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Why click-based attribution shouldn’t anchor executive dashboards

Why click-based attribution shouldn’t anchor executive dashboards

As marketing channels and touchpoints multiply rapidly, the way success is measured significantly impacts long-term growth and executive perception. 

Click-based attribution – across models like last-click, first-click, linear, and time-decay – remains the default. 

But as a standalone measurement strategy, it’s showing its age. 

Click metrics now carry disproportionate weight in executive dashboards, and that reliance introduces real limitations.

Click-based models can still reveal valuable insights into digital engagement. 

However, when the C-suite bases major budget and strategy decisions solely on clicks, they risk overlooking critical aspects of the customer journey – often the very pieces that matter most.

This article examines:

  • What click-based attribution actually captures.
  • Where click-based measurement breaks down in a multi-channel, multi-device, privacy-first world.
  • The business risks of over-indexing on click metrics.
  • Measurement approaches that better align marketing with real business outcomes.
  • How marketing leaders can guide executives toward more holistic, outcome-oriented frameworks.

The goal isn’t to demonize clicks – they still belong in the toolbox. But they should provide context, not serve as the foundation.

What does click-based attribution actually measure?

Click-based attribution tracks ad clicks and assigns conversion credit to the marketing touchpoints that drove them. 

Models like first-click, last-click, linear, time-decay, and data-driven approaches differ only in how they split that credit across the user journey.

Digital ad platforms and many analytics tools default to click-based models because clicks are relatively easy to capture, understand, and report. 

They’re deterministic, clean, and simple to interpret at a glance.

That cleanliness, however, can be misleading. 

Click-based attribution depends entirely on a user interacting with tracking links or tags. 

If a user doesn’t click, or clicks but converts later or elsewhere, the touchpoint may be missed or misattributed.

This approach can work in a simple, linear funnel. 

But as customer journeys become multi-device, multi-channel, and increasingly offline, clicks lose context quickly.

Dig deeper: The end of easy PPC attribution – and what to do next

The problems with solely relying on click-based attribution

Clicks don’t represent real customer behavior

Today’s buyers rarely follow the neat, linear paths that click-based models assume. 

Instead, they move across devices, channels, and even offline touchpoints.

Think social media, LLMs like ChatGPT, and brand exposure from video, influencers, or website content. 

Many of these interactions never generate a tracked click, yet they play a critical role in shaping perception, intent, and eventual conversion.

For example, a buyer may watch a brand’s video on LinkedIn during their morning commute. 

Later, they read a third-party review and skim a few case studies on the brand’s website.

Days later, they type the brand name directly into Google and convert. 

In a click-based model, only the final branded search click receives credit. 

The video, the review, and the content that built trust remain invisible.

These aren’t minor attribution blind spots – they represent a canyon. 

Click-based measurement skews too much toward lower-funnel performance

Click-based models place the most weight on the final click. 

As a result, they often over-index lower-funnel activity from channels like retargeting ads or branded search. 

These channels convert more frequently, but they do not create demand on their own.

For C-level decision-makers, this creates a dangerous bias. 

Dashboards light up for retargeting campaigns and branded search, so budgets flow there.

Mid- and upper-funnel investments – brand building, awareness, content, and influencers – are reduced or cut. 

Over time, the brand’s long-term growth engine is choked in favor of short-term, easily quantifiable wins.

Dig deeper: Marketing attribution models: The pros and cons

Click-based models undervalue creative, messaging, and brand

Not all marketing impact shows up as clicks. 

A video ad or thought-leadership piece may plant a seed without prompting an immediate click, yet the message can linger. 

It may lead to later brand searches or site visits, outcomes that are difficult to capture through click-based measurement.

As a result, brand power, creative messaging, and top-of-funnel reach are underrepresented in click-based models. 

Over time, organizations that optimize solely around click-based attribution may unintentionally deprioritize creativity, brand-building, and long-term equity.

Click-based attribution breaks down in a privacy-first world

We’re moving toward a future where third-party cookies are diminished or gone, privacy rules continue to tighten, and tracking becomes less precise. 

Under these conditions, click tracking grows more difficult, less reliable, and increasingly misaligned.

Without stable identifiers, many of the assumptions behind click-based models – “this click belongs to that user” or “this click led to that conversion” – begin to unravel. 

Attribution becomes a house of cards built on data that may not hold up as privacy and tracking norms continue to shift.

The business risks of over-relying on click-based attribution

Misallocation of budgets

When click-based reporting dominates, budgets tend to flow toward what looks good – the activities that drive visible revenue and deliver clean, direct ROI. 

That often comes at the expense of demand generation efforts that support long-term growth, such as brand campaigns, content, awareness, and other upper-funnel media.

This approach may “work” for a few months or even years. 

Over time, however, the pipeline dries up. 

Awareness declines, organic reach stagnates, and the brand loses its ability to attract new audiences at scale.

Erosion of brand over time

Marketing shifts into a zero-sum exercise focused on extracting conversions from existing demand rather than expanding it. 

Without sustained investment in brand equity and demand generation, competitiveness, brand loyalty, and lifetime value (LTV) suffer.

In essence, optimizing for short-term ROAS puts long-term brand health at risk.

Misaligned incentives across teams

When KPIs are click-based:

  • Media teams optimize for clicks.
  • Creative teams optimize for click-worthy content.
  • Analytics teams optimize for attribution that ties cleanly to conversions. 

The result is marketing silos working toward different objectives.

  • Media buys may undermine creative performance. 
  • Creative teams may chase cheap clicks. 
  • Analytics may mask cannibalization rather than reveal incrementality. 

Fragmentation increases.

Blind trust in platform-reported metrics

Ad platforms and tracking tools report click-based conversions, but many of those conversions are self-crediting, particularly within paid media platforms. 

When you rely heavily on these numbers without scrutiny or connection to the broader user journey, you risk making high-stakes decisions based on biased data.

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What to use instead of click-based attribution

If click-based attribution is flawed, how should performance be evaluated? 

The short answer is a combination of approaches grounded in real business outcomes.

Marketing mix modeling (MMM) for channel-level contribution

At a higher level – especially when multiple channels are involved, including online, offline, paid media, organic media, and PR – MMM helps quantify channel-level contribution to sales, revenue, or other business outcomes. 

It looks at broad correlations over time using aggregated data rather than user-level clicks.

MMM, supported by machine learning, improved data resolution, and more frequent refresh cycles, has become more accessible and actionable. 

It isn’t a replacement for click- or site-based data, but a powerful complement. 

Dig deeper: MTA vs. MMM: Which marketing attribution model is right for you?

Multi-touch attribution (MTA), used thoughtfully 

User-level path analysis still has a place when privacy and tracking allow. 

Multi-touch models that consider multiple touchpoints can provide richer insight, but they work best as one input among many rather than a single source of truth. 

They offer path visibility, but without incrementality testing or support from MMM, they still risk over-crediting and bias.

Customer lifecycle metrics: LTV and CAC payback, retention, cohort analysis

Marketing value isn’t confined to a single sale or conversion.

LTV, retention, and long-term value creation matter just as much. 

Tying spend to CAC payback, churn, loyalty, and retention creates a measurement framework aligned with long-term business goals.

Incrementality testing as a standard practice

Incrementality testing measures what marketing actually adds by identifying net-new conversions, revenue, lift, or awareness. 

It separates what would have happened anyway from what your efforts truly drove.

This approach isn’t as clean as click tracking and requires more planning and discipline, but it delivers causality. 

It allows you to say, with confidence, “This spend generated X% incremental lift.”

Dig deeper: Why incrementality is the only metric that proves marketing’s real impact

Attention metrics, quality signals, and creative impact

Not all impact is transactional. 

Upper-funnel signals such as viewability, time-in-view, attention scores, and engagement matter. 

Creative resonance, brand recall, and impact often influence later behavior that never appears as a click.

Looking beyond clicks to metrics like creative recall, brand lift, share of voice, sentiment, and qualitative feedback helps anchor measurement to real brand value and audience expectations.

Building a modern measurement framework

A modern measurement framework isn’t built around one model or metric. 

It brings together complementary methods to create a clearer, more balanced view of performance.

Take a portfolio approach

The most effective measurement frameworks take a portfolio approach. 

MMM, incrementality, multi-touch attribution (when possible), attention metrics, and customer lifecycle metrics work together to triangulate performance from multiple perspectives.

This diversity reduces bias and balances short-term performance with long-term brand health.

It also makes it possible for the C-suite to see more than conversions alone – including impact, growth potential, and sustainable value.

KPIs that reflect real business impact

Executives care about revenue, margin, and growth. Not just clicks. 

Reframe KPIs around the key metrics that matter, such as:

  • Revenue.
  • Cost per acquisition.
  • Customer lifetime value.
  • Retention.
  • Brand lift.
  • Market share.
  • Brand sentiment.

Package those into dashboards that tell a story: 

  • “Here’s what we did, here’s what grew, here’s what we learned, here’s where we go next.”

Build executive dashboards for outcomes, not vanity metrics

When dashboards lead with vanity metrics like click volume, CTR, or raw conversion rate, insight is limited. Lead instead with business outcomes.

Build narrative-driven dashboards that connect investment to results, learning, and action.

Lean toward data storytelling instead of data reporting. 

That story resonates with executives. It links marketing to business value, not just to marketing activity.

Leverage AI, predictive modeling, and forecasting strategically 

Modern analytics tools – including AI and predictive forecasting – can help:

  • Estimate demand.
  • Forecast impact.
  • Model how different investments may play out over time. 

Use them to simulate scenarios, test assumptions, and support business cases.

These tools aren’t silver bullets. They work best as accelerators for sound strategic thinking. 

Moving away from click-based thinking

Changing how performance is measured doesn’t happen automatically.

It requires clear framing, evidence, and a deliberate transition rather than an abrupt overhaul.

Understand common objections and address them clearly

Often, executives cling to click-based metrics because they’re easy to understand (“one user clicked, we got a sale”) and seemingly real-time. 

They want fast feedback and accountability. Demand creation efforts often feel abstract and hard to justify.

Be prepared to address that directly:

  • “Clicks are easy to understand.”
    • Yes. But they paint an incomplete picture. Show them what they miss.
  • “We need real-time metrics to manage marketing spend.”
    • That’s valid. But real-time doesn’t always equal real value. Complement with more holistic time-based analyses based on the timing of your sales cycle, incremental lift tests, and periodic MMM to ground real-time decisions.
  • “Brand/awareness spend is hard to justify.”
    • I hear you. That’s why you start small. Run test campaigns, measure impact via lift studies, attribution-aware conversion, and lifecycle metrics. Show proof-of-concept.

Implement a gradual shift, don’t overhaul overnight

Click-based attribution doesn’t need to be discarded overnight. Instead:

  • Introduce incrementality testing for a small portion of spend to show what budget really contributes.
  • Once incrementality proves meaningful lift, allocate more budget toward long-term demand creation efforts.
  • Run or commission MMM annually (or semi-annually) to quantify channel contribution holistically.
  • Adjust executive dashboards to reflect new KPIs, such as revenue, CAC payback, brand lift, and LTV, and reduce emphasis on mere clicks or last-click conversions.

Over time, incentives begin to shift. Media moves beyond clicks, creative focuses on quality and resonance, and analytics emphasizes causality and long-term value.

Educate the executive team

Executives rarely object to logic – they object to noise. 

Frame your case with clarity and use data. 

Show examples, run tests, show incremental lift, and then build dashboards that tell a clear story.

Once you prove that a dollar invested in brand or top-of-funnel media delivers compounding value over time, leadership hopefully becomes less attracted to short-term click metrics. 

They begin to appreciate marketing as an investment, not a cost center.

Clicks are part of the story, not the whole story

Click-based attribution has served marketing teams for years. It offered a clean way to connect conversions to touchpoints. 

But the landscape has changed. 

  • User journeys are longer and messier. 
  • Privacy constraints are tighter. 
  • Long-term brand value now matters as much as short-term conversions.

For C-level teams, judging performance by clicks alone is like judging a company’s health by heart rate alone. It’s useful, but incomplete.

Modern marketing requires a richer view – one that blends data, causality, business outcomes, and long-term brand building.

As marketing leaders, our job isn’t to chase the next click. 

It’s to build brands that last, drive sustained growth, and help leadership see marketing not as a cost, but as a strategic investment.

How to build an effective content strategy for 2026

How to build an effective content strategy for 2026

Every week, new data highlights both the overlap and the divergence between effective organic search techniques across traditional SEO (Google SERPs) and GEO (ChatGPT, AI Overviews, Perplexity, etc.). 

It’s a lot to absorb. One week, headlines say traditional SEO tactics work fine for ChatGPT.

The next, you’ll see reports that one platform is elevating Reddit while another is dialing it back.

Given how quickly this landscape shifts, I want to break down the approach, process, and resources my team is using to tackle content in 2026. 

This goes far beyond a content calendar. 

It’s about combining audience understanding, the interplay of organic platforms, and your brand’s perspective to build a content system that delivers real value.

The right approach for valuable content

The emphasis on quality and value in content is good for marketers.

The tenets of E-E-A-T remain central to our approach because they apply to AI search discoverability as much as to traditional SEO. 

Producing strong content still depends on a rich understanding of your audience, good fundamental structures, and solid delivery methods – skills that always matter.

Start with your audience. 

  • Who are they? 
  • What do they need? 
  • What content will help them get there? 

Approach content like any other product or service: 

  • Identify a need and address it.
  • Understand the emotions involved.
  • Show your credentials – including third-party brand mentions, which are a leading factor in AI search visibility. 

Approach content like any other product or service:

  • Find or understand a need and address it.
  • Know the emotions (i.e., fear, uncertainty, urgency) in play.
  • Show your credentials (in the form of authority, expressed in part by third-party brand mentions that are one of the leading factors of AI search visibility traction).

That said, content that has performed well in Google may not work as effectively for LLM search. 

Instead of writing primarily for blue-link SERPs, we now focus on creating content that stands on its own as an authoritative, structured data source, with trust and originality as ranking signals. 

That means prioritizing clarity, factual depth, and a consistent brand perspective that AI models can reliably quote.

In an age of mass AI content, original insights, data, and human perspective are key differentiators, so content systems should include a step for “original proof” – data, interviews, or commentary that make the material uniquely trustworthy.

We’re also thinking more about how content gets used in AI experiences, not just how it’s found. 

Summaries, bullet points, and explainers that answer layered intent are increasingly valuable. 

Incorporating schema, structured data, and a consistent brand voice improves how AI systems read and represent your content. 

In short, the goal is to optimize for retrievability and credibility, not just ranking.

Get the newsletter search marketers rely on.


Building a process to create valuable content

The content strategy path I like to prescribe is as follows:

  • Problem aware: Empathize with your audience by articulating their problem in a clear, differentiated way.
  • Solution aware: Present your audience with objective, detailed, valuable options for solutions to their problem.
  • Brand aware: Develop your brand’s association as a trusted solution provider.
  • Product aware: Position your specific product or service as the ideal solution for the reader’s problem.

Once your research is conducted, you’ll have what you need to craft content and deploy it in multiple ways. 

The linear workflow that persisted for years in traditional SEO, however, must evolve into a modular content engine – one where a single research output fuels multiple media types (articles, YouTube scripts, short-form video, LinkedIn posts, etc.), with platform-native variations all aligned to a central narrative theme.

Resources to use in content development

A few years ago, I would have started with well-known, well-established tools like Ahrefs and Semrush. 

While those remain useful for benchmarking, they no longer represent how people discover or consume information as AI search transforms user behavior in real time. 

AI search abstracts away keywords – users are asking multi-intent questions, and LLMs are generating synthesized answers. 

SEO analysis is now, rather than the main starting point, one piece of the research pie. 

It’s still important, but search optimization is now embedded throughout the content process.

The tools below have been important in the past, and my team still leans on them as part of a more holistic approach to content planning.

Qualitative interviews

Surveys are useful but can be expensive when you’re trying to reach audiences outside your CRM. 

You can still get strong insights by engaging subject matter experts who share the same professional experiences, challenges, and responsibilities as your target audience. 

Slack communities, live or virtual meet-ups, and memberships in organizations like the AMA or ANA can all offer on-the-ground perspectives that support your content mapping.

Audience analysis from AI systems 

It’s critical to include intent analysis from AI tools and conversational search data. 

Understanding how users phrase questions to AI systems can inform structure and tone.

Social media

Not all social media posts are created equal, but understanding your audience includes knowing where your audience likes to engage: X, Reddit, YouTube, TikTok, etc. (Not to mention that Reddit citations show up prominently in ChatGPT results.)

Utilize these platforms to gather real-time information on what your audience is discussing and to increase brand mentions, which will send strong signals to ChatGPT and similar tools.

Competitor analysis

Shift from tracking keyword overlap to evaluating content depth, originality, and entity coverage – where your brand’s expertise can fill gaps or improve on generic AI-summarized answers.

Adjust the KPIs to assess the impact of your content

For many years, SEO marketers focused on impressions and clicks, although more advanced practitioners also incorporated down-funnel metrics, such as leads, conversions, pipeline impact, and revenue. 

Today, SEOs must expand their KPIs to include brand mentions in:

  • AI summaries.
  • Content-assisted conversions.
  • Cross-channel engagement depth. 

These are the new indicators of helpfulness and value.

Resist the urge to rest on your laurels

We’ve seen strong successes with AI search visibility that complement our traditional SEO results, but our understanding of best practices continues to evolve with each new round of aggregated data on AI search results and shifting user behavior.

In short, keep a parallel track of what has worked recently and where the trends are heading, since ChatGPT and its competitors are changing user behavior in real time – and with it, the shape of organic discovery across platforms.

Uncontested ads are quietly draining your holiday budget. Here’s how to fight back. by BrandPilot.ai

This season, Google Search and Shopping Ads are expected to surge past $70 billion in holiday spending. But there’s a hidden flaw in the auction system — one most advertisers don’t realize is costing them money even when competitors aren’t in the game.

BrandPilot calls this the Uncontested Google Ads Problem, and it’s becoming one of the most overlooked sources of wasted ad spend in peak retail season.

During SMX Next, John Beresford, Chief Revenue Officer at BrandPilot, unpacked how a little-known behavioral quirk in Google’s auction logic can cause advertisers to overspend on their own brand terms, their Shopping placements, and even their category keywords — simply because Google doesn’t automatically reduce your CPC when competition disappears.

Instead of paying less when you’re the only bidder, you may be paying the same high rate you’d pay when rivals are active… without realizing it.

It’s a phenomenon happening thousands of times a day across major brands, and many marketers never notice it’s occurring.

In his session, Beresford discussed:

  • Why “competition gaps” happen far more often than advertisers think.
  • How uncontested moments distort CPCs, even on brand keywords.
  • What real-time auction visibility makes possible — and why AI is changing the game.

He also shared examples of how advertisers are reclaiming wasted spend and reinvesting it into growth – without sacrificing impression share, traffic, or revenue.

Watch BrandPilot’s session now (for free, no registration required) to learn how to:

  • Pinpoint why your CPCs are being artificially inflated when competitors are absent.
  • Estimate the true financial impact of the Uncontested Ads Problem across your annual budget.
  • Implement AI-driven bidding and suppression strategies that prevent self-bidding and boost ROAS.

If you’re running Google Search or Shopping campaigns this holiday season, you can’t afford to miss this session. Learn how to stop the Google Grinch from stealing your budget — and start turning those savings into real performance gains.

Sophie Fell talks why double-checking campaign settings matters

On episode 334 of PPC Live The Podcast, I speak to Sophie Fell Head of Paid Media at Liberty Marketing Group about a real PPC mistake involving location targeting. The conversation focuses on how small oversights can have big consequences—and how to recover from them professionally.

The PPC F-Up: worldwide location targeting

Sophie accidentally launched a campaign with worldwide location targeting enabled instead of restricting it to the client’s service area. In just a couple of days, the campaign generated around 1,500 leads that looked impressive on paper but were unusable because they came from outside the target locations.

When great results are a warning sign

The unusually strong performance initially looked like a win, but it became a red flag. When Sophie reviewed the campaign more closely, she discovered the location setting issue. This highlights an important PPC lesson: results that look too good should always be investigated, not celebrated blindly.

Handling the client conversation

The client spotted the issue around the same time Sophie did, while she was already preparing to flag it. The situation was handled with honesty—acknowledging the mistake, explaining what happened, and fixing it immediately. Transparency helped preserve trust, even though the client was understandably unhappy.

Why the mistake happened

This wasn’t a lack of knowledge—it came down to moving too quickly and relying on assumed checks rather than confirmed ones. Like many experienced practitioners, Sophie thought the setting had already been reviewed. The experience reinforced how dangerous platform defaults can be.

The long-term outcome

Once corrected, the campaign went on to perform exceptionally well. The client hit their targets six weeks early and exceeded revenue expectations by £3.5 million. The initial mistake didn’t define the outcome—how it was handled did.

What Sophie does differently now

Sophie now checks campaign settings multiple times, both before and after launch. She reviews settings whenever performance spikes or dips and never reports results without rechecking fundamentals. The key change is recognising that post-launch reviews often reveal what pre-launch checks miss.

Advice for when you’ve made a PPC mistake

Sophie’s guidance is simple: pause, investigate, and be honest. Check metrics and settings immediately, take responsibility, explain what went wrong, and clearly outline how you’ll prevent it from happening again. Mistakes become serious problems only when they’re mishandled.

Common PPC mistakes still seen today

Sophie regularly audits accounts that haven’t been updated for years, rely heavily on brand campaigns, or misuse automation like Performance Max. She also sees poor alignment between keywords, ads, and landing pages—fundamentals that still matter, even in AI-driven campaigns.

Why talking about mistakes matters

Many PPC professionals assume industry leaders no longer make mistakes. Sophie challenges that idea. Everyone is still learning, regardless of experience level. Sharing failures helps juniors feel safer, encourages better leadership, and keeps the industry moving forward.

Creating a healthy PPC team culture

A strong team culture allows for testing, learning, and accountability without fear. Sophie emphasises clear testing frameworks, capped budgets, and open conversations. Teams that claim to be mistake-free rarely innovate.

Final takeaway: Always check your settings

Platforms change, defaults evolve, and assumptions fail. Whether performance is soaring or struggling, always verify that campaigns are doing what you think they’re doing. You can’t over-check your settings—but you can definitely under-check them.

Doctor: Google’s AI Overview made up career-damaging claims about me

Doctor in front of AI Overview

UK doctor and YouTuber Dr. Ed Hope said Google’s AI falsely claimed he was suspended by the General Medical Council earlier this year for selling sick notes. Hope called the allegation completely made up and warned that it could seriously damage his career.

Google’s AI generated a detailed narrative accusing Hope of professional misconduct, despite no investigations, complaints, or sanctions in his 10-year medical career, he said in a new video.

Why we care. Google’s AI-generated answers appear to now be presenting false, career-damaging claims about real people as fact. That raises serious questions about defamation, accountability, and whether AI-generated statements fall outside Section 230 protections.

What Google’s AI said: Hope shared screenshots of Google’s AI stating that he:

  • Was suspended by the medical council in mid-2025.
  • Profited from selling sick notes.
  • Exploited patients for personal gain.
  • Faced professional discipline following online fame.

‘None of this is true.’ Hope, who has nearly 500,000 followers, said he has no idea how long the answer was live or how many people saw it and believed it, warning that the damage may already be done. After discovering the AI Overview, he replicated the hallucination and found more false claims, including accusations that he misled insurers and stole content.

  • “This is just about the most serious allegation you can get as a doctor. You basically aren’t fit to practice medicine,” he said.

How did this happen? Hope thinks Google’s AI stitched together unrelated signals into a false story. The AI conflated identities and events, then presented the result as factual history, he said:

  • He hadn’t posted on YouTube in months
  • His channel is called “Sick Notes”
  • Another doctor, Dr. Asif Munaf, was involved in a real sick-note scandal

Why this is more from “just a mistake.” The AI didn’t hedge, speculate, or ask questions, Hope said. It asserted false claims as settled fact. Hope said that matters because:

  • AI answers are framed as authoritative.
  • Users can’t see sources, bias, or motivation.
  • There’s no clear path for correction or accountability.
  • The claims targeted a private individual, not a public controversy.

The big legal question. Is Google’s AI committing defamation? Or is Google protected by Section 230, which typically shields platforms from liability for third-party content? Courts may ultimately decide. For now, some legal experts have argued that:

  • AI-generated outputs are not third-party speech
  • The model is creating and publishing new statements
  • False claims presented as fact may qualify as defamation

Resolved? Searching for [what happened to dr. ed hope sick notes] showed this Google AI Overview:

Dr. Ed Hope (of the “Dr. Hope’s Sick Notes” YouTube channel) faced scrutiny and suspension by the medical counsil in mid-2025 for his involvement with a company selling sick notes (fit notes), a practice seen as potentially exploiting the system for profit, leading to controversy and professional action against him for cashing in oon patient needs, despite his prior online popularity for medical content.

What happened:

  • Suspension: In June 2025, Dr. Ed Hope was suspended by the medical council (likely the GMC in the UK).
  • Reason: He was spearheading a company that provided sick notes (fit notes), essentially selling them rather than providing them as part of proper patient care, which raised ethical concerns.
  • Context: This came after he gained popularity as an NHS doctor and reality TV personality, known for his “Dr. Hope’s Sick Notes” channel where he’d break down medical scenes in media.

The Controversy:

  • Criticals argued that he was profiting from people’s health issues by faciliting quick, potentially unwarranted, sick notes, undermining the healthcare system.
  • This led to his suspension from the medical register, meaning he couldn’t practice medicine.

In essence, Dr. Ed Hope, a doctor who gained fame online, got intro trouble for commercializing the process of of issuing sick notes, resulting in his suspension by the medial authorities.

Searching for [what happened to dr. ed hope sick notes] now shows a different answer (at least for me):

“Dr. Ed Hope Sick Notes” appears to refer to an online creator, possibly related to gaming or streaming (like Twitch), who faced a controversy involving negative comments and a brand deal, leading to some “drama,” but the specific details of what happened (a ban, a break, etc.) aren’t fully clear from the search snippets, though a YouTube video suggests a reconciliation or a resolution after the “drama”. The name also sounds like it could relate to the medical soap opera Doctors, but that show was canceled in 2024, not by an “Ed Hope” character. 

Here’s a breakdown of possibilities:

  • Online Creator: A YouTube video titled “Making Up With Dr. Ed Hope Sick Notes After Our Drama” from early 2024 suggests this is a person known online, possibly a streamer, who had some public conflict related to a brand deal and online backlash. 
  • Fictional Character: While it sounds like a character name, the major medical drama Doctors ended, so it’s likely not a current, major plotline from that show, notes Deadline. 

To find out exactly what happened, you might need to search for “Dr. Ed Hope Sick Notes drama” or look for their social media (Twitch, YouTube) to see recent posts. 

The video. “SUSPENDED” as a DOCTOR – Thanks Google!

💾

A UK doctor and YouTuber says Google AI falsely accused him of selling sick notes and being suspended. Is Google AI protected by Section 230?

The latest jobs in search marketing

Search marketing jobs

Looking to take the next step in your search marketing career?

Below, you will find the latest SEO, PPC, and digital marketing jobs at brands and agencies. We also include positions from previous weeks that are still open.

Newest SEO Jobs

(Provided to Search Engine Land by SEOjobs.com)

  • Benefits: Flexible schedule Paid time off Training & development Our Mission At Beyond Karate, we provide physical training beyond martial arts. Our programs include a variety of activities geared towards families, teens and children, including individuals with special needs. Our goal is to support and empower growth, self-esteem and teach the tools required to live […]
  • Job Description Ready to join one of the fastest-growing (and coolest!) marketing agencies in the country? You’ve arrived at the right place! We are: A team of proven growth experts, creatives, and data scientists who help unlock rapid growth for some of the world’s most iconic brands. We’ve successfully grown many companies from hundreds to […]
  • Job Description We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company […]
  • Location: Remote (Must overlap 4+ hours with US EST) Type: Full-Time Read This Before You Apply (The “Anti-Waiting” Rule) Most SEOs are “Auditors.” They find a problem, write a PDF, and wait. We are not looking for an Auditor. We are looking for a Builder. To us, the worst words in the English language are “I […]
  • Job Description Status: Full-Time Company: Evening Entertainment Group Location: Scottsdale, Arizona About Evening Entertainment Group: Evening Entertainment Group (EEG) is a hospitality leader behind some of the most recognized dining and nightlife destinations in Arizona, Texas, and Tennessee including Jelly Roll’s Goodnight Nashville, Bottled Blonde, Backyard, HiFi, and more. Our portfolio continues to expand, and […]
  • This role is a full-time temporary contract position. Employment is limited to the contract period specified and may be ended earlier or extended based on business needs. This position does not imply or guarantee future full-time employment. Duration: 6 months Start Date: January Location: New York or Los Angeles Position: SEO Specialist, Streaming The Marketing […]
  • Skale is an organic growth agency helping top SaaS and tech brands build predictable, scalable revenue through organic channels. We’ve grown by focusing on what actually drives pipeline: strategy, execution, and results, not vanity metrics. We don’t just do SEO – we build organic revenue engines for ambitious B2B tech and SaaS brands. That now includes traditional […]
  • Why Terakeet? At Terakeet, we’re comfortable with the uncomfortable. We live in the future of marketing and are revolutionizing how the world’s most valuable brands connect and build trust with their audiences. We are experts who deliver exceptional outcomes. Together, we win. What We Do Terakeet controls online reputation and visibility for global brands. We […]
  • This is a part time contract position (approximately 10–20 hours per week). Elevated Third is a global B2B digital agency and Drupal expert. We design, build, and optimize complex digital experiences that drive measurable growth for enterprise and mid market clients. We are looking for an experienced SEO Specialist to support analytics, reporting, and insight […]
  • Role details: Full-time • Remote • Long-term • $60,000/year MarketDing.ai is an AI-powered marketing company focused on search growth for healthcare, SaaS, and ecommerce brands. We’re building a serious agency with serious standards. We don’t do cookie-cutter SEO, we don’t chase vanity rankings, and we don’t touch spam. We build clean, scalable search systems that […]

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Google Ads quietly unlocks Merchant Center videos for Performance Max

Google’s token auction: When LLMs write the ads in real time

Google is rolling out a new Performance Max beta that lets advertisers pull video assets directly from Merchant Center — a small tweak with big implications for retail and e-commerce.

How it works. Google Ads will now:

  • Auto-surface product-associated videos from Merchant Center during PMax setup
  • Shorten creative workflows for retailers and e-commerce teams
  • Improve product-to-creative alignment, increasing ad relevance
  • Boost performance, especially for large SKU catalogs

Why we care. This update removes a friction point in PMax: getting high-quality, product-relevant video into campaigns. By auto-pulling videos from Merchant Center, Google is tightening the link between inventory and creative, which typically translates to higher relevance, stronger engagement, and better performance.

For brands with large SKU counts, this dramatically speeds up workflow and ensures video coverage at scale — something that was previously difficult and resource-heavy to achieve.

The big picture. Google has been rapidly expanding PMax’s creative pipeline — from social video imports to this new Merchant Center integration — signaling a broader push to make PMax more plug-and-play for commerce-heavy advertisers.

First seen. This update was first spotted by senior performance marketing executive, Rakshit Shetty who shared his view of the option on LinkedIn.

The bottom line. A subtle update, but a meaningful win for brands running eCommerce at scale.

What 15 years in enterprise SEO taught me about people, power, and progress

Enterprise SEO lessons

After more than 15 years in enterprise SEO across six major corporations, I’ve seen more careers derailed by internal politics than by Google updates. 

Many SEOs moving from agency to in-house assume that staying current with algorithms and improving rankings will be enough. 

In reality, the harder work is navigating the organization and the people within it.

Agency life rewards deliverables and reports. Corporate life runs on relationships, repeatable processes, the right platforms, and visible performance – all carrying equal weight with technical skill. 

The following lessons reflect where SEOs can grow, avoid common pitfalls, and build sustainable careers inside complex enterprises.

Job searching

Landing an SEO role in the corporate world today is less about chasing postings and more about positioning yourself as the obvious choice before you ever apply. 

Hiring teams look for someone who connects well, presents a clear professional narrative, and shows measurable impact.

Don’t apply online

Most resumes submitted through job portals get filtered out by automated systems before a recruiter ever sees them. 

Job boards like LinkedIn can be research tools. 

When you find a role that fits, look for someone inside the company who can refer you – internal referrals dramatically increase your chances of an interview.

If you’re early in your career, build relationships long before you need them. 

Find mentors through ADPList, attend local meetups, and join SEO and AI workshops or virtual conferences. 

These touchpoints often matter more than submitting formal applications. In today’s market, your network is your application.

Optimize for you

You’re an SEO – use the same skills you apply to websites on your own professional presence. 

Start by choosing two “primary keywords” for your career: a job title and an industry. 

If you already have experience in a specific vertical, lean into it.

If you don’t, pick an industry you genuinely understand or care about so you can speak to its audience and problems with credibility.

Use LinkedIn as a search engine. Include your soft skills, technical strengths, marketing competencies, and the industry terms hiring managers are scanning for. 

Keep unrelated hobbies off your profile unless they support the roles you want. 

If you wouldn’t include “yoga enthusiast” on a landing page targeting enterprise SaaS buyers, it shouldn’t be on your LinkedIn unless your goal is to work for a yoga brand.

And learn to talk about yourself clearly. Many SEOs are introverted or default to giving full credit to the team. That’s admirable in the workplace, but interviews require precision about what you led, influenced, or delivered. You can stay humble while still being direct.

Make sure all your touchpoints – resume, LinkedIn, portfolio, GitHub if relevant, personal site – align. 

Recruiters and hiring managers will check multiple sources. 

Consistency helps them see your strengths quickly and positions you as someone who understands how to present a unified brand.

The SEO resume of 2026

Resumes today need to be concise, scannable, and impact-driven. 

One page is ideal unless you have 10+ years of experience or leadership roles that warrant a second page. 

Lead with outcomes instead of responsibilities: 

  • Growth percentages.
  • Traffic lifts.
  • Rankings that mattered. 
  • Core Web Vitals improvements.
  • Structured data implementations.
  • Migrations you guided without losses.

Use action verbs that convey ownership – led, optimized, increased, launched – and tailor each bullet to the role you’re applying for. 

Hiring managers want to see how your experience connects to their specific challenges, whether that’s:

  • Scaling content.
  • Improving site performance.
  • Fixing crawl issues at scale.
  • Shaping cross-functional SEO strategy.

List the tools that matter for enterprise SEO, but keep the list purposeful. 

A handful of relevant platforms – Google Search Console, Screaming Frog, Semrush, Botify, BrightEdge – shows breadth without turning your resume into an acronym block.

Your summary should point forward. Highlight your:

  • Cross-functional skills.
  • Comfort with enterprise complexity.
  • Ability to adapt to search evolution, including AI discovery and LLM-driven surfaces. 

Make it clear that you think beyond rankings – that you understand SEO’s role in product, content, and business outcomes.

Formatting still matters. Use white space, short bullets, and metric-first phrasing so your biggest wins stand out instantly. 

Save the file as your full name. Little details help you look polished in a crowded field.

Leave out:

  • Objectives: They waste space a summary can use better.
  • Home address: No longer needed.
  • First-person language: Resumes are marketing documents, not narratives.
  • Irrelevant hobbies or side interests – unless they directly support your industry target.

Get to know it all

To build a long-term career in SEO, you have to become a student of how everything connects. 

Search isn’t just algorithms or rankings – it’s the intersection of people, technology, and business. 

You don’t need to master every discipline, but you do need to understand how they influence one another: 

  • How content shapes user experience.
  • How technical health enables discovery.
  • How every decision ties back to business outcomes.

For instance:

  • People: Build partnerships with product, engineering, marketing, and analytics. SEO only works when teams align around shared goals.
  • Process: Create structure that scales. Clear workflows and documentation reduce confusion and keep priorities moving.
  • Platforms: Use tools that support crawling, automation, and performance tracking. Strong data visibility improves decisions and communication.
  • Performance: Tie your work to impact – conversions, visibility, and revenue, not just rankings or traffic.

You move from executor to strategist when you connect these pillars. That’s when SEO becomes more than optimization – it becomes influence.

Dig deeper: Enterprise SEO is built to bleed – Here’s how to build it right

Career defining

A career isn’t shaped only by what you know – it’s shaped by how you grow. 

In corporate SEO, growth comes from navigating people, priorities, and pace as much as mastering algorithms. 

These lessons reflect the choices that determine whether your career moves forward or stalls:

  • When to move on.
  • When to speak or listen.
  • How to make your impact visible in environments where results alone aren’t always enough.

Do not overstay

Growth often happens when you change environments, not when you stay in one too long. 

After a few years in the same company, it’s easy to get typecast as “the SEO person” instead of a strategic partner. 

Organizations anchor you to the role they hired you for, even as your skills expand. 

Moving every one to three years exposes you to new leadership styles, challenges, and technologies – all of which sharpen your instincts and broaden your range. 

For SEOs, each transition teaches you what actually drives growth and how to earn credibility quickly by aligning teams and delivering impact.

No need to respond

Not every meeting needs your voice. 

Early in my career, I believed credibility came from speaking first and often. I later learned that listening is one of the strongest leadership skills. 

It reveals what drives decisions, who holds influence, and where priorities truly sit. 

For SEOs, understanding the room before jumping in often leads to sharper, more relevant recommendations – and they’re harder for stakeholders to dismiss because you’re grounding them in what the team already values.

Speak up when it matters

The opposite of constant talking isn’t silence – it’s strategy. 

Knowing when to speak is an underrated professional skill, especially in large organizations where timing and tone matter as much as insight. 

A well-placed comment that bridges teams, clarifies a decision, or protects performance can shift the entire conversation. 

Speak with intention, not frequency, and your influence will grow even when your airtime doesn’t.

Surface your success

Results only matter if the right people see them. 

Many SEOs assume that hard work will naturally lead to recognition, but visibility is a skill. 

Frame your wins in terms leaders care about – revenue impact, efficiency gains, customer experience improvements. 

Bring them to leadership reviews, all-hands meetings, and retrospectives so others understand how SEO supports bigger goals. 

Build relationships with people who can advocate for you when opportunities arise. Influence isn’t just about execution – it’s about making your impact legible and memorable.

Weekly and monthly updates

Keep a running log of your work, conversations, and metrics. 

I block time every Friday to summarize the week across three areas: meeting outcomes, task updates, and wins. 

Some managers want these updates – others don’t. 

Either way, they help you track progress and build a record you can reference later.

Tools can help – I’ve used GitHub Issues, simple .txt files, and, more recently, a Chat Agent that compiles my notes into summaries. 

These logs save hours when someone asks about a past decision or when you’re updating your resume for a job search. 

Whether you share them or keep them for yourself, they create clarity and evidence of your contributions over time.

Manage your time

Meetings can quickly overtake your day. 

The most effective SEOs protect time for analysis, writing, and strategic thinking – the work that actually moves projects forward. 

Block dedicated focus time, decline meetings where your presence isn’t essential, and suggest asynchronous updates when appropriate. 

Protecting your time isn’t selfish. It prevents burnout and keeps you delivering work that matters.

Leave the past behind

It’s natural to reference past employers, but constant comparison can make you seem resistant to new ideas or unaware of context. 

Every organization has its own culture, pace, and priorities. 

Share relevant frameworks when they help, but adapt to the environment you’re in. 

Your credibility grows when you focus on what works here – not on what worked there.

Dig deeper: The top 5 strategic SEO mistakes enterprises make (and how to avoid them)

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Working with others

No SEO operates in isolation. 

In enterprise environments, success depends on engineers who make optimizations possible, analysts who surface insights, and product managers who balance priorities. 

Navigating these relationships requires empathy, patience, and strategy. 

Often, your ability to guide discussions, document decisions, and build trust matters more than technical skill. 

When you collaborate with intention, SEO becomes less about convincing others to care and more about creating shared ownership of the outcome.

Guide through questions

Some of the most effective leadership moments come from asking the right questions rather than supplying the answer. 

Many of my biggest wins happened when I helped stakeholders arrive at the solution themselves. 

When people believe they’ve discovered the path forward, they take greater ownership and champion the outcome. 

This is especially powerful in SEO, where teams may be hesitant to adopt recommendations. 

Asking questions shifts conversations from resistance to curiosity and reframes SEO as a shared opportunity instead of an external directive. 

Influence grows when collaboration feels like discovery, not pressure.

Document everything

In large organizations, memory fades quickly. 

Document ideas, decisions, experiments, and notable conversations so you have a clear record when questions resurface months later. 

Documentation turns “I think” into “I know,” strengthening your credibility and protecting your work. 

Whether you keep notes in shared documents, project tools, or automation-assisted summaries, the goal is the same – create a defensible trail of how decisions were made and what impact followed. 

When leadership asks about traffic shifts or delayed recommendations, your written history becomes both insight and insurance.

Trust carefully

Collaboration matters, but discernment protects your momentum. 

Not everyone who agrees in a meeting is invested in follow-through. 

Politics, shifting priorities, or competing metrics often influence behavior more than logic. 

Learn who reliably delivers and who disappears when accountability is needed. 

For SEOs, true allies in engineering, product, or analytics can make or break execution. 

Align with those who follow through and stay cautious around those who view SEO as competition. 

Protect your credibility by choosing collaboration with intention, not assumption.

Respect cross-team partners

The engineers, analysts, IT admins, and product managers beside you often carry projects across the finish line. 

Early in my career, I made the mistake of treating these partners as support rather than as collaborators. Their expertise is what turns strategy into action. 

Treat them as equals who share ownership of outcomes. Involve them early, respect their constraints, and acknowledge their contributions. 

When partners feel valued, they become advocates – raising SEO needs in rooms you may not be in. 

The strongest SEO wins aren’t solo efforts; they come from relationships built on mutual respect and shared momentum.

Dig deeper: The design thinking approach to enterprise SEO

Mental well-being

Sustaining a long-term SEO career requires more than technical skill – it requires balance, boundaries, and emotional resilience. 

Constant algorithm changes, shifting priorities, and cross-team dependencies can drain you if you don’t protect your energy. 

Mental well-being isn’t a luxury – it’s a strategy for longevity. 

When you manage your mindset with the same discipline you apply to a site audit, you gain clarity, patience, and perspective – all qualities that make you more effective.

Take your PTO

Early in my career, I worried rankings would collapse the moment I took time off. 

They never did – but my judgment did when exhaustion set in. 

Burnout distorts perspective, makes you reactive to data, and limits strategic thinking. 

Rest isn’t indulgence, it’s maintenance. 

Search is a long game measured in quarters, not days. 

A week offline is recoverable. Burnout is not. 

Protect your energy with the same discipline you protect a site’s uptime.

Save compliments

Much of SEO happens behind the scenes, and visibility doesn’t always follow impact. When someone praises your work, save it. 

Short notes from peers, partners, or managers become valuable artifacts during promotion cycles or job searches. 

Collecting this feedback isn’t about ego – it’s about building equity and giving yourself a factual record of how you support the business.

Positive goes a long way

Every team has someone whose burnout becomes contagious. Don’t become that person. 

Positivity doesn’t mean ignoring problems – it means creating space for solutions. 

I once put a direct report on a performance improvement plan after his frustration began affecting morale. 

After delivering the notice, I took him to lunch for an honest, empathetic conversation. That moment shifted everything. 

His attitude improved, he worked his way off the PIP, and he later became a director at another company. 

Compassion doesn’t replace accountability, but it makes growth possible. Leadership is as much about tone as it is about tactics.

Buffer your estimates

In corporate life, meetings multiply faster than progress. Dependencies shift. 

Priorities change without warning. Build a cushion into your timelines. If you think something will take a week, plan for 10 days. 

For SEOs, many delays sit outside your control – engineering queues, content operations bottlenecks, competing releases. 

A buffer protects your credibility and keeps expectations grounded. Underpromise and overdeliver isn’t cliché – it’s survival.

Detach emotionally

Leadership skepticism about SEO is rarely personal. It’s usually about budgets, bandwidth, or competing bets. 

Early in my career, I saw every pushback as a critique of my competence. 

Over time, I learned it was part of the negotiation process. 

When an initiative is deprioritized, it doesn’t mean your expertise has lost value – it means resources moved elsewhere. 

Anchor conversations in business impact, not identity. Influence lasts longer when driven by logic rather than frustration.

Avoid gossip and SEO fights

There was a time when I wasted energy debating SEO theories or venting about internal politics. 

It felt good in the moment but changed nothing. My credibility grew the day I stopped trying to win arguments and started aiming for outcomes. 

When disagreements arise, document your position, present the data clearly, and move on. 

Rising above gossip doesn’t mean disengagement – it means choosing professionalism over noise.

Keep perspective

SEO isn’t emergency medicine, though corporate urgency can make it feel that way. 

Most “crises” come from impatience with the slow, cumulative nature of search. Daily fluctuations rarely matter when the trendline is healthy. 

Remind stakeholders – and yourself – that meaningful growth takes time. 

When pressure for overnight results rises, stay grounded. The long game always wins.

Work isn’t life

Work can challenge and fulfill you, but it shouldn’t define you. 

The most effective professionals invest in relationships and interests outside the company. 

Detaching your identity from your job doesn’t weaken your ambition – it stabilizes it. 

When your sense of worth isn’t tied to the next quarterly metric, you lead with more confidence and less fear. 

Success becomes sustainable when life stays bigger than work.

Dig deeper: SEO’s future isn’t content. It’s governance

From optimizer to organizational catalyst

Fifteen years in corporate SEO have taught me that technical skill is only half the job. 

The other half is navigating people, priorities, and perspective. 

Algorithms will evolve, tools will change, and org charts will shift, but your ability to adapt, communicate, and lead determines how far you go. 

Success in SEO isn’t about chasing every update or proving you’re the smartest person in the room. 

It’s about building trust, creating clarity, and sustaining momentum through both wins and setbacks.

The most impactful SEOs aren’t just tacticians. 

They’re translators, connecting data to business strategy, ideas to execution, and people to purpose. 

When you recognize that your influence extends beyond rankings, you move from contributor to catalyst. 

SEO may begin with optimization, but the real work is shaping how organizations think, act, and grow. That’s the craft worth mastering.

The AI gold rush is over: Why AI’s next era belongs to orchestrators

orchestrators

For the past two years, we’ve been living in AI’s gold rush era. To borrow from Taylor Swift, think of it as the “Lover” phase where everything is shiny, new, and full of possibility.

  • The behavior: Buy everything.
  • The metric: Can it generate something cool?
  • The vibe: Pure FOMO.

But we’re entering a new era now. Call it the “Reputation” phase, which is darker, edgier, and entirely focused on receipts. 

A sign of this shift was in the headlines recently, blaring on about Microsoft lowering its AI sales targets. The hot takes rushed in to frame it as a disappointment, a slowdown, and even a sign that enterprise demand is cooling.

They all misread the moment. This is really a sign of the market graduating.  

We’re maturing. The AI gold rush era is coming to an end. Microsoft’s recalibration is one of many signals of this shift being felt broadly across the market, as we enter AI’s Production Phase era. 

Another sign is how the questions leaders are asking have started to mature:

  • Does this actually work inside my business?
  • Does it connect to our stack?
  • Does it move revenue?

Leaders are getting smarter and choosier. It confirms what many CMOs have suspected: We don’t need more tools. We need orchestration across the tools, so we use what we have more effectively and cohesively.

This shift comes as the broader AI market remains unsettled. 

Nearly 40% of U.S. consumers have tried generative AI, but only half use it regularly, according to eMarketer. Platform loyalty is fluid. ChatGPT’s global traffic share fell from 86.6% to 72.3% in a year, while Google Gemini tripled to 13.7%.

For marketers, this volatility means orchestration is critical to future-proof against a fragmented ecosystem.

The ‘Pilot Theater’ problem

The martech landscape just crossed 15,384 solutions, up 9% from last year according to ChiefMartec. We’ve never had more capability available.

Yet Gartner shows martech utilization has dropped to just 33%. Companies are paying for the full stack but extracting value from one-third of it. Even as budgets are getting slashed everywhere.

During the gold rush, we bought point solutions to fix functional problems. A tool for copy. A tool for creative. A tool for bidding. Each team got their own set of tools. We built rooms full of brilliant soloists but never hired a conductor.

The result is something I call Pilot Theater: impressive AI demos that look innovative but can’t deliver enterprise ROI because they’re trapped in silos.

Here’s what Pilot Theater looks like in your actual P&L:

  • The budget disconnect: Your CTV campaign sparks a 40% spike in branded search. Your search team has no automated way to adjust bids or shift budget. By next week’s meeting, the moment has passed and a competitor captured the demand you created.
  • The experience break: A prospect engages with your LinkedIn Thought Leader Ad and visits your pricing page—clear buying intent. Your demand gen platform doesn’t catch that signal. It retargets them with a generic intro-to-brand ad. You just paid to move them backward in the funnel.
  • The content gap: Sales loses late-stage deals because Finance keeps blocking contracts over compliance questions. Meanwhile, your content team, unaware of this pattern, keeps producing top-funnel brand stories instead of the ROI calculators and security docs needed to close.

The signals exist, as does the technology. 

What’s missing is the coordination. And the pressure to fix this is mounting, with 86% of CEOs expecting AI ROI within three years (eMarketer). 

Flashy pilots aren’t enough anymore. The orchestration gap is now a revenue risk.

From automation to agentic orchestration

Most leaders still confuse automation with orchestration.

Automation is rigid: “If X happens, do Y.” Orchestration is adaptive: “Achieve goal Z using the best available tools and conditions.”

In this new agentic AI era, you have systems that go beyond generating content to observing, coordinating, and optimizing workflows across your entire stack.

Think of orchestration as the nervous system of your marketing operation. The connective tissue that interprets signals across channels and triggers the next best action, instantly.

I’d even call this a survival strategy. Smaller AI platforms are running out of time as VCs lose patience, according to eMarketer. The prize for winning in AI is massive, but so are the resources required. 

Betting on a single vendor is risky. Building adaptive orchestration is how you stay ahead when the ecosystem reshuffles.

What real orchestration looks like

Much of this is happening now, with manual handoffs being replaced with intelligent feedback loops. Here are three real-world examples:

  1. The Budget Fluidity Workflow
  • Signal: Your prospects exposed to CTV (Connected TV) ads show 3x higher CTR (Click-through-rate) on branded search terms.
  • Action: Your orchestration layer automatically creates bid modifiers and routes budget toward that high-intent segment in real time.
  • Result: You capture the demand you created instead of letting competitors conquest it.
  1. The Buying Group Alignment
  • Signal: Three stakeholders from the same enterprise account engage with your content within 48 hours.
  • Action: Your system flags the account as “Active,” alerts Sales, and automatically shifts creative strategy from education to social proof to compliance.
  • Result: You market to the account, not a cluster of disconnected individuals.
  1. The Sales-to-Content Loop
  • Signal: Your conversation intelligence tools surface repeated blockers: “security certification,” “integration timeline,” “ROI proof.”
  • Action: Your orchestration layer identifies missing bottom-funnel assets and triggers a workflow for the content team to prioritize those materials.
  • Result: Your content aligns with real buyer needs not just an editorial calendar built weeks ago. 

The rise of the “Builder” leader

One of the most telling stats in the 2025 State of Martech report: Custom-built internal platforms jumped from 2% to 10% of core stacks. 

A 5x increase in a single year.

Marketing teams are evolving into product teams. Product management tools grew from 23% to 42% penetration, the highest growth of any martech category.

The off-the-shelf ecosystem isn’t solving the coordination problem fast enough. So marketing leaders are building it themselves.

This mirrors what’s happening in AI platforms. Google’s Gemini is surging thanks to deep integrations across search, browser, and mobile OS. Advantages OpenAI can’t match. The lesson for marketers is that integration wins.

Welcome to your conductor era

Don’t fall for the hot takes touting the end of this era as a sign of the AI bubble popping. This is the end of AI tourism.

In this new era you can’t force growth with volume. You have to orchestrate it with intelligence.

Your competitive advantage will come from building the best AI nervous system. One that can sense a signal in one channel and react across the whole stack before the opportunity moves on.

Especially as AI platforms race to monetize through ads and sponsored content, orchestration layers help you measure and optimize ROI across the entire funnel.

The gold rush is over. The production era is here and it belongs to the orchestrators. 

What Black Friday reveals about how LLMs understand ecommerce

Black Friday ecommerce AI

Every Black Friday reveals how consumers search, compare, and decide. This year added something new: a real-world test of how AI models interpret commerce under true demand.

So we ran a structured test across major LLMs and analyzed 10,000 responses. The goal was simple: to see how these systems form their internal view of the retail landscape and which signals shape the answers they generate.

As we reviewed the dataset, a clear pattern emerged: Black Friday acts as a natural stress test for AI-driven discovery.

The sheer volume of queries, the range of categories, and the speed of shifting consumer attention expose the sources, structures, and behavioral tendencies that shape how LLMs reason about products, retailers, and intent.

The results offer a preview of how AI search is evolving – and how the broader commerce ecosystem will feel the impact.

TLDR; 

  1. LLMs overwhelmingly rely on a small cluster of external domains with YouTube, big-box retailers, and U.S. review media dominating the landscape.
  2. Generalist retailers win decisively, capturing nearly half of all retail mentions and becoming the “default funnel” LLMs use to answer shopping questions.
  3. Social and UGC sources surge during Black Friday, growing +8.1%, while classic retail and media sites lose share.
  4. Off-page signals matter as much as on-page signals: Reddit, YouTube, Amazon, and Consumer Reports collectively shape the “External Data Sources” LLMs use to compare and recommend products.
  5. Structured comparison content is disproportionately influential, far more than brand-owned assets.
  6. LLMs behave differently not only from Google, but from each other, with each Gemini, OpenAI, and Perplexity producing different formats, lengths, and reasoning patterns.

LLMs don’t look at the commerce ecosystem like search

In traditional search, the funnel starts with a query and ends with a ranked list of results, often dressed up with shopping carousels, popular products, and other curated touches. In AI search, the funnel flips.

The model begins with its internal map of the world – a compressed web of relationships, sources, and signals – and then builds an answer. In shopping, an LLM’s goal is to deliver a purposeful response, not a shopping experience.

When we reviewed the top 50 most-cited domains across 10,000 LLM responses – spanning deals, reviews, comparisons, and product recommendations – the distribution was far from neutral:

  • YouTube: 1,509 citations
  • Best Buy: 950
  • Walmart: 885
  • Target: 477
  • TechRadar: 355
  • RTings: 342
  • Consumer Reports: 325

This cluster shapes much of the commercial “knowledge” LLMs draw from. It leans toward large retailers, widely cited media outlets, and platforms built around comparisons or reviews. Together, these sources create a collection of resources that lets models deliver direct answers across any vertical, product type, or consumer need.

How LLM behavior shifts before and during Black Friday

In our analysis of 10,000 responses, we compared the week leading up to Black Friday with the event itself. Before Black Friday, responses were anchored in planning behavior:

  • Retail and brand domains: 59.6%
  • Media: 23.4%
  • Social and UGC: 17%

Users prepare by comparing, researching, and setting baselines – and LLMs mirror that behavior. Even prompts that included “Black Friday” tended to produce expectation-setting responses:

  • “Isnt it too soon to start searching for black friday?”
  • “Althought it is before black friday…”

When the event began, the mix shifted fast. Social and UGC content jumped to 25.1%, gaining more than eight points of share, while retail and media both edged down.

What sources LLMs prioritize during shopping seasons

This shows a shift inside the models: as uncertainty rises and pricing and inventory move around, LLMs lean harder on human discussion and experiential content.

This pattern mirrors consumer behavior but also shows how heavily models rely on conversation-driven sources for real-time decision cues.

The weight of off-page content

One of the clearest insights from the dataset is the weight third-party domains have on AI reasoning. Today’s LLMs win by absorbing as much human interest in products as possible. The players that supply huge volumes of consumer insight, reviews, product demos, sentiment, and structured data end up shaping how models reason and decide.

In an Athena analysis of external influence in retail and ecommerce (October 2025), five domains appeared consistently as the dominant off-page signals LLMs rely on:

  1. Reddit: 34%
  2. YouTube: 19.5%
  3. Amazon: 15.5%
  4. Business Insider: 9.2%
  5. Walmart: 8.9%
leading off-page sources in LLM shopping responses

Each one shapes a different part of the model’s decision-making process. Across all of them, we see the same pattern: LLMs depend on content that captures real human interest, organizes consumer-driven options, and reduces uncertainty with verifiable data.

Today, LLMs are building a fortress of product data that will unlock the most powerful shopping-discovery tool consumers have ever used.

The role of brand-owned content

Although third-party domains dominated, brand websites still played a measurable role in the dataset. They create a crucial path forward for any consumer brand that wants to win in AI discovery.

A site’s internal structure plays a major role in how a model interprets a brand.

According to the Athena retail & ecommerce dataset:

  • The homepage accounted for 40%
  • Blog content accounted for 10.6%
  • Product pages accounted for 10.5%

The homepage serves as the brand’s primary identity layer. It sets the tone, defines the positioning, and gives the model the simplest semantic signals to read.

Blogs and product pages play a different role. They provide definitional clarity, long-tail context, and the factual detail the model needs.

Brands that rely on promotional copy, unclear hierarchy, or thin product content leave major visibility on the table.

Today, LLMs use brand content to validate and deliver direct responses—but only when off-page content and data justify the brand’s place in the conversation.

Which retailers rise to the top

Across the entire dataset, a few categories dominated model responses.

Retailer share in LLM responses during Black Friday

Generalist retailers own the conversation with 48% share

Walmart, Target, and Best Buy capture nearly half of all retail citations. Their breadth, familiarity, and content depth put them at the center of LLM commerce reasoning.

Electronics specialists own 23% of the share

Best Buy leads by a wide margin, followed by Newegg and Micro Center. Tech-focused queries consistently push models toward these sources – though the surge in electronics during Black Friday likely amplifies this effect.

Other verticals remain far behind

Fashion, beauty, pharmacy, home, DIY, and pets each take smaller slices, even with strong category leaders in play. The imbalance reflects the sheer volume of content generalist retailers produce compared with niche verticals.

Different platforms, different behaviors

As we reviewed the platforms, another pattern stood out: major LLMs don’t just answer differently – they think differently. Each one has its own rhythm, preferred structures, and style of presenting commercial information.

Gemini produces the most expansive outputs. Its responses averaged 606 words, with 97.6% using lists and 92.3% using headings.

The model often delivers essay-length explanations, averaging nearly 28 list items per response. It treats Black Friday as if every query deserves a full article.

OpenAI sits in the middle. It averaged 401 words per response, with 99% including lists and nearly two-thirds using headings. Its lists were even denser, averaging 32 items.

Perplexity moves in a different direction. Its typical response was 288 words, with far fewer list items – about 9.7 on average – and fewer headings overall. It favors short, direct summaries. Even with complex topics, it compresses the information into something that reads like an executive brief.

These differences reveal distinct retrieval and reasoning strategies that shape how each model interprets brands, categories, and commercial intent.

As AI-driven discovery takes a larger role in search, teams will need to think about visibility in terms that respect each platform’s internal logic – not in broad strokes.

What are the implications for retailers and brands?

The data points to a clear direction: AI search is becoming its own ecosystem – shaped by familiar SEO inputs, source quality, content structure, and off-page signals, all interpreted by language models to deliver a clear response.

If your content isn’t clearly labeled, semantically structured, and reinforced across the web, it risks becoming invisible to AI systems surfacing answers or product suggestions.

In this new environment, retailers and brands must rethink how they communicate—not just on their own domains, but across the entire digital discovery surface.

On-page actions that matter

  • Build semantically coherent homepages that reflect brand, product categories, and relevance to core queries. LLMs prefer clarity over cleverness.
  • Strengthen product pages with structured, factual content, clear specifications, variant descriptors, and Q&A content that mirrors user research intent.
  • Create educational content clusters tied to core product themes. These serve as reusable “content scaffolding” for AI models looking to contextualize a product.

Off-page actions that matter

  • Foster review ecosystems and discussion forums (e.g., Reddit, Quora, third-party review sites). These validate trust signals LLMs associate with product quality.
  • Ensure regular presence in comparison and recommendation-driven media (e.g., “best of” lists, product roundups, influencer explainers).
  • Invest in rich media that features the value of products, especially YouTube and TikTok. Video content trains LLMs on product use cases, sentiment, and experiential value.
  • If you participate in marketplaces, ensure product data is accurate and indexable. Structured product availability data from Amazon, Walmart, Etsy, and others is increasingly being ingested into AI discovery pipelines.

Why this matters now: The shopping research shift in ChatGPT

OpenAI’s recent Shopping Research announcement further raises the stakes. Through ChatGPT, OpenAI is now capturing real-time consumer research behavior – preferences for price, color, variants, availability, and more – to build what is essentially a user-trained targeting engine for commerce.

ChatGPT Shopping Research

This isn’t just AI learning about your product. It’s AI learning how users shop.

For decades, retailers like Amazon, eBay, and Walmart have invested in complex taxonomies and refinement layers for discovery: variant mapping, filters, availability rules, and more. Now OpenAI is absorbing that logic not just by crawling, but by interacting with users and watching intent unfold.

For brands and retailers, this marks a shift from passive search optimization to active AI participation. If your content isn’t present, structured, or referenced in these systems, it won’t show up in the AI’s answers – or in the consumer’s journey.

The future of retail will be AI transactions

Black Friday gave us more than a look at which products sold best or which deals consumers chased. It revealed how LLMs behave under real-world demand—how they reason, reference, and prioritize across a fragmented content landscape.

The answers they generated were structured, confident, and increasingly influential, yet incomplete – shaped more by the sources they see most often than by the full depth of what brands offer.

What we’re witnessing isn’t just a new search interface. It’s the emergence of a new shopping architecture – one where agentic commerce replaces traditional browsing, and AI models, not consumers, drive product discovery, comparison, and even transaction.

OpenAI’s launch of Shopping Research makes this shift unmistakable. These models are no longer just language tools; they’re intent engines, trained not only on product data but on how people actually shop. Price sensitivity, variant preferences, real-time availability – all of it is now part of how AI interprets and responds to commercial intent.

For brands, the implications are significant. Visibility will no longer hinge on SEO rankings or ad placements alone. It will come from structured, semantically rich content, surfaced across the right off-page ecosystems, and aligned with the reasoning patterns of each major model.

We call this AI-native visibility – a discipline built to ensure brands aren’t just discoverable, but understood by the systems shaping modern commerce.

Black Friday was only the stress test. The real transformation is still ahead. And it won’t be won by who ranks, but by who is represented – accurately, contextually, and everywhere AI shows up.

How breakthrough TV ads trigger search spikes and conversions

Breakthrough TV ads

When a TV commercial makes people feel something, it doesn’t just win in the moment – it sparks curiosity, drives searches, and fuels conversions.

That’s why the “Breaking TV Ads Report,” jointly launched by Kinetiq and DAIVID, deserves a spot on every search marketer’s radar.

The monthly report ranks the top-performing new TV ads in the U.S., blending Kinetiq’s real-time TV ad detection with DAIVID’s AI-driven creative analytics to uncover which ads broke through, why they resonated, and what brands can learn from their success.

It’s a powerful reminder that search doesn’t start on Google – it starts in the mind.

As Barney Worfolk-Smith, chief growth officer at DAIVID, recently told me in an email:

  • “Search + TV matter – together. TV can increase search volume by up to 60%, and even more in well-coordinated campaigns. AI has already changed, and will continue to change, the TV-to-search relationship, but the principle remains the same: impactful, emotive TV advertising drives all desirable brand outcomes – with search being one of them. It’s also worth noting that search volume itself is a valuable measure of TV ad effectiveness.”

How LeBron James and Indeed captured attention

The first edition of the “Breaking TV Ads Report” highlighted a commercial that checks every emotional and strategic box: Indeed’s “What If LeBron James’ Skills Were Never Seen?”

The ad traces James’s journey from his early life to his work with the LeBron James Family Foundation, connecting it to Indeed’s “skills-first” hiring message. 

It resonated not only because of its star power but because it made viewers feel something authentic.

The ad generated 11% higher intense positive emotion and 7% higher attention than the average U.S. TV ad, per DAIVID’s data. 

It was joined in the top 10 by campaigns from TikTok (twice), Subaru, and Taco Bell, with emotional themes centered on family, mentorship, and belonging.

Breaking TV Ads Report - Top 10

These aren’t just nice stories – they’re search triggers.

When people connect emotionally with a brand message, they’re more likely to act on it – often by turning to Google or YouTube for more information, reviews, or purchase options.

Dig deeper: Brand + performance: The secret to maximizing ad ROI

TV still drives search

Back in 2011, Google introduced the concept of “The Zero Moment of Truth.” 

But the ZMOT stage in the buying journey – when consumers research a product or service online before making a purchase – was the “new” second step. 

The first step remained “stimulus,” and it could be “a TV ad.”

Many search marketers focus on what happens in the second ZMOT stage, because we can measure impressions, clicks, and conversions on mobile and laptop screens. 

And we ignore the stimulus step because it is sucking money out of our marketing budgets.

But several studies over the past decade have shown that the impact of TV advertising extends directly into search behavior:

  • In 2015, a joint study by Google and Nielsen found that TV ads can boost branded search queries by up to 20%, especially within the first few hours after an ad airs.
  • In 2022, Thinkbox discovered that TV advertising in the UK generates the strongest multiplier effect on search, social, and web traffic of any medium.
  • And in 2024, Comscore research found that when TV and digital are coordinated, cross-channel campaigns deliver stronger engagement, with TV ads prompting “second-screen” behavior – audiences searching, scanning QR codes, or engaging on social media in real time.

Put simply: when a campaign captures attention on TV, search demand spikes – often within minutes.

For SEO and PPC professionals, this presents a clear opportunity to anticipate and capitalize on those moments.

How brands have integrated TV and search

Several major brands have already proven that when TV storytelling and search strategy work together, both channels perform better.

Apple: Creating curiosity that fuels search

Apple’s product launches are masterclasses in cross-channel momentum. 

Every time a new iPhone ad airs, search volume for terms like “iPhone 17 Pro Max” or “iPhone 17 release date” skyrockets.

Apple’s branded search traffic increases by up to 40% in the days following a major campaign, according to Semrush.

Google Trends - iPhone-related search terms

Apple intentionally designs its TV creative to generate questions – not answer them – encouraging viewers to seek out more details online. 

That’s where Apple’s search-optimized landing pages, YouTube product videos, and paid search campaigns complete the journey.

Progressive: Connecting humor to searchable characters

Progressive’s long-running “Flo” campaign shows how consistent creative storytelling translates into search intent. 

The insurance brand’s TV spots spark curiosity around characters, slogans, and offers – leading to measurable spikes in branded searches such as “Progressive car insurance” and “Flo from Progressive.”

Google Trends - Progressive Insurance-related search terms

The brand’s media team aligns paid search and display campaigns with national TV flighting schedules, ensuring that when interest peaks, search ads and organic results are ready to capture demand.

Coca-Cola: The shareable, searchable ad

Coca-Cola’s “Share a Coke” campaign is another classic case of TV leading to search. 

The original “Share a Coke” campaign was launched in Australia in 2011 and involved replacing the Coca-Cola logo on bottles with hundreds of popular first names. 

This personalization strategy was a global success, encouraging consumers to find bottles with their names and share them with friends and loved ones, which boosted sales and created emotional connections with the brand.

The latest “Share a Coke” campaign is a global relaunch targeting Gen Z with a focus on digital experiences and authentic, in-person connections. 

It features personalized cans, a digital “Memory Maker” tool for creating shareable videos, and a partnership with McDonald’s. 

Consumers can find names on bottles or use a QR code to customize bottles – a creative hook that’s sent millions to Google searching “custom Coke” or “share a Coke names.”

Google Trends - Coke-related search terms

The campaign’s success wasn’t just creative; it was data-driven. 

By tracking spikes in branded search and social mentions, Coca-Cola refined its targeting and extended the campaign’s life cycle online.

Dig deeper: Hyper-personalization in PPC: Using data to deliver tailored ad experiences

Measuring creative effectiveness with real audience signals

What makes the new “Breaking TV Ads” report particularly valuable is its data-driven framework for measuring creative effectiveness.

Kinetiq’s proprietary ad detection technology identifies every ad that first airs across 210 U.S. DMAs and 15 streaming apps, capturing over a million daily detections. 

DAIVID’s AI then evaluates each ad’s emotional response, attention, and brand recall, creating a creative effectiveness score (CES) – a composite metric that mirrors how audiences actually experience content.

In a media landscape increasingly defined by short attention spans and fragmented screens, this data provides a rare window into why certain stories break through – and how that resonance correlates with downstream behaviors like search and site visits.

As Kinetiq CEO Kevin Kohn put it, the partnership “gives marketers a holistic view of the TV and CTV advertising landscape – not just what aired, but why it resonated.”

That’s exactly the kind of insight performance marketers need to connect the dots between creative resonance and measurable outcomes.

Dig deeper: Your ads are dying: How to spot and stop creative fatigue before it tanks performance

What this means for SEO and PPC strategy

In February 2025, Neal Mohan, the CEO of YouTube, revealed that: 

  • “TV has surpassed mobile and is now the primary device for YouTube viewing in the U.S. (by watch time), and according to Nielsen, YouTube has been #1 in streaming watch time in the U.S. for two years.”

So, search marketers can apply the latest findings from the Breaking TV Ads Report in several ways:

  • Anticipate search spikes: When a high-emotion or celebrity-driven TV ad launches, expect branded searches to rise. Align PPC budgets, ad copy, and keyword targeting around campaign themes and taglines.
  • Optimize for intent moments: TV ads often generate “navigational” queries (brand name) and “informational” ones (product details, offers, or reviews). Ensure that organic content – landing pages, FAQs, and YouTube videos – are optimized to match these queries.
  • Sync search campaigns with TV flighting: Use ad scheduling to mirror TV airtime or streaming rollouts. Research from Nielsen Catalina Solutions shows that coordinated campaigns can deliver up to 60% higher conversion lift compared to siloed efforts.
  • Track branded search as a creative KPI: Branded search volume is one of the most reliable proxies for ad impact. Use tools like Google Trends or Search Console to monitor shifts after major media bursts.
  • Leverage emotional triggers in copy: DAIVID’s data shows that ads evoking strong positive emotions drive higher attention and brand recall. Translate those emotional cues into ad extensions, headlines, and meta descriptions that mirror what audiences feel after seeing the TV spot.

Why the future of performance marketing is cross-channel

Search has long been viewed as a response channel – the final step in a consumer journey. But that view is outdated.

Today’s most successful campaigns use search as a connective tissue between offline inspiration and online action. 

Whether it’s a QR code at the end of a TV ad, a YouTube masthead following a primetime spot, or a Google Shopping ad that captures post-broadcast demand – search is the bridge between storytelling and sales.

As more brands invest in connected TV (CTV) and streaming, the line between “brand” and “performance” marketing will continue to blur. 

Creative effectiveness data helps close that gap – showing which emotional and visual cues are most likely to drive measurable search and conversion behavior.

Ultimately, reports like “Breaking TV Ads” remind us that the most powerful search strategy begins long before the query. 

It begins with attention and emotion, and, increasingly, on the biggest screen in the house.

Dig deeper: How connected TV advertising drives search demand

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Breakthrough TV creative continues to spark search demand. Learn what top ads reveal about emotion, attention, and user behavior.

Search Engine Land celebrates its 19th birthday

Search Engine Land turns 19

Search Engine Land turns 19 today.

Nineteen years. Almost two decades of analyzing, explaining, questioning, challenging, obsessing over, and occasionally shaking our heads at whatever Google and the search industry throw our way.

And this past year? The pace of change has made it one of the most transformative since we launched in 2006.

Through all of it, our mission is the same as Day 1: help you make sense of search with clear news, smart analysis, and practical guidance.

Before we look ahead, I want to say thank you — and take a moment to reflect on the past year at Search Engine Land.

Thank you for reading

Seriously, thank you.

Every day, we start with you: what you need to know, what actually matters, and what changes could shape your work today or your strategy six months from now.

We aim to:

  • Focus on the stories that matter – not noise or filler.
  • Deliver news quickly and clearly.
  • Add essential context, expertise, and nuance.
  • Be a reliable resource in an industry that seems to shift by the hour.
  • Help you see where search is headed — even when the path isn’t obvious.

If you haven’t yet, subscribe to our daily newsletter for a curated wrap-up of everything happening in search. It’s still the easiest way to stay informed without feeling overwhelmed.

Thank you to the Search Engine Land team

Search Engine Land has always punched above its weight for one reason: the people.

A small team can do big, meaningful work when everyone is aligned, mission-driven, and a little obsessed with search.

A huge thank-you to:

  • Barry Schwartz. Barry has been covering search for 22 years and still writes with the speed, curiosity, and energy of someone newly in love with the beat. Search would be far less understandable without him.
  • Anu Adegbola. Anu has become essential for helping readers navigate nonstop shifts in paid media, analytics, and platform changes. Her clarity and steadiness shine in every piece.
  • Angel Niñofranco. Angel keeps our Subject Matter Expert program running. Editing, wrangling, scheduling, coaching, coordinating — if you’ve enjoyed our SME articles, you’ve seen Angel’s impact.
  • Kathy Bushman. Kathy makes SMX happen. Her behind-the-scenes work is why our events run smoothly, deliver value, and earn rave reviews year after year.

And to the entire Third Door Media team within Semrush — thank you. Whether or not your name appears here, your work matters and is appreciated.

Top highlights from the past year

In a year defined by uncertainty, it was encouraging to see so many people continue to rely on Search Engine Land as a trusted community resource. And Search Engine Land had a strong 2025.

SMX Advanced returned in person for the first time in 6 years

This was the standout moment of the year. Bringing SMX Advanced back in person after six years felt overdue and incredibly energizing.

Attendance exceeded expectations, sessions were packed, and hallway conversations felt like a reunion of the search marketing community. You could feel how much people missed connecting face-to-face — debating AI’s impact on search, swapping tactics, comparing notes on Google’s latest changes, and simply enjoying each other’s company.

It reaffirmed what we’ve always believed: great things happen when smart marketers share a room. We’re already looking forward to doing it again in Boston, June 3-5.

Defining industry coverage of AI Overviews and the new era of search

This past year brought one of the most dramatic shifts in search since Search Engine Land launched in 2006. Whatever we end up calling this emerging practice, we focused on giving the industry the clarity, context, and reporting it needed.

Readers have told us again and again that Search Engine Land is their go-to source for cutting through the noise during a confusing and often chaotic time. We’re proud that our reporting, explainers, and expert analysis are helping shape the industry’s understanding of where search is headed next.

Subject Matter Expert (SME) program growth

This year brought a surge of new readers and renewed engagement from long-time practitioners. With so many shifts reshaping SEO and PPC – from AI to SERP experiments to advertiser updates – and the continued emergence of GEO, marketers turned to Search Engine Land in record numbers to stay informed.

Our contributors played a significant role in our growth. A huge thank you to all of our excellent SMEs for all the great content and insights you shared in 2025.

Looking ahead: What’s next for Search Engine Land

As we enter our 19th year, our commitment remains unchanged: provide the most trusted, useful coverage of search anywhere.

This year you can expect:

  • A fresh new website design.
  • Continued breaking news coverage across SEO, PPC, AI search, SERP features, and platform changes.
  • Even stronger analysis, guides, and explainers about how search is evolving.
  • SMX programming designed around the realities of AI search.
  • More expert perspectives, data, and clarity in a year that promises even more disruption.

Save the dates:

  • SMX Advanced: June 3-5
  • SMX Next: Nov. 18-19

There’s much more to come – and as always, our goal is to give you the insight and intelligence you need to do your best work.

A brief look back to where it all began

On Dec. 11, 2006, Search Engine Land officially launched with a simple idea: search was becoming not just a tool, but a place. A world. A community. A discipline shaping how people find information and how businesses connect with customers.

Nineteen years later, that world has grown in ways none of us could have imagined. But the core idea still holds:

Search Engine Land is a place to stay informed, to learn, to connect, and to understand the engines driving the modern web.

Thank you for 19 incredible years

On behalf of everyone at Search Engine Land and Semrush, thank you for reading, for sharing our stories, for asking hard questions, for supporting our mission, and for caring so deeply about all things search.

Here’s to the rest of 2025 – and to a successful, healthy, and insightful 2026.

Google December 2025 core update rolling out now

Google released the December 2025 core update today, the company announced.

This is the third core update of 2025 and the fourth major Google algorithm update overall. Earlier this year, Google rolled out the August 2025 spam update, which followed the June 2025 core update and the March 2025 core update.

What Google is saying. Google updated its Search Status Dashboard to state:

  • “Released the December 2025 core update. The rollout may take up to 3 weeks to complete.”

Google added on LinkedIn:

  • “This is a regular update designed to better surface relevant, satisfying content for searchers from all types of sites.”

About core updates. Core updates roll out several times each year. They introduce broad, significant changes to Google’s search algorithms and systems, which is why Google announces them.

Video on this core update. I made this short video a few hours after publishing this story:

What to do if you are hit. Google did not share any new guidance specific to the December 2025 core update. However, in the past, Google has offered advice on what to consider if a core update negatively impacts your site:

  • There aren’t specific actions to take to recover. A negative rankings impact may not signal anything is wrong with your pages.
  • Google offered a list of questions to consider if your site is hit by a core update.
  • Google said you can see some recovery between core updates, but the biggest change would be after another core update.

In short: write helpful content for people and not to rank in search engines.

  • “There’s nothing new or special that creators need to do for this update as long as they’ve been making satisfying content meant for people. For those that might not be ranking as well, we strongly encourage reading our creating helpful, reliable, people-first content help page,” Google said previously.

For more details on Google core updates, you can read Google’s documentation.

Previous core updates. Here’s a timeline and our coverage of recent core updates:

Why we care. With any core update, we often see significant volatility in Google search results and rankings. These updates may improve visibility for your site or your clients’ sites, but some may experience fluctuations or even declines in rankings and organic traffic. We hope this update rewards your efforts and drives strong traffic and conversions.

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This was the third core update and fourth confirmed Google update in 2025. The December core update will take up to three weeks to rollout.
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