Category: Opinion

Navigating the AI SEO Renaissance: Unveiling Industry Shifts
In the process of exploring brand visibility in the AI era, I’ve immersed myself in the evolving terminology and strategies that are reshaping the landscape. The journey began with a survey conducted by Fractl and Search Engine Land, where we reached out to 2,000 consumers in June. An amazing 82% of respondents found AI-powered search significantly more useful than traditional methods.

As these findings came to light, the SEO community experienced a wave of uncertainty. Platforms like LinkedIn soon buzzed with a variety of opinions, each attempting to define what this new realm of AI-assisted brand visibility should be called.

Suggestions ranged from GEO, AEO to AISO, with some shifting towards LLMO. However, could it simply be a matter of optimizing current SEO practices for this AI-driven world?

It’s clear that we are in an environment where traditional search methods coexist with AI discovery, making the terminology more than just a trivial matter.

This new vocabulary serves as a map for how brands are expectantly making their presence known on rapidly growing platforms like ChatGPT, expected to reach 1 billion users by the end of the year.

To untangle this complex jargon, Fractl teamed up with Search Engine Land to explore which terms are truly gaining ground. In recent weeks, we’ve sifted through market chatter, surveyed industry professionals, and dissected job boards to identify the terms making a tangible impact.

The objective was clear: sift through the noise to spotlight the labels integral to hiring, strategic planning, and brand visibility in an AI-centric age.

Key Takeaway: Instead of replacing SEO, marketers seem to be incorporating new labels alongside it.

Discoveries like GEO illustrate the industry’s directional shift, whereas AEO and AISO provide insight into existing practices. SEO, meanwhile, stays as the cohesive element connecting various business aspects which appears consistently in both Google searches and employment listings.

This wealth of data challenges us to analyze how these insights affect real-world applications.

1. Setting the Industry Baseline: Insights from Third Door Media Subscribers

While large datasets provide a foundational understanding, consulting with active practitioners gives the nuanced context needed for practical application. For that, we surveyed Third Door Media subscribers with two crucial questions:

Right away, it was evident that some terms hold more weight within the industry than others. Our research showed that:
- 84% acknowledge GEO (Generative Engine Optimization).
- 61% are familiar with AEO (Answer Engine Optimization).
- 60% know AISEO (Artificial Intelligence Search Engine Optimization).
The rest of the terms seem confined to niche recognition, like AIO (Artificial Intelligence Optimization), and others.

Usage displayed a deeper and more telling trend. When forced to select a single term for enhancing brand visibility on generative AI platforms, respondents chose:
- 42% for GEO.
- 16% for AISEO.
- 14% for SEO or AEO.
This discrepancy points to an ongoing dilemma within the sector.

Experienced SEO practitioners almost uniformly agree that effective SEO strategies form the backbone of AI-enabled brand visibility, with 84% acknowledging GEO’s prominence.

Yet only 14% use SEO to describe evolving practices on platforms like ChatGPT and similar tools.

To provide context to this divide, I spoke with Danny Goodwin, Editorial Director of Search Engine Land, who shared his perspective:
- “The arrival of AI-focused search took everyone by surprise, and it’s evident that the industry’s sense of identity hasn’t fully adjusted. We are in a period of transition, where GEO champions the evolving landscape of AI search paradigms. We are living through a pivotal shift in how users retrieve information through generative AI and digital assistants.”
- “Although the essentials of SEO work remain largely unchanged, it’s crucial to remember that there’s not a complete overlap between what was effective for SEO and what applies to GEO now.”
- “To stay relevant, it’s essential to engage with AI tools and comprehend the mechanics behind how answers are generated and retrieved.”
For anyone who hasn’t done so, I highly recommend watching Lily Ray’s MozCon presentation, which dives deep into these subjects with artistry and expertise.

Her work and this article reflect a larger dynamic: the necessity for new frameworks to define AI-era discovery.

2. Google Search Trends Unveil Surging AI-Era Terms

We’ve gone beyond mere search volume analysis on Google Trends, turning our focus to the rate of search acceleration over recent quarters to pinpoint which terms are gaining momentum as 2025 draws to a close.

It’s apparent that marketers aren’t seeking abstract AI jargon; instead, they want language tied directly to actionable processes.
- ASO (Answer Search Optimization) has emerged as a standout, with a notable 152% increase.
- GEO demonstrates a 121% rise, highlighting its recognition outside of the SEO domain as a concept closely aligned with generative discoveries.
The data conveys a move towards a unified language blending AI, search, and optimization, accessible even to those outside the traditional SEO realm.

3. Social Media Sentiment: A Community’s Reaction

While Google Trends illustrates curiosity, LinkedIn captures cultural nuance. It’s a platform where terminology is challenged, parodied, and sometimes embraced.

Over a three-month period, we analyzed approximately 6,400 LinkedIn posts, identifying that although GEO commands awareness and usage, the term that currently leads positive sentiment is much simpler: SEO.
- SEO remains a cornerstone on LinkedIn with a positive sentiment in 90.4% of discussions, slightly ahead of its 85% positivity rating on Reddit.
- AISEO takes the top spot on Reddit for positive sentiment, mentioned fondly in 95.8% of posts, while also earning favor on LinkedIn with an 84.8% positivity rating.
Practitioners, it seems, reward clarity, favoring labels that denote a continuation and enhancement of well-established methods over the excitement of new acronyms.

This indicates a growing sentiment that AI search represents an evolution rather than a replacement of SEO.

Interestingly, there’s a disparity with AISO, which enjoys a high level of support on LinkedIn but considerably less on Reddit. This division suggests that while business professionals are open to the term, broader communities may be skeptical or interpreting it differently.

4. The Hiring Landscape: Insights from Job Market Data

Expanding our study to the job market, we analyzed 33,250 U.S. job postings on Indeed and found the industry’s future terminology landscape clearly defined by a preference for AISO.

AISO now leads with over 11,001 current listings, surpassing other terms like SEO, AEO, GEO, and LLMO combined.

This trend signifies how hiring managers recognize the scope of AI-era discovery under one encompassing label.

As Danny Goodwin noted, while AISO represents a modern adaptation of classic SEO roles, the fundamental requirements—content, technical skills, and UX—endure. Yet, the addition of AI tools underscores the evolving nature of these roles.

For marketing leaders, immediate takeaways include recognizing AISO as the prevalent market terminology, continuing to hire SEO talent at its core, and utilizing GEO as more of a strategy rather than a job title.

Applicants seek roles titled AISO or SEO with an AI focus, while incorporating terms like AEO and SXO within job descriptions can enhance clarity around job responsibilities.

So, What’s Next?

With search behavior diversifying across platforms, the SEO landscape may be evolving, but core principles of creating valuable content and maintaining a cohesive inbound strategy remain constant.
- SEO isn’t obsolete.
- GEO isn’t a fleeting trend.
- AISO isn’t avoidable.
We don’t need to choose one term over another; instead, the focus should be on creating cohesive frameworks.
- Utilize SEO to set team objectives, budgets, and expectations.
- Leverage GEO to encapsulate the shift towards generative discovery.
- Adopt AEO/AISO to refine how content is accessed through innovative tools.
Ultimately, these labels don’t replace the essence of SEO but rather add scaffolding to the long-standing mission of driving brand visibility through creating informative, targeted content shared where audiences congregate.

Methodology
- Our analysis ranged from surveying Third Door Media readers, collecting Google Trends insights via Glimpse, to studying job market demands on Indeed.
- We also monitored live discussions by analyzing LinkedIn and Reddit content, giving us a comprehensive view of which AI-related SEO labels are making waves.
Inspired by this post on Search Engine Land.
November 21, 2025
Boost Trust and Cut Costs with Enhanced Creator Content
Have you ever wondered how amplifying content from creators can actually save money and build trust with your audience? Well, I’ve seen firsthand how paid amplification not only cuts down media costs but also brings in new potential partners.

Brands, including mine, often invest in influencer and affiliate promotions. Yet, many of us stop short of giving the content the reach it deserves, believing the creator’s audience alone is sufficient. But there’s so much more we can do.

By using paid marketing, integrating it into my site, and sharing it across different channels, I’m not just promoting their work. I’m leveraging their brand recognition and strengthening my relationship with them.

It’s true, I may pay influencers an upfront fee, commission, or give them a product for their promotion. But that’s not where our relationship ends.

Amplification truly becomes an advantage here, unlocking more value from the creator relationships I’ve already established.

Why amplifying creator content pays off

Let’s dive into why amplifying creator content can be so beneficial.

Trusted validation

When someone trustworthy backs up my product, store, or company, I gain credibility, especially in competitive fields where trust isn’t always assured, like jewelry or insurance.

For example, picking a hotel near Disney or on a Caribbean island can be daunting with so many choices and mixed opinions. But if someone trusted chooses my brand, that might just sway the decision.

I can utilize this content in ads to reach new audiences or test it with email or SMS list subscribers who haven’t converted yet. The same strategy works for remarketing efforts too.

A third-party endorsement can make a significant difference, even when I sing my own praises.

Lower media costs

Certain influencers might be out of budget, but promising them that their ads will reach new, similar audiences might bring their costs down.

By allowing them to use their affiliate links in this amplified content, they can earn commissions, which shares the risk on both ends by reducing fees and incorporating commission-based rewards.

If the influencer earns more through commissions, they might drop their fees altogether and join as a regular affiliate, freeing up my budget for experimentation with new partners.

Alternatively, we could split the costs, covering part of their media fee while they earn the rest via commissions—opening new avenues to explore and test partners.

Dig deeper: The best affiliate networks by need and use case

More discoverable content

There’s magic in content that’s naturally shareable—be it for its humor, virality, or relevance. More people sharing amplified content can lead to wider discovery and referencing, with additional pathways directing traffic back to my site.

Public accounts mean search engines and tools like ChatGPT can index these links, boosting my visibility and traffic.

Affiliate recruitment

When reputable accounts start promoting a vendor, it’s an indicator of earning potential. By amplifying this content, I open up opportunities for others who resonate with those influencers to join as affiliates.

Some might reach out for collaborations, while others might dive into the affiliate world themselves.

Big names endorsing my brand builds trust, making newer partners feel assured that my program is credible.

We encourage our clients to pursue this approach as it effectively streamlines affiliate recruitment and activation, two of the most challenging aspects of the affiliate marketing sphere.

Starting ambassadors and influencers as affiliates ensures fairness. If collaborations prove lucrative, we can transition to hybrid models, minimizing risk while granting them entry.

Not all clients are keen on this model, but those who adopt it see significant benefits, expanding their partner network while sharing risks.

Dig deeper: Affiliate managers: It’s time to shift your focus beyond media

Putting creator amplification into practice

Here are the strategies I frequently employ to maximize the impact and extend the reach of creator content:
- Launching PPC ads that lead to a dedicated landing page presenting the content.
- Utilizing the content in social media or YouTube ads as representations of our brand.
- Incorporating the content into product pages, long-form content, and categories or collections.
- Sending email campaigns that link to or prominently feature the creator’s name, image, and messaging.
The options are abundant. It all boils down to identifying where my audience resides and if my potential customers can be found there too.

Boosting influencer and ambassador content goes beyond merely doing their job. It’s an astute business move.

I borrow their trust and credibility, tapping into their audience while utilizing the content to persuade on-the-fence clients.

Dig deeper: Why creator-led content marketing is the new standard in search

Inspired by this post on Search Engine Land.
November 21, 2025
Mastering AEO: How Brands Thrive in the Age of AI-Driven Search
As I navigate the evolving landscape of search engines, I’m seeing a shift across industries. AI systems now prioritize answering first and linking later, reshaping how brands can gain visibility. It’s clear that I’m required to look beyond traditional rankings and consider how brands are interpreted and cited within AI-generated results.

The concept of Answer Engine Optimization (AEO) has transitioned from a novel idea to an essential practice. For me, structure, clarity, and credibility have become vital signals that assist large language models in interpreting, summarizing, and confidently presenting content.

Yet, these implications aren’t uniform across industries. For instance, AEO is transforming product discovery in retail, challenging accuracy in healthcare, and testing monetization in the publishing world. Each sector faces unique challenges regarding visibility, control, and trust. In the following sections, I’ll delve into how leading industries are adapting to this answer-driven search environment and what it takes to remain discoverable when AI crafts the first impression.

Ecommerce and Retail: Structured Data as Digital Shelf Space

For those of us in ecommerce, the game is changing as AEO reshapes how consumers find and compare products. Generative search results now display comprehensive product details like pricing, specs, and reviews, often without a single site visit, directly affecting our organic traffic and brand impressions.

Retailers who are ahead of the curve are investing in product-level schema, feed optimization, and engaging, conversational copy that resonates with the way shoppers phrase their questions. Structured data has become as critical as digital shelf space in ensuring accurate product information when AI engines build summaries.

I see innovative brands exploring AI shopping assistants and voice commerce, positioning themselves in the next wave of purchasing experiences. For instance, in September 2025, Google Cloud and Albertsons launched a Conversational Commerce Agent, emphasizing the potential of conversational search in shaping customer purchases.

Healthcare: Prioritizing Accuracy as a Visibility Signal

In healthcare, AI-driven search brings intense scrutiny. When generative systems present medical summaries, accuracy, compliance, and patient trust are paramount. Health organizations are countering this with verified data partnerships, expert-reviewed content, and structured medical markup to demonstrate expertise and source credibility.

Healthcare organizations leveraging AEO can uphold accuracy while enhancing patient education through conversational AI and symptom-based guidance. However, the challenge remains, balancing innovation with liability, ensuring AI-accessible content is both discoverable and defensible.

For example, a major hospital system launched a physician-reviewed FAQ hub with schema markup in April 2025, helping its content appear in AI Overviews through verified credentials.

Finance and Banking: E-E-A-T in Full Effect

In the finance sector, which is traditionally governed by E-E-A-T (Expertise, Authoritativeness, Trustworthiness), AEO further raises the bar. AI-generated responses summarize complex topics like refinancing and investing without the user visiting calculators or comparison tools.

As I observe, leading financial institutions are refining their content to be data-backed, author-attributed, and highly contextual to ensure expertise is maintained within AI summaries. Some banks are even developing AI assistants, integrating advisory experiences within their ecosystems, ensuring they remain part of the answer path rather than just a citation.

In September 2025, Bank of America launched its AskGPS generative AI assistant for business clients, transforming product guides and FAQs into a conversational tool providing instant, contextual answers.

Travel and Hospitality: Competing with the AI-Generated Itinerary

Travel planning has been revolutionized by generative AI, automating entire itineraries with hotels, restaurants, and routes. This reduces clicks for traditional travel publishers and booking sites, pushing brands to optimize local intent and implement schema for reviews and events to ensure accurate AI citation.

Travel brands are integrating with voice assistants or developing their own AI trip planners, taking back visibility by controlling the experience instead of just contributing data. This sector requires brands to master both storytelling and structured data for inclusion in AI-generated itineraries.

Agoda, for instance, launched an AI-powered Vacation Planner for Indian travelers in June 2025, delivering personalized itineraries using advanced AI technologies.

Education and EdTech: Creating Content That Resists Summarization

In education, AEO poses a clear risk: if AI can explain concepts instantly, learners might never visit educational sites. The solution seems to lie in crafting interactive, proprietary learning experiences that can’t simply be reduced to a single paragraph.

Advanced learning outcomes, conversational modules, and instructor-certified insights help content stand out in AI ecosystems. EdTech leaders are turning AEO into opportunity, integrating AI tutoring tools and partnerships that position their expertise within the generative loop rather than resisting it.

In April 2025, Cengage expanded its Student Assistant AI tool, integrating it across diverse courses to enable students to interact and apply concepts proactively.

Media and Publishing: Transitioning from Clicks to Citations

For media and publishing, AEO is somewhat existential. AI systems that summarize analyses challenge our traditional referral traffic and ad models based on page views. To combat this, publishers are pursuing content-licensing deals with AI providers and focusing on content styles that resist easy paraphrasing, like investigative reporting and original data.

In an answer-driven ecosystem, being cited as the source behind an AI-generated answer becomes crucial for visibility. Thought leadership, brand voice, and original data have become as important to visibility as backlinks once were.

For example, in May 2025, The New York Times signed a multi-year licensing deal with Amazon, allowing its content to be used in Amazon’s AI offerings, showcasing a shift toward citation-based visibility.

Cross-Industry Takeaways

As I analyze various sectors, three patterns consistently emerge:
- Integration Over Isolation: The most successful brands form partnerships or integrate technically with AI ecosystems instead of merely hoping to be cited by them.
- Signaling Trust Through Structure: Schema markup, transparent sourcing, and expert authorship help AI differentiate credible content.
- Conversational Clarity Triumphs: Using natural language that mirrors how users phrase questions improves both SEO and AEO performance.
Highly regulated sectors like finance and healthcare face tighter compliance constraints, while areas like retail and travel thrive on faster innovation cycles. Yet, the guiding principle is the same: clarity, credibility, and structure define success in an answer-driven world.

The Future: Where SEO Meets AEO

In my view, AEO builds on SEO’s foundation, expanding optimization into how content is processed by AI. With this expansion, search is shifting focus from relevance to confidence, rewarding content that AI can summarize accurately and cite confidently.

This transformation demands a strategic blend of technical precision and editorial insight. Schema, sourcing, readability, and tone now collaborate to determine if a brand appears in AI results or fades away.

The next evolution of search favors those of us who seamlessly blend strategy and engineering, crafting information optimized to resonate within AI systems.

Inspired by this post on Search Engine Land.
November 20, 2025
Unleash Google Ads Demand Gen for Maximum Impact
I understand that today’s consumers are constantly bombarded online.
I mean, I too find myself scrolling YouTube Shorts, tracking TikTok influencers, navigating Gmail promotions, and doubting if that viral Facebook video is real or AI-driven—all before I even have lunch!
The path from intent to conversion used to be straightforward, but now, in this attention-driven economy, making purchase decisions has become a complex affair.
Yet, many advertisers haven’t adapted to this reality. They still focus solely on search-based intent, missing out on entire audiences who don’t make it to the search bar.
Google’s Demand Gen campaigns are my secret weapon here, allowing me to escape this trap by fostering discovery and condensing the sales funnel.
Success isn’t complicated, but it requires mastering three elements: engaging creative content, strategic audience outreach, and rigorous testing methods.
The Demand Gen Opportunity
I see Demand Gen as the perfect blend of Google’s visual placements like YouTube, Gmail, and Discover matched with refined audience targeting and creative optimization.
Think of it as social advertising uniquely adapted for Google’s ecosystem. These campaigns tap into users’ browsing habits rather than their search activities, making them ideal for raising brand awareness.
Consumer behavior has undeniably shifted towards visual discovery, demanding more consumer touchpoints before sealing the deal.
YouTube, after all, is a largely visual platform and is now the second-most-used social media platform with a whopping 2.6 billion users worldwide.
In this new landscape, the purchase funnel is not only noisier but also more complex.
Unfortunately, many marketers still treat Demand Gen like search, expecting instant conversions—a mindset that misses the point.
To me, Demand Gen is about breaking consumption patterns, igniting interest, and nurturing intent over time.
Marketers who can shift their mindset will see their performance compound, growing stronger with each impression.
This is my go-to guide for nailing Demand Gen campaigns right from the start.
Element 1: Creative That Commands Attention
Thanks to modern tools, creating high-quality assets no longer requires expensive agencies.
And this matters—a lot. Visual content is a major conversion driver.
YouTube viewers are twice as likely to purchase something they’ve seen in a video and four times more likely to seek new products on the platform.
If advertisers don’t master visual storytelling, they’ll miss speaking the language of today’s consumers.
The Four-Part Framework for Demand Gen Creative
Crafting successful creative assets doesn’t have to be a guessing game. The best assets adhere to a four-part framework:
- Grab attention immediately: Capture interest within the first three seconds to stop that scroll.
- Build brand recognition: Maintain a consistent visual identity across all placements to fortify brand recall.
- Create emotional resonance: Make the viewer feel something meaningful.
- Provide clear direction: Guide viewers on what to do after watching.
Testing Creative Approaches
I believe testing is pivotal in refining creative content. Experiment with various types like educational, product-focused, and testimonial formats.
Educational content is great for awareness at the funnel’s top, while testimonials enhance consideration mid-funnel and product-focused creatives encourage conversion at its base.
Finding what resonates with your audience is key, and optimizing for each unique platform—what works on YouTube may not on Gmail—is crucial.
Dig deeper: Google’s Demand Gen upgrade: Key changes and success strategies
Element 2: An Audience Strategy That Matches Intent
I always think of audience strategy as an extension of creative development. Every audience is unique and should be addressed differently at various funnel stages.
Before spending a dime, I make sure to identify who my audience is and the actions I want them to take.
To do this, I start with the classic reporter’s questions:
- Who is your target audience?
- What are you trying to convey?
- Where do they find their information?
- Why would they care about your message?
Once audiences are defined, I align messages to their respective stages, aiming to guide them smoothly through the journey.

My goal is to nudge them to the next step without rushing them into a conversion.
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Audience Targeting Recommendations
After honing in on audience and creative message, it’s time to target them effectively within Demand Gen campaigns.
To start, I often create custom audiences, as they provide optimal control and granularity.
These can be built using keywords, URLs, or app usage, focusing on those most likely to take the desired action.
Happily, lookalike audiences have returned to Demand Gen campaigns, allowing targeting of prospects similar to existing customers.
Affinity and in-market audiences can also be targeted, enabling outreach to those with both broad interests and those in active consideration phases.
Campaign Structure Best Practices
When launching Demand Gen campaigns, I adhere to a few best practices:
- Start with separate campaigns for remarketing and prospecting as they have distinct goals and targeting options.
- Allow campaigns to run for 30 days at least before making changes.
- Consider dedicated campaigns for specific placements like Gmail, Discover, or YouTube.
- Test shorts-only campaigns, noting the format converts differently on mobile due to instantaneous decisions.
Consistent messaging and visuals across platforms is a must for building brand recall and reducing touchpoints before purchase.
Dig deeper: Google pushes Demand Gen deeper into performance marketing
Element 3: Testing and Optimization
Having set up my Demand Gen ads, it’s time to delve into testing and optimization.
Variables abound in these campaigns; hence, I meticulously test one element at a time for clarity and precision.
This endeavor isn’t about pinpointing one solution but focuses on persistent optimization. Trends change, and what works today may need tweaking in a few months.
Establishing Testing Parameters
I typically classify my testing into three main categories:
- Creative: Discover which creative elements resonate more. This could include content types, hooks, or video styles.
- Placement: Determine which approaches work where by testing on Gmail, Discover, and YouTube.
- Audience: Compare performances across differing audiences, such as custom vs. lookalike or remarketing vs. prospecting.
As I continue testing, performance trends inform future creative, messaging, and placement choices.
Consistently successful approaches allow scaling through budget increases for particular placements or audiences.
Set Realistic Time Horizons
Initial Demand Gen outcomes don’t reflect longer-term impact. Brand awareness takes time to build.
I advise allowing a 60 to 90-day period for campaigns to stabilize and gain traction.
Why Demand Gen Campaigns Fail
Failures in Demand Gen execution are rare. More often, it’s mismeasured and prematurely abandoned campaigns that falter.
This leads many away from Demand Gen entirely.
Here’s how I steer clear of prevalent missteps:
Unrealistic Expectations
Many start Demand Gen campaigns expecting similar returns to those of direct search campaigns.
Once those high expectations aren’t met, campaigns get abandoned.
The remedy is setting realistic expectations from the start.
Demand Gen builds brands and fills sales funnels, providing compound results if given the room to operate.
Measurement Myopia
This often accompanies unrealistic expectations. Relying solely on last-click attribution undervalues Demand Gen’s impact.
I suggest considering these alternatives:
- Use platform comparables: A Google Ads metric similar to social ads’ view-through method.
- Observation mode: Incorporate Demand Gen audiences into search campaigns to track if brand searches rise.
- Holistic brand metrics: Evaluate if brand growth is happening across channels, indicative of brand awareness.
If only last-click returns are considered, you undervalue your efforts.
Unrealistic Timelines
Don’t halt campaigns within 30 days if results disappoint, and avoid hasty changes.
I stay committed to a 60 to 90-day evaluation period while managing stakeholder expectations regarding timing.
Master Discovery to Win the Future
Attention is at its peak, and the progression of paid media leans towards visuals and discovery.
Brands sticking to search will face growth challenges.
Success in this terrain relies on three pillars:
- Engaging creative.
- Thoughtful audience targeting.
- Consistent testing.
Together, they foster performance and grow brand awareness.
The competitive edge will favor those mastering discovery today.
Large budgets aren’t essential for starting. Commitment to principles and patience with results suffice.
Demand Gen campaigns can embed your brand in your audience’s daily online life.

Inspired by this post on Search Engine Land.
November 20, 2025
Marketing’s Evolution: Embracing Engineering and AI

For a significant part of my marketing career, creativity, intuition, and an almost magical knack for connecting with audiences drove our success. We’d brainstorm campaign ideas, spend weeks executing them, and then eagerly analyze the outcomes.

I have Theodore Levitt’s “The Marketing Imagination” sitting on my bookshelf. It reminds me of how we’ve longed for unified insights about customers. Yet, our technology often offers a fragmented view, never capturing the customer’s full journey. The idea of one tool to give us a panoramic view remains elusive—a mythical nirvana.

Today, our landscape is changing rapidly. A new paradigm emerges—marketing driven by data and precision, resembling the structured work of engineers rather than the whimsical world of Mad Men. For me, this shift is thrilling as it blends art with systems and processes familiar to developers.

This transformation isn’t theoretical; it’s the heartbeat of digital evolution. The central idea of “The Digital Helix” presents marketing as a constant growth engine, energized by data and adapting to customer signals in real-time.

From Campaigns to Continuous Systems

In the past, marketing campaigns had distinct start and end points. We worked through long phases—briefing, creating, launching, measuring, and then repeating the cycle. But modern digital customers are restless, navigating multiple channels and expecting immediate brand interaction.

This demands a transition from episodic campaigns to perpetual systems—self-correcting, learning, and evolving without the need for interruption. In engineering, this is continuous integration; in marketing, it allows us to alter messaging, content, and offers dynamically, mid-course.

Here, marketing transforms into a form of system design. It requires ongoing engineering and a mindset of agility and continuous learning. We, as marketers, must blend creativity with practical engineering approaches to thrive.

Why the Shift is Happening Now

There are five core reasons why marketing is evolving into an engineering mindset.

1. Data as the Core Material

Much like engineering relies on inputs, marketing is driven by data. Every customer interaction, be it a click, search, or video pause, serves as input to our decision-making engine. We harness real-time customer data to guide strategies and automate responses, ensuring marketing decisions are precise and predictive.

Data is not a secondary consideration; it is the foundation of our marketing experience. It provides direction, allowing us to construct innovative ideas and guide our strategies effectively every day.

2. Modular, Reusable Assets

Developers often rely on libraries and frameworks. Similarly, marketing now focuses on creating modular content pieces that can be reused across platforms—enhancing efficiency and coherence.

Leading brands are designing “APIs for brand” to streamline the use of logos, imagery, and narratives, echoing engineering practices like version control and modularity, akin to Lego or Tesla’s methodologies.

3. Agile Becomes the Default

Agility is crucial. Long planning cycles can’t match the pace of changing customer preferences. We adopt sprint-based workflows, borrowing from Agile methodologies, to test, iterate, and optimize marketing strategies on-the-go.

4. Journeys as Living Architectures

The traditional customer funnel evolves into a dynamic experience architecture. We guide customers through personalized pathways, continually adjusting based on real-time behaviors—akin to managing traffic systems.

5. AI and Automation as the Toolchain

AI and automation streamline our marketing processes, much like toolchains in development. These technologies enhance efficiency and personalization, empowering us to focus on creative storytelling while managing complex data flows.

Engineers with Empathy — Marketing’s New Mandate

This integration of data and humanity enhances rather than replaces the marketer’s role. We rely on empathy and creativity within scalable systems to connect with audiences genuinely and effectively.

Tomorrow’s marketers need to blend engineering skills with storytelling capabilities—testing, refining, and optimizing narratives just like prototypes.

The transformation of marketing is not merely theoretical—it reflects a broader integration of engineering principles, creating a more responsive and anticipatory approach to customer engagement.

Inspired by this post on Search Engine Land.

November 20, 2025
Navigating AI’s Impact: From Diversity to Commercialization

I’ve always been fascinated by how Google Search has driven innovation by rewarding high-quality content with visibility and traffic. In the last article, I explored the risks of Google AI over-personalizing results and reinforcing filter bubbles.

This time, I’m examining a different concern. If Google’s new AI results lean toward uniformity, favoring big brands and consensus views, it might stifle creativity and innovation, while speeding up the web’s commodification.

Some might think this worry is naive, as the internet is largely commodified. Historically, however, small websites believed they had a shot at ranking and driving traffic. The internet has been perceived as a vast digital marketplace of ideas. But with AI models seeking consensus, appearing in AI search when you diverge from mainstream could become challenging.

AI systems & consensus

Consider the companies that lost all their traffic and rankings in the Helpful Content Updates. Small affiliate sites, which added valuable content through product reviews and comparisons, were mostly eliminated from organic rankings.

To gain traffic via Google, these companies now resort to buying ads or leveraging platforms like TikTok and Instagram. Most choose the latter, abandoning efforts to rank in Google entirely. Not all sites losing visibility lacked editorial quality—some offered high-value, human-focused content.

The core issue is that if these companies vanish, the diversity of information indexed by Google—and now utilized in AI search—becomes limited. Prodding smaller publishers to migrate to social platforms could further diminish web diversity. If independent creators face consistent exclusion from rankings, their drive to share unique perspectives might dwindle.

Social media could serve as a counterbalance in Google’s strategy, which is somewhat promising. Google recently decided to rank YouTube Shorts within Discover, and has a ‘Short Video’ tab on many results. It’s also showing increased interest in posts from Reddit and LinkedIn. Maybe, in Google’s perspective, unique opinions should emerge from independent creators, while mainstream views stem from larger brands. Only time will reveal the truth.

The impact of advertising

Ads in AI Overviews are already appearing, giving us a glimpse into Google’s monetization plans for AI. Meanwhile, we can analyze how Google has altered ads and ecommerce to accommodate AI.

The move to Performance Max (PMAX) bidding in Google Ads has perplexed many advertisers. Its opaque system limits control and data visibility, potentially making advertisers complacent as Google assures better returns with reduced effort. However, what happens if advertisers wish to understand their audience deeply?

When Google manages PMAX bidding without disclosing what works, it learns about your customers using your resources without sharing insights. This deprives you of applying these learnings across other advertising channels. In some sectors, Google might learn enough to bypass you with customers, similar to Google Travel integrating Flights, Hotels, and more. Truly, AI is a double-edged sword.

This tactic could extend to Google Merchant Center. By pooling retailer data, Google refines PMAX campaigns, delivering precise ads at ideal times, boosting conversion, and using AI tools like Circle to Search and Google Lens.

Google’s aggressiveness in promoting its ad options strikes me distinctly. I encountered an ad via a full-screen takeover on an organic SERP—a rarity for Google whose full-screen takeovers usually signal terms changes or opt-ins.

Recent Terms and Conditions underline Google’s user data sharing across Alphabet properties to personalize advertising. This sharing combines with modeled data to fine-tune targeting on both micro and macro levels.

It seems Google will continue this path unless opposed. Google’s vast market share limits alternatives for searchers, publishers, and advertisers, offering them few escape options. This enables Google to prioritize monetized AI results over organic traffic, though adjusted ad labeling might blur distinctions further.

The updated Terms and Conditions, shown to EU users, emphasize Google’s data use across platforms. Including Google Ad services in the update illustrates their reach through our ad data, indicating how advertisers fund Google’s platform enhancements, despite limited data access.

So what can we do to protect the health of the internet?

I’m captivated by AI’s potential, often diving in with reckless excitement. I confess to leaning towards “AI doomism,” believing negative scenarios are more probable due to our tendencies and lack of oversight.

Once technology manifests, it cannot be undone, particularly online, where it is ever rememberable. Human memory is flawed, but the internet remembers, so the AI genie is now out of the bottle.

So, how do we prepare for AI’s future and craft frameworks, guidelines, and rules preserving internet health while fostering AI innovation? How do we allow diverse content discoveries without stifling AI progress?

I believe in collaboration between digital marketing and publishing industries, which are already uniting to protect copyright interests. Operating separately won’t generate internet-protecting measures on either side.

Until solid AI regulations are created and enforced, setting collective, collaborative internet protection standards surpasses individual interests. Like unionized workers defend against exploitation by powerful companies, we need collective bargaining and protection.

Some EU movements aim for broader digital and AI regulation, but digital marketing and SEO might benefit from self-developed, community-enforced standards, moving beyond “black hat” or “white hat” labels, especially for AI. It’s a dialogue worth pursuing.

Inspired by this post on Search Engine Land.

November 19, 2025
Unlocking Automation: How OpenAI’s New Tools Revolutionize AI Agents

I always knew that automation was transforming PPC, but recently, I’ve seen how OpenAI’s groundbreaking tools are taking this transformation to new heights.

Automation has shaped PPC for decades, with the landscape constantly evolving. My journey started with developing the first AdWords Editor and writing about automation layering. Now, we’re seeing a new era unfold.

The way AI processes information is shifting. This change isn’t driven by traditional platforms like Google, but by pioneers like OpenAI.

AI was mostly known for handling tasks related to human language—copywriting, summarizing, reporting. But now, LLMs are delving into computer language, creating the software that boosts our efficiency.

At OpenAI’s DevDay in San Francisco, I witnessed the introduction of AgentKit, a tool that brings AI into action-handling territory. This marks a shift where PPC optimization techniques can transcend campaigns, integrating into comprehensive workflows.

Imagine if AI could manage your routine tasks, from adding client reports to your dashboard before you even access your emails, to scheduling meetings, drafting agendas, and ensuring adherence to brand guidelines while drafting ad copy.

These advancements are within reach, without the need for technical expertise.

Mainly, if you can break down tasks into actionable steps, you can set up an agent to execute them.

Dig deeper: 4 ways to connect your ads data to generative AI for smarter PPC

An AI agent is not just an algorithm; it’s a versatile aide equipped to deduce necessary actions and execute them through connected tools.

Unlike traditional, rigid software with deterministic steps, agents offer flexibility and adapt to scenarios without requiring exhaustive pre-programming.

This evolution in automated assistance is something I had glimpsed in early iterations—now, a more sophisticated agent can execute real-world tasks formulated in the virtual sandbox of GPT innovations.

Dig deeper: AI agents in PPC: What to know and build today

The appeal of OpenAI’s AgentKit lies in its ability to transform lengthy coding sessions into quick, non-technical builds, akin to “Zapier for AI.”

Unlike traditional software, AgentKit leverages AI’s reasoning instead of fixed rules, making it an innovative tool for marketers like me aiming to automate tasks efficiently.

AgentKit provides a visual workflow built around familiar tools like Gmail and Dropbox, ensuring seamless integrations and ease of use.

Dig deeper: How to get smarter with AI in PPC

Inspired by this post on Search Engine Land.

November 19, 2025
Combatting Affiliate Fraud: Secure Your 2026 Growth

Affiliate marketing is a major driver of revenue, but it also hides significant losses. I’ve seen firsthand how brand bidding, ad hijacking, coupon abuse, and subtler forms of affiliate fraud can erode ROI and distort attribution figures.

The critical issue isn’t whether these challenges exist, but rather understanding how much they’re impacting our business. In this article, I delve into the most prevalent types of affiliate marketing fraud. I’ll also share insights on how modern tools like Bluepear offer advanced affiliate fraud detection strategies that protect our growth, reputation, and budget.

Not all affiliate programs offer the same benefits, nor do they come with the same risks. Particularly in SaaS, where affiliate commissions can be between 20% to 70%, these programs become highly enticing targets for fraudsters.

Fraudsters exploit trust gaps, often bidding on brand terms or using shady tactics like ad hijacking and coupon code misuse to siphon off profits. A staggering 63% of affiliate marketers identify these threats as their primary concern.

Unfortunately, much of this fraud operates under the radar. Affiliates execute campaigns and manage landing pages without real-time monitoring, which means you may end up paying commissions on existing traffic or, worse, funding brand impostors.

Let’s dig deeper into common fraud tactics and how to recognize and counteract them early on. Equipped with strategies, you can shield your program from such threats.

I focus on four primary fraud tactics: brand bidding, ad hijacking, coupon abuse, and non-compliant content. Each poses unique challenges but can be counteracted with the right preventative measures.

Brand bidding occurs when someone purchases ads using your brand name. This diverts potential customers who are actively searching for your product, resulting in needless commission payments. It’s crucial to maintain a detailed list of brand-related keywords in your affiliate terms and monitor for sudden spikes in performance metrics.

Ad hijacking mimics your paid search ads, lowering your campaign visibility. Regular checks and test searches can expose these fraudulent activities.

Coupon abuse is trickier; it manipulates traffic from affiliates who rank high for brand-related coupon searches. Ensuring coupon activity is pre-approved and regularly monitoring search results helps mitigate this fraud.

Non-compliant content can easily escape detection. Cloaking tactics mean users see different content than compliance teams. Establish strong creative guidelines and treat content audits as an ongoing activity.

Defending against affiliate fraud requires continuous vigilance, clear program rules, and leveraging technology. Platforms like Bluepear use automated systems to highlight and eliminate fraud, giving you back control.

For 2026, my focus is on building stronger relationships with affiliates, ensuring transparency, and promoting a culture that prioritizes honesty and clear communications.

Ultimately, affiliate fraud is a continually evolving threat. By understanding these tactics, setting clear expectations, and utilizing advanced tools, we can protect our interests and secure sustainable growth.

Inspired by this post on Search Engine Land.

November 19, 2025
3 AI Research Modes Revolutionizing Search: Brand’s Winning Edge
With the rise of AI-driven discovery, I’ve realized that brand strength is crucial. Let me share what it takes to be the top pick across explicit, implicit, and ambient research modes.
It’s clear to me now how essential an AI resume has become as a C-suite-level asset, reflecting the core of our digital strategies.
To harness its full potential, I first need to grasp where AI implements it throughout the user journey.
How AI has rewritten the user journey
Historically, my strategies were shaped by the inbound methodology.
I crafted content around a user-driven journey through stages of awareness, consideration, and decision, with traditional SEO fueling these moments.
Today, that journey has been fundamentally reshaped.
AI assistive engines, like conversational systems such as Gemini, ChatGPT, and Perplexity, are compressing the funnel.
These systems move users from discovery to decision in enclosed environments.
I call this the BigTech walled garden AI conversational acquisition funnel.
For marketers like me, this shift feels like a loss of control.
I no longer own the click, the landing page, or the carefully designed funnel.
However, from the consumer’s viewpoint, the change is a welcome one.
People desire a straightforward, trusted answer.
This isn’t contradictory. It’s today’s reality.
My role is to align with this model by proving to AI that my brand is the most credible source.
This means updating our ultimate goal.
For commercial queries, winning is less about visibility.
It’s about achieving that perfect click – when an AI acts as a trusted advisor and selects your brand as the best solution.
To reach this point, I need to expand my focus from explicit branded searches to the three modes of research AI currently uses:
- Explicit.
- Implicit.
- Ambient.
Together, these define the new strategic landscape and lead to one undeniable truth.
In an AI-driven ecosystem, the brand reigns supreme.
3 types of research redefining what search is
These three behaviors demonstrate how users now discover, evaluate, and select brands through AI.
Explicit research (brand): The final perfect click
Explicit research involves any query that includes a specific brand name, such as:
- Searches directly for your name.
- Queries like “Brand name reviews.”
- Comparisons like “Brand vs. competitor.”
These moments are high-stakes when potential clients, partners, or investors are actively researching a brand.
This stage represents the decision point in the funnel, where people seek detailed information or conduct an AI-driven due diligence before committing.
What they discover here is essentially your digital business card.
Having a robust AI assistive engine optimization (AIEO) strategy locks down these bottom-of-funnel opportunities first.
It’s crucial for me to develop an AI resume – a brand SERP equivalent – that is compelling, accurate, and persuasive so that those actively searching can convert.
Branded terms present the most accessible and critical conversion points in the new conversational funnel and form the basis of AIEO.
Implicit research (industry/topic/comparison): Being top of algorithmic mind
Implicit research involves topical queries without a brand name.
These are the comparison or problem-focused questions at the top and middle of the funnel.
To succeed here, I ensure my brand is always at the top of algorithmic mind, where AI instinctively selects my brand as the most credible, relevant, and authoritative for a user’s question.
- Consideration: If someone asks, “Who are the best personal injury law firms in Los Angeles?”, the AI formulates a shortlist, and it’s pivotal to make sure my brand is on it.
- Awareness: If someone inquires, “What are personal injury legal options after a car accident?”, my inclusion depends on whether the AI trusts and recognizes my brand already.
Implicit research transcends keywords. It’s focused on being algorithmically understood, with a demonstrated authority on various topics.
Here’s how it typically works:
- The algorithms grasp my identity.
- They effectively apply credibility signals, incorporating expanded Google frameworks like E-E-A-T and N-E-E-A-T-T.
- I’ve provided the necessary content to showcase topic authority.
If I meet these criteria, I can become a top choice for user-AI interactions at the onset and middle of the funnel, where implicit research thrives.
Ambient research (push by software): Where the algorithms advocate for you
Ambient research is all about AI proactively suggesting my brand to users who aren’t actively seeking information.
This forms a major shift, as it goes beyond the funnel – it is pre-awareness.
Examples include:
- AI suggesting my name in Google Sheets when someone evaluates ROI.
- Displaying my profile in Gmail or Outlook as a recommended consultant.
- Meeting summaries in Google Meet or Teams highlighting my brand as the solution to a critical challenge.
Here, users aren’t seeking information.
The AI confidently proposes a solution, positioning itself as an advocate for my brand.
This is the ultimate goal, indicating that my brand holds a dominant status as the top choice within a niche.
Achieving this level of trust comes from creating a consistent digital presence that teaches AI my brand’s reliability.
Thanks to Seth Godin’s concept of “permission marketing,” AI has been conditioned to grant permission for my brand’s suggestions.
While it might seem like a rare occurrence in 2025, ambient research is poised to grow, making it a lucrative opportunity for those who prepare now.
The walls are rising in the AI walled garden 2.0 – a new, more restrictive AI ecosystem.
The next evolution will feature AI assistive agents.
These agents won’t merely recommend solutions. They’ll execute them.
When an agent books flights, orders products, or hires consultants on behalf of users, there’s no room for second-place contenders.
This creates a zero-sum environment in AI.
If my brand isn’t the trusted default, it’s not considered an option.
Rethink your funnel: Brand is the unifying strategy
Although the traditional funnel of awareness, consideration, and decision remains, AI has irrevocably altered the journey.
Focusing solely on explicit research is a losing strategy.
While it secures the funnel’s bottom, it leaves the middle and top open for competitors to emerge and be recommended.
Expanding to implicit research is an improvement, but it remains reactive, waiting for a selection from a list.
This approach will fail as ambient research expands, as the AI will be making the first introduction.
This environment necessitates a brand-first strategy.
Brand is constant across all three research modes. AI:
- Recognizes you in explicit research due to your brand’s accuracy.
- Includes you in implicit research because it trusts your topical credibility.
- Advocates for you in ambient research since it has learned your brand is an optimal default solution.
By focusing on understandability, credibility, and deliverability, I’m not just optimizing for one type of search.
I’m systematically teaching AI to trust my brand at every possible interaction.
The brands that excel in this education will be those AI recommends across all three research modes.
It’s time to adapt or risk exclusion from the conversation.
Your final step: The strategic roadmap
Now, I understand the what – the AI resume – and the where – the three research modes.
Let’s address the how: a comprehensive strategic roadmap for mastering the algorithmic trinity using a multi-speed approach that systematically enhances my brand’s authority.

Inspired by this post on Search Engine Land.
November 18, 2025
How Positionless Marketing Can Solve AI Adoption Challenges

Research from Forrester and insights from Blain’s Farm & Fleet have shown me that the real obstacle in AI adoption isn’t the technology itself; it’s how we approach marketing tasks.

Imagine a chocolate company with a cherished, decades-old recipe. They ask an AI tool to identify cost-cutting measures. After several ingredient eliminations and promising margins, sales plummet. Finally, someone tastes the product: “This isn’t even chocolate anymore.”

Aly Blawat from Blain’s Farm & Fleet shared this during a MarTech webinar to highlight why 82% of marketing teams struggle with AI: automation devoid of human insight often exacerbates failure.

According to a Forrester study for Optimove, just 18% of marketers feel at the vanguard of AI adoption, despite 80% anticipating enhanced targeting through AI. Only a quarter have active AI use cases in production.

As Forrester’s Rusty Warner explains, many await software with built-in safeguards before fully embracing AI. Currently, marketing runs like an assembly line, ill-suited for AI’s potential to overhaul workflows.

Positionless Marketing could be the answer. Here, marketers manage everything from data to campaign launches independently, allowing swift action and reserved teamwork for larger initiatives.

Blain’s Farm & Fleet trialed AI for their brand’s cohesive tone across platforms, utilizing Jasper, a protected system. Warner suggests starting small to build confidence, ensuring data integrity for effective AI outcomes.

Successful marketing teams centralize critical data definitions, providing essential signals directly to marketers. Adoption lags not due to the technology, but because organizations aren’t structured to exploit it effectively.

Balancing automation with authentic customer engagement means deploying AI where it can be most beneficial while maintaining a genuine brand experience. At Blain’s Farm & Fleet, human oversight ensures alignment with customer expectations.

The future points toward AI in execution, allowing unique, personalized customer journeys. This shift demands organizations to enhance customer experience expertise across all channels.

For effective AI integration, restructuring marketing workflows and focusing on measurable outcomes are key. The vision includes less manual effort, fewer illustrative meetings, and more tangible customer impact.

By 2026, AI adoption is expected to soar with more vendors providing embedded, coherent AI solutions. Brands like Blain’s Farm & Fleet illustrate the transformation—the right AI application fosters growth, far beyond superficial changes.

Ultimately, AI can’t repair broken systems but amplifies existing conditions. Successful teams must adapt modern workflows and mindset shifts to harness AI’s full potential.

Inspired by this post on Search Engine Land.

November 18, 2025