Microsoft launches Publisher Content Marketplace for AI licensing

The future of remarketing? Microsoft bets on impressions, not clicks

Microsoft Advertising today launched the Publisher Content Marketplace (PCM), a system that lets publishers license premium content to AI products and get paid based on how that content is used.

How it works. PCM creates a direct value exchange. Publishers set licensing and usage terms, while AI builders discover and license content for specific grounding scenarios. The marketplace also includes usage-based reporting, giving publishers visibility into how their content performs and where it creates the most value.

Designed to scale. PCM is designed to avoid one-off licensing deals between individual publishers and AI providers. Participation is voluntary, ownership remains with publishers, and editorial independence stays intact. The marketplace supports everyone from global publishers to smaller, specialized outlets.

Why we care. As AI systems shift from answering questions to making decisions, content quality matters more than ever. As agents increasingly guide purchases, finance, and healthcare choices, ads and sponsored messages will sit alongside — or draw from — premium content rather than generic web signals. That raises the bar for credibility and points to a future where brand alignment with trusted publishers and AI ecosystems directly impacts performance.

Early traction. Microsoft Advertising co-designed PCM with major U.S. publishers, including Business Insider, Condé Nast, Hearst, The Associated Press, USA TODAY, and Vox Media. Early pilots grounded Microsoft Copilot responses in licensed content, with Yahoo among the first demand partners now onboarding.

What’s next. Microsoft plans to expand the pilot to more publishers and AI builders that share a core belief: as the AI web evolves, high-quality content should be respected, governed, and paid for.

The big picture. In an agentic web, AI tools increasingly summarize, reason, and recommend through conversation. Whether the topic is medical safety, financial eligibility, or a major purchase, outcomes depend on access to trusted, authoritative sources — many of which sit behind paywalls or in proprietary archives.

The tension. The traditional web bargain was simple: publishers shared content, and platforms sent traffic back. That model breaks down when AI delivers answers directly, cutting clicks while still depending on premium content to perform well.

Bottom line. If AI is going to make better decisions, it needs better inputs — and PCM is Microsoft’s bet that a sustainable content economy can power the next phase of the agentic web.

Microsoft’s announcement. Building Toward a Sustainable Content Economy for the Agentic Web

Read more at Read More

Web Design and Development San Diego

Inspiring examples of responsible and realistic vibe coding for SEO

Vibe coding is a new way to create software using AI tools such as ChatGPT, Cursor, Replit, and Gemini. It works by describing to the tool what you want in plain language and receiving written code in return. You can then simply paste the code into an environment (such as Google Colab), run it, and test the results, all without ever actually programming a single line of code.

Collins Dictionary named “vibe coding” word of the year in 2025, defining it as “the use of artificial intelligence prompted by natural language to write computer code.”

In this guide, you’ll understand how to start vibe coding, learn its limitations and risks, and see examples of great tools created by SEOs to inspire you to vibe code your own projects.

Vibe coding variations

While “vibe coding” is used as an umbrella term, there are subsets of coding with support or AI, including the following:

Type Description Tools
AI-assisted coding  AI helps write, refactor, explain, or debug code. Used by actual developers or engineers to support their complex work. GitHub Copilot, Cursor, Claude, Google AI Studio
Vibe coding Platforms that handle everything except the prompt/idea. AI does most of the work. ChatGPT, Replit, Gemini, Google AI Studio
No-code platforms Platforms that handle everything you ask (“drag and drop” visual updates while the code happens in the background). They tend to use AI but existed long before AI became mainstream. Notion, Zapier, Wix

We’ll focus exclusively on vibe coding in this guide. 

With vibe coding, while there’s a bit of manual work to be done, the barrier is still low — you basically need a ChatGPT account (free or paid) and access to a Google account (free). Depending on your use case, you might also need access to APIs or SEO tools subscriptions such as Semrush or Screaming Frog.

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To set expectations, by the end of this guide, you’ll know how to run a small program on the cloud. If you expect to build a SaaS or software to sell, AI-assisted coding is a more reasonable option to take, which will involve costs and deeper coding knowledge.

Vibe coding use cases

Vibe coding is great when you’re trying to find outcomes for specific buckets of data, such as finding related links, adding pre-selected tags to articles, or doing something fun where the outcome doesn’t need to be exact.

For example, I’ve built an app to create a daily drawing for my daughter. I type a phrase about something that she told me about her day (e.g., “I had carrot cake at daycare”). The app has some examples of drawing styles I like and some pictures of her. The outputs (drawings) are the final work as they come from AI.

When I ask for specific changes, however, the program tends to worsen and redraw things I didn’t ask for. I once asked to remove a mustache and it recolored the image instead. 

If my daughter were a client who’d scrutinize the output and require very specific changes, I’d need someone who knows Photoshop or similar tools to make specific improvements. In this case, though, the results are good enough. 

Building commercial applications solely on vibe coding may require a company to hire vibe coding cleaners. However, for a demo, MVP (minimum viable product), or internal applications, vibe coding can be a useful, effective shortcut. 

How to create your SEO tools with vibe coding

Using vibe coding to create your own SEO tools require three steps:

  1. Write a prompt describing your code
  2. Paste the code into a tool such as Google Colab
  3. Run the code and analyze the results

Here’s a prompt example for a tool I built to map related links at scale. After crawling a website using Screaming Frog and extracting vector embeddings (using the crawler’s integration with OpenAI), I vibe coded a tool that would compare the topical distance between the vectors in each URL.

This is exactly what I wrote on ChatGPT:

I need a Google Colab code that will use OpenAI to:

Check the vector embeddings existing in column C. Use cosine similarity to match with two suggestions from each locale (locale identified in Column A). 

The goal is to find which pages from each locale are the most similar to each other, so we can add hreflang between these pages.

I’ll upload a CSV with these columns and expect a CSV in return with the answers.

Then I pasted the code that ChatGPT created on Google Colab, a free Jupyter Notebook environment that allows users to write and execute Python code in a web browser. It’s important to run your program by clicking on “Run all” in Google Colab to test if the output does what you expected.

This is how the process works on paper. Like everything in AI, it may look perfect, but it’s not always functioning exactly how you want it. 

You’ll likely encounter issues along the way — luckily, they’re simple to troubleshoot.

First, be explicit about the platform you’re using in your prompt. If it’s Google Colab, say the code is for Google Colab. 

You might still end up with code that requires packages that aren’t installed. In this case, just paste the error into ChatGPT and it’ll likely regenerate the code or find an alternative. You don’t even need to know what the package is, just show the error and use the new code. Alternatively, you can ask Gemini directly in your Google Colab to fix the issue and update your code directly.

AI tends to be very confident about anything and could return completely made-up outputs. One time I forgot to say the source data would come from a CSV file, so it simply created fake URLs, traffic, and graphs. Always check and recheck the output because “it looks good” can sometimes be wrong.

If you’re connecting to an API, especially a paid API (e.g., from Semrush, OpenAI, Google Cloud, or other tools), you’ll need to request your own API key and keep in mind usage costs. 

Should you want an even lower execution barrier than Google Colab, you can try using Replit. 

Simply prompt your request and the software will create the code, design, and allow testing all on the same screen. This means a lower chance of coding errors, no copy and paste, and a URL you can share right away with anyone to see your project built with a nice design. (You should still check for poor outputs and iterate with prompts until your final app is built.)

Keep in mind that while Google Colab is free (you’ll only spend if you use API keys), Replit charges a monthly subscription and per-usage fee on APIs. So the more you use an app, the more expensive it gets.

Inspiring examples of SEO vibe-coded tools

While Google Colab is the most basic (and easy) way to vibe code a small program, some SEOs are taking vibe coding even further by creating programs that are turned into Chrome extensions, Google Sheets automation, and even browser games.

The goal behind highlighting these tools is not only to showcase great work by the community, but also to inspire, build, and adapt to your specific needs. Do you wish any of these tools had different features? Perhaps you can build them for yourself — or for the world.

GBP Reviews Sentiment Analyzer (Celeste Gonzalez)

After vibe coding some SEO tools on Google Colab, Celeste Gonzalez, Director of SEO Testing at RicketyRoo Inc, took her vibing skills a step further and created a Chrome extension. “I realized that I don’t need to build something big, just something useful,” she explained.

Her browser extension, the GBP Reviews Sentiment Analyzer, summarizes sentiment analysis for reviews over the last 30 days and review velocity. It also allows the information to be exported into a CSV. The extension works on Google Maps and Google Business Profile pages.

Instead of ChatGPT, Celeste used a combination of Claude (to create high-quality prompts) and Cursor (to paste the created prompts and generate the code).

AI tools used: Claude (Sunner 4.5 model) and Cursor 

APIs used: Google Business Profile API (free)

Platform hosting: Chrome Extension

Knowledge Panel Tracker (Gus Pelogia)

I became obsessed with the Knowledge Graph in 2022, when I learned how to create and manage my own knowledge panel. Since then, I found out that Google has a Knowledge Graph Search API that allows you to check the confidence score for any entity.

This vibe-coded tool checks the score for your entities daily (or at any frequency you want) and returns it in a sheet. You can track multiple entities at once and just add new ones to the list at any time.

The Knowledge Panel Tracker runs completely on Google Sheets, and the Knowledge Graph Search API is free to use. This guide shows how to create and run it in your own Google account, or you can see the spreadsheet here and just update the API key under Extensions > App Scripts. 

AI models used: ChatGPT 5.1

APIs used: Google Knowledge Graph API (free)

Platform hosting: Google Sheets

Inbox Hero Game (Vince Nero)

How about vibe coding a link building asset? That’s what Vince Nero from BuzzStream did when creating the Inbox Hero Game. It requires you to use your keyboard to accept or reject a pitch within seconds. The game is over if you accept too many bad pitches.

Inbox Hero Game is certainly more complex than running a piece of code on Google Colab, and it took Vince about 20 hours to build it all from scratch. “I learned you have to build things in pieces. Design the guy first, then the backgrounds, then one aspect of the game mechanics, etc.,” he said.

The game was coded in HTML, CSS, and JavaScript. “I uploaded the files to GitHub to make it work. ChatGPT walked me through everything,” Vince explained.

According to him, the longer the prompt continued, the less effective ChatGPT became, “to the point where [he’d] have to restart in a new chat.” 

This issue was one of the hardest and most frustrating parts of creating the game. Vince would add a new feature (e.g., score), and ChatGPT would “guarantee” it found the error, update the file, but still return with the same error. 

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In the end, Inbox Hero Game is a fun game that demonstrates it’s possible to create a simple game without coding knowledge, yet taking steps to perfect it would be more feasible with a developer.

AI models used: ChatGPT

APIs used: None

Platform hosting: Webpage

Vibe coding with intent

Vibe coding won’t replace developers, and it shouldn’t. But as these examples show, it can responsibly unlock new ways for SEOs to prototype ideas, automate repetitive tasks, and explore creative experiments without heavy technical lift. 

The key is realism: Use vibe coding where precision isn’t mission-critical, validate outputs carefully, and understand when a project has outgrown “good enough” and needs additional resources and human intervention.

When approached thoughtfully, vibe coding becomes less about shipping perfect software and more about expanding what’s possible — faster testing, sharper insights, and more room for experimentation. Whether you’re building an internal tool, a proof of concept, or a fun SEO side project, the best results come from pairing curiosity with restraint.

Read more at Read More

Web Design and Development San Diego

LinkedIn: AI-powered search cut traffic by up to 60%

AEO playbook

AI-powered search gutted LinkedIn’s B2B awareness traffic. Across a subset of topics, non-brand organic visits fell by as much as 60% even while rankings stayed stable, the company said.

  • LinkedIn is moving past the old “search, click, website” model and adopting a new framework: “Be seen, be mentioned, be considered, be chosen.”

By the numbers. In a new article, LinkedIn said its B2B organic growth team started researching Google’s Search Generative Experience (SGE) in early 2024. By early 2025, when SGE evolved into AI Overviews, the impact became significant.

  • Non-brand, awareness-driven traffic declined by up to 60% across a subset of B2B topics.
  • Rankings stayed stable, but click-through rates fell (by an undisclosed amount).

Yes, but. LinkedIn’s “new learnings” are more like a rehash of established SEO/AEO best practices. Here’s what LinkedIn’s content-level guidance consists of:

  • Use strong headings and a clear information hierarchy.
  • Improve semantic structure and content accessibility.
  • Publish authoritative, fresh content written by experts.
  • Move fast, because early movers get an edge.

Why we care. These tactics should all sound familiar. These are technical SEO and content-quality fundamentals. LinkedIn’s article offers little new in terms of tactics. It’s just updated packaging for modern SEO/AEO and AI visibility.

Dig deeper. How to optimize for AI search: 12 proven LLM visibility tactics

Measurement is broken. LinkedIn said its big challenge is the “dark” funnel. It can’t quantify how visibility in LLM answers impacts the bottom line, especially when discovery happens without a click.

  • LinkedIn’s B2B marketing websites saw triple-digit growth in LLM-driven traffic and that it can track conversion from those visits.
    • Yes, but: Many websites are also seeing triple-digit (or more) growth in LLM-driven traffic. Because it’s an emerging channel. That said, this is still a tiny amount of overall traffic right now (1% or less for most sites).

What LinkedIn is doing. LinkedIn created an AI Search Taskforce spanning SEO, PR, editorial, product marketing, product, paid media, social, and brand. Key actions included:

  • Correcting misinformation that showed up in AI responses.
  • Publishing new owned content optimized for generative visibility.
  • Testing LinkedIn (social) content to validate its strength in AI discovery.

Is it working? LinkedIn said early tests produced a meaningful lift in visibility and citations, especially from owned content. At least one external datapoint (Semrush, Nov. 10, 2025) suggested that LinkedIn has a structural advantage in AI search:

  • Google AI Mode cited LinkedIn in roughly 15% of responses.
  • LinkedIn was the #2 most-cited domain in that dataset, behind YouTube.

Incomplete story. LinkedIn’s article is an interesting read, but it’s light on specifics. Missing details include:

  • The exact topic set behind the “up to 60%” decline.
  • Exactly how much click-through rates “softened.”
  • Sample size and timeframe.
  • How “industry-wide” comparisons were calculated.
  • What tests were run, what moved citation share, and by how much.

Bottom line. LinkedIn is right that visibility is the new currency. However, it hasn’t shown enough detail to prove its new playbook is meaningfully different from doing some SEO (yes, SEO) fundamentals.

LinkedIn’s article. How LinkedIn Marketing Is Adapting to AI-Led Discovery

Read more at Read More

Web Design and Development San Diego

Are we ready for the agentic web?

Are we ready for the agentic web?

Innovations are coming at marketers and consumers faster than before, raising the question: Are we actually ready for the agentic web?

To answer that question, it’s important to unpack a few supporting ones:

  • What’s the agentic web?
  • How can the agentic web be used?
  • What are the pros and cons of the agentic web?

It’s important to note that this article isn’t a mandate for AI skeptics to abandon the rational questions they have about the agentic web. 

Nor is it intended to place any judgment on how you, as a consumer or professional, engage with the agentic web.

LinkedIn poll on Copilot Checkout

With thoughts and feelings so divided on the agentic web, this article aims to provide clear insight into how to think about it in earnest, without the branding or marketing fluff.

Disclosure: I am a Microsoft employee and believe in the path Microsoft’s taking with the agentic web. However, this article will attempt to be as platform-agnostic as possible.

What’s the agentic web? 

The agentic web refers to sophisticated tools, or agents, trained on our preferences that act with our consent to accomplish time-consuming tasks.

In simple terms, when I use one-click checkout, I allow my saved payment information to be passed to the merchant’s accounts receivable systems. 

Neither the merchant nor I must write down all the details or be involved beyond consenting to send and receive payment.

For fun, I put this question to four different AI models, and the responses are telling: 

  • Copilot: “The agentic web is an emerging layer of the internet where AI agents can reason and take actions on behalf of people or organizations, turning expressed intent into outcomes while preserving user choice, transparency, and control.” 
  • Gemini: “The agentic web is an evolution of the internet where autonomous AI agents – rather than just human users – interact with websites, APIs, and each other to perform complex tasks and make decisions on our behalf. “
  • Perplexity: “The agentic web is an emerging phase of the internet where autonomous AI agents act as the primary interface, navigating, interpreting, and taking actions across websites and services on behalf of users with minimal human involvement.” 
  • Claude: “The agentic web is an evolution of the internet where AI agents autonomously navigate, interact with, and complete tasks across websites and services on behalf of users.” 

I begin with how different models answer the question because it’s important to understand that each one is trained on different information, and outcomes will inevitably vary.

It’s worth noting that with the same prompt, defining the agentic web in one sentence, three out of four models focus on diminishing the human role in navigating the web, while one makes a point to emphasize the significance of human involvement, preserving user choice, transparency, and control.

Two out of four refer to the agentic web as a layer or phase rather than an outright evolution of the web. 

This is likely where the sentiment divide on the agentic web stems from.

Some see it as a consent-driven layer designed to make life easier, while others see it as a behemoth that consumes content, critical thinking, and choice.

It’s noteworthy that one model, Gemini, calls out APIs as a means of communication in the agentic web. APIs are essentially libraries of information that can be referenced, or called, based on the task you are attempting to accomplish. 

This matters because APIs will become increasingly relevant in the agentic web, as saved preferences must be organized in ways that are easily understood and acted upon.

Defining the agentic web requires spending some time digging into two important protocols – ACP and UCP.

Dig deeper: AI agents in SEO: What you need to know

Agentic Commerce Protocol: Optimized for action inside conversational AI 

The Agentic Commerce Protocol, or ACP, is designed around a specific moment: when a user has already expressed intent and wants the AI to act.

The core idea behind ACP is simple. If a user tells an AI assistant to buy something, the assistant should be able to do so safely, transparently, and without forcing the user to leave the conversation to complete the transaction.

ACP enables this by standardizing how an AI agent can:

  • Access merchant product data.
  • Confirm availability and price.
  • Initiate checkout using delegated, revocable payment authorization.

The experience is intentionally streamlined. The user stays in the conversation. The AI handles the mechanics. The merchant still fulfills the order.

This approach is tightly aligned with conversational AI platforms, particularly environments where users are already asking questions, refining preferences, and making decisions in real time. It prioritizes speed, clarity, and minimal friction.

Universal Commerce Protocol: Built for discovery, comparison, and lifecycle commerce 

The Universal Commerce Protocol, or UCP, takes a broader view of agentic commerce.

Rather than focusing solely on checkout, UCP is designed to support the entire shopping journey on the agentic web, from discovery through post-purchase interactions. It provides a common language that allows AI agents to interact with commerce systems across different platforms, surfaces, and payment providers. 

That includes: 

  • Product discovery and comparison.
  • Cart creation and updates.
  • Checkout and payment handling.
  • Order tracking and support workflows.

UCP is designed with scale and interoperability in mind. It assumes users will encounter agentic shopping experiences in many places, not just within a single assistant, and that merchants will want to participate without locking themselves into a single AI platform.

It’s tempting to frame ACP and UCP as competing solutions. In practice, they address different moments of the same user journey.

ACP is typically strongest when intent is explicit and the user wants something done now. UCP is generally strongest when intent is still forming and discovery, comparison, and context matter.

So what’s the agentic web? Is it an army of autonomous bots acting on past preferences to shape future needs? Is it the web as we know it, with fewer steps driven by consent-based signals? Or is it something else entirely?

The frustrating answer is that the agentic web is still being defined by human behavior, so there’s no clear answer yet. However, we have the power to determine what form the agentic web takes. To better understand how to participate, we now move to how the agentic web can be used, along with the pros and cons.

Dig deeper: The Great Decoupling of search and the birth of the agentic web

How can the agentic web be used? 

Working from the common theme across all definitions, autonomous action, we can move to applications.

Elmer Boutin has written a thoughtful technical view on how schema will impact agentic web compatibility. Benjamin Wenner has explored how PPC management might evolve in a fully agentic web. Both are worth reading.

Here, I want to focus on consumer-facing applications of the agentic web and how to think about them in relation to the tasks you already perform today.

Here are five applications of the agentic web that are live today or in active development.

1. Intent-driven commerce  

A user states a goal, such as “Find me the best running shoes under $150,” and an agent handles discovery, comparison, and checkout without requiring the user to manually browse multiple sites. 

How it works 

Rather than returning a list of links, the agent interprets user intent, including budget, category, and preferences. 

It pulls structured product information from participating merchants, applies reasoning logic to compare options, and moves toward checkout only after explicit user confirmation. 

The agent operates on approved product data and defined rules, with clear handoffs that keep the user in control. 

Implications for consumers and professionals 

Reducing decision fatigue without removing choice is a clear benefit for consumers. For brands, this turns discovery into high-intent engagement rather than anonymous clicks with unclear attribution. 

Strategically, it shifts competition away from who shouts the loudest toward who provides the clearest and most trusted product signals to agents. These agents can act as trusted guides, offering consumers third-party verification that a merchant is as reliable as it claims to be.

2. Brand-owned AI assistants 

A brand deploys its own AI agent to answer questions, recommend products, and support customers using the brand’s data, tone, and business rules.

How it works 

The agent uses first-party information, such as product catalogs, policies, and FAQs. 

Guardrails define what it can say or do, preventing inferences that could lead to hallucinations. 

Responses are generated by retrieving and reasoning over approved context within the prompt.

Implications for consumers and professionals 

Customers get faster and more consistent responses. Brands retain voice, accountability, and ownership of the experience. 

Strategically, this allows companies to participate in the agentic web without ceding their identity to a platform or intermediary. It also enables participation in global commerce without relying on native speakers to verify language.

3. Autonomous task completion 

Users delegate outcomes rather than steps, such as “Prepare a weekly performance summary” or “Reorder inventory when stock is low.” 

How it works 

The agent breaks the goal into subtasks, determines which systems or tools are needed, and executes actions sequentially. It pauses when permissions or human approvals are required. 

These can be provided in bulk upfront or step by step. How this works ultimately depends on how the agent is built. 

Implications for consumers and marketers 

We’re used to treating AI like interns, relying on micromanaged task lists and detailed prompts. As agents become more sophisticated, it becomes possible to treat them more like senior employees, oriented around outcomes and process improvement. 

That makes it reasonable to ask an agent to identify action items in email or send templates in your voice when active engagement isn’t required. Human choice comes down to how much you delegate to agents versus how much you ask them to assist.

Dig deeper: The future of search visibility: What 6 SEO leaders predict for 2026

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4. Agent-to-agent coordination and negotiation 

Agents communicate with other agents on behalf of people or organizations, such as a buyer agent comparing offers with multiple seller agents. 

How it works 

Agents exchange structured information, including pricing, availability, and constraints. 

They apply predefined rules, such as budgets or policies, and surface recommended outcomes for human approval. 

Implications for consumers and marketers 

Consumers may see faster and more transparent comparisons without needing to manually negotiate or cross-check options. 

For professionals, this introduces new efficiencies in areas like procurement, media buying, or logistics, where structured negotiation can occur at scale while humans retain oversight.

5. Continuous optimization over time 

Agents don’t just act once. They improve as they observe outcomes.

How it works 

After each action, the agent evaluates what happened, such as engagement, conversion, or satisfaction. It updates its internal weighting and applies those learnings to future decisions.

Why people should care 

Consumers experience increasingly relevant interactions over time without repeatedly restating preferences. 

Professionals gain systems that improve continuously, shifting optimization from one-off efforts to long-term, adaptive performance. 

What are the pros and cons of the agentic web? 

Life is a series of choices, and leaning into or away from the agentic web comes with clear pros and cons.

Pros of leaning into the agentic web 

The strongest argument for leaning into the agentic web is behavioral. People have already been trained to prioritize convenience over process. 

Saved payment methods, password managers, autofill, and one-click checkout normalized the idea that software can complete tasks on your behalf once trust is established.

Agentic experiences follow the same trajectory. Rather than requiring users to manually navigate systems, they interpret intent and reduce the number of steps needed to reach an outcome. 

Cons of leaning into the agentic web 

Many brands will need to rethink how their content, data, and experiences are structured so they can be interpreted by automated systems and humans. What works for visual scanning or brand storytelling doesn’t always map cleanly to machine-readable signals.

There’s also a legitimate risk of overoptimization. Designing primarily for AI ingestion can unintentionally degrade human usability or accessibility if not handled carefully. 

Dig deeper: The enterprise blueprint for winning visibility in AI search

Pros of leaning away from the agentic web 

Choosing to lean away from the agentic web can offer clarity of stance. There’s a visible segment of users skeptical of AI-mediated experiences, whether due to privacy concerns, automation fatigue, or a loss of human control. 

Aligning with that perspective can strengthen trust with audiences who value deliberate, hands-on interaction.

Cons of leaning away from the agentic web 

If agentic interfaces become a primary way people discover information, compare options, or complete tasks, opting out entirely may limit visibility or participation. 

The longer an organization waits to adapt, the more expensive and disruptive that transition can become.

What’s notable across the ecosystem is that agentic systems are increasingly designed to sit on top of existing infrastructure rather than replace it outright. 

Avoiding engagement with these patterns may not be sustainable over time. If interaction norms shift and systems aren’t prepared, the combination of technical debt and lost opportunity may be harder to overcome later.

Where the agentic web stands today

The agentic web is still taking form, shaped largely by how people choose to use it. Some organizations are already applying agentic systems to reduce friction and improve outcomes. Others are waiting for stronger trust signals and clearer consent models.

Either approach is valid. What matters is understanding how agentic systems work, where they add value, and how emerging protocols are shaping participation. That understanding is the foundation for deciding when, where, and how to engage with the agentic web.

Read more at Read More

Web Design and Development San Diego

7 digital PR secrets behind strong SEO performance

7 digital PR secrets behind strong SEO performance

Digital PR is about to matter more than ever. Not because it’s fashionable, or because agencies have rebranded link building with a shinier label, but because the mechanics of search and discovery are changing. 

Brand mentions, earned media, and the wider PR ecosystem are now shaping how both search engines and large language models understand brands. That shift has serious implications for how SEO professionals should think about visibility, authority, and revenue.

At the same time, informational search traffic is shrinking. Fewer people are clicking through long blog posts written to target top-of-funnel keywords. 

The commercial value in search is consolidating around high-intent queries and the pages that serve them: product pages, category pages, and service pages. Digital PR sits right at the intersection of these changes.

What follows are seven practical, experience-led secrets that explain how digital PR actually works when it’s done well, and why it’s becoming one of the most important tools in SEOs’ toolkit.

Secret 1: Digital PR can be a direct sales activation channel

Digital PR is usually described as a link tactic, a brand play or, more recently, as a way to influence generative search and AI outputs.

All of that’s true. What’s often overlooked is that digital PR can also drive revenue directly.

When a brand appears in a relevant media publication, it’s effectively placing itself in front of buyers while they are already consuming related information.

This is not passive awareness. It’s targeted exposure during a moment of consideration.

Platforms like Google are exceptionally good at understanding user intent, interests and recency. Anyone who has looked at their Discover feed after researching a product category has seen this in action. 

Digital PR taps into the same behavioral reality. You are not broadcasting randomly. You are appearing where buyers already are.

Two things tend to happen when this is executed well.

  • If your site already ranks for a range of relevant queries, your brand gains additional recognition in nontransactional contexts. Readers see your name attached to a credible story or insight. That familiarity matters.
  • More importantly, that exposure drives brand search and direct clicks. Some readers click straight through from the article. Others search for your brand shortly after. In both cases, they enter your marketing funnel with a level of trust that generic search traffic rarely has.

This effect is driven by basic behavioral principles such as recency and familiarity. While it’s difficult to attribute cleanly in analytics, the commercial impact is very real. 

We see this most clearly in direct-to-consumer, finance, and health markets, where purchase cycles are active and intent is high.

Digital PR is not just about supporting sales. In the right conditions, it’s part of the sales engine.

Dig deeper: Discoverability in 2026: How digital PR and social search work together

Secret 2: The mere exposure effect is one of digital PR’s biggest advantages

One of the most consistent patterns in successful digital PR campaigns is repetition.

When a brand appears again and again in relevant media coverage, tied to the same themes, categories, or areas of expertise, it builds familiarity. 

That familiarity turns into trust, and trust turns into preference. This is known as the mere exposure effect, and it’s fundamental to how brands grow.

In practice, this often happens through syndicated coverage. A strong story picked up by regional or vertical publications can lead to dozens of mentions across different outlets. 

Historically, many SEOs undervalued this type of coverage because the links were not always unique or powerful on their own.

That misses the point.

What this repetition creates is a dense web of co-occurrences. Your brand name repeatedly appears alongside specific topics, products, or problems. This influences how people perceive you, but it also influences how machines understand you.

For search engines and large language models alike, frequency and consistency of association matter. 

An always-on digital PR approach, rather than sporadic big hits, is one of the fastest ways to increase both human and algorithmic familiarity with a brand.

Secret 3: Big campaigns come with big risk, so diversification matters

Large, creative digital PR campaigns are attractive. They are impressive, they generate internal excitement, and they often win industry praise. The problem is that they also concentrate risk.

A single large campaign can succeed spectacularly, or it can fail quietly. From an SEO perspective, many widely celebrated campaigns underperform because they do not generate the links or mentions that actually move rankings.

This happens for a simple reason. What marketers like is not always what journalists need.

Journalists are under pressure to publish quickly, attract attention, and stay relevant to their audience. 

If a campaign is clever but difficult to translate into a story, it will struggle. If all your budget’s tied up in one idea, you have no fallback.

A diversified digital PR strategy spreads investment across multiple smaller campaigns, reactive opportunities, and steady background activity. 

This increases the likelihood of consistent coverage and reduces dependence on any single idea working perfectly.

In digital PR, reliability often beats brilliance.

Dig deeper: How to build search visibility before demand exists

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Secret 4: The journalist’s the customer

One of the most common mistakes in digital PR is forgetting who the gatekeeper is.

From a brand’s perspective, the goal might be links, mentions, or authority. 

From a journalist’s perspective, the goal is to write a story that interests readers and performs well. These goals overlap, but they are not the same.

The journalist decides whether your pitch lives or dies. In that sense, they are the customer.

Effective digital PR starts by understanding what makes a journalist’s job easier. 

That means providing clear angles, credible data, timely insights, and fast responses. Think about relevance before thinking about links.

When you help journalists do their job well, they reward you with exposure. 

That exposure carries weight in search engines and in the training data that informs AI systems. The exchange is simple: value for value.

Treat journalists as partners, not as distribution channels.

Secret 5: Product and category page links are where SEO value is created

Not all links are equal.

From an SEO standpoint, links to product, category, and core service pages are often far more valuable than links to blog content. Unfortunately, they are also the hardest links to acquire through traditional outreach.

This is where digital PR excels.

Because PR coverage is contextual and editorial, it allows links to be placed naturally within discussions of products, services, or markets. When done correctly, this directs authority to the pages that actually generate revenue.

As informational content becomes less central to organic traffic growth, this matters even more.

Ranking improvements on high-intent pages can have a disproportionate commercial impact.

A relatively small number of high-quality, relevant links can outperform a much larger volume of generic links pointed at top-of-funnel content.

Digital PR should be planned with these target pages in mind from the outset.

Dig deeper: How to make ecommerce product pages work in an AI-first world

Secret 6: Entity lifting is now a core outcome of digital PR

Search engines have long made it clear that context matters. The text surrounding a link, and the way a brand is described, help define what that brand represents.

This has become even more important with the rise of large language models. These systems process information in chunks, extracting meaning from surrounding text rather than relying solely on links.

When your brand is mentioned repeatedly in connection with specific topics, products, or expertise, it strengthens your position as an entity in that space. This is what’s often referred to as entity lifting.

The effect goes beyond individual pages. Brands see ranking improvements for terms and categories that were not directly targeted, simply because their overall authority has increased. 

At the same time, AI systems are more likely to reference and summarize brands that are consistently described as relevant sources.

Digital PR is one of the most scalable ways to build this kind of contextual understanding around a brand.

Secret 7: Authority comes from relevant sources and relevant sections

Former Google engineer Jun Wu discusses this in his book “The Beauty of Mathematics in Computer Science,” explaining that authority emerges from being recognized as a source within specific informational hubs. 

In practical terms, this means that where you are mentioned matters as much as how big the site is.

A link or mention from a highly relevant section of a large publication can be more valuable than a generic mention on the homepage. For example, a targeted subfolder on a major media site can carry strong authority, even if the domain as a whole covers many subjects.

Effective digital PR focuses on two things: 

  • Publications that are closely aligned with your industry and sections.
  • Subfolders that are tightly connected to the topic you want to be known for.

This is how authority is built in a way that search engines and AI systems both recognize.

Dig deeper: The new SEO imperative: Building your brand

Where digital PR now fits in SEO

Digital PR is no longer a supporting act to SEO. It’s becoming central to how brands are discovered, understood, and trusted.

As informational traffic declines and high-intent competition intensifies, the brands that win will be those that combine relevance, repetition, and authority across earned media. 

Digital PR, done properly, delivers all three.

Read more at Read More

Web Design and Development San Diego

Google: 75% of crawling issues come from two common URL mistakes

Google discussed its 2025 year-end report on crawling and indexing challenges for Google Search. The biggest issues were faceted navigation and action parameters, which accounted for about 75% of the problems, according to Google’s Gary Illyes. He shared this on the latest Search Off the Record podcast, published this morning.

What is the issue. Crawling issues can slow your site to a crawl, overload your server, and make your website unusable or inaccessible. If a bot gets stuck in an infinite crawling loop, recovery can take time.

  • “Once it discovers a set of URLs, it cannot make a decision about whether that URL space is good or not unless it crawled a large chunk of that URL space,” Illyes said. By then it is too late and your site has slowed to a halt.

The biggest crawling challenges. Based on the report, these are the main issues Google sees:

  • 50% come from faceted navigation. This is common on ecommerce sites, where endless filters for size, color, price, and similar options create near-infinite URL combinations.
  • 25% come from action parameters. These are URL parameters that trigger actions instead of meaningfully changing page content.
  • 10% come from irrelevant parameters. This includes session IDs, UTM tags, and other tracking parameters added to URLs.
  • 5% come from plugins or widgets. Some plugins and widgets generate problematic URLs that confuse crawlers.
  • 2% come from other “weird stuff.” This catch-all category includes issues such as double-encoded URLs and related edge cases.

Why we care. A clean URL structure without bot traps is essential to keep your server healthy, ensure fast page loads, and prevent search engines from getting confused about your canonical URLs.

The episode. Crawling Challenges: What the 2025 Year-End Report Tells Us.

Read more at Read More

Web Design and Development San Diego

Microsoft rolls out multi-turn search in Bing

Microsoft today rolled out multi-turn search globally in Bing. As you scroll down the search results page, a Copilot search box now dynamically appears at the bottom.

About multi-turn search. This type of search experience lets a user continue the conversation from the Bing search results page. Instead of starting over, the searcher types a follow-up question into the Copilot search box at the bottom of the results, allowing the search to build on the previous query. Here’s a screenshot of this feature:

Here’s a video of it in action:

What Microsoft said. Jordi Ribas, CVP, Head of Search at Microsoft, posted this news on X:

  • “After shipping in the US last year, multi-turn search in Bing is now available worldwide.
  • “Bing users don’t need to scroll up to do the next query, and the next turn will keep context when appropriate. We have seen gains in engagement and sessions per user in our online metrics, which reflect the positive user value of this approach.”

Why we care. Search engines like Google and Bing are pushing harder to move users into their AI experiences. Google is blending AI Overviews more deeply into AI Mode, even as many publishers object to how it handles their content. Bing has now followed suit, fully rolling out the Copilot search box at the bottom of search results after several months of testing.

Read more at Read More

Web Design and Development San Diego

Why most SEO failures are organizational, not technical

Why most SEO failures are organizational, not technical

I’ve spent over 20 years in companies where SEO sat in different corners of the organization – sometimes as a full-time role, other times as a consultant called in to “find what’s wrong.” Across those roles, the same pattern kept showing up.

The technical fix was rarely what unlocked performance. It revealed symptoms, but it almost never explained why progress stalled.

No governance

The real constraints showed up earlier, long before anyone read my weekly SEO reports. They lived in reporting lines, decision rights, hiring choices, and in what teams were allowed to change without asking permission. 

When SEO struggled, it was usually because nobody rightfully owned the CMS templates, priorities conflicted across departments, or changes were made without anyone considering how they affected discoverability.

I did not have a word for the core problem at the time, but now I do – it’s governance, usually manifested by its absence.

Two workplaces in my career had the conditions that allowed SEO to work as intended. Ownership was clear.

Release pathways were predictable. Leaders understood that visibility was something you managed deliberately, not something you reacted to when traffic dipped.

Everywhere else, metadata and schema were not the limiting factor. Organizational behavior was.

Dig deeper: How to build an SEO-forward culture in enterprise organizations

Beware of drift

Once sales pressures dominate each quarter, even technically strong sites undergo small, reasonable changes:

  • Navigation renamed by a new UX hire.
  • Wording adjusted by a new hire on the content team.
  • Templates adjusted for a marketing campaign.
  • Titles “cleaned up” by someone outside the SEO loop.

None of these changes look dangerous in isolation – if you know before they occur.

Over time, they add up. Performance slides, and nobody can point to a single release or decision where things went wrong.

This is the part of SEO most industry commentary skips. Technical fixes are tangible and teachable. Organizational friction is not. Yet that friction is where SEO outcomes are decided, usually months before any visible decline.

SEO loses power when it lives in the wrong place

I’ve seen this drift hurt rankings, with SEO taking the blame. In one workplace, leadership brought in an agency to “fix” the problem, only for it to confirm what I’d already found: a lack of governance caused the decline.

Where SEO sits on the org chart determines whether you see decisions early or discover them after launch. It dictates whether changes ship in weeks or sit in the backlog for quarters.

I have worked with SEO embedded under marketing, product, IT, and broader omnichannel teams. Each placement created a different set of constraints.

When SEO sits too low, decisions that reshape visibility ship first and get reviewed later — if they are reviewed at all.

  • Engineering adjusted components to support a new security feature. In one workplace, a new firewall meant to stop scraping also blocked our own SEO crawling tools.
  • Product reorganized navigation to “simplify” the user journey. No one asked SEO how it would affect internal PageRank.
  • Marketing “refreshed” content to match a campaign. Each change shifted page purpose, internal linking, and consistency — the exact signals search engines and AI systems use to understand what a site is about.

Dig deeper: SEO stakeholders: Align teams and prove ROI like a pro

Positioning the SEO function

Without a seat at the right table, SEO becomes a cleanup function.

When one operational unit owns SEO, the work starts to reflect that unit’s incentives.

  • Under marketing, it becomes campaign-driven and short-term.
  • Under IT, it competes with infrastructure work and release stability.
  • Under product, it gets squeezed into roadmaps that prioritize features over discoverability.

The healthiest performance I’ve seen came from environments where SEO sat close enough to leadership to see decisions early, yet broad enough to coordinate with content, engineering, analytics, UX, and legal.

In one case, I was a high-priced consultant, and every recommendation was implemented. I haven’t repeated that experience since, but it made one thing clear: VP-level endorsement was critical. That client doubled organic traffic in eight months and tripled it over three years.

Unfortunately, the in-house SEO team is just another team that might not get the chance to excel. Placement is not everything, but it is the difference between influencing the decision and fixing the outcome.

Get the newsletter search marketers rely on.


Hiring mistakes

The second pattern that keeps showing up is hiring – and it surfaces long before any technical review.

Many SEO programs fail because organizations staff strategically important roles for execution, when what they really need is judgment and influence. This isn’t a talent shortage. It’s a screening problem

The SEO manager often wears multiple hats, with SEO as a minor one. When they don’t understand SEO requirements, they become a liability, and the C-suite rarely sees it.

Across many engagements, I watched seasoned professionals passed over for younger candidates who interviewed well, knew the tool names, and sounded confident.

HR teams defaulted to “team fit” because it was easier to assess than a candidate’s ability to handle ambiguity, challenge bad decisions, or influence work across departments.

SEO excellence depends on lived experience. Not years on a résumé, but having seen the failure modes up close:

  • Migrations that wiped out templates.
  • Restructures that deleted category pages.
  • “Small” navigation changes that collapsed internal linking.

Those experiences build judgment. Judgment is what prevents repeat mistakes. Often, that expertise is hard to put in a résumé.

Without SEO domain literacy, hiring becomes theater. But we can’t blame HR, which has to hire people for all parts of the business. Its only expertise is HR.

Governance needs to step in.

One of the most reliable ways to improve recruitment outcomes is simple: let the SEO leader control the shortlist.

Fit still matters. Competence matters first. When the person accountable for results shapes the hiring funnel, the best candidates are chosen.

SEO roles require the ability to change decisions, not just diagnose problems. That skill does not show up in a résumé keyword scan.

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

When priorities pull in different directions

Every department in a large organization has legitimate goals.

  • Product wants momentum.
  • Engineering wants predictable releases.
  • Marketing wants campaign impact.
  • Legal wants risk reduction.

Each team can justify its decisions – and SEO still absorbs the cost.

I have seen simple structural improvements delayed because engineering was focused on a different initiative.

At one workplace, I was asked how much sales would increase if my changes were implemented.

I have seen content refreshed for branding reasons that weakened high-converting pages. Each decision made sense locally. Collectively, they reshaped the site in ways nobody fully anticipated.

Today, we face an added risk: AI systems now evaluate content for synthesis. When content changes materially, an LLM may stop citing us as an authority on that topic.

Strong visibility governance can prevent that.

The organizations that struggled most weren’t the ones with conflict. They were the ones that failed to make trade-offs explicit.

What are we giving up in visibility to gain speed, consistency, or safety? When that question is never asked, SEO degrades quietly.

What improved outcomes was not a tool. It was governance: shared expectations and decision rights.

When teams understood how their work affected discoverability, alignment followed naturally. SEO stopped being the team that said “no” and became the function that clarified consequences.

International SEO improves when teams stop shipping locally good changes that are globally damaging. Local SEO improves when there is a single source of location truth.

Ownership gaps

Many SEO problems trace back to ownership gaps that only become visible once performance declines.

  • Who owns the CMS templates?
  • Who defines metadata standards?
  • Who maintains structured data? Who approves content changes?

When these questions have no clear answer, decisions stall or happen inconsistently. The site evolves through convenience rather than intent.

In contrast, the healthiest organizations I worked with shared one trait: clarity.

People knew which decisions they owned and which ones required coordination. They did not rely on committees or heavy documentation because escalation paths were already understood.

When ownership is clear, decisions move. When ownership is fragmented, even straightforward SEO work becomes difficult.

Dig deeper: How to win SEO allies and influence the brand guardians

Healthy environments for SEO to succeed

Across my career, the strongest results came from environments where SEO had:

  • Early involvement in upcoming changes.
  • Predictable collaboration with engineering.
  • Visibility into product goals.
  • Clear authority over content standards.
  • Stable templates and definitions.
  • A reliable escalation path when priorities conflicted.
  • Leaders who understood visibility as a long-term asset.

These organizations were not perfect. They were coherent.

People understood why consistency mattered. SEO was not a reactive service. It was part of the infrastructure.

What leaders can do now

If you lead SEO inside a complex organization, the most effective improvements come from small, deliberate shifts in how decisions get made:

  • Place SEO where it can see and influence decisions early.
  • Let SEO leaders – not HR – shape candidate shortlists.
  • Hire for judgment and influence, not presentation.
  • Create predictable access to product, engineering, content, analytics, and legal.
  • Stabilize page purpose and structural definitions.
  • Make the impact of changes visible before they ship.

These shifts do not require new software. They require decision clarity, discipline, and follow-through.

Visibility is an organizational outcome

SEO succeeds when an organization can make and enforce consistent decisions about how it presents itself. Technical work matters, but it can’t offset structures pulling in different directions.

The strongest SEO results I’ve seen came from teams that focused less on isolated optimizations and more on creating conditions where good decisions could survive change. That’s visibility governance.

When SEO performance falters, the most durable fixes usually start inside the organization.

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

Read more at Read More

Is SEO Dead in 2026?

Is traditional SEO is dead? Not exactly. But definitely evolving. Google still controlled a whopping 89% of all U.S. web traffic in 2025. It’s still a search powerhouse, no doubt, but it isn’t the only show in town anymore.  

SEO as we know it is no more. The way people find information is changing dramatically.

Google’s rolling out 12-plus algorithm changes per day. At the same time, platforms like TikTok, Amazon, and generative AI tools like ChatGPT and Claude are becoming major players in the search game. 

Let’s face it. Traditional SEO tactics aren’t always the best option.  

To succeed, you must adapt.  

In 2026, it’s less about search engine optimization and more about search everywhere optimization.  

Let’s dig into the data for a pulse check on SEO in 2026. 

Key Takeaways

  • SEO isn’t dead, but traditional tactics alone won’t cut it. To stay visible, your strategy must account for AI Overviews, zero-click searches, and shifting user behavior across platforms.
  • AI Overviews and SERP features now dominate page one. If your content isn’t cited or structured for AI, you risk being invisible—no matter your ranking.
  • Brand signals like search volume, authority, and trust matter for AI visbility. Google favors entities, not just pages. Build real-world credibility if you want to rank.
  • Optimize for LLMs and SEO at the same time. Clear formatting, concise answers, and fact-rich content help you rank and get quoted in generative results.
  • Search is no longer just on Google. Users discover content through social media, marketplaces, and AI engines—your optimization strategy needs to reach beyond traditional search.

Is SEO Dead?

Google doesn’t share its search volume data. However, approximations place it in the tens of billions, somewhere over 15 billion per day. 

This shows that SEO still holds weight, but AI and LLM searches are growing. Currently, these platforms account for about 6% of global search volume, which doesn’t seem like much. But when you consider that the number is about triple what it was a year ago, it makes marketers start to take notice.

According to SmartInsights, the top 3 positions carry double-digit click-through rates, but these drop drastically for positions lower down the page. Just look at the chart below: 

A graphic showing Google CTR growth for featured snippets.

This drastic drop highlights how Google’s been steadily moving toward a “zero-click” search experience.  

Does this mean AI Overviews are surely going to kill SEO? Well, no, but they’re definitely shaking things up. In fact, Google’s been moving toward its “answer engine” model and its new AI mode for a while now. 

Features like featured snippets and answer boxes already provide concise information directly on the search results page, reducing the need for users to click through to websites.

This trend is driven by the rise of “zero-click content”—content that’s so comprehensive and informative that it satisfies user intent right on the search engine results page (SERP).

Essentially, users can find their answers without visiting a website.

AI Overviews take the zero-click approach to a whole new level, providing even more content directly in the search results.

A graphic saying "What are the top trends in digital marketing."

So, how do we come to grips with both truths—that zero-click search directly results in less engagement with SEO results and that organic search is still a significant driver of traffic?

A common concern for marketers is that emerging AI engines, like ChatGPT, will kill the industry as we know it. But consider this: AI search engines still rely on Google and other algorithm-driven engines for information.

Instead of assuming SEO is dead, we should consider how SEO works today in conjunction with these trends.

 
The Face of the New SEO Campaign

To understand what success looks like in the new world of search, let’s look at a successful campaign of one of our NP Digital clients, RefiJet. 

RefiJet has quickly become a leader in the motorcycle and auto loan refinancing space over the last decade. But to grow further, they needed to differentiate themselves from competitors and grow their digital footprint, all while AI search was changing the very way the game is played. Their company also faced macroeconomic challenges as high interest rates pushed many borrowers to the sidelines.

Our strategy for them blended new AI search principles with traditional SEO best practices. We focused on traditional technical SEO aspects such as crawlability, site speed, and structured data optimization. These moves boosted RefiJet’s inclusion in AI overviews.

Next, we launched on-page optimization tactics. These were aimed at catching traditional long-tail, high-intent search queries. We also leveraged retrieval-augmented generation (RAG) to showcase RefiJet’s authority in its space and boost citations across the web.

Stats showing the result of NP Digital's campaign with RefiJet.

This blended approach helped RefiJet achieve some pretty eye-catching results:

  • Their SERP features increased 30,800% (that’s not a typo) since May 2024
  • Their rankings in the highly coveted 1-3 slots in Google increased 522% year-over-year
  • Traffic from LLMs is up 2012% and site-wide page views from LLMs are up 7144% year over year.
  • Most importantly, RefiJet’s funded loans from organic search and LLMs are up 178% year over year.

So, no. Traditional SEO is not dead. The “new” strategy just takes a modern, blended approach to modern search problems.   

SEO Isn’t Dying (It’s Just Changing)

So, is SEO dead? At this point, I think you know my answer. 

That would be a resounding no. 

SEO isn’t going anywhere. However, for brands to find success with SEO strategies, there are specific things to keep in mind when developing campaigns. 

We know Google functions more as a discovery engine but here is what else you need to know to dominate SERPs. 

AI Is Taking Up A Larger Portion of the SERPs

If you’ve searched for anything on Google lately, you’ve probably seen it. That big, AI-generated box right at the top—pushing organic results further down the page.

Google’s AI Overviews are live, and they’re eating up prime SERP real estate. For certain keywords, especially broad informational ones, they dominate. And if your content doesn’t get cited in those summaries? You might not even show above the fold.

But it’s not just AI Overviews. Google has been quietly expanding other SERP features too, like interactive knowledge panels, visual product listings, “Discussions and Forums,” and even its experimental AI mode inside Search Labs. The days of ten blue links are long gone.

An example AI overview.
An example AI overview.

This shift doesn’t mean SEO is over. It means we have to rethink how we optimize. Your content still needs to be the best answer, but now it also needs to be the kind of content Google’s AI is willing to quote.

If you haven’t yet, start digging into how AI Overviews work. See which types of pages Google is pulling from. Understand the patterns.

SEO isn’t dying. But the way we earn visibility is shifting. Fast.

Technical Fundamentals Still Matter

Google’s focus isn’t backlinks, keyword density, or a specific SEO metric. Instead, the focus is on a seamless and enjoyable user experience. 

What metrics does Google use to gauge user experience?  

Using a clear navigation structure is a good place to start. If you want people to spend a lot of time on your site, you need to understand how users navigate. This includes using a clear URL structure, enabling breadcrumbs, and linking internally

Core Web Vitals—a set of standardized metrics Google uses to measure real-world page performance—is another good launchpad. These include: 

  • Largest Contentful Paint (LCP): The time from when a user starts loading a page until the largest image or text block is visible in the viewport. Goal: 2.5 seconds or less.  
  • Interaction to Next Paint (INP): The time between a user action, like a click or key press, and the next time it takes for the page to respond. Goal: 200 milliseconds or less.  
  • Cumulative Layout Shift (CLS): How much a webpage’s layout unexpectedly shifts during loading. Goal: A CLS score of less than 0.1.  

Other important user experience metrics include dwell time, time spent on page, bounce rate, and exit rate. You can find these metrics in Google Analytics. 

So, how can you improve user experience? There are a few steps you can take that will positively impact the metrics mentioned above: 

  • Improve site speed: The faster your site loads, the better experience the user will have (We saw the impact this can have in our RefiJet example). You can gauge site speed with tools like PageSpeed Insights and Pingdom.  
Google PageSpeed Insights.
  • Optimize for mobile: You can’t afford to not optimize for mobile, as it accounts for more than 50% of web traffic. Tools like PageSpeed Insights can give you the information you need to start, like eliminating render-blocking resources or reducing unused code. You will also want to consider a responsive design if you’re not already using one. 
Errors found in Google PageSpeed Insights.

Social Search Is Taking A Larger Share

Google remains a powerful tool, but, as we’ve established, it’s no longer the sole player in search and discovery. 

Platforms like TikTok, Reddit, and even voice search engines—such as Alexa and Siri—are reshaping SEO. The question is: Are you reshaping your strategies to match them? 

When Google is deciding what to rank and where to rank it, it looks past its own dataset toward other spots online, like the platforms mentioned above.  

The SproutSocial interface.

Source: https://sproutsocial.com/insights/social-media-search/

All these platforms have one thing in common: They cater to users who prefer quick, conversational, or visual content. 

So, what does optimizing your content strategy to leverage these platforms look like in practice? Each app has its own wrinkles you need to consider to maximize your performance across channels:

  • Reddit: Participate in relevant subreddits and provide value without overtly promoting. 
  • YouTube: Create a combination of long-form and short-form videos, targeting different users on the platform. 
  • Voice search: Focus on conversational keywords and provide clear answers to common questions. 

You may be asking, why don’t users just use those platforms to find what they need? 

They do, but before you say “SEO does not matter,” remember while Google is a search engine, it can provide results from other platforms, making them relevant.  We’ve seen this recently with Reddit results surging to the top of the SERPs, and showing up in a whopping 97.5 percent of Google search queries for product reviews.

As younger audiences use social media or videos more for discovery, Google will continue to update and adapt to meet user needs. And since Google pulls from so many different spaces (not just social), it still offers more reliable results on topics people want to find. 

Take Reddit, for example. It shows up in a whopping 97.5 percent of Google search queries for product reviews. 

Google Loves Brands

As your brand grows, you’ll find your rankings climb because Google takes authority, trustworthiness, and relevance into account. Typically, well-established brands have a higher authority and level of trustworthiness. Branded search volume is the number of searches for keywords containing your brand name on a search engine. This is one of the metrics for tracking growth because it reflects user’s interest and awareness of your brand.  

Let’s consider what happens when you type “men’s running shoes” into Google’s search bar. Here is an example of what you might get: 

A list of results for men's running shoes.

Brands, brands, and more brands. 

If you search my name, Google assumes you want to look at my website, businesses, and information about me or my social accounts. 

Results of a Google search for Neil Patel.

Often, Google assumes that people searching for these terms already know what they want (and likely plan to make a purchase). This is especially the case if a customer is searching for an already well-established brand.  

So, how do you establish your brand?  

Aligning with the E-E-A-T framework is a good start. When your brand exudes Expertise, Experience, Authoritativeness, and Trustworthiness, Google will notice (and so will users).  

To build those signals:

  • Create content that shows off your real-world experience and authority. Think in-depth tutorials or original research. Customer stories help, too.
  • Earn mentions and backlinks from reputable sources. Digital PR matters here.
  • Foster community. Social proof, like reviews, forum engagement, or user-generated content, tells Google and users that your brand is alive and active.

While some argue SEO is dead, building brand authority proves otherwise. In the age of AI and zero-click searches, it’s your ticket to higher rankings and increased visibility. 

To be clear, E-E-A-T doesn’t only help for branded terms. Be sure to optimize for branded and non-branded terms to get in front of the most users. 

Intent Is More Important Than Ever

Google is getting better at understanding intent, and users expect results that feel tailored to what they actually want, not just what they typed. If someone searches “best running shoes,” are they looking to buy now, compare options, or read reviews? If your page doesn’t match that intent, it’s not going to rank or convert.

It’s not just about categories like “informational” or “transactional” anymore, either. Google’s updates and AI enhancements have made search more personalized. Things like location and device type all influence which results appear and in what format.

That means one-size-fits-all content just won’t cut it. You need to build pages that solve specific problems for specific searchers, and make it obvious within the first few seconds that your content delivers the answer.

Look at the top results for your target terms. What kind of experience is Google rewarding? Long guides? Product roundups? Local directories?

When you align with intent, you’re not just improving your SEO, you’re giving users what they came for. And that’s how you win in the long run.

Create Content That’s Friendly For LLMs and SEO (there’s crossover)

Your niche is where your product or services fit in the market. What do you offer, and LLM tools like ChatGPT and Perplexity are changing how people search. Users have the ability to ask a question and get an instant summary. That means your content has to be referenced in this zero-click section of the search.

This is where LLMO (large language model optimization) comes in. It overlaps with SEO in a lot of ways. Clear structure and concise answers are good for both. But there are key differences.

LLMs don’t care about keyword density; they care about relevance and clarity. They’re more likely to pull from well-organized content (read as “easy to parse”) and rich in facts. Formatting matters. Use short copy blocks and bulleted lists to increase readability, and, on the technical side, clean HTML and schema markup help machines understand your content even more.

When it comes to backlinks, they still matter for SEO, but LLMs are more influenced by how well your content explains a topic.

If you want to future-proof your content, think about both: ranking high in search and being the source that LLMs pull from when people skip the SERPs entirely. For example below, well-known and reviewed medical sources pop up for this medical question.

A medical LLM report.

Smart content creators are already optimizing for both worlds. Don’t get left behind.

User-Generated Content/Original Content Matters

Have you noticed that when you search on Google, your results are different than those Google is focusing on rewarding content that actually shows experience.

That’s why original content, especially from real users, is more valuable than ever. Some good examples of this type of content are:

  • Customer reviews
  • Community Q&As
  • Case studies
  • Proprietary research
  • Photos from your team.

Here’s an example of a successful UGC campaign from GoPro:

A UGC campaign example from GoPro

Source: https://www.sevenatoms.com/blog/ugc-marketing-examples

These types of content act as trust signals that feed directly into Google’s E-E-A-T framework (experience, expertise, authoritativeness, and trustworthiness).

If you haven’t already, get familiar with E-E-A-T. It’s the lens Google uses to figure out if your content deserves to rank. And in a world where LLMs are regurgitating the same surface-level info, showing firsthand knowledge is how you stand out.

User-generated content helps with that. So does publishing original insights—whether that’s internal data, lessons learned, or your unique take on industry trends. This is the kind of material Google can’t find anywhere else. It’s also what LLMs prefer to cite when pulling answers.

If you’re just rephrasing what’s already out there, you’re invisible. But if you create something worth referencing, both humans and machines will take notice.

Start building a content library that’s not just SEO-optimized, but undeniably your brand.

Focus Metrics Are Changing

Clicks and rankings used to be the gold standard in SEO. Not anymore.

Today, traditional SEO numbers like clicks and rankings only tell part of the story. With AI Overviews and zero-click searches taking over the SERPs, it’s possible to “rank” without getting any traffic. In this new environment, the way we measure success needs to evolve.

Instead of obsessing over position one, look at visibility across AI and SERP features. Are you showing up in AI summaries? In featured snippets? In the “People Also Ask” box? These touchpoints matter more now because they shape user behavior before a click even happens.

Engagement metrics are shifting, too. Scroll depth, dwell time, and interaction with on-page elements can reveal more about content quality than bounce rate ever did. The same goes for branded search volume and return visits—both strong signs that your content is resonating.

Search Everywhere Optimization Has Taken Center Stage

Search engines no longer corner the market on search. Non-search platforms, like social media and generative AI engines, are increasingly being used for search and discovery, disrupting traditional SEO norms. 

This is what search everywhere optimization is all about.  

You can no longer assume that users are only using search engines to find services and products that they need. They’re also using marketplaces (e.g., Amazon, Walmart), social media (e.g., TikTok, Pinterest), and generative AI (e.g., ChatGPT).  

This means you need to expand your search optimization efforts, well, everywhere! Here’s how: 

  • Social media: Platforms like TikTok and Instagram prioritize engaging, visual content. Optimize by using trending hashtags, creating shareable posts, and collaborating with influencers. Forums like Reddit are also highly cited in LLM results.
  • Generative AI engines: Tools like ChatGPT are shaping search behavior by delivering conversational and context-aware responses. Businesses should focus on producing concise, relevant, and authoritative content to rank within these engines. 
  • Marketplaces: Amazon and similar sites act as search engines for product discovery. Ensuring optimized product titles, descriptions, and reviews is crucial. 

We’ve seen this trend of the expanded search surface for a while now, but in 2026, your audience can be found across more platforms than ever. That’s why finding where your audience hangs out, and spending time to see how they’re interacting within the community, is such an important part of modern marketing strategy.

The traditional direct path of top-of-funnel to mid-funnel to bottom-of-funnel doesn’t play anymore. Your audience can convert from virtually anywhere in today’s market. Understand where they are, understand how they’re interacting, and understand the nuances of marketing on each platform, and you’ll be good to go.

FAQs

 

Is local SEO dead?

Not even close. Local SEO remains essential for businesses that rely on local customers. In fact, features like the local pack, Google Business Profiles, and map results are highly influential, especially on mobile. What’s changing is how users find you. Optimize for reviews and local content to stay competitive.

How long will SEO exist?

SEO is here to stay, but it continues to evolve. As long as people use search engines, social platforms, and AI tools to discover information, SEO will exist, even if tactics evolve. 

Conclusion

SEO isn’t dead; it’s adapting to how people search today.

With AI reshaping the SERPs and user behavior shifting fast, what worked five years ago won’t cut it now. But the fundamentals still matter: create useful content, match search intent, and build trust with your audience.

If you’re unsure where to start, look at your content strategy. Are you prioritizing originality and structure? That’s what both Google and LLMs are rewarding.

Now’s also the time to rethink how you measure success. Traffic is great—but brand signals like engagement and trust are carrying more weight, and will only grow in importance in the future.

Want more tactical advice? Check out our guides on search engine trends and how to improve your SEO rankings.

Modern platforms like AI didn’t kill SEO; they just made it smarter. And we all need to follow suit.

Read more at Read More

Web Design and Development San Diego

Google Ads API update cracks open Performance Max by channel

Is your account ready for Google AI Max? A pre-test checklist

As part of the v23 Ads API launch, Performance Max campaigns can now be reported by channel, including Search, YouTube, Display, Discover, Gmail, Maps, and Search Partners. Previously, performance data was largely grouped into a single mixed category.

The change under the hood. Earlier API versions typically returned a MIXED value for the ad_network_type segment in Performance Max campaigns. With v23, those responses now break out into specific channel enums — a meaningful shift for reporting and optimization.

Why we care. Google Ads API v23 doesn’t just add features — it changes how advertisers understand Performance Max. The update introduces channel-level reporting, giving marketers long-requested visibility into where PMax ads actually run.

How advertisers can use it. Channel-level data is available at the campaign, asset group, and asset level, allowing teams to see how individual creatives perform across Google properties. When combined with v22 segments like ad_using_video and ad_using_product_data, advertisers can isolate results such as video performance on YouTube or Shopping ads on Search.

For developers. Upgrading to v23 will surface more detailed reporting than before. Reporting systems that relied on the legacy MIXED value will need to be updated to handle the new channel enums.

What to watch:

  • Channel data is only available for dates starting June 1, 2025.
  • Asset group–level channel reporting remains API-only and won’t appear in the Google Ads UI.

Bottom line. The latest Google Ads API release quietly delivers one of the biggest Performance Max updates yet — turning a black-box campaign type into something advertisers can finally analyze by channel.

Read more at Read More