Reflecting on my journey in search marketing, I’ve embraced the evolution while recognizing that human creativity remains at the core of an AI-driven world.
Embarking on this career back in 1996, I initially dived into SEO and expanded to paid search by 1998. After a period of burnout in a different sector, I plunged into website design and became an at-home affiliate marketer for giants like Amazon and eBay.
Back in 1998, the launch of Goto.com marked the real start of the pay-per-click era, introducing a groundbreaking model where clicks had monetary value instead of just impressions.
Google’s dominance wasn’t solidified until 2006-2007, when advertisers were compelled to engage with its complex systems, transitioning us from sporadic advertising efforts to comprehensive digital campaign management.
The broader industry shifted significantly, evolving from grassroots operations to a corporate environment driven by venture capital, high salaries, and extravagant events.
Reflecting on the changes, two major milestones transformed paid search: the complexity introduced by Google’s organic algorithm updates and the efficiency brought by automated bidding, freeing time for strategic creativity.
Discussing past strategies, I’m not nostalgic about Single Keyword Ad Groups (SKAGs), but I do miss features like the original Enhanced Cost-Per-Click and specific geo-targeting tools that once offered greater control.
As we look ahead, it’s clear that AI can’t wholly take over advertising accounts; human creativity will continue to play a pivotal role in connecting with our inherently illogical nature.
Reflecting on the past, I made some incorrect predictions, like overestimating the speed of mobile adoption, while correctly assessing that voice search would integrate into regular queries rather than becoming a separate entity.
If I could advise my younger self, it would be to invest more in Google stock – a simple yet significant insight looking back over two decades.
From the super early days of Google through using AI today for SEO – we covered a lot in this interview.
Vanessa Fox was the individual who was instrumental in what we call Google Search Console today. I sat down with Vanessa Fox for a one-on-one interview to discuss the early days of Google, how Search Console came about, and the industry’s evolution to what it is now.
We spoke about what it was like to work at Google in the early days, how XML Sitemaps turned into Webmaster Tools, which then evolved into Search Console, and what it was like collaborating with Matt Cutts. We also delved into the story of how she sold her Google stock options too early and her journey from Google to writing at Search Engine Land, this site.
Vanessa shared insights into the early days of SEO misconceptions, her Panda SEO audits and recoveries, and the fascinating ways AI is transforming search and SEO.
As I navigate through the ever-evolving world of search engine optimization, I’ve come across a revelation that I believe could change the game. It’s something I like to call ‘YBYS’: Your brand equals your SEO.
The simplest approach to staying relevant, even in the face of AI-driven search changes, is surprisingly straightforward: focus on building a real brand.
Every day, I hear two questions repeatedly in meetings with various businesses.
“How do we get back our Google clicks?”
“How do we show up in all the LLMs?”
The answer, although not always welcomed, is simple: build your brand. The old tactics like keyword stuffing and excessive backlinking have lost their long-term effectiveness.
While search-and-answer bots can indeed be manipulated in the short term, the real, lasting value comes from being genuine and credible.
Let’s take the example of two brands: Crayola and Monday Mandala. Crayola may be the well-known brand you think of for crayons, but Monday Mandala brings more traffic for coloring-related searches. It’s remarkable, but true!
Even though Crayola wins in brand recall, Monday Mandala excels in attracting clicks. This dynamic shows how brand recognition can be just as important as clicks in the world of AI-driven search engines.
We’re in an age where building a memorable brand is invaluable, extending its impact beyond the fluctuations of search engine algorithms.
Search has fragmented, yet a brand’s strength hasn’t. In past years, search meant asking Google, clicking a link, and landing on a website. Nowadays, the landscape is far more complex, with answers appearing across multiple platforms.
So, what stands the test of time when users no longer click links? It’s brand memory. Users remember names, trust established relationships, and value recommendations. These aspects travel with them, transcending the traditional boundaries of your website.
Your brand essentially becomes your SEO. SEO tactics are still useful, but the underlying core of a brand makes you unforgettable.
I strive to integrate this philosophy, highlighting that your brand lives beyond just your online presence. Recognizable brands endure, driving loyalty and sustainable growth.
Attending Google I/O 2026 for the first time felt like stepping into a realm of boundless energy and optimism, almost as thrilling as witnessing a crowning ceremony.
The initiatives launched last year have transformed into robust pillars of growth. Ask Maps, for instance, has become the blueprint for introducing Ask YouTube. Gemini 3.5 Flash fuels Antigravity, akin to Claude Code but under Google’s banner, and Googlers are already harnessing it to construct the exciting features shown on stage.
The pace of innovation was breathtaking, everything rolled out swiftly and assuredly.
Every announcement seemed to cater to a diverse audience.
Gemini Omni was likened to Nano Banana but designed for video content (see this strange proof).
Smart glasses are making a much-discussed return.
There are video game-like experiences that can be instantly prompted and played.
The capability for Workspace to bring documents to life with mere conversations.
A feature allowing the transformation of Google Maps images into surreal dreams seems more like a solution waiting for a problem, perhaps for Hollywood studios looking to bypass on-location shoots?
I even have Gemma on my phone, enabling in-flight conversations with a smaller model. (Thanks to American Airlines’ free Wi-Fi, I’m all set.)
And yet, the most intriguing element remains to be addressed.
Gemini and Search: Converging Evolution
Gemini is beginning to resemble Search, while Search is adopting features of Gemini.
Both platforms now include features that satisfy similar needs: keeping tabs on the web and alerting users when something of interest arises.
In Search, these are known as information agents. In Gemini, they go by Spark or Daily Brief. The connection is unmistakable.
I asked a product manager about their approach to long-term feature management and overlapping utilities. Their response was simple: “Right now, it’s all about velocity.”
Shipping fast is the mantra shared by three other product managers, all behind key I/O features initiated and deployed within this whirlwind year, 2026. It’s astounding.
The product manager elaborated, “Velocity is achieved through reduced managerial overhead.”
This implies jumping on board quickly and figuring out the finer details later.
Once You See It, You Can’t Unsee It
Armed with this understanding, the rest of the day wore a new perspective. The demos were impressive, yet I pondered: what’s the next step with these innovations?
Though I now have Gemma on my phone, one developer couldn’t provide a tangible day-to-day use case. I witnessed AI Mode’s monitoring prowess by prompting it to “keep me updated.” Despite seeing the connection of components, my questions about managing these alerts as they age went unanswered, indicating it’s still an early-stage demo.
Many features appear not to address their second-order effects thoroughly. It seems engineers are using these systems at a command line level rather than considering user interfaces.
A notable point is my current inability to delete old Gemini chats in a web browser, a functionality available in the Mac app.
Universal Cart Sparks Discussions
A frequently mentioned feature during I/O was Universal Cart, Google’s new cross-platform shopping protocol.
My opinion? If you’re Google, it’s an exciting development because, upon adoption, it further solidifies their control over the complete shopping experience. Conversely, for others, this development might be a cause for concern.
Despite these concerns, the group I conversed with didn’t seem troubled, feeling distanced from the growing anti-AI sentiment in the U.S.
Speaking with an SEO expert at a major ecommerce brand implementing Universal Cart, they related the velocity comment to their own implementation experience, describing it as feeling rushed.
Just four days before I/O, Google’s Search quality team advised publishers to “write for humans, not AI.” Shortly thereafter, the AI agent team demonstrated capabilities where Google’s own agents browse, interpret, transact, and create web content.
As Google shifts towards AI handling more tasks, the advice given to publishers starts to sound less sincere.
Impact on the Web Ecosystem
I don’t wish to undermine the engineers’ efforts. I communicated my respect for their work directly to them. Building products for search and clients myself, I can relate to frequent criticisms over compliments.
Still, the potential downside of overlapping features, difficulty in managing or reconciling data could lead to significant technical challenges later. The current AI strategy appears to be: prioritize feature utilization first, reconcile later.
Nevertheless, I admire Google’s rapid progress and look forward to future developments. Leveraging substantial resources, they can experiment comprehensively to identify successes.
Regrettably, my enlightening conversation with the product manager was abruptly concluded as we were asked to vacate the premises.
Spotting the Bright Spots
Google reports unprecedented high search query volumes. They are enhancing authentication and provenance through SynthID’s expansion into Search and Chrome, welcoming new partners like OpenAI, and integrating C2PA content credential verification.
These are indeed significant accomplishments.
However, the relentless pace might lead to unforeseen challenges. My hope is that the quest for speed doesn’t further destabilize the already-fragile web ecosystem.
In conclusion, it’s undeniably an exhilarating era for search technology.
As I delved into audits across Prince Edward Island, one issue stood out: businesses with significant expertise weren’t visible to AI systems because their knowledge wasn’t rendered into a machine-readable format.
Despite their leadership in biotech, manufacturing, and other sectors, critical business information was often trapped in PDFs, behind forms, or muddled in vague marketing copy. It was also disconnected from structured data systems that AI engines need for verification.
We’re living in a world where 88% of companies are integrating AI. Yet, McKinsey notes that 86% of leaders admit to being unprepared for its daily integration.
Many brands mistakenly equate AI visibility with being featured in a Gemini summary or a ChatGPT result, without solidifying the structured digital groundwork needed for ongoing visibility.
AI Visibility: The Basics Before the Buzz
If you’re only focusing on large language model (LLM) responses, you’re lagging. LLM visibility reflects authority—it doesn’t build it.
According to a study by Responsive, 22% of B2B buyers now use generative AI for vendor research. Traditional search use is expected to drop by 50% by 2028 as AI solutions become the go-to answer engines, as Gartner predicts.
Now, discovery happens through synthesizing answers rather than listing URLs. Until you’re part of the Knowledge Graph as a verified entity, your brand’s visibility will be inconsistent.
The Insights from 19 Case Studies: Expertise Powers AI Search
AI systems value concrete, structured data over descriptive text. Brands chasing fleeting AI mentions without anchoring their data won’t achieve lasting visibility, but those establishing structured data relationships will always be recognized.
Thus, SEO has evolved from simply creating content to becoming an information architect. As the case studies reveal, expertise remains a key signal that AI systems can interpret.
Case No.
Entity
Industry
The discovery
The SME solution
1
BioVectra
Biotech
Technical authority trapped in PDFs
Encoded cGMP data into facts
2
Wyman’s
Food manufacturing
Sustainability was a narrative
Structured supply chain schema
3
Murphy Hospitality Group
Hospitality
Invisible venue specifications
Constructed event logic
4
Invesco
FinTech
Opaque compliance data
Built regulatory ground truth
5
Sekisui Diagnostics
MedTech
Innovation lacked readability
Engineered diagnostic logic triples
Why SEOs Must Focus on Education
The main obstacle to AI readiness is the gap in education. We must evolve into information architects, comprehending our clients’ business logic deeply.
SEOs as Subject Matter Experts
Understanding is foundational. For instance, auditing a biotech firm requires a grasp of compliance as keen as their lead scientist’s.
AI relies on structured context for accurate answers. Vague marketing language feeds insufficient responses.
Clients Must Prepare Their Data
Data quality and governance activation equate to maximizing AI-driven value. SEOs must educate clients on digital presence impacting AI brand perception.
Focus on True AI Authority
Appearing in a ChatGPT reply isn’t the goal; becoming an authoritative node in the Knowledge Graph is. It ensures visibility across AI platforms like Gemini and Claude.
AI advancements will persist rapidly. SEOs and clients not prioritizing structured data will be left behind in AI discovery systems.
Every Monday, I dive into my role as a paid media manager knowing the chaos that awaits. From Google Ads to TikTok and Reddit, my task is to pull the data from each platform, put it into a comprehensible spreadsheet, and report to my boss by 10 a.m. Amidst all this, I try to decipher what worked last week and why. It’s a frenetic start to the week, to say the least.
Remembering when managing multi-channel campaigns meant juggling just Google Ads and a Facebook campaign feels almost nostalgic now. Today, it’s a tangled web of 12 channels, each with their peculiarities in terms of attribution logic and campaign structures. The disarray is real and mostly ignored, to the detriment of performance marketers like me.
I realize that this Monday morning ritual is less about campaign management and more about tedious chores like data entry and reformatting. Managing campaigns across numerous networks involves reopening platforms repeatedly just to align disparate data points.
The prevailing problem isn’t just the time I lose, but the lag it introduces to my operations. When my performance data is scattered across various platforms, delays in identifying key insights can lead to wasted budgets. The inconsistency in strategies across channels further exacerbates the issue.
I’ve come to understand that relying on native dashboards from Google, Meta, and others won’t rescue us from this inefficiency. These platforms prefer keeping us tethered to their interfaces, contributing to the fragmentation. But a paradigm shift is on the horizon: AI-native management tools that promise seamless cross-platform synchronization without the need for multiple dashboards.
The change is happening right now, reimagining how campaigns are managed with AI. It means planning campaigns with simple briefs and automatically syncing creative adjustments across all channels. This reorientation is not just an incremental improvement but a transformational leap that alleviates the operational burdens we’ve carried for too long.
For agencies like mine, AI brings another boon: automated and branded client reports that compile multi-network performance data without the Sunday-night grind.
What actions can we take this week? First, I’ll track where my hours truly go throughout a week — seeing is believing when it comes to confronting administrative bloat. Second, standardizing naming conventions across accounts is surprisingly effective in smoothing out cross-platform wrinkles. Third, I’ll delve into evaluating current AI-native tools, as I suspect many teams are operating on outdated assumptions about their capabilities.
Achieving an operational edge in paid media transcends budget size. It’s about faster data-action cycles, unified cross-network performance views, and liberating our teams from the laborious chains of manual processing. This operational edge could mean the difference between thriving and merely surviving in a competitive landscape.
Recently, I’ve been exploring the fascinating divergence in AI adoption between professional circles and general consumers. According to Datos and SparkToro’s latest data, this trend is becoming increasingly apparent.
It was intriguing to see how AI usage is starting to plateau among consumers while remaining on the rise in professional environments. Tools like Claude, ChatGPT, and Gemini are seemingly more popular in the B2B landscape.
Why we care. As I delve deeper into AI’s impact, it’s becoming clear that a universal AI strategy won’t work for everyone. It’s essential to identify whether my audience aligns with these broader trends or if their AI engagement habits are entirely different.
ChatGPT desktop growth slowed. From Fishkin’s analysis, it appears that ChatGPT’s usage in the U.S. has stagnated over recent months while Claude and Gemini continue their growth trajectories. It seems that professionals are continually finding value in these tools.
At its zenith, 37% of U.S. desktop users engaged with OpenAI or ChatGPT back in September 2025. This number dipped slightly to 34% by March, a trend mirrored, albeit with higher numbers, in the EU and U.K.
Claude gained with professionals. I noticed Claude is particularly gaining traction among professional users. Fishkin’s data suggests a significant rise in usage among business professionals, resonating with the notion that AI adoption is stronger in B2B contexts.
The analysis even revealed that Claude’s use among B2B professionals was 373% higher than the U.S. average, reinforcing the tool’s growing popularity in business circles.
Consumer audiences look different. Interestingly, when it comes to the retail-shopping consumer audience, ChatGPT isn’t as prevalent, being 15% less likely to be used compared to the typical American consumer. For this group, Claude isn’t even in the top four AI tools.
This might explain why AI seems so prevalent in professional networks like LinkedIn, while its visibility is not as pronounced among general consumers.
The research. You can view Rand Fishkin’s detailed insights on LinkedIn by watching his video here.
Today, I’m excited to share that Google is making significant enhancements to Asset Studio, aimed at helping advertisers like us generate creative assets more efficiently by leveraging the power of Gemini. This was announced at Google Marketing Live 2026.
Driving the news. Asset Studio will now feature AI-driven creation capabilities across text, images, and videos, allowing us to use natural language prompts to guide the process.
Google assures us that the platform is capable of understanding:
Marketing briefs
Brand guidelines
Website content
Campaign goals
By doing so, it generates creative assets that span different themes and formats, tailored to our needs.
Additionally, Google is integrating the Gemini Omni, their multimodal model, into Asset Studio. This enhances our workflows, especially in video creation.
With 1-Click Creative Testing, we can quickly identify top-performing assets in terms of campaign objectives. This means more efficient testing and better results for us.
How it works. By applying Gemini models, Asset Studio interprets our marketing briefs, guidelines, and objectives. Using natural language prompts, we can generate and perfect our assets, whether they’re text, image, or video. Plus, Gemini Omni ensures our video workflows are seamless.
The aim is clear: centralize creative production and minimize the challenges we face when building campaigns across platforms like Google and YouTube.
Why we care. Creative production bottlenecks are a major issue for us advertisers. Google’s updates show that integrating generative AI into our workflows makes creative production much more streamlined.
For those of us managing cross-platform campaigns, the ability to swiftly generate and test creative assets is a game-changer.
What to watch. As we automate more of our creative processes, it’s important to compare the performance of AI-generated assets against those from traditional workflows. We might need to rethink approval processes and brand safety in light of AI’s growing role.
Availability. We can expect the new Asset Studio features to become globally available in English this summer, opening up new possibilities for our advertising strategies.
Dig deeper. There are more updates from Google Marketing Live 2026 that are worth exploring for additional insights and tools that could benefit our campaigns. For example:
Today, I’m excited to share that Google is making Analytics 360 even more powerful by integrating the Meridian marketing mix modeling platform. They’ve also introduced a new predictive conversion metric that promises to enhance media mix decisions for advertisers.
I learned about these updates during the Google Marketing Live 2026 event, where Google unveiled several enhancements aimed at expanding measurement capabilities. The integration of Meridian, Google’s open-source marketing mix modeling tool, directly into Analytics 360 is a significant step forward.
Driving the news. With this integration, I’m able to unify first-party and cross-channel data, measure incremental performance, forecast campaign outcomes, and optimize media mix investments with greater ease.
Moreover, Google is rolling out Qualified Future Conversions (QFCs), a predictive reporting metric powered by Gemini. QFCs link current ad activity to future sales signals like branded search behavior, providing insights that were previously harder to visualize.
How it works. From my perspective, Meridian combines first-party data, media signals, and cross-channel performance metrics in Analytics 360. This helps to model incremental impact while Qualified Future Conversions use Gemini’s predictive signals to understand potential future purchasing behaviors.
In the long run, Google aims to integrate QFC insights into Meridian for more accurate predictive modeling. This is part of their broader effort to simplify measurement and refine ROI forecasting in today’s complex media landscape.
Why we care. As I’ve observed, measurement and attribution are becoming increasingly challenging with evolving customer journeys and the emphasis on privacy. These latest updates highlight Google’s commitment to helping advertisers like us better understand and plan for long-term performance.
The combination of Meridian and QFCs can empower marketers to make better budgeting decisions by accurately linking current campaign activity to future outcomes. It’s a tool we should all keep an eye on.
What to watch. Predictive measurement is becoming crucial. I’m looking forward to testing whether Meridian and QFCs can offer more actionable forecasting compared to existing solutions.
Availability. I found out that Meridian integrations are rolling out globally in Google Analytics 360, supporting all languages. QFCs are in a restricted global pilot phase, with wider beta access anticipated later this year.
Dig deeper. If you’re interested, there’s more news from Google Marketing Live 2026, including tests of new conversational ad formats and AI-powered tools in the Merchant Center, as well as expansions across various Google services.
I’m excited to share that Google is enhancing its Direct Offers with AI-generated bundles, native checkout features, and enticing travel deals. This announcement, made at Google Marketing Live 2026, marks a significant upgrade for the platform.
Driving the news. Google aims to make promotional offers more visible within AI-powered Search experiences.
Brands will soon have the ability to upload a variety of promotional types:
– Discounts
– Giveaways
– Local coupons
– Product bundles
Google’s Gemini will assist in creating personalized offers that align with search intent. This means tailored promotions based on user queries and browsing habits.
How it works. Advertisers can upload eligible promotions and campaign guardrails through Google Ads. Gemini will then curate relevant offers like bundles and discounts that resonate with the shopper’s search and browsing behavior.
Additionally, Google is introducing native checkout support for merchants using the Universal Commerce Protocol (UCP), enabling users to complete purchases directly within AI-driven shopping experiences.
Travel partners such as Booking and Expedia will soon showcase travel offers directly within AI-assisted trip planning features, enhancing the overall travel booking experience.
Why we care. This integration is transforming promotions into an integral part of conversational shopping, steering away from conventional deal extensions and static offers.
Advertisers now need to optimize their promotions to fit within AI-powered discovery and recommendation systems.
The introduction of native checkout options is expected to streamline the transition from product discovery to conversion, potentially boosting sales.
What to watch. It’s worth observing how Google’s shift towards AI-assisted promotional commerce influences conversion rates and consumer shopping patterns.
Availability. Currently, Direct Offers is available as a pilot for advertisers in the U.S.
Dig deeper. Stay informed with more updates from Google Marketing Live 2026:
