LLM Visibility Case Study: How Home Depot Is Winning AI Search

When people ask any LLM about home improvement, Home Depot is consistently the first brand mentioned. It ranks first in share of voice across Google AI Mode, ChatGPT, Perplexity, and Gemini, beating competitors like Lowe's and Amazon.

Something's working for them. And we wanted to know what, so we analyzed Home Depot's AI search playbook and reverse engineered it into six plays any ecommerce brand can apply.

What the data revealed

First, let's look at the numbers to make it clear why Home Depot is worth learning from. The findings below are based on Semrush's Enterprise AIO reports pulled in February 2026. Three numbers stood out immediately: 1. Share of voice: Home. 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 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.

6 plays to improve your ecommerce store's LLM visibility

Let's start with the most important factor behind Home Depot's LLM visibility: its organic search foundation. 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 same pattern also shows up in Better SEO and LLM Visibility, where the practical question is how the signal becomes visible.

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.

Play 1: Build your organic search foundation first

Organic search is the foundation of LLM visibility. So, every other play in this list builds on this one. AI platforms don't generate answers from nothing. They pull from web content that already performs well in traditional search. (Even. 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. This connects with AI Is Merging Paid and Organic Visibility when the same signal needs a clearer operating decision.

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.

Play 2: Own the consideration stage

The queries that generated the most mentions for Home Depot in this analysis skewed heavily toward buyers who are ready to act and not just browse. The data supports this, which suggests that more than half of the queries Home Depot. 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.

Play 3: Reinforce your key business drivers

LLMs don't just recommend brands based on what's on their pages. They build associations from everything consistently said about a brand across the web, both on its own site and across third party sources. Semrush's report identifies what. 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.

Play 4: Build a how to content moat

Most ecommerce brands optimize their product pages but neglect the content that comes before the purchase. The guides, how tos, and planning resources that help someone decide what to buy and how to use it. Home Depot has a large library. 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.

Play 5: use user generated signals

According to a Semrush study, Reddit, LinkedIn, Facebook, Quora, and Instagram are among the most cited domains on LLMs. User generated content (UGC), like reviews, forum threads, Q&As, and community discussions, carries significant. 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.

Play 6: Follow AI optimization best practices

A big reason Home Depot performs well in AI search is that the brand follows a range of AI optimization best practices. These may not be its competitive advantage on their own, because several competitors do the same. But they do stack up,. 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.

Start with a benchmark of your AI search visibility

Home Depot didn't build this AI visibility overnight. It took years of organic search investment, a large volume of content, and a massive physical and digital presence (most of which it built before "AI visibility" was even a thing.) But. 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.

What the data revealed in practice

Introduction When people ask any LLM about home improvement, Home Depot is consistently the first brand mentioned. It ranks first in share of voice across Google AI Mode, ChatGPT, Perplexity, and Gemini, beating competitors like Lowe's and. 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: lLM Visibility Case Study: How Home Depot Is Winning AI Search: the Strategic Visibility Angle should be treated as a visibility signal, not a standalone headline. Introduction When people ask any LLM about home improvement, Home Depot is consistently the first brand mentioned. It ranks first in share of voice across Google AI Mode, ChatGPT, Perplexity, and Gemini, beating competitors like Lowe's and Amazon. Something's. A useful companion note is to Improve Your Brand’s LLM Visibility, because it looks at a nearby part of the same system.

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.