The Real Reason AI Recommends Your Competitor & What to Do About It

Kris Jones joined me for an episode of Search Engine Journal's podcast. He has been in search since the late 1990s and now runs the agency LSEO, after building and selling Pepper Jam.

We spent most of the conversation on one question, which is what actually decides whether an AI system recommends your brand. Kris gave me a one word answer early on, and everything else in the episode came back to it.

AI Took Over The Comparison Step

Traditional search handed you options and left the comparing to you. You opened tabs, weighed what you found, and decided. Kris pointed out that AI systems now do that comparing on the user's behalf and hand back a decision. Traditional. The search implication is whether the section improves the evidence around the page, not simply whether it adds more wording. Clear entities, crawlable structure, internal links, and useful context are what make the topic easier to evaluate.

The useful check is whether this improves the system behind search performance, not only the words on the page. Internal links, crawlable content, clear entities, current evidence, and a sensible page structure all help the recommendation become easier to trust.

Why Brand Is The Bridge

I asked Kris where these systems are pulling their information from. His answer was brand signals, and specifically what other people are publishing about you. That reframes the work. You are no longer trying to win a position on a. The practical read is that brand signals need to be consistent enough for both people and AI systems to form a stable view of the company, its expertise, and its trust signals.

The risk is usually hidden in the execution layer. A page can look fine to a human and still fail for an automated visitor if the form, call to action, rendering path, or confirmation step is not accessible enough for the agent to complete the task. A useful companion note is Finding Client Opportunities in Competitor Feedback, because it looks at a nearby part of the same system.

The Awards Your Competitors Are Applying For

Kris named the cheapest immediate step available to most businesses, and it is one plenty of marketers have quietly written off. Identify every credible third party award and recognition available in your industry, then go get them. He. The practical question is what this changes in the system: the page structure, the evidence presented, the measurement habit, or the way the topic is connected to related work.

Brand Messaging Is The New NAP Consistency

Getting mentioned is not the finish line. Kris kept coming back to the context of a mention, meaning what the surrounding content actually says about you. He compared it to the early days of local SEO, when we all learned that a business. The practical read is that brand signals need to be consistent enough for both people and AI systems to form a stable view of the company, its expertise, and its trust signals. The same pattern also shows up in What AI Says About Your Locations, where the practical question is how the signal becomes visible.

The operational question is whether the public business data is complete enough to support the query. Hours, categories, services, reviews, photos, and page content need to reinforce each other so Google can understand the business in a specific situation, not only as a generic listing.

When AI Overviews Gets Your Pricing Wrong

I have a concrete example of what that costs. I worked with a chain of adult education schools whose tuition figures were being pulled into Google AI Overviews from a Reddit thread that was roughly a decade old. The number showing up was. For search teams, the important part is not the headline movement by itself. It is whether the shift changes which communities, forums, video surfaces, or publisher pages now satisfy the query better than the old ranking pattern.

Don't Set Your Baseline From ChatGPT And Google

One tip I want people to take out of this conversation is to widen the list. When you get into your Google Analytics data, the click rate coming from ChatGPT will probably baseline lower than you expect. It grows from here, and so does. Local visibility depends on whether the details across pages, profiles, categories, reviews, photos, and service descriptions reinforce the same answer for a specific location based query.

The reporting question is whether this signal changes a decision. If it only creates another number in a dashboard, it adds noise. If it helps separate profile activity, website visits, calls, bookings, and direction requests, it can make local performance easier to understand.

What Should Marketers Tackle First?

Two things from this episode are worth acting on before your next planning cycle. The first is an audit. Ask an AI assistant to recommend a vendor in your category, read what it says about you, and check whether any of it is out of date. Local visibility depends on whether the details across pages, profiles, categories, reviews, photos, and service descriptions reinforce the same answer for a specific location based query.

AI Took Over The Comparison Step in practice

Introduction Kris Jones joined me for an episode of Search Engine Journal's podcast. He has been in search since the late 1990s and now runs the agency LSEO, after building and selling Pepper Jam. We spent most of the conversation on one. For search teams, the important part is not the headline movement by itself. It is whether the shift changes which communities, forums, video surfaces, or publisher pages now satisfy the query better than the old ranking pattern.

What the visibility signal actually changes

What the visibility signal actually changes: the Real Reason AI Recommends Your Competitor & What to Do About It should be treated as a visibility signal, not a standalone headline. Introduction Kris Jones joined me for an episode of Search Engine Journal's podcast. He has been in search since the late 1990s and now runs the agency LSEO, after building and selling Pepper Jam. We spent most of the conversation on one question, which is. This connects with Real Reason Internal Links Quietly Decay & when the same signal needs a clearer operating decision.

What the visibility signal actually changes: the practical question is whether the page, brand evidence, and surrounding content make the answer easier to trust. If that support is weak, search systems can still understand the topic but fail to connect it confidently to the brand.

What the visibility signal actually changes: that is why the response should begin with an audit of the evidence already on the site before creating a new asset. The fastest improvement is often a clearer page, a better internal link, or a stronger explanation of why the brand belongs in the answer.

Where the evidence needs to be tested

Where the evidence needs to be tested: a single study or ranking observation should not become a strategy by itself. It should become a diagnostic prompt: which source is being trusted, which query pattern is affected, and which part of the site would make that trust easier to earn?

Where the evidence needs to be tested: that keeps the response grounded. The goal is to improve the evidence chain around the topic rather than publish another summary that repeats what every other page already says.

Where the evidence needs to be tested: the important distinction is between a useful signal and a fashionable talking point. A useful signal changes the brief, the page structure, the linking plan, or the measurement view.