AI Search Is Becoming Agentic: How I Would Prepare a Brand Now

Caleb Turner on August 11, 2026

How brands can earn AI visibility, selection, and agentic action

There are two distinct things happening in AI search, and I think most people are blurring the lines between them.

First, there’s AI search optimization. That’s about being found, understood, cited, and picked when someone asks an AI a question your brand could answer. Second, there’s agentic optimization. That’s different. That’s about helping an AI actually finish a task on your site, whether that’s booking something, buying something, or filling out a form.

Both matter. Neither is optional anymore. That’s the whole game in a nutshell. Get retrieved, get understood, get chosen, and make sure the path after that doesn’t fall apart.

Key takeaways:

AI search recommends, agentic search acts, and your site needs to be ready for both.
SEO fundamentals are still the base everything else should be built on.
Clear facts, direct answers, and credible mentions drive both retrieval and preference.
Semantic HTML and stable forms make your site usable for agents, not just humans.
Measure real business outcomes, not just how often you get cited.

What Is the Difference Between AI Search and Agentic Search?

Here’s the real difference between AI search and agentic search. It comes down to what happens after the system finds the information.

AI search retrieves sources, weighs the evidence, and hands you a recommendation. Agentic search doesn’t stop there. It can include navigating a site, filling out a form, checking if something’s in stock, requesting a quote, or knocking out whatever task actually needs doing. In this way, it serves as the user’s “agent”.

A few ways to think about where each approach draws the line:

Traditional SEO asks one question: can a human or machine even find this page?
AEO and GEO push further: can the machine understand the content, retrieve it, cite it, and actually prefer this brand over the next one?
Agentic optimization goes a step beyond that: can the machine get the user’s goal accomplished with this specific business, not just talk about it?

I got into some of this with Tory Gray, an SEO strategist I interviewed recently. I didn’t want another surface-level chat about ranking in ChatGPT. We dug into rendering, prompt tracking, server logs, the standards still taking shape, and what agents might actually start doing on a website soon.

Tory made a point that I agree with. AI search is mostly SEO with a few new channels bolted on. Agentic work is a different animal entirely. The bots are different, the actions are new, the requirements keep shifting, and nobody has measurement fully figured out yet.

I agree with her on that one.

Why Does Agentic Search Matter Now?

Here’s what I’m seeing right now, and I think most people are misreading it.

Google Agent is Google’s named fetcher for Google-hosted agents that can navigate the web and act on a user’s behalf. That’s it. It’s not a product name you’ll see marketed anywhere, and it’s definitely not Googlebot. Googlebot builds the search index. Google Agent represents something different: a live task being carried out on someone’s behalf in real time on behalf of the user. And as I mentioned earlier, this is agentic search.

I’ll be straight with you, it’s not a complete picture either. Google hasn’t mapped this identity to every agentic product it runs, so we’re looking at part of the activity, not all of it.

Project Mariner as a standalone experiment is done. But don’t mistake retirement for disappearance. That browser automation work didn’t vanish; it just moved. You’ll find it now inside Gemini Agent and baked into the agentic features showing up in AI Mode. Chrome Auto Browse also now delivers the same broader class of browser automation directly inside Chrome.

If you care about search strategy, AI Mode is where I’d focus. Google has said the action layer there can pull together live web browsing, partner integrations, the Knowledge Graph, and Google Maps all at once.

On my end, I keep the traffic separated because lumping it together tells you nothing useful. Googlebot, OAI SearchBot, Claude SearchBot, and PerplexityBot are your search and indexing crawlers, plain and simple.

ChatGPT User, Claude User, and Perplexity User are different; that’s user-directed retrieval: someone asked for something specific, and the bot went and got it. Then you’ve got Google Agent and signed ChatGPT Agent traffic, which can mean actual operation on a site. And local browser agents are the trickiest of all, because half the time they just look like normal human traffic.

Here’s why any of this should matter to you. A brand can do everything right. Rank well, get recommended by the AI, check every box, and still lose the customer at the finish line. Why? Because the agent hit a firewall challenge, or got stuck on a CAPTCHA, or timed out, or ran into a broken form, or the page was labeled in a way the machine couldn’t parse. The visibility battle isn’t the only battle anymore. The second question is whether the path from recommendation to action actually holds up, and it needs to hold up for machines just as much as it does for people.

How Should You Optimize for AI Search?

I recommend starting with the pages closest to revenue. The service and product pages that actually drive decisions. That kind of page has to answer the main question immediately, make it obvious who it’s for, walk through what working together looks like, and handle the objections buyers already have in their head before they even ask.

Here’s the part most people miss. Every section should ideally give its answer right away, not three sentences in, after some warm-up. AI systems usually pull a single chunk of a page, not the whole thing. If that chunk can’t stand on its own, it never gets used, no matter how good the rest of the page is.

Once the on-site work actually holds up, I go look everywhere else. Because that’s really where trust gets built or lost.

Getting retrieved is step one. Getting picked is a completely different issue, and it often comes down to whether the evidence outside your website backs up what you’re claiming on it.

How Should You Make Your Website Agent-Ready?

Here’s what I actually do when I audit a site for agent readiness. I don’t click through a few pages and call it good. I run the entire flow start to finish, whether that’s a quote, a booking, a checkout, an application, or just a basic contact form. That’s where the real problems live, not in some surface-level page review.

I check the real links, real buttons, real labels, real inputs, and real select controls. Every interactive element needs a name a machine can actually read, and every label has to be properly tied to its field. This isn’t optional anymore. Chrome has said flat out that agents rely on the accessibility tree to understand a page, so accessible names, stable layouts, and the emerging WebMCP support matter more than most people realize right now.

Rendering is where things tend to fall apart. If your JavaScript is fragile, some retrieval systems only see half the page, sometimes an empty shell and nothing else. And if your layout shifts late, an agent can click the wrong thing simply because a button moved half a second too late. So my audit covers all of it. The raw HTML response, what actually renders, the accessibility tree, layout shift behavior, server responses, and whether the whole workflow completes cleanly from start to finish.

Example: An Agentic Local-Service Journey

Let me walk through a real example, because I think this is where people get the mental model wrong.

Someone asks an AI assistant to find a reputable roof cleaner near Charleston, one that does soft washing, and they want an estimate this week. The first job for the system is just finding businesses that actually fit that ask. That part is SEO and AEO. It’s pulling from search results, maps, service pages, reviews, whatever signal exists out there.

Then comes the sorting. Out of everything it found, which business actually matches what this person needs? Location, method, reputation, can they even get there this week, whatever proof exists that this company is the real deal. That’s not regular SEO doing the work anymore. That’s AEO, relevance optimization, and maybe conversion rate optimization deciding who earns the pick.

Here’s the part most people miss, though. Even after a brand wins that comparison, even after it’s clearly the best match, there’s still a third job waiting. The system has to go to that website and actually submit the estimate form on the person’s behalf. This third job is where agentic search comes into play.

And I’ve watched good businesses lose leads they already won right here. The form doesn’t fill in correctly. It hits a bot detector and stalls. The fields are vague or mislabeled, so the system can’t figure out what goes where. All that effort getting found and getting picked, and it falls apart because the technical door never opened.

Which Emerging Technologies Deserve Attention?

I want to flag a few emerging technologies worth watching, because they’re tied to real business use cases instead of just being noise. WebMCP, mentioned earlier in this article, is the one I’m paying closest attention to. Chrome describes it as a proposed standard for exposing structured website tools to AI agents. So instead of an agent fumbling through a form field by field, guessing what goes where, it could just call a defined tool request_estimate and skip straight to the outcome.

That said, WebMCP is still in the early days. I wouldn’t commit serious engineering time to it unless you’ve got a repeatable, valuable action that actually justifies the build.

The same logic applies to llms.txt. It’s not a proven ranking factor, but it can help AI agents understand and navigate through a website, which is where I see potential value.

Google’s Open Knowledge Format is a different thing entirely. It structures portable knowledge in Markdown with metadata, but it’s not a universal standard for public search or website actions. People blur these together, and it just creates confusion.

How Should You Measure AI Search and Agentic Performance?

I measure AI search and agentic performance across behavior, visibility, and business results. Tory and I got into this exact model because citations alone don’t prove anything. A brand can get cited all day and still not see a dime of value from it.

Start with the logs. Go into your server and CDN logs and see which bots and agents are actually touching your assets, and whether they’re getting blocked with 403s, throttled with 429s, timing out at 499, or hitting 5xx errors. When speaking about agentic bots: Google Agent and verified, signed ChatGPT Agent traffic deserves first-class treatment in your metrics. But here’s the blind spot nobody talks about enough. Claude in Chrome, Browse with Copilot, Perplexity Comet, and a growing pile of custom agents often just look like regular browser traffic. You won’t always know an agent touched your site unless you go looking for it.

From there, track a stable set of high-intent prompts over time. Watch for mentions, citations, which sources get selected, whether the facts are even accurate, and your share of voice against competitors. This is directional. It’s a sample, not a real record of what real customers are doing across every possible query.

Then tie it all back to something that actually matters. Qualified traffic, assisted conversions, leads, and revenue. I said this in an interview and I’ll say it again. I care about revenue. I care about leads. I care about driving real business value from this work. Visibility is a leading indicator; it tells me something is working before the revenue shows up, but it’s never the final score.

Which Tools Help Research and Measure This Shift?

There’s a plethora of new tools flooding the market right now, and honestly, most of them do very specific jobs. Exa pulls relevant webpages and passages for AI systems. DataForSEO gives you the bigger picture on SEO and AEO data. SerpApi shows you exactly what a search interface is returning at a given moment. Different tools, different purposes.

Here’s what I’ve learned running SEO Rank Media. The tool itself isn’t the point. What matters is whether it gets my clients the result they actually need. So we use all of it, plus our own internal AI and automation, to pull in the kind of information that actually moves the needle.

At the end of the day, I’m not trying to sell anyone on a piece of software. I’m building a strategy around the business in front of me, and I’ll pull whatever tool fits that job. That’s the whole approach. Customize first, then figure out which tools get you there.

What Should You Do Next?

Preparation for agentic search comes down to the path from discovery to recommendation to action, and you need to strengthen every step of it.

Start with the technical SEO foundation. Then make your key claims answer-ready, so an AI can actually pull them out and use them without guessing. After that, go audit how AI tools are already describing your brand. You might be surprised, and not always in a good way. Last step, and the one people skip, is testing whether an agent can actually complete a real customer journey with you, start to finish.

If you want a real baseline instead of a guess, I offer an AI visibility and agentic readiness audit. Reach out to me, and I’ll show you exactly where your brand is getting retrieved, where you are losing preference to someone else, and where technical friction is quietly blocking your next round of qualified leads.

Google’s New OKF Is Hot. Do You Actually Need It?

Caleb Turner on August 5, 2026

Google’s new OKF is hot off the press. There’s a lot of hype around it, so let me explain what it is and why it may matter to you.

An OKF “bundle” is a directory of Markdown files. Each file explains one concept, such as a product, service, policy, or process, and includes a small block of structured information.

The files can link to one another, creating a connected map of what a business consists of.

That map, at least in theory, could make information about a business easier for AI systems to retrieve, connect, and understand—provided the bundle is accessible to those systems.

Why does that matter?

Before the search and retrieval systems behind Google, ChatGPT, Claude, and other AI platforms can explain your business or recommend it to a potential customer, they must first find, read, interpret, and connect information about it.

Making your business easier for these systems to understand is an important part of relevance optimization for the modern search environment.

Some AI systems use retrieval-augmented generation, or RAG, to locate relevant information and incorporate it into a response.

Others use AI agents—software assistants that can decide what to investigate next, compare multiple sources, and complete a sequence of tasks on a user’s behalf.

OKF is designed to help systems like these consume structured knowledge. Because it uses clearly labeled, linked, plain-text files, it can make relationships between products, services, policies, processes, and other concepts easier to interpret.

That could become useful as more prospective customers turn to Google, ChatGPT, Claude, and similar tools to research products, compare services, and identify businesses.

If these systems can access and correctly understand what your company offers, whom it serves, how its services connect, and why it is credible, your business may be better positioned to appear in relevant research and recommendation workflows.

But OKF Is Not a New SEO Requirement

This is where I’d slow down a bit and make sure we’re making a sober, realistic assessment.

OKF came from Google Cloud’s data and analytics organization, not the Google Search team.

Google has not announced OKF as:

A ranking factor
An AI Overview requirement
An AI Mode optimization feature
A crawler directive
A replacement for schema markup, XML sitemaps, or normal web pages

Does that mean OKF is irrelevant? Absolutely not.

In fact, one could argue that one should not expect Google to tell the whole truth about how to manipulate its systems to rank and recommend you more.

But the fact remains that you should treat any claim that publishing an OKF folder will improve rankings or earn more ChatGPT and Google AI citations as speculation.

This may become a confirmed future use case, but it has not been proven.

Does Your Business Need OKF?

For most small and midsize businesses, my answer today is:

Probably not yet.

A local contractor with weak service pages, inconsistent business information, poor reviews, and indexing problems will not fix those issues by creating an OKF bundle.

The same applies to a professional-services company whose website does not clearly explain who it serves, what it does, where it operates, or why a buyer should trust it.

OKF becomes more relevant when a company:

Has large amounts of valuable knowledge spread across several systems
Is actively developing internal or customer-facing AI agents
Maintains extensive technical documentation, datasets, APIs, or product information

The Bigger SEO and AEO Lesson

Although most businesses probably don’t need to implement OKF today, they should pay attention to what it represents.

My larger takeaway, which hopefully you can also recognize, is that search has moved beyond finding pages that mention the correct words.

AI systems increasingly need to retrieve specific facts, understand how those facts relate, determine which version is current and reliable, and assemble the information into an answer or action on behalf of users.

Your competitive advantage is therefore becoming less about publishing the highest number of pages and more about maintaining the clearest, most reputable, best-connected source of truth.

The New Local SEO Reality: AI Up Top, Trust Still Underneath

Caleb Turner on May 12, 2026

If you want the short version, here’s what I’m seeing right now. Local SEO is still very much alive, but the way people discover and choose local businesses is changing. Google is moving toward a more conversational, AI-engine experience, so it’s not enough to just rank anymore. Your business also needs to be easy for Google to understand, easy for AI systems to summarize, and easy for real people to trust.

I recently sat down with Darren Shaw from Whitespark, and the conversation reminded me why local SEO is still one of the most valuable parts of search.

Darren has been in this space long enough to see local search evolve from simple map pack tactics into a much more sophisticated system of proximity, relevance, reviews, business data, and now AI recommendations.

That kind of perspective matters to me. A lot of people in SEO get distracted by the latest acronym or trend, but what I appreciate about Darren is that he has seen enough cycles to know what actually holds up over time.

The main takeaway of the conversation was pretty simple. AI is changing the way people experience search, but it is not replacing strong local SEO fundamentals. If anything, it is making them even more important.

The local search interface is changing

The local search interface is changing because people are no longer limited to short keyword searches like “plumber near me” or “dentist Dallas.” They are asking longer, more specific questions. They want recommendations based on urgency, preference, trust, location, availability, and context.

That changes the job of local SEO.

For a long time, local SEO was mostly about ranking in the local pack for short keywords. I still think that matters. I just don’t think it tells the whole story anymore. In an AI search environment, the bigger question is whether the system understands your business well enough to recommend it in the right situation.

That’s why I think Google’s Ask Maps feature matters. Google is turning Maps into a Gemini-powered conversational experience where people can ask real-world questions about places and get personalized recommendations based on Maps data. To me, that’s a pretty clear signal. Maps is becoming more than a directory. It’s becoming an AI search layer that helps people make real-world decisions.

When I look at a search like finding a nearby dentist who is good with anxious patients and offers evening appointments, I see a very different kind of intent than a simple “dentist near me” search. The practice that wins that query is usually not just the one closest to the person searching. It is the one with the clearest service information, the strongest reviews, useful supporting content, and enough trust signals that Google feels confident recommending it.

That’s where local SEO is headed.

Local SEO was never just about ranking

I never viewed local SEO as just a rankings play. A local business does not win because it shows up. It wins when someone chooses it. Rankings give you visibility. Selection is what turns that visibility into revenue.

That’s where I see a lot of businesses get stuck. They obsess over where they appear and ignore how they look when a real customer starts comparing options. You can rank well and still lose the lead if your Google Business Profile feels thin, your reviews do not build trust, your photos look outdated, or your service details do not answer the question the buyer actually has.

That matters even more now because AI-driven local search is not just about retrieving businesses. It is comparing them. It is summarizing them. It is trying to decide which option looks most useful for the person searching.

So when I look at local visibility, I want a business to be built for both retrieval and preference. Retrieval means Google can find it and understand it. Preference means the system has enough confidence to show it as the better fit. That’s the standard I care about.

Reviews are one of the strongest trust layers in local SEO

I think reviews are one of the strongest trust layers in local SEO because they influence both rankings and conversions. Darren made that point clearly in our conversation, and I agree with him completely.

A lot of business owners still think about reviews as reputation management. That is part of it, but it’s not the whole story. Reviews are also content. They capture the real customer experience in natural language. People talk about services, staff, neighborhoods, problems, outcomes, wait times, pricing concerns, and the reasons they chose that business in the first place.

That kind of language helps customers decide, but it also helps search systems understand the business at a deeper level.

If patients keep saying a dental office is great with nervous patients, that is a meaningful signal. If homeowners keep mentioning emergency roof repair after storms, that matters too. If restaurant customers keep bringing up gluten-free options, fast service, parking, or atmosphere, that gives useful context.

I think this matters even more in AI local search because the query is getting more conversational. People are not just searching for a category anymore. They’re looking for the right fit.

Review recency matters more than most businesses realize

Review recency matters more than most businesses realize because customers and search systems both care about what’s happening now. A business with a large review count but no recent activity can look stale. A business with fewer total reviews but consistent new reviews can look active, trusted, and relevant.

That does not mean businesses should chase reviews in a sloppy or aggressive way. It means review generation should become part of the operating process. Ask at the right time. Make it easy. Train the team. Use a simple review link or QR code when appropriate. Follow up naturally. Keep the process tied to real customer experience.

The mistake is treating reviews like a one-time campaign. Reviews should be a steady signal that the business is active, trusted, and still delivering.

That is especially important in competitive local markets where every business claims to be the best. Reviews give buyers and AI systems a stronger reason to believe one business over another.

Your Google Business Profile has to be built like a conversion asset

I look at a Google Business Profile as a conversion asset, not a box to check. A lot of local buyers decide who to call before they ever spend much time on a website, so the profile itself has to help you win the click, the call, or the visit.

That is one reason local SEO has been more protected from AI disruption than pure informational SEO. If someone wants a definition or a basic how-to answer, AI may handle that without sending the user anywhere. But if someone needs a dentist, lawyer, plumber, med spa, restaurant, HVAC company, or roofer, they still have to choose a real business.

And a lot of that choice happens inside Google.

Your categories, services, products, photos, reviews, posts, hours, attributes, and business description all shape that decision. Some of those elements can affect rankings. Others do more of the conversion work. I care about both.

I see too many businesses treat their Google Business Profile like a one-time setup task. They choose a category once, add a few photos, write a generic description, and move on. Then they wonder why competitors with stronger profiles keep getting the calls.

That’s not how I approach it.

If your profile is one of the main places customers compare you, it needs to be built intentionally and managed like a living visibility asset.

Categories can quietly make or break local visibility

Categories are one of those local SEO details that seem small until they start costing a business real visibility. I check them early because they tell Google what kind of business it is. If the primary category is too broad or just not aligned with the core offer, you can create a relevance problem before anything else even gets a chance to help.

I see this a lot. A law firm selects “law firm” when the better fit might be personal injury attorney, criminal justice attorney, or bankruptcy attorney. A dental practice might not reflect the services it actually wants to be found for, which means it can miss visibility for higher-intent searches tied to emergency dentistry, cosmetic dentistry, implants, or orthodontics.

This is one of the first things I look at in a local SEO audit because it’s simple, but the impact can be significant. The primary category needs to match the main thing the business wants to be found for. Then the supporting categories, services, website content, reviews, and citations all need to reinforce that same relevance. That’s how I help close the gap between what a business offers and what Google understands.

Citations are still useful, but they are not a magic shortcut

Citations still matter, sure, but I don’t look at them as the shortcut they used to be in local SEO.

I think of them as trust and legitimacy signals.

If a business only shows up on its website and Google Business Profile, that’s a pretty thin footprint. If the same business information shows up consistently across major directories, industry platforms, local sources, review sites, and other trusted third-party profiles, the business looks more established and easier to verify.

I think that matters for Google. I also think it matters even more as AI systems take a bigger role in local discovery.

What I would not do is push a business into hundreds of weak directories just to inflate the count. I would focus on building a clean, consistent presence in the places that actually matter. That usually means major business directories, relevant local sites, industry-specific platforms, review sources, and professional associations.

The right mix depends on the business. If I am working with a lawyer, I am looking at legal directories. If it is a dentist, I want healthcare-related profiles. If it is a home services company, I am thinking about home services platforms, local associations, and trade directories.

I am not after volume here. I am after confidence.

AI local search rewards complete information

AI local search rewards complete information because conversational searches need more context.

A short keyword search might only need a service and a location. But if someone is looking for the best emergency plumber nearby who can come out tonight and has strong reviews, the system has a lot more to evaluate. It has to understand the service, the urgency, the area, the availability, the review quality, and whether the business looks trustworthy.

If your business does not communicate those details clearly, you are asking Google and AI tools to fill in the blanks. I do not like building marketing strategies around guesswork. I would rather feed the system better information.

That starts with the basics. I want the website to answer real buyer questions. I want the Google Business Profile to list clear services. I want reviews that are recent and specific. I want citations to stay consistent. I want photos that build trust. And I want the content to explain who the business helps, what it does, where it works, and why someone should choose it.

This is not about stuffing keywords into every sentence. It is about making the business easier to retrieve, understand, compare, and recommend.

That is the difference I see between old local SEO and local SEO built for AI search.

Old SEO tactics are not enough by themselves

Old SEO tactics are not enough on their own anymore, especially in local search. Google is doing more than matching words. It’s getting more interpretive. It’s trying to understand the business itself, the context around the search, the evidence behind the claims, the sentiment around the brand, and whether the fit is actually right for that customer’s need.

That does not make traditional SEO useless. I still care about the fundamentals. Technical health matters. Crawlable pages matter. Strong content matters. Internal linking, backlinks, local relevance, and clean business data all still do real work.

But now I see those pieces as support for something bigger.

I am not just asking if a business can rank for a keyword. I am asking if Google would feel confident recommending that business for a specific situation.

That shift changes how I approach local strategy.

A generic service page is not enough. A thin Google Business Profile is not enough. A few old reviews are not enough. A list of locations without real local proof is not enough.

If a business wants to win, it has to become the clearest and most credible answer for the situations it wants to own.

That’s the work.

The biggest opportunity is fixing selection, not just visibility

The biggest opportunity is fixing selection, not just visibility. Most businesses want more rankings, but many of them are already leaking leads from the visibility they have.

If your profile gets impressions but few calls, that is a selection problem. If people click your profile but choose a competitor, that is a selection problem. If you rank locally but your reviews, photos, services, and website do not build confidence, that is a selection problem.

This is why I don’t separate SEO from conversion.

A stronger review profile can improve trust. Better photos can reduce hesitation. Clearer services can increase relevance. Better website content can support both users and AI systems. Stronger citations can reinforce legitimacy. A better Google Business Profile can turn more visibility into actual leads.

That is how local SEO should be judged.

Not just “Did rankings move?”

The better question is, “Did the business become easier to find, trust, and choose?

Local SEO is getting more conversational, more personalized, and more influenced by AI, but the goal is still the same. I want the right customers to find your business, trust what they see, and feel confident choosing you.

What has changed is the standard. If you want to show up well in AI local search, your business needs complete information, recent reviews, accurate categories, clear service details, consistent listings, and content that answers the real questions people ask before they ever contact you.

If you want a practical game plan, schedule a call with me. I’ll show you where your local visibility is leaking, what is keeping your business from being preferred, and which fixes I would prioritize first.

Top-Rated SEO Agencies in Los Angeles: How to Find the Right Firm (With a Comparison Framework)

Caleb Turner on February 22, 2026

TL;DR — Top-Rated SEO Agencies in Los Angeles: How to Find the Right Firm (With a Comparison Framework)

If you’re trying to hire an SEO agency in Los Angeles, the best choice is the one that matches your goals, market, and internal capacity, not the one that shows up #1 on a random (and often paid-for) list.

- Build a shortlist using proof (case studies, reviews) and consistent third-party feedback, not hype.

- Define “top-rated” as measurable results, transparent reporting, ethical tactics, and strong communication.

- Use a scoring rubric to compare agencies across services, evidence, reporting, and fit.

- Verify everything: ask for examples, a clear plan, and specifics on how success will be measured.

Why I don’t believe there’s one “best” Los Angeles SEO agency

There isn’t one best Los Angeles SEO agency because the right partner depends on your goals, budget, timeline, and how competitive your market is.

When someone asks me who the “best” firm is, my first question is always: best for what outcome? More calls? More qualified leads? More e-commerce revenue? Visibility in AI answers? Those are different problems, and they require different strengths.

This guide is the exact framework I use when I’m helping someone choose a partner: clear definitions, hard verification, and a simple scoring system.

How to build a qualified shortlist of SEO agencies in Los Angeles

A qualified shortlist of SEO agencies in Los Angeles is built by filtering for proven experience, consistent feedback, and clear specialization.

Here’s how I do it:

1. Start with real constraints.
  Budget range, timeline, what success looks like, and what your team can handle internally.
2. Look for specialization that matches your business model.
  Local service businesses, multi-location brands, e-commerce, and B2B lead generation each have different SEO requirements.
3. Check for consistency, not perfection.
  One glowing testimonial doesn’t matter. Repeated patterns do, especially around communication and delivery.
4. Use referrals as a shortcut to the truth.
  Ask peers what it’s like after the contract is signed.
5. Require proof.
  A serious agency can show you what they did, why they did it, and what changed, without hiding behind vague language.

What “top-rated” should mean (and how to verify it)

A top-rated SEO agency is one that consistently improves the right business metrics, reports transparently, and can explain their strategy clearly.

Here’s what I look for and what you should verify:

Top-rated SEO means measurable results

“Measurable results” means you can tie SEO work to outcomes like leads, revenue, qualified traffic, or visibility improvements, not just rankings.

Verification checklist:

- Real case studies with before/after metrics

- Clear definitions of what improved (and why)

- Context: industry competitiveness, starting point, timeframe

Top-rated SEO means transparent reporting

Transparent reporting means you can see what work was done, what it impacted, and what’s planned next.

Verification checklist:

- A sample report or dashboard

- A cadence you can live with (and actual explanations, not screenshots)

- Ownership clarity: who writes, who optimizes, who builds, who approves

Top-rated SEO means ethical tactics

Ethical tactics mean the work aligns with search engine guidelines, avoids manipulation, and doesn’t rely on “secrets.”

Verification checklist:

- They explain link acquisition plainly

- They’re clear about content quality standards

- They don’t pitch shortcuts that “always work”

Top-rated SEO means realistic commitments

“Realistic commitments” means no one should promise a specific #1 ranking by a fixed date, but a good agency can commit to measurable progress with defined assumptions.

Verification checklist:

- Any “guarantee” is tied to clearly defined visibility or performance metrics

- They explain what variables can change outcomes (competition, technical debt, approvals, site history)

What services a strong Los Angeles SEO agency should offer

A strong Los Angeles SEO agency should cover technical SEO, content strategy, on-page optimization, authority building, and performance tracking.

Depending on your goals, you may also want:

- Local optimization (map presence, location pages, reviews strategy)

- Conversion rate optimization (so traffic turns into revenue)

- Support for AI-driven search visibility (content that’s easy to extract, cite, and trust)

The point isn’t to buy everything. The point is to make sure the agency can deliver what your model needs—without outsourcing critical pieces blindly.

A simple scoring rubric to compare SEO agencies objectively

A scoring rubric helps you compare SEO agencies apples-to-apples by grading the same factors across every proposal.

Score each category from 1 (poor) to 5 (excellent):

Category	What to look for	Score (1–5)
Services	Coverage of technical, content, authority, local (if needed), analytics	1–5
Proof / Evidence	Case studies, references, clear examples, credible outcomes	1–5
Reporting & Communication	Clarity, cadence, access to data, proactive insights	1–5
Fit & Culture	Transparency, collaboration style, industry understanding	1–5

Then add one more filter:
If the agency can’t explain the plan in plain English, the score is irrelevant. Confusion becomes cost.

Example: comparing two common agency “types” in Los Angeles

Comparing two agency types works best when you score them against your priorities, not against each other’s marketing.

Below is an illustrative example using the rubric:

Agency Type	Services	Proof	Reporting	Fit	Who it’s best for
Full-service growth partner	5	4	4	4	Businesses that want one team across SEO + adjacent growth needs
Local SEO-focused lead gen specialist	4	4	3	5	Local businesses that want a tight SEO scope and strong pipeline focus

If you’re a local service business, you might weight fit + local strategy higher. If you’re e-commerce, you might weight technical + conversion higher. The rubric stays the same; the weights change.

FAQs

How many SEO agencies should I interview in Los Angeles?

Interviewing at least three SEO agencies is usually the sweet spot because you’ll hear different strategies, pricing models, and levels of transparency. By the third call, patterns show up fast, especially around what’s fluff versus what’s real.

Should I hire a local Los Angeles SEO agency or a remote one?

Hiring local can help if your success depends on local search dynamics, but location matters less than communication, process, and proof. A remote team can still win if they understand your market, move quickly, and report clearly.

What are the biggest red flags when choosing an SEO company?

The biggest red flags are vague deliverables, unclear reporting, refusal to show proof, and promises that sound too precise to be real. If the agency can’t tell you what they’ll do in month one and how it will be measured, that’s a problem.

What should an SEO proposal include?

An SEO proposal should include scope, deliverables, timeline, KPIs, reporting cadence, and responsibilities on both sides. The best proposals also state assumptions (like implementation access, content approvals, and dev support) so expectations don’t get misaligned.

Choosing a top-rated SEO agency in Los Angeles is about verification and fit, not hype. Build a shortlist with proof, define what “top-rated” means for your business, use a consistent rubric, and don’t be afraid to ask direct questions.

Ready to make the choice easier?

If you want a second set of eyes on your site and a clear plan you can actually act on, my team at SEO Rank Media offers a free consultation and site audit so you can see what’s holding your visibility back and what to fix first.

When you’re ready, schedule a call, and I’ll help you map a practical SEO strategy built for where search is going (including AI-driven discovery), not just where it’s been.

The llms.txt debate: what’s real, what’s hype, and how to use it (safely)

Caleb Turner on October 9, 2025

Short version:
llms.txt is a proposal, not a formal web standard. Some sites ship it; some AI tools and SEO plugins promote it. Google says you don’t need it to show up in AI Overviews or any other Google products.

But: …like any public .txt file, an llms.txt URL can be crawled and indexed, so in rare cases a bare, unstyled text page could show up in search instead of your real, designed page.

I know of someone who created a playful file called cats.txt to make a simple point: Google can index plain text files if they’re publicly accessible and discoverable. In other words, the name doesn’t matter; if it’s a .txt and reachable, it can show up in search, just like any other indexable file type.

If a text file is publicly visible on your site, search engines can list it, which you certainly don’t want. To prevent this, send X-Robots-Tag: noindex in the HTTP response (works for non-HTML files), and if you want to point search engines to the right page, add a Link: <https://your-page>; rel=”canonical” header. Here’s what a real plain-text doc looks like in a browser (the kind that could hypothetically rank if you don’t block indexing):
https://developers.cloudflare.com/llms.txt.

Google’s documentation covers both the noindex response header for non-HTML resources and using an HTTP canonical header.

Below is a clear walk-through, first in plain English (with analogies), then the technical details and safest practices.

What is llms.txt?

llms.txt is a simple text file you put at example.com/llms.txt. The file lists or summarizes your most important pages in Markdown, so AI systems can more easily read and use your content. Think of it like a cheat-sheet menu for bots: “Here are the dishes you should try; here’s how to ingest or interpret them.” It’s inspired by robots.txt and sitemaps, but it isn’t an official protocol like those are, just a community proposal.

Today, there’s no universal adoption. A directory of live implementations shows many developer-tooling/docs sites experimenting, often paired with a bigger llms-full.txt that expands the content.

John Mueller / Google’s stance: In a conversation with Caleb and a few other colleagues, Google’s John Mueller made it clear what side of the debate he’s on. You don’t need llms.txt; the guidance is to keep following normal SEO practices.

Why is there a debate?

John Mueller comment highlighting the llms.txt debate around SEO tools, AI search hype, and whether websites need the file.

The “we don’t need this” camp

Google says it won’t use llms.txt for AI search results, so for many sites this is optional at best.
llms.txt isn’t a standard; support and behavior differ by bot. In other words, don’t expect consistent results.

The “we’re seeing activity in the wild” camp

Practitioners have shared examples and logs showing Google indexing llms.txt pages, alongside surges of bot hits when large platforms roll it out, because it’s just a public text file like any other.
That doesn’t prove Google uses llms.txt for AI search results. It only proves that public .txt files can be crawled and indexed, which Google’s docs have said for years.

A layperson’s guide to the technical bits

robots.txt vs noindex
robots.txt is like a bouncer who tells certain crawlers not to walk certain halls. It doesn’t guarantee your URLs won’t show up in the search phone book (the index). Pages blocked in robots can still be indexed by URL if they’re linked elsewhere. If you truly don’t want a URL in the index, use noindex; that’s a separate rule delivered in HTML or HTTP headers.
X-Robots-Tag and canonical
For non-HTML files like .txt, the right place to control indexing is the HTTP response header.
- X-Robots-Tag: noindex = “don’t list this address in Google.”
- Link: <https://example.com/page>; rel=”canonical” = “If you do need to reference this, use our public address here.” (Google supports canonical in the header for non-HTML formats.)
User-Agent/UA and why blocking by UA isn’t enough
“UA” is the name badge a crawler shows at the door (e.g., Googlebot, GPTBot). You can write per-UA rules in robots.txt, and major AI vendors document their UA strings.

But name badges can be forged; to be sure a request is truly a vendor’s bot, verify by reverse-DNS/IP, not just the UA string. Cloudflare has even accused some AI crawlers of stealth crawling (changing badges and IPs).

“Cloaking” and dynamic rendering
Serving different content to bots than to users is a slippery slope. Google considers cloaking a spam tactic when bots and users see materially different things. Google also deprecated dynamic rendering (bot-only HTML) as a long-term approach. If you want a bot-friendly version, keep the substance the same as what people see.

The cannibalization risk (and how to avoid it)

User reviewing a raw indexed page showing the cannibalization risk of llms.txt replacing a designed website page in search results.

Imagine your llms.txt ranks for a branded query. A searcher clicks and lands on a wall of plain text with no design, navigation, or conversion paths. That’s the risk: poor UX and lost revenue. It’s not hypothetical; plain text files do get indexed, and practitioners have shown real examples of llms.txt and llms-full.txt pages in the index. We also showed an example earlier in this article.

Fix: keep llms.txt fetchable (so AI tools can read it) but non-indexable in web search with:

X-Robots-Tag: noindex

Link: <https://www.example.com/your-preferred-page>; rel=”canonical”

These are HTTP headers on the llms.txt response, not tags inside the file. This is the safest, standards-compliant way to prevent cannibalization while still letting crawlers pull your file.

If you still want to experiment: safest practices

SEO analyst reviewing safe llms.txt testing practices with analytics before experimenting with AI search visibility.

1) Treat llms.txt as optional and experimental

Ship it only if it supports real goals. Keep expectations modest; it’s a proposal, not a protocol.

2) Prevent web-search cannibalization

Serve HTTP headers on llms.txt (and llms-full.txt if you publish one):

X-Robots-Tag: noindex
Optional: Link: <https://www.example.com/the-main-URL>; rel=”canonical”

Think: “Please don’t list this file in the phone book. If you must reference something, here’s the main storefront.”

3) If you want to block certain AI crawlers elsewhere, do it the right way

In robots.txt, write rules per UA (e.g., User-agent: GPTBot). Vendors like OpenAI document their bot names.
For high-stakes data, verify IPs (reverse DNS) because UA strings can be faked. Google documents how to verify Googlebot; similar logic applies to others.
Be aware: some AI bots have been accused of ignoring robots.txt or crawling stealthily, so consider edge-level blocking if needed (WAF/CDN).

4) What to put in llms.txt (if you use it)

Link to canonical, public pages that you want AI systems to cite: FAQs, policies, product specs, pricing explainers, and key how-tos. Keep it concise; don’t dump the whole site.

5) Instrumentation & monitoring

A .txt file is just raw text. Web browsers don’t run code inside it, so you can’t drop a JavaScript analytics snippet (like GA/GTAG) into a .txt file and expect it to fire. Browsers only execute scripts when the content is served as a script/HTML type, not text/plain.

If you still want to see who’s fetching that file, look at your server or CDN access logs. Those logs list every request (time, IP, user-agent, URL, etc.), so you can count hits to /llms.txt even without JavaScript. Examples: Apache’s access log and Cloudflare Logs.

Watch Search Console: If a text file starts appearing in “Indexed,” revisit your headers. Google’s docs confirm indexing can occur even without crawling the content (e.g., when discovered by links).

6) Don’t block JS/CSS for Googlebot

If your SEO defense plan includes blocking scripts to hide unique content from AI, be careful: blocking JS/CSS broadly can break rendering in Google Search. If you must, target AI bots individually, not Googlebot

The bottom line (for decision-makers)

Business decision-maker weighing the pros and cons of llms.txt for AI search strategy and safe SEO implementation.

Not required: Google’s AI Mode doesn’t depend on llms.txt; normal SEO still wins.
Not a standard: It’s a proposal with uneven support. Useful for experimenting, especially for docs-heavy products; not a silver bullet.
If you try it, ship it safely:
- Put it at the root.
  
  Keep it short and link to your best pages.
  
  Send X-Robots-Tag: noindex and, if helpful, a header canonical.
  
  Keep content parity; avoid UA-based “special versions” that diverge.
- If you must block certain AI bots elsewhere, use per-UA robot rules plus IP verification at the edge; be aware of stealth crawlers.

If you want a place to start, you can base your evaluation on current adoption (developer docs, ecosystems, and directories of live files) and any internal log evidence you have about bot hits to llms.txt. Then decide whether it’s worth maintaining a curated cheat sheet for AI or whether your time’s better spent doubling down on structure, internal links, and copy the proven levers. SEO Rank Media is among the leaders in the AI search conversation. Reach out to explore how we can set your brand up for the future.

Caleb Spoke With SEMrush, Here’s What Happened

Caleb Turner on August 25, 2025

I recently compared notes with my good friend Nick Eubanks, VP of Owned Media at SEMrush. We aligned on two truths: 1) classic SEO is table stakes; 2) GEO/AEO is now where growth compounds. Nick also shared what his team is seeing on the ground: traffic from LLM-assisted journeys tends to convert better because people use assistants to research and shortlist—so by the time they hit your site, they’re warmer. In one study, conversion rates were ~4.4× higher from LLM traffic vs. traditional organic. Combined with our own client data, the takeaway is clear: being present in AI answers isn’t a vanity metric—it’s a revenue lever. You can view the full video here.

What actually changed (and why you should care)

Under the hood, AI platforms (like Google’s AI Mode) follow a similar pipeline when they search the web: your content is chunked into passages, embedded as vectors (to capture meaning), fetched by high-speed retrieval, filtered by hybrid re-rankers, and then woven into a natural-language answer. If your passages aren’t crystal-clear semantically, they’re less likely to be pulled into that answer layer. Think “optimize for meaning and entities,” not just keywords.

Google has also published sensible basics for the AI era: keep your site crawlable, avoid blocking AI crawlers (Google-Extended, GeminiBot, GPTBot), use clear headings and schema, and ensure what’s in your structured data actually matches what users see. Over-restrictive snippet settings can remove you from summaries entirely.

No, SEO isn’t dead—it’s your eligibility layer

All of the fundamentals still determine whether you’re “in the pool”:

Technical hygiene: sane robots.txt and open sitemaps; don’t block JS/CSS required to render full pages; allow Google-Extended, GeminiBot, and GPTBot.
On-page semantics: precise H1–H3 hierarchy, answer-like formatting, and schema (FAQ/HowTo/Product/Organization). Write in short, extractable passages with concrete stats and full dates.
Internal links & authority: Interlink topic clusters with descriptive anchors; keep building high-quality links and local citations (they’re still a ranking and trust signal, and they feed AI answers).

Think of this as your eligibility layer. Without it, GEO/AEO can’t help you.

GEO/AEO: the layer that gets you retrieved and quoted

Answer engines select passages, not just pages. That means writing “atomic” content—one idea per paragraph, tight sentences, tables or lists where they help, and entity-rich language (use exact names for people, places, and products, minimize pronouns). Each paragraph should stand alone as a mini-answer that a model can lift verbatim.

Two GEO/AEO practices our clients find immediately useful:

Vector validation: Before publishing, embed your draft passages and check similarity against your target questions. Iterate until the cosine similarity is strong (we treat ≥0.85 as a healthy threshold). It’s a quick way to pre-test “retrievability.”
Monitor AI citations: Track when your URLs surface inside Google AI Mode, Perplexity, and ChatGPT. If citations dip, refresh and tighten the affected passages. This is your “share of voice” in AI.

Local & service businesses

Local SEO is currently less affected by AI search engines. When people search in their local area for services, they almost always search on Google, and more specifically the map pack.

People have evolved to use LLMs to research and compare local businesses, so think of AI search optimization as complementary, not primary, for local service-based businesses.

Local also remains a smart place to invest because the evidence LLMs prefer—real reviews, practitioner bios, photos, and third-party citations—maps cleanly to what local SEO already does well.

Assistants won’t just list options; they’ll recommend one provider and explain why. Help them help you:

Fortify proof: Showcase review excerpts, credentials, and outcomes as short, quotable blocks.
Citations & consistency: Keep your NAP data clean and expand high-relevance local citations; it improves Maps visibility and gives answer engines more reliable signals to quote.

Watch GA4 and Search Console, but with added context: impressions and AI citations often lead the way; raw CTR can be misleading when assistants satisfy the query in-place.

What to do next (simple, high-impact moves)

You don’t need a full overhaul to benefit from GEO/AEO. Start here:

Open the gates: sanity-check robots.txt and server logs; allow Google-Extended, GeminiBot, and GPTBot; keep XML/RSS feeds current.
Make content “answer-able”: give each H2 a direct ≤80-word answer, then details. Use tables/lists for facts and include full dates.
Strengthen semantics: ensure one topic per page, clean H1–H3, and add relevant schema (FAQ/HowTo/Product/Organization).
Validate vectors: quickly test your top five money pages for cosine similarity against priority questions; revise ambiguous phrasing.
Distribute beyond your site: publish the same answers (adapted) across formats—web, video, and communities—because LLMs cite the whole web, not just your domain. For example, studies show that Reddit is a place that AI search engines love to quote from.

Will traditional SEO fade away?

Not in the next five or ten years. People will always compare, verify, and buy; what’s changed is the quality bar and the interface. In our clients’ data and in my conversation with Nick, the brands winning AI placements combine (a) clean technical SEO and authoritative content with (b) GEO/AEO practices that make them more likely to be cited in AI searches. That’s the new landscape for 2025-2026.

The State of SEO in 2025–2026: How to Measure, Adapt, and Thrive in a Decoupled Search Landscape

Caleb Turner on July 15, 2025

The search landscape in 2025–2026 presents both profound challenges and unprecedented, yet exciting, opportunities. The emergence of AI-powered search interfaces (like Google’s AI Mode and ChatGPT-style interactions) has disrupted traditional SEO models. Executives and marketing leaders are grappling with a crucial question: How do we measure SEO performance when the connection between impressions, visibility, and traffic is increasingly blurred?

This article outlines a clear, structured framework for measuring SEO in this new era. Focusing on input metrics, channel metrics, and performance metrics while offering practical guidance for organizations to navigate and succeed in the future of search.

I. Understanding the Decoupling: Traffic Down, Impressions Up

The foundational insight for SEO in 2025–2026 is the “great decoupling”: impressions are increasing, yet traffic is decreasing. Search engine results are no longer a linear, trackable funnel where a keyword ranking translates cleanly into a click.

Key Drivers:

AI-generated answers (ChatGPT, Google’s AI Overviews) reduce the need to click through to websites.
Search console limitations: There’s no equivalent console for AI environments, making it hard to gauge visibility.
Crawlers lack JavaScript rendering, so SEO teams must ensure content is served in HTML and is readily accessible.

This disruption demands a new mindset. Instead of measuring SEO purely as a performance channel, we must also embrace it as a branding and visibility channel, akin to social media or PR.

II. Three Stratified Layers of Measurement

To understand and communicate SEO performance in this AI-driven landscape, measurement must be stratified into three key layers:

1. Input Metrics (What You Control)

These are the levers SEO teams actively manage to influence visibility:

Content relevance scores: Use models to score how well passages of content align with user queries—especially synthetic AI prompts.
Competitor comparison: Benchmark content relevance against sites appearing in AI citations.
Indexability: Ensure content is properly indexed and can be crawled (avoiding reliance on JavaScript rendering).
Bot activity tracking: Monitor how frequently bots request your pages (via logs) to infer visibility across AI platforms.
Technical health: Fixing broken links, optimizing XML sitemaps, improving mobile performance.

Why it matters: These metrics reflect SEO effort and foundational health. While they don’t tie directly to ROI, they inform higher-order outcomes like visibility and traffic.

2. Channel Metrics (How You’re Seen)

These measure visibility and share of voice across platforms—even when user behavior is opaque.

Citation appearance frequency: Are you cited in AI answers (like ChatGPT, Perplexity, etc.)?
Visibility and share of voice: Tools like Profound.ai provide snapshots of how often and where your brand appears.
Sentiment analysis: Gauge tone and context of mentions across platforms.
Competitor visibility benchmarking: Compare brand visibility in key channels vs. rivals.

Caution: These metrics are probabilistic, not deterministic. They lack absolute accuracy due to the black-box nature of AI engines. But with consistent methodology, you can get precise trend data over time.

3. Performance Metrics (What Converts)

While visibility is critical, outcomes still matter. Performance metrics help you assess business impact.

Traffic and referral volume: Track click-throughs to your site (using GA4 or similar).
On-site engagement: Time on site, bounce rates, and session duration remain essential indicators.
Conversion actions: Leads, purchases, newsletter signups—standard KPIs still apply.
Lift studies: Correlate campaigns with subsequent traffic or brand lift (especially when direct attribution is impossible).

Key takeaway: Although attribution is harder, ROI measurement still exists, especially when paired with thoughtful experimentation (e.g., pre/post visibility studies in ChatGPT or Google AI results).

III. Strategic Reporting for Different Stakeholders

Understanding who needs what data is critical in shaping your SEO reporting and communication.

For CMOs and Executive Teams:

Focus on high-level visibility and brand performance.
Show traffic and conversions.
Break visibility into three categories:
- Brand protection: Are people seeing and engaging with your brand positively?
- Category visibility: How do you perform for non-branded industry terms?
- Long-tail specificity: Are you capturing niche but high-intent queries?

For SEO Managers:

Dive deeper into input metrics like content scoring, ranking shifts, crawl stats, and prompt analysis.
Develop frameworks for prompt taxonomy tracking to understand conversational intent.
Monitor bot activity and integrate clickstream data sources like Datos or SimilarWeb for AI-derived referrals.

IV. Tracking Prompts and Redefining Funnel Models

Search is no longer a clean funnel. With conversational AI, users ask multi-turn prompts that don’t always build on each other linearly.

The Challenge:

Prompt chains are hard to track: Subsequent questions often lack reference to the first.
Search intent is messier: Traditional categories (navigational, informational, transactional) fall short.

What to Do:

Start building a new taxonomy of prompts:
- Use machine learning or clustering to group related queries.
- Focus on entity-based tracking rather than keyword tracking.
Advocate for “also asked” datasets for ChatGPT and similar tools.
Track topical coverage over exact matches to ensure visibility across semantic variations.

V. Future-Proofing SEO Strategy

Here’s a blueprint for adapting and thriving in the evolving SEO environment:

1. Adopt Branding-Minded Thinking

Treat SEO as both a traffic driver and a visibility channel. Just like social media, the goal isn’t always a click—it’s awareness, perception, and presence.

2. Monitor New Metrics Religiously

Set up dashboards that reflect the stratified model:

Input (content quality, indexation)
Channel (AI visibility, share of voice)
Performance (engagement, conversions)

3. Invest in Visibility Platforms

Use tools like Profound.ai, Datos, SimilarWeb, and custom log analysis to monitor visibility in AI ecosystems.

4. Prepare for Attribution Limitations

Don’t expect clean lines between exposure and ROI.

Use proxy metrics (like sentiment and citations) as indicators.
Run pre/post experiments to estimate impact.

5. Educate Up and Down

CMOs: Ask your teams to deliver visibility + performance metrics.
SEO Teams: Prepare leadership for a branding-oriented, less attributional future.

VI. Looking Ahead: Ranking’s Role Isn’t Dead—Just Evolving

Contrary to popular belief, rankings still matter—but as an input, not a goal. Even as AI interfaces dominate, they’re still underpinned by traditional ranking models (e.g., RAG—Retrieval-Augmented Generation).

If the major platforms stop showing the “10 blue links,” third-party platforms like Ahrefs or Majestic may recreate ranking-based models to simulate that layer. So, ranking visibility will remain a valuable signal, but not the primary KPI.

Conclusion: Embrace the Complexity, Drive the Clarity

The new SEO frontier is complex, decentralized, and fragmented. Yet it offers an exciting opportunity for marketing leaders and technical SEOs to reshape their strategy around influence, visibility, and user experience—not just clicks.

By adopting a layered measurement strategy, building new taxonomies, and embracing AI as a visibility partner rather than an adversary, brands can position themselves for durable relevance in the next era of search.

Next Steps:

Audit your current SEO reporting and identify gaps in the three-layer framework.
Start tracking AI citations and build prompt-specific monitoring.
Schedule leadership alignment sessions to reframe expectations and educate stakeholders.

The brands that thrive in 2025–2026 won’t cling to outdated KPIs—they’ll be the ones shaping meaningful visibility in a world where awareness comes before the click.

How AI Mention Trackers Work: A Clear Guide to Understanding Visibility in Large Language Models

Caleb Turner on July 14, 2025

Artificial intelligence is becoming more deeply embedded in the way users search for, engage with, and consume information online. Businesses are now facing a new visibility frontier: large language models (LLMs) like ChatGPT, Claude, Google’s Gemini, and Perplexity. These AI tools are rapidly shifting how people discover brands and products, but there has long been a missing piece for marketers: how can you measure your brand’s presence across these tools?

Enter AI mention trackers—tools like Profound, Peec AI, and others that are helping brands figure out how often they appear in AI-generated answers. Think of them as the modern-day equivalent of media monitoring tools, but instead of scanning newspapers or websites, they scan what the AIs are “saying” about you. Let’s walk through exactly how these tools work, step by step, in simple and clear terms.

Step 1: Feeding Questions to AI Models

The first thing an AI mention tracker does is simulate real-world user queries. For example, if you sell coffee, it might generate prompts like:

“What are the best coffee brands for home brewing?”
“Which companies sell sustainable coffee beans?”

These questions are either preloaded by the tool or customized by the user. Then, the tool asks these questions to various AI platforms—ChatGPT, Claude, Perplexity, and others. These queries are sent using APIs or simulated browser sessions, mimicking the behavior of a real user.

To make the results more robust, the tool may vary how it phrases the questions, capturing a wider net of responses. This ensures the data reflects how real users might engage with AI tools.

Step 2: Collecting the AI’s Answers

Once the questions are submitted, the AI models reply with natural-language answers. The tracker collects all of these answers—a big pool of unstructured text. If the AI provides source citations or links (as Bing or Google often do), the tool grabs those too.

This phase is about capturing everything that the AI outputs, regardless of whether your brand appears yet.

Step 3: Detecting Brand Mentions

Now comes the scanning. The tool searches through each AI-generated answer looking for specific brand names, website URLs, or product terms. It checks to see if, for example, “Acme Coffee” or “acmecoffee.com” shows up in the text.

This is similar to a human pressing “Ctrl+F” and looking for their company’s name. The tool notes:

Where the mention appeared
How often it appeared
In what context (Was it a top recommendation? Just a mention in passing?)

If the brand doesn’t appear, that’s recorded too. These “non-mentions” are equally important because they show where the AI isn’t recognizing your brand.

Step 4: Counting and Aggregating Mentions

The tracker now tallies up the results across many queries and platforms. This helps quantify your brand’s visibility. You might learn that your brand appeared in:

8 out of 20 questions on ChatGPT
10 out of 20 on Google Gemini
Only 3 out of 20 on Bing Chat

These numbers are typically translated into metrics like “share of voice” (SOV) or mention frequency. Tools like Profound display this in an easy-to-read dashboard, comparing your visibility to your competitors.

Over time, this creates trend lines that show whether your brand’s AI visibility is improving or declining.

Step 5: Attributing Mentions to Sources

A crucial part of these tools is identifying why an AI mentioned your brand. In many cases, it’s because of external sources cited by the AI model. For example:

Bing Chat might footnote your brand with a link to a popular review site
Google’s AI Overviews might mention your company and cite your blog or Wikipedia

The tracking tool records these citations and links them to your mentions. This is called “citation analysis.” It helps you understand which articles, websites, or publications are fueling your AI visibility.

When an AI doesn’t mention you but mentions a competitor, these tools can also highlight what sources were cited for them. This gives you ideas about where you might need more coverage.

Step 6: Presenting the Results

All of this data gets organized into a simple dashboard. It might tell you:

Your brand was mentioned in 40% of answers about “best coffee brands” on ChatGPT this month
That’s up from 30% the month before
The most frequently cited source was HomeBarista.com
Competitor JavaWorld appeared more often than you on Google SGE

Some tools also analyze sentiment: whether the AI’s tone was positive, neutral, or negative about your brand. While more advanced, this adds another layer to understanding your visibility.

A Real-Life Example: Acme Coffee

Imagine you run a fictional brand called Acme Coffee. You want to know if AI tools are recommending you when people ask about coffee.

The tracker sends prompts like “What are the best coffee brands?” to ChatGPT, Claude, Google Gemini, and Bing Chat.
ChatGPT responds with: “Some great coffee brands are Acme Coffee, BeanCo, and JavaWorld.” The tool flags that Acme was mentioned.
Google’s AI says: “According to HomeBarista.com, Acme Coffee roasts top-tier beans.” The tool notes the mention and attributes the source.
Bing Chat doesn’t mention Acme at all but includes JavaWorld. That’s also important intel.

After querying multiple questions and platforms, the tracker produces a report:

Acme was mentioned in 7 out of 10 queries on ChatGPT
5 out of 10 on Google Gemini
3 out of 10 on Bing Chat
Most Acme mentions cited HomeBarista.com
JavaWorld beat Acme by 2 mentions across the board

Tools Like Ahrefs Add Another Layer

Some platforms, like Ahrefs, take a slightly different but powerful approach. Rather than running queries in real time, Ahrefs leverages a vast existing database of AI responses and questions. You can type in a brand name or topic like “sneakers” and instantly see a list of relevant queries and AI answers that reference the topic.

This lets you:

Identify competitor gaps (queries where your competitors show up but you don’t)
Discover new topic opportunities (queries you never thought of that relate to your niche)

This retrospective approach complements real-time trackers like Profound or Peec AI by giving you a broader strategic view.

Tracking LLM Traffic in GA4: Why It Matters

AI visibility isn’t just theoretical. Brands are already seeing meaningful traffic driven by AI tools. Tracking this traffic in Google Analytics 4 (GA4) is now essential.

While Google Search Console still blends AI Overview and AI Mode traffic with regular search, GA4 gives you tools to segment this data more precisely.

Two Main Tracking Approaches:

GA4 Explore Reports:
- Create a session segment using a custom regex filter to capture traffic from AI sources like ChatGPT, OpenAI, Copilot, Gemini, Perplexity, etc.
- Visualize this data with line graphs, bar charts, or tables.
Looker Studio Reports:
- For detailed reports: Create a new channel group in GA4 for AI traffic.
- For quicker views: Use the same regex filter in your Looker Studio tables and charts.

These dashboards let you:

Track how much traffic is coming from AI tools
See which pages are being visited from AI answers
Understand whether your AI visibility is translating into real engagement

Final Thoughts: Why This Matters

The future of search is increasingly conversational and AI-driven. Tools like Profound, Peec AI, and Ahrefs help marketers stay ahead by answering this crucial question:

“Are the AIs talking about me?”

If they are, great—you can double down on what’s working. If not, you can take action to increase visibility by improving the content on sites that AIs pull from.

AI mention trackers give marketers, PR pros, and SEOs a crucial lens into how modern algorithms perceive and recommend their brands. By bridging the gap between traditional SEO metrics and AI-powered search behaviors, these tools ensure your strategy remains both measurable and forward-looking.

Start tracking now, and you’ll not only see how often you appear in the AI conversation, but you’ll also start shaping it.

The 5‑Step Trust Surge Framework

Caleb Turner on April 22, 2025

Why “Trust” Is Your Fastest‑Growing Practice Asset

Trust Surge Framework

When someone Googles “implant dentist near me” or “dermatologist that actually listens”, they’re half‑deciding whether to hand over their health (and a few thousand dollars) before they ever meet you. In a 2024 BrightLocal survey, 87 % of patients said they trust online reviews as much as a personal recommendation when choosing a provider. Translation: Your digital presence is now your front‑desk receptionist, chair‑side manner, and waiting‑room aroma—all rolled into one.

The Trust Surge Framework compresses what marketing pros normally spread out over months into a tight six‑and‑a‑half‑minute routine you can repeat every quarter. Grab your stethoscope (or mirror and explorer) and let’s dive in.

Step 1 – Perfect Your Profile

Fill Every Blank Space

Google Business Profile (GBP), Healthgrades, and Zocdoc: each listing is a formal introduction. An incomplete profile is the digital equivalent of showing up to the OR without scrubs. Make sure:

Name‑Address‑Phone (N‑A‑P) are identical everywhere (Suite # vs. Ste. throws algorithms into an existential crisis).
Categories are procedure‑specific: “Periodontist—Implant Dentistry” will outrank plain old “Dentist.”
Business hours include phone‑answering times, not just when you’re drilling or prescribing.

Pro Tip: Copy and paste your N‑A‑P into a pinned note. Whenever you open a new directory, paste, rinse, repeat.

Visual Proof

Slip a side‑by‑side screenshot into your marketing playbook: one perfectly filled GBP and one “sloppy” with a generic logo and no hours. Let the night‑and‑day difference humble the team.

Step 2 – Show, Don’t Tell

20+ High‑Res Photos

Humans process images 60,000× faster than text (it’s science—and also why we can spot a crooked painting before reading the caption). Aim for:

Team headshots that reveal you own an iron, not just a white coat.
Facility shots—reception, operatories, even your fancy autoclave.
HIPAA‑safe before/after photos. (Crop faces or get explicit consent—patients in 2025 know their rights and how to leave one‑star missiles.)

A 15‑Second Walkthrough Video

Smartphone + gimbal = a mini Netflix tour. Keep it:

Tight: 15–20 seconds—long enough to show you have walls, short enough to finish before the anesthetic wears off.
Vertical: Reels and Shorts love 9:16.
Captioned: 85 % of viewers watch on mute while waiting for the hygienist.

Step 3 – Ethical Review Harvesting

The Post‑Visit Email

While the patient is still marveling at their symmetrical gumline, send an email:

Subject: “How did we do? (takes 30 seconds)”
Body: single sentence + bold “Leave a Review” button that lands directly on your GBP review box.
Open rates average 61 % for post‑care emails—triple most newsletters.

The Discreet QR Card

On the checkout desk, place a 3 × 5 card:

Scan ➜ Review ➜ (optional selfie with new smile)

Patients love high‑tech touches; you love not handing out paper forms like it’s 1999.

Zero Incentives = 100 % HIPAA‑Safe

“You’ll enter a gift‑card raffle” sounds generous until the Office for Civil Rights comes knocking. Keep it to gratitude only. (Besides, no one wants a $15 coffee card from the person who just billed their insurance $3,000.)

Step 4 – HIPAA‑Proof Responses

The 48‑Hour Rule

Reply to every review—glowing or scathing—within two days. Silence reads like guilt; slow replies read like you’re too busy counting money.

Reviewer Mood	Your HIPAA‑Safe Template
Ecstatic: “Dr. Lee made my veneers look natural.”	“Thank you for the kind words! We love creating confident smiles. – Dr. Lee’s Team”
Furious: “They ruined my root canal!”	“We’re sorry to hear you’re disappointed. Please call our office at 555‑7890 so we can help.”

Notice what’s missing? No protected health info. No: “Ah yes, Mrs. Gonzalez, about that molar #19…”

Gold Standard: Thank ➜ Apologize (if needed) ➜ Move offline. In that order. Every time.

Step 5 – Audit & Repeat

Monthly Citation Scan

Use a free tool like Whitespark’s Local Citation Finder or low‑cost BrightLocal to export every listing. Fix any N‑A‑P drift (suite #, new phone line, spelling variations).

Track Star Ratings

Dump ratings into a Google Sheet:

Month	Google	Yelp	Zocdoc	Healthgrades	Avg.
Jan	4.6	4.2	4.7	4.5	4.5
Feb	4.7	4.3	4.8	4.6	4.6

If any platform drops 0.2 stars or more, launch a micro‑campaign: email last month’s satisfied patients and politely ask for a review.

Quarterly Photo Refresh

New team member? Remodel your lobby? Swap out images before they start looking like dental X‑rays from the ’80s.

Putting It All Together (Spoiler: It Compounds)

Individually, each step nudges conversion rates. Together, they create a trust flywheel:

Optimized profiles rank you higher in Maps.
Visual proof keeps bounce rates low.
Fresh reviews raise click‑through rates (CTR) by up to 35 % compared to listings with fewer than five recent reviews.
HIPAA‑safe responses show regulators—and patients—you know the rules.
Routine audits prevent “citation creep” that erodes local rankings over time.

By month three, most practices see:

10–25 % lift in organic phone calls.
5‑point jump in review counts (without begging Grandma to write another).

A noticeable drop in lead cost from Google Ads because the algorithm rewards listings with higher Quality Scores.

Common Excuses (And Their Cavity‑Free Counterpoints)

Excuse	Rebuttal
“I’m a surgeon, not a TikToker.”	Great—record once and let your receptionist upload. You’ve spent years mastering sutures; this is 15 seconds with a smartphone.
“Patients don’t care about photos.”	Before scrolling any further, check your phone. Count how many photos you liked today. Your patients did the same—right before Googling you.
“Responding to reviews is awkward.”	So is explaining a root canal. Yet you do it daily. Have an assistant do it for you.

Metrics That Matter (Steal‑This Dashboard)

Profile Completeness Score – Aim for 100 % across top five directories.
Photo Count – Minimum 20, update quarterly.
Review Velocity – ≥ 3 new Google reviews/month.
Average Response Time – < 48 hours.
Citation Consistency – 0 mismatches.

Plug these into Looker Studio (formerly Data Studio). Set red/yellow/green conditional formatting—because nothing motivates like a bright‑red cell screaming “FIX ME.”

Final Checkup: Your 30‑Day Sprint Plan

Week	Action	Outcome
1	Audit & perfect GBP + top directories	100 % profile completeness
2	Shoot photos & 15‑s walkthrough	20+ images uploaded
3	Launch post‑visit email + QR card	First wave of new reviews
4	Reply to all reviews and build KPI tracker	HIPAA‑proof reputation engine

Rinse, repeat next quarter. The Trust Surge framework scales: whether you’re a solo endodontist or a 10‑op insurance‑free powerhouse, the principles stay identical; just swap one practitioner selfie for ten.

Parting Wisdom from the Mouth (Mirror) of Experience

Patients can’t smell your lavender essential oils through a screen, but they can smell neglect. Show them you care online, and they’ll assume you care even more in person. Besides, nothing tastes sweeter than a five‑star review, except maybe post‑op ice cream (try the vanilla, skip the nuts).

Ready to spark your own Trust Surge Framework? Crack open that spreadsheet, pop your phone on the charger, and book a 30‑minute strategy call with SEO Rank Media. When the timer dings, you’ll be one step closer to a waiting room that feels like a Beyoncé concert—minus the pyrotechnics, plus a whole lot of booked appointments.

Zero-Click SEO

Caleb Turner on April 15, 2025

Is it the end of ‘the click’? Okay, maybe that’s a tad bit dramatic. If you’ve heard of zero-click marketing, you’ll know that it’s not exactly new, but it’s making serious headway in the digital marketing world, and it’s time for you to hop on board.

See, the quiet revolution we’re seeing online isn’t about long-tail keywords or 3D landing pages (that would be kind of cool, though). Instead, it’s more subtle. Things are happening right in front of you that you probably aren’t noticing.

So, if you’re not updated with the latest trends, you might feel like you’re falling behind and that your business is fading into the background. But if you’re reading this, don’t worry; you’re already one step ahead.

Zero-click SEO is when users can see your content and engage with it without a single click.

I know, I know. You’ve been spending years focusing on building your business’s website traffic. But zero-click doesn’t mean your efforts have zero value.

Let’s talk about what zero-click SEO is, how it’s changing the online world, and what you can do to avoid being left behind.

What Is Zero-Click SEO?

Normally, SEO focuses on optimizing your content to bring traffic to your website.

Ah, traditional SEO. Those were the good ol’ days. And while the traditional idea behind SEO is still valuable, zero-click SEO is a bit different.

Instead of creating a strategy that drives traffic to your website, zero-click SEO focuses on showing your content where people are already spending their time and consuming content without directly clicking through to it.

What does this mean? This can include:

Featured snippets and AI Overviews on Google
Engaging content posted on your Google Business profile
In-app content on platforms like Instagram and TikTok
AI-generated summaries from tools like Perplexity or ChatGPT
Podcast mentions, newsletter blurbs, and other coverage that doesn’t link out

Now, don’t take it personally. Zero-click SEO is not here to leave your website in the dust. Instead, it’s about influencing people where they already are. And that can be even more powerful than traffic.

Is Zero-Click Taking Over?

It’s a question everyone has when new information like this pops up. With so many things changing, it’s normal to think, Is this something I should pay attention to? In short, yes.

According to a study by S p arkToro, almost 60% of all Google searches end without a click. That’s a lot. This means most people who look up a query on Google end their session without clicking on any results. In other words, most people aren’t going to your website.

What happens to the other 40%? Those users know where they want to go—and that’s great. But for the remaining 60%, they’re still figuring out.

Let’s go over why zero-click SEO is a necessity.

1. Google isn't sending you traffic anymore

It’s time to accept the truth. As you saw above, almost two-thirds of all Google searches end without a single click. I even used an italicized font—that’s how serious it is.

What this means is that Google is answering queries directly within the search results, whether it’s through AI overviews, product previews, featured snippets, or knowledge panels.

Maybe you see this as a bummer because you want people to come to your website. But remember what we spoke about earlier? You know, the 60% of users end their search sessions without making a click? So for most queries, you weren’t getting the traffic anyway.

Instead, you need to look at this from a different angle. Google’s goal is to give people what they want, which is straightforward, concise content that answers their queries.

How will this affect your business? Taking advantage of the advice given in this article will help position you as a trusted expert, influencing the user whether they click or not.

2. Social platforms aren’t link friendly

Sorry, but the glory days of social media as a place to share blog posts and drive traffic are long gone.

And it doesn’t matter which platform we’re talking about, whether Instagram, Facebook, Reddit, or X. Algorithms are deprioritizing content with external links. It’s not a myth; it’s a reality. Hootsuite found that tweets without links receive 25% more engagement than those with links.

Why? Because these platforms want their users to stay on their apps. An external link means they leave the app, and that’s a no-no. If you’ve been on Instagram or X lately, you’ll have noticed they don’t allow clickable links in captions at all.

In this case, you want to focus on creating content on those platforms that are so valuable users won’t want to leave. Sure, you may not get the website traffic you want, but you’ll earn trust and attention.

3. Outreach without links is a winner

Backlinks are the holiest of all when it comes to off-page SEO. However, these days, there’s more that’s usually needed.

If you haven’t seen a link request email in some time, that’s because they’re in your spam folder. Backlinks have been so used and abused by SEOs that they usually end up in spam.

Rather than requesting links, sending pitches that focus on your product, brand, or research as something newsworthy is more relevant. Remember, zero-click SEO is about influencing without the click.

So, getting mentioned in a trusted newsletter, having a soundbite on a podcast, or a shoutout on a subreddit may not bring in traffic, but it’ll help you gain attention and trust.

4. AI and LLMs aren’t into links

We can’t forget this one. Language models like ChatGPT, Gemini, and AI tools like Perplexity and Bing Copilot are the shiny new innovations.

But these platforms aren’t always going to send you traffic.

They like to answer the users’ questions right within their platforms, with no need for backlinks.

You want your brand to be mentioned within your niche—frequently. These platforms base their answers on context and relevancy. If your brand shows consistency in its niche and provides relevant content, these platforms will take information from you. In other words, you need to be everywhere possible that people are talking about your industry. It’s the best way to be seen.

How to Shift to Zero-Click SEO

It’s a lot to take in, we know. If people don’t need to click, how can you measure what’s working?

See, we all know that traffic is a vanity metric, and the digital marketing world needed a shake-up. Traffic doesn’t mean conversions, and we all know that. Here’s what matters more:

Who’s hearing about you?
Are you influencing decision-making?
Are you building brand trust and awareness?
Are the impressions becoming conversions?

You might have seen the LinkedIn post by Wil Reynolds, where he wrote about how his traffic dropped by 41% but his newsletter sign-ups were up by 65%. How does that happen? Because conversions don’t only come from traffic, but also from trust, recommendations, and delivering value wherever the customer finds you.

To pivot your strategy and incorporate zero-click SEO in your business, do the following:

Write for AI

While you should write for your audience, you also want to make sure your content is clear and concise (AI loves that). You should use bullet points, lists, and short paragraphs. Write for your readers and for AI.

Create social content

Create content that doesn’t need a link to prove its value. Focus on storytelling, infographics, accurate data, and tutorials to create content that engages and provides value.

Track the right KPIs

Rather than only focusing on “website visitors” (it’s time to let it go), focus on the following metrics:

Branded search volume
Social engagement and reach
Direct traffic or type-in visits
Conversion rates and revenue
Podcast or media mentions
Share of voice in AI outputs

Don’t only focus on links

Don’t spend all your time and effort worrying about links. Instead, focus on getting your brand talked about. Connect with journalists and content creators to gain attention and trust.

Influence > Traffic

Zero-click SEO isn’t something new, but it is becoming a serious part of digital marketing. Whether it’s Google or a social media platform, their goal is the same: they all want users to stay on their sites. For AI, this means providing the information they need without them having to leave the platform.

To give users what they want while also getting what you need as a business owner, focus on building influence. It’ll last you longer than a click. So, build trust, show up everywhere, and create the value your audience needs.

Will you get the traffic you want? Maybe not, and you’ll need to accept that, at least in the short run. But what you will get is a deeper, more genuine, and more aligned marketing strategy that you’ve needed all along.

SEO Rank Media believes that the best digital strategies integrate the best of both worlds, leveraging traditional SEO alongside zero-click SEO for a more holistic approach. By balancing efforts to drive website traffic with strategies that capture direct attention through AI, social media, and other zero-click platforms, businesses can maximize their online influence and establish greater trust with their audience. To explore how this dual strategy can be tailored to your business’s unique needs, feel free to reach out and set up a call with our team.