can’t fully handle alone.

SEO isn’t going away; it’s becoming more sophisticated.

The businesses that succeed will be the ones that blend innovative tools with strategic thinking and treat SEO as a long-term investment in visibility and value.

The new wave of SEO isn’t just about driving traffic. It’s about showing up where your customers are asking questions, building credibility, and creating a footprint that supports all your other channels.

• Visibility builds trust. Even if someone doesn’t click, seeing your name in search results reinforces brand awareness.
• SEO feeds other channels. The insights you gain from search, what people ask, how they ask it, and what ranking help shape your messaging everywhere else.
• Strong content earns attention. Helpful, original content can drive engagement on-site, across social media, and in sales conversations.
• It remains one of the most cost-effective ways to acquire leads, especially for branded and high-intent queries.

Search may not deliver the same volume of clicks, but it still shapes perception, influence, and decision-making.

SEO remains one of the most effective ways to stay visible and valuable in an increasingly AI-driven world.

Change What You Measure

The Great Decoupling is not just an SEO story. It’s a business visibility story. More people may see your brand, but fewer will visit your site.

That means you can’t just measure success by traffic. You need to consider engagement, recall, and brand strength.

Search is becoming a reputation game. If people trust you, they’ll find you, even if they don’t click the first time.

The companies that win won’t be the ones who chase rankings; they’ll be the ones who earn attention. Attention is potentially the “new click.”

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Aligning The CIO, CFO & CMO For Search‑Driven ROI via @sejournal, @TaylorDanRW

The traditional linear path from awareness to conversion is no longer the norm.

Users today interact with generative engines like ChatGPT, Gemini, and Perplexity, as well as voice interfaces and proprietary search platforms that bypass the familiar search engine results pages (SERPs) entirely.

In this landscape, classic SEO tactics alone are no longer enough.

AI compresses the consideration phase by combining information from multiple sources into a single trusted output. A user no longer needs to review 10 blue links and click through to various websites.

Instead, they ask a question and receive a concise, reasonably tailored response. This change forces brands to reassess their approach to competing for visibility.

Visibility within AI-generated results is driven less by paid placement and more by a mix of expert content, credible signals, and structured data.

Brands need to focus on the depth and clarity of their expert-led content, build strong reputational signals across third-party platforms, and ensure their use of schema and structured data supports inclusion in AI summaries.

They must also prioritize being referenced in the knowledge bases and datasets these AI systems rely on.

As discovery becomes more conversational and context-led, users no longer refine keywords. They follow intent-led journeys. Discovery is shifting from a focus on ranking to one of relevance.

To remain visible, organizations must realign their digital strategies to align with how generative models perceive trust and authority.

This requires joined-up efforts across technology, finance, and brand leadership, with specific responsibilities falling to the Chief Information Officer (CIO), Chief Financial Officer (CFO), and Chief Marketing Officer (CMO) – the C-level triumvirate.

The CIO

Structured machine-readable data is essential for visibility in AI-driven search.

The CIO plays a crucial role in ensuring that content is accessible and optimized across the systems on which AI models rely.

This includes enabling discoverability across platforms, offering APIs and knowledge graphs that large language models can use, and upholding data security and compliance when sharing information.

Modernizing content infrastructure is vital. Enterprise content must be indexable, high-performing, and properly structured to ensure optimal search results.

Beyond the web, CIOs must consider how enterprise knowledge is externalized and leveraged. Are internal repositories accessible in structured formats? Is brand data mapped to schemas recognized by AI systems? Can content be updated in real-time to maintain accuracy?

CIOs must also work closely with legal and compliance teams to ensure effective collaboration and compliance.

Together, they need to define governance rules for exposing data to AI models, set rate limits and permissions, and use synthetic or anonymized data when required.

True agility is not just about building flexible systems; it’s also about embracing change. It is about creating AI-native structures that support clean data flows, reduce technical debt, and prepare for how emerging technologies will consume information.

The CFO

Traditionally, marketing spending has been assessed through direct attribution. However, AI search enables complex, non-linear journeys and ambient brand exposure that may not result in clicks but still significantly influence buying decisions.

CFOs must update financial models to reflect these softer signals. Budgets should focus on readiness, high-quality content, strong data structures, and AI-aligned infrastructure rather than just media spending.

Attribution models must include interactions with AI systems, even when those are indirect.

Mentions or recommendations by AI engines build brand trust and influence intent, even without a direct click. These harder-to-measure moments still matter and should be included in attribution models and long-term planning.

CFOs should approve investment in ongoing content creation, structured knowledge bases, and systems that help AI access and trust their content.

Like building physical infrastructure, this work offers lasting benefits and positions the brand for visibility as AI search becomes the norm.

The challenge is to shift from short-term performance to long-term discoverability and influence.

The CMO

In an AI-driven search world, visibility is shaped by more than just brand storytelling. It depends on how the brand is reflected in the data that powers these systems.

AI models combine answers from multiple sources, meaning the brand narrative is heavily influenced by third-party data, structured content, and the quality of information shared across the web.

The CMO must ensure the brand becomes the trusted answer, not just another mention. This involves managing messaging across all content areas, including earned, owned, and partner-based content, while ensuring that citations, expert profiles, and trusted content are indexed and referenced.

Strategic visibility needs clear, joined-up messaging. AI rewards consistency and authority. Fragmented messaging weakens both.

That is why CMOs need to bring together PR, product marketing, and content teams to create a unified narrative that AI can recognize and rely on.

Accurate strategic positioning means the brand is present before the user arrives, built into the answers AI provides. This is about planning for visibility at the knowledge level, not just the content level.

In a world of automated systems and answer engines, this is where trust and competitive edge are built.

Reporting On AI-Driven Visibility: Metrics That Matter

To keep leadership aligned and justify investment, organizations need useful cross-functional metrics that reflect visibility in AI-led environments. These indicators matter across CIO, CFO, and CMO roles.

• Share of Voice: Measures brand presence across AI platforms compared to competitors. Useful for CMOs watching narrative authority.
• Organic Traffic Value: Assigns a value to organic traffic by estimating what the same reach would cost through paid ads. Important for CFOs tracking return.
• Presence in AI Summaries and Snapshots: Tracks how often the brand appears in AI answers or summaries. It helps gauge marketing and strategic visibility.
• LLM Prompt Coverage: Checks how discoverable content is across known large language model datasets and guides CIOs in content infrastructure planning.
• Non-Click Influence Metrics: Captures mentions, impressions, and indirect interactions in AI systems. Signals have a broader impact on user choices.
• Entity Graph Coverage: Tracks inclusion in structured databases like Google Knowledge Graph or Wikidata. Reflects data readiness and visibility.

By linking these metrics to executive goals, financial impact, technical performance, and brand strategy, organizations can ensure that their AI search efforts are effective and measurable.

Executive Alignment Is Non-Negotiable

AI search is not just another channel. It is a new space for enterprise visibility. Success depends on joined-up action across leadership. The CIO must build compliant, scalable systems.

The CFO must back smart investments in discoverability. The CMO must craft a brand story that AI can understand.

A real advantage emerges when these roles are united around a single strategy, combining technical flexibility, financial foresight, and a straightforward narrative.

When leadership is aligned, organizations do not just react to AI – they leverage it.

In a world where visibility comes from connected data, the winning brands will treat discoverability not as a marketing goal but as a core part of how they operate and lead.

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When SEO Can Be A Brand Health Signal via @sejournal, @TaylorDanRW

One thing that rarely gets enough attention in SEO is how user behavior, trends, and sentiment toward a brand shape performance.

It doesn’t just apply to traffic from new queries. It also affects how many people choose to click on your brand in search results.

When something shifts outside of SEO, like a wave of negative press, seasonal change, or a shift in consumer preferences, it can lead to more or fewer branded searches.

It can also bring new associations with your brand, such as a rise in negative reviews or more online mentions that carry a clear tone. These can be early signs that something is changing. Often, the change hasn’t shown up anywhere else yet.

This is why SEO can act like a canary in the coal mine. It can surface early warning signs before customer satisfaction scores drop or sales start to slide.

Organic search data can reveal early cracks in brand trust, preference, or product satisfaction.

Search Reflects Real-Time Thinking

Search is one of the few places where people show exactly what they are thinking. They do it without filters, without needing to contact anyone, and without revealing who they are.

This makes it very different from leaving a review or speaking to a customer service team.

Search gives users a way to explore concerns, check claims, or validate ideas in private. That makes SEO data more private and potentially more honest than surveys or social media.

When people begin to doubt your brand, consider alternatives, or worry about price or quality, those feelings often show up in search before they show up anywhere else.

If people are asking whether your brand is legitimate or if your deliveries arrive on time, these are not throwaway questions. They are signs that something might be going wrong. These moments often come before complaints appear in reviews or support tickets.

Search behavior is usually the first place to spot a shift in public opinion. SEO data updates all the time, which means you get a live read on how your brand is landing with users. You can spot changes even if your rankings or revenue haven’t moved yet.

This is even more important now that people use AI and LLM tools more often. These models can show outdated or negative content that still lingers online. This affects how your brand appears across a wider landscape than just Google Search.

Signals That Point To Brand Trouble

SEO has often been judged on traffic and rankings, but not all signals are about performance. Some are predictive. They show up in how users frame queries, stack questions, and explore comparisons.

These behaviors reflect how they move through the search journey to find what they need.

Here are a few signs that can point to growing brand problems:

Drop In Branded Search Volume

If fewer people are searching for your brand name over time, it might mean you’re losing relevance or being overtaken by competitors.

Sometimes, it’s just seasonal. Sometimes, it’s the result of a big push from a rival. Either way, it’s worth a closer look and worth talking about across teams.

Growth In Negative Sentiment Keywords

Search engines have long been aware of sentiment. You can see this in how Google highlights review terms like “refund,” “problem,” or “delivery issue.”

If more users are typing these words alongside your brand, it can suggest rising frustration. Often, this happens before customer service sees a spike or before review scores drop.

Users asking whether your brand is trustworthy or if it’s a scam are not always doing so out of curiosity. Sometimes, they are actively trying to avoid making a mistake.

These moments are decision points, and they can cause people to switch to a competitor who has fewer trust issues in search.

Falling CTR On Branded Results

If your branded listings are getting fewer clicks and you haven’t changed your paid strategy, something might be off.

It could be that negative news, poor reviews, or competitor ads are winning attention. It could also mean users know your brand but are now choosing to avoid it.

New “People Also Ask” Questions

Google’s “People Also Ask” feature reacts to the wider search landscape. If questions like “Is this brand legit?” or “Does this product work?” start appearing next to your listings, it’s a reflection of growing uncertainty.

These shifts often point to new concerns that haven’t yet reached your team.

Standard Dashboards Don’t Show This

Most brands use a familiar mix of tools to track performance. These usually include sales numbers, social mentions, customer service logs, and net promoter scores. These are helpful, but they only show what’s already happened.

SEO data is different. It captures what users are wondering right now. It reflects unfiltered curiosity or concern. People don’t always leave feedback, but they often search when something feels wrong. That’s what makes search such a powerful signal.

Even the best social listening tools only rely on what users are willing to share in public. Search data shows what users are trying to understand privately. This gives you an early edge.

When SEO Is Seen Only As Performance

If you treat SEO as only a rankings or traffic tool, you miss a wider opportunity. That approach is becoming less useful in modern search, especially with the rise of AI. Search is evolving, and so is how users engage with it.

Organic search can show the small cracks in perception long before those cracks grow into bigger problems.

This layer is often ignored because it doesn’t sit neatly in a performance dashboard, but it can be one of the most valuable tools for protecting a brand’s reputation.

Build The Feedback Loop

Spotting the signals is only the first step. To get real value, you need a way to feed this information back to the right teams.

In most companies, SEO insights stay with the marketing or content teams, but PR should be looped in so they can act fast or use the data to shape their response.

Customer support should know what users are searching for so they can update scripts or prepare for new types of complaints.

Product teams can look at whether confusing searches are tied to real product issues. Brand and customer experience teams can adjust messaging on high-impact pages.

Final Thoughts

SEO isn’t just about growth. It’s a lens into what your audience is thinking and feeling. When used properly, it can surface early signs of trouble before they appear in sales, reviews, or tickets.

Brands that treat SEO as a signal, not just a channel, can spot problems early, act faster, and protect what matters most.

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Explaining Agentic SEO To The C-Level via @sejournal, @TaylorDanRW

AI has quickly carved out a central role in SEO, with widespread adoption across tasks like content generation, image, and video creation.

Generative AI makes headlines and is exciting, but the operational use of AI can be just as impactful.

This evolution is now being referred to as Agentic SEO. It’s not just about chasing rankings, keywords, or pleasing Google’s algorithms.

It’s about using AI to get more done with less friction. While I won’t define Agentic SEO here, Vincent Terrasi offers a great deep dive if you want to explore further.

What Is Agentic SEO?

Agentic SEO relies on AI agents powered by large language models such as OpenAI, Claude, Perplexity, Gemini, or Llama.

These agents autonomously or semi-autonomously take on tasks that have traditionally demanded heavy manual effort from humans. They are virtual team members helping cut down repetitive, low-value work.

These AI agents are used for various tasks that are becoming standard in SEO today. They can:

• Research and generate content ideas at scale.
• Analyze data pulled from third-party tools.
• Compare the similarity of content across large sets of webpages.
• Generate metadata and suggest internal linking strategies across massive content libraries.

Agentic SEO isn’t a substitute for SEO professionals. It acts more like a power-up, amplifying what your team can accomplish without replacing the strategic thinking and expertise they bring.

Human insight still drives the engine. AI clears the path for better focus.

The key message for C-suite executives and business leaders is this: Agent-based workflows offer a real operational advantage.

As competitors adopt these technologies, staying still may mean quietly losing your edge. Embracing AI in your SEO strategy doesn’t just keep you in the game. It pushes you forward.

The Benefits Of Agentic SEO

From a leadership perspective, it’s essential to recognize that Agentic SEO isn’t just another tool to add to the stack; it’s a shift in how SEO teams operate.

This new operational model supports faster execution, broader experimentation, and a more intelligent allocation of resources.

While it might not directly drive growth overnight, the boost in efficiency makes it easier to scale impact and hit key performance indicators (KPIs) with fewer roadblocks.

Increased Productivity

With Agentic SEO, teams can manage larger workloads without a proportional increase in staff.

That doesn’t mean you eliminate headcount or growth, but those on the team can handle significantly more, analyzing big datasets, cutting down on menial tasks, and spending more time on high-impact work.

This is especially valuable for in-house teams under pressure to deliver results on lean budgets.

It also strengthens the case for expanding your team’s scope and potential by replacing the mundane with critical thinking and strategic analysis.

Faster Execution And More Experimentation

By automating routine tasks, Agentic SEO enables SEO professionals to shift their energy toward strategy, creative problem-solving, and SEO experimentation.

With the busywork handled, they can test more ideas, iterate on content faster, and adapt quickly to shifting trends.

Over time, this makes teams more effective and helps individuals grow their skill sets and adjust in real-time.

Improved Consistency And Quality Control

AI agents can follow structure, apply formatting standards, and flag inconsistencies across the content of hundreds of pages, keyword clusters, or multiple datasets overlaid on each other.

This reduces human error and boosts quality, which is particularly important at the enterprise level.

It also allows team members who may not be data-savvy to perform and share insights without always relying on analysts, reducing bottlenecks and speeding up workflows.

Tighter Alignment With Broader AI Strategy

Agentic SEO sits at the intersection of AI, data, and marketing operations. It’s a logical and relatively low-risk next step for companies already exploring AI across other departments.

Tools are readily available, costs are reasonable, and results are measurable. This makes Agentic SEO a practical way to extend your AI investment into an area with clear return on investment (ROI).

What This Means For Your Organization

Agentic SEO changes how SEO teams function. For leadership, that means rethinking staffing, budgets, and how you scale operations.

You’ll be able to run larger campaigns with leaner teams, experiment more often, and shift hiring priorities toward support roles that strengthen your overall marketing engine.

Engineers and product teams will spend less time on repetitive site audits and documentation, while AI agents help with QA and standard operating procedures.

Data teams can use agents to uncover trends faster, correlating them with external factors. I always use the example of spotting sales patterns between rainy days and umbrella sales, without the delay of manual analysis.

The good news is you don’t need to overhaul your entire system. Many existing workflows can be restructured into agents. Start small. Scale as you see results.

Final Thoughts

Agentic SEO isn’t just another passing trend. It’s a fundamental shift in how SEO work gets done.

As AI agents grow more capable and easier to implement, teams that learn to work alongside them will outperform those clinging to old methods.

This isn’t about replacing people.

It’s about breaking through the time sinks and bottlenecks that limit your SEO team’s potential.

With the busywork out of the way, your experts can do what they do best: Think bigger, move faster, and deliver results at a scale traditional methods can’t match.

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Telling Better Stories With SEO Data To Show Business Impact via @sejournal, @TaylorDanRW

In data-heavy organizations, SEO remains one of the most misunderstood areas at the executive level.

This isn’t because of a lack of information but because much of that information lacks clarity or relevance.

SEO teams regularly produce dashboards, audits, and detailed reports, yet these rarely answer the business questions executives care about.

Charts showing keyword shifts or small traffic gains often miss the point when leadership asks:

• Where are we winning?
• Where are we losing?
• How does this impact revenue, risk, or market share?

The data must go beyond numbers for SEO to matter in the boardroom. It needs to tell a story that connects performance with business goals.

That means moving past surface-level metrics and focusing on insights that highlight opportunities, reveal competitive threats, and align with strategic priorities.

The aim isn’t to simplify SEO for executives but to elevate it. The goal is to turn it into a strategic narrative showing how organic search supports business growth.

The Core Issue: Data Without Context Gets Ignored

Most SEO reports are designed for technical teams, not business leaders. They are filled with keyword rankings, crawl errors, and technical diagnostics.

While necessary for day-to-day operations, these metrics often fail to explain why they matter to the business.

Executives are not looking for lessons in structured data or site architecture. They want to know what’s driving growth, where the risks are, and how they compare to competitors.

When SEO data is not tied to business outcomes, it becomes noise. In environments where attention is limited, that noise gets overlooked.

The missing piece is context. The SEO lead in an enterprise organization isn’t just responsible for collecting data. Their role is to shape that data into a story that informs business decisions.

That story should show how organic search impacts revenue, reduces paid advertising costs, or reveals shifting customer demand. Without this lens, even strong SEO results can go unnoticed.

What Executives Want From SEO Reporting

SEO reporting often turns into a list of disconnected metrics instead of a focused business narrative.

SEO reporting needs to speak about growth, risk, efficiency, and competitive advantage to be effective with executives. Here’s how that approach looks in action:

Business Alignment

Executives want to see how SEO contributes to the outcomes they are accountable for, such as acquiring customers, entering new markets, or reducing spending.

They don’t need to know how many keywords rank in the top 10. They want to see how organic traffic is supporting entry into a new vertical or how it’s helping reduce paid media dependency.

Tie SEO outcomes to business goals.

For example, instead of reporting a 20% rise in non-brand clicks, frame it as a surge in qualified visits to key product pages.

Show how that growth aligns with a wider initiative like expanding mid-market presence or improving retention through better content.

Competitive Intelligence

SEO offers a view into competitors’ digital activity that few other channels can match. Executives want to understand how their brand stacks up in search and what competitors do differently.

Good reporting highlights shifts in search share, gaps in content coverage, and emerging competitors in valuable categories.

Rather than simply reporting your ranking changes, provide insight into where rivals are gaining ground. This makes SEO a forward-looking tool that helps guide competitive strategy.

Risk Awareness

Organic traffic may seem like a stable channel. Still, it can be affected by algorithm changes, technical issues, or outdated content. Executives need early warnings about threats to performance.

Call out signals like declining rankings in high-value areas, growing dependence on branded search, or performance drops after site changes. Emphasize what’s at stake.

For example, losing visibility in a critical product line could mean lost revenue if left unaddressed. When framed in business terms, SEO risks become easier to act on.

Efficiency Indicators

Executives are focused on return. They want to know where SEO is most effective, where resources might be wasted, and how to make smarter investments.

Show which content types perform best, which SEO initiatives save paid media costs, or where organic traffic delivers stronger conversion rates than other channels.

Also, identify low-performing assets that need improvement. Help leadership see SEO as a lever for both growth and efficiency.

Transforming SEO Data Into Strategic Stories

Once you understand what matters to executives, you must convert SEO data into a straightforward, actionable narrative.

Reports alone don’t drive decisions. Stories do.

A strong SEO narrative follows a few simple steps:

Start With The Business Challenge

Open with a relevant issue. Is visibility falling in a key market? Is a high-growth segment being missed?

Begin with a problem or opportunity that has business importance.

Support It With The Right Data

Bring in the SEO metrics that matter. Use only what moves the story forward, such as search demand, ranking trends, or traffic shifts. Keep it focused and easy to follow.

Use Visuals For Clarity

Executives don’t want dense tables. Use simple visuals like charts or comparisons that make the insight immediately clear. It should take seconds to grasp the message.

Link To Commercial Impact

Explain how SEO performance connects to business outcomes.

For example, a drop in rankings for a key category might affect the pipeline, or a rise in organic visibility might reduce paid search spending. Linking revenue, cost, or growth goals is obvious.

End With Clear Recommendations

Conclude with what needs to happen. What should be prioritized? What is the potential upside or downside? Provide a clear path to action instead of just analysis.

SEO Storytelling Is A Strategic Skill

The strength of an SEO program isn’t just in how much data it captures. It lies in how clearly that data is used to influence business decisions.

At the enterprise level, SEO reflects market signals, customer intent, and competitive shifts. When framed correctly, it becomes a strategic advantage.

Executives don’t need to understand the technical details. They need to know how SEO supports their goals. Your role is to connect the dots between search behavior and business impact.

When SEO reporting stops being a technical summary and starts becoming a business insight engine, it earns its place at the table.

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Developing A Content Strategy In Regulated Industries via @sejournal, @TaylorDanRW

Throughout my career, I’ve worked with companies across highly regulated sectors, including finance, insurance, banking, and tobacco.

Navigating these industries means understanding how regulation influences every part of your content strategy, from the adjectives you can use for tobacco flavors to the exact phrasing required for financial products.

Once you understand the sector’s rules, the brand’s culture, and the internal culture, regulation becomes less about finding the right words and more about creating solid systems.

Governance is what makes the difference.

Understand The Regulatory Environment

Before going into tactics and solution mode, it’s critical to understand the regulatory environment you’re working in.

When creating content for healthcare, finance, gambling, pharmaceuticals, or legal services, the regulations exist for a reason, and ignoring them could lead to fines for you, your client, and damaged reputations.

That being said, staying compliant doesn’t mean you have to lose your creative edge, nor does it mean all your content needs to become homogenous and beige.

Start by identifying the specific laws and guidelines for your audience, product, and region. Ask questions like:

• What disclosures are required?
• What claims are restricted?
• Are there regional differences that affect content distribution?

Set alerts on government websites, follow industry regulators, and maintain strong relationships with legal advisors who know your space.

Too often, content teams bring legal in at the end of the content ideation and production process. However, it works much better when early compliance is involved.

When legal teams understand the purpose of your content, and you understand their concerns, you can work together to produce content that’s both effective and safe.

Some of the most trusted brands in regulated industries have turned these legal constraints into strengths.

They’ve built credibility with their audiences by focusing on clarity, transparency, and education. Rather than viewing regulation as a limit, they see it as a structure that guides them in creating honest, valuable content.

Build Systems That Scale

In regulated industries, content needs to do more than look good. It must be accurate, reviewed, approved, and ready to change.

This means your strategy should focus on the process behind the content as much as the content itself. Sound systems allow you to move quickly while still meeting compliance requirements.

Start by outlining your content workflow.

Define every phase, from idea generation to legal review, publication, and updates.

Clarify who is responsible for each step and what is expected of them. This will reduce confusion and prevent delays when multiple teams are involved.

Involving the legal team during this process also means you can create a “working contract” with them, and understand the lead times on requests made to them, preventing unforeseen delays in getting content live.

Next, put governance in place. Assign specific roles, create clear review steps, and standardize how things are formatted.

With everyone working from the same playbook, your team can focus on quality without second-guessing the process. You can use frameworks like RACI and DARCI to streamline this even further.

A modular content model can also help. This involves breaking down content into reusable parts like approved disclaimers, product blurbs, calls-to-action, and visuals.

These components can be mixed and matched across emails, landing pages, and social posts without requiring fresh legal review.

For example, a financial services team might have a pre-cleared copy for risk disclosures or action-oriented phrases. These blocks can be assembled into different content pieces, speeding up production and lowering compliance risk.

The more structure you build early, the more freedom your team has to create quickly and responsibly.

Make Trust The Foundation

Trust takes time to build, but it’s essential in regulated industries. Audiences are cautious, especially regarding health, legal, or financial matters.

Start by clarifying any relationships or interests with other companies or content providers. If you’re using affiliate links, sponsored messaging, or partnerships, make them easy to see and understand.

Data privacy is another area that consumers are increasingly focusing on.

Aside from the standard cookie compliance banner, let users know what information you collect, why it matters, and how you use it.

Avoid complicated legal language. Instead, use straightforward explanations and place them somewhere easy to find. When people understand how their data is handled, they’re more likely to feel safe engaging with your brand.

If your content includes legal or regulatory information, offer a simplified version alongside the official language. People appreciate clarity, and understanding what they’re reading builds trust and keeps them engaged.

Transparency does more than meet legal requirements. It shows your audience that you have nothing to hide.

When people feel like they’re getting the whole picture, they’re more likely to return, recommend you, and believe in what you stand for.

In regulated industries, transparency is not just a value; it can also be a competitive advantage.

Stay Agile As Rules Change

Regulated industries are constantly evolving. Laws are updated, platforms revise their terms, and consumer expectations shift.

A strong content strategy can’t just meet today’s standards – it has to be built for change.

Start by keeping your editorial calendar flexible. Leave room to adjust for news cycles, regulation updates, or unexpected events. Rigid production timelines can trap your team when things change suddenly.

Set up a system to stay on top of industry and legal updates. Use alerts, follow regulatory bodies, and assign someone on your team to track changes that could impact your content.

Being proactive allows you to stay compliant before changes take effect.

Review existing content regularly. Blog posts, landing pages, and downloads should be considered living documents.

If something becomes outdated, update it quickly and clearly. This shows you take your responsibilities seriously and helps maintain audience trust.

Technology makes this easier. Collaboration tools, modular content systems, and centralized approval workflows allow you to adapt without compromising quality or compliance.

The faster your team can respond to change, the stronger your brand will be.

Change is guaranteed in regulated industries, and maintaining a record of all content being produced means that when regulations are updated, you can quickly implement changes without impacting your content production plans.

By keeping a close relationship with your client’s legal team and by keeping abreast of industry developments, you can be aware of potential future regulatory changes and incorporate them into your content strategy and production calendar.

Final Thoughts

You don’t have to choose between creativity and compliance.

Your team can create effective content that aligns with regulations with the right systems, tools, training, and processes.

The structure you build shouldn’t hold you back. It should give your team the confidence to move faster and the clarity to make better decisions.

In regulated industries, strong foundations are what allow great content to thrive.

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