LLM Visibility: 4 Website Changes That Help AI Tools Find Your Brand

This is Post 2 of 3 in a series documenting a live LLM visibility audit on my own brand. Post 1 covered the baseline results. Post 3 will share the 30-day data.

In my last post, I shared the results of auditing my own LLM visibility. The short version: strong brand recognition, zero category visibility. When someone searched for me by name, three out of four AI tools found me. When someone searched for what I do — without knowing my name — I didn’t appear once across twenty responses.

That’s not a content quality problem. It’s a structure and distribution problem.

So I got to work.

Here’s exactly what I changed — and why each decision matters for how AI tools read, process, and cite your brand.

Decision 1: Rewrote the “How I Help” page from bullets to prose

This was the first change I made, and it might be the least obvious one.

My original page used bullet points to describe my services. Clean, scannable, standard. The problem is that LLMs don’t parse bullet fragments the way humans do. They’re looking for complete sentences, clear subject-verb-object structure, and explicit statements of what a business does and who it serves.

A bullet that says “LLM Visibility and AI Search” tells an AI model almost nothing on its own.

A sentence that says “I help marketing teams understand and improve how their brand shows up in AI-generated answers across ChatGPT, Perplexity, Google AI Overviews, and similar surfaces” is something a model can actually work with — and repeat back accurately when someone asks about it.

So I rewrote the page in prose. Same services, same positioning. Just structured in a way that’s readable to both humans and machines.

Decision 2: Named LLM Visibility as a standalone service

In my original copy, LLM visibility was implied — woven into language about AI readiness and go-to-market strategy. It wasn’t named directly or given its own space.

That was a mistake.

AI tools surface brands in category results when those brands are clearly and explicitly associated with specific terms. If I want to appear when someone asks “who helps with LLM visibility,” the phrase “LLM visibility” needs to appear on my site — not as jargon, but as a named, defined service with context around what it means and who it’s for.

I added LLM Visibility and AI Search as a named service with its own description. I also made sure the language on the page mirrors the actual prompts a buyer might use — not my language, but the language they reach for when they have the problem.

Decision 3: Built a full FAQ page

This one is underused by almost everyone, and it might be the highest-ROI change on the list.

FAQ pages written in natural language — real questions, complete answers — are exactly what AI models are trained to surface. When someone asks ChatGPT “what does an LLM visibility consultant do?” or “how do I know if my brand shows up in AI search?” the model is looking for a source that answers that question clearly and directly. A well-written FAQ page is essentially a pre-formatted answer key.

I built mine around the actual questions I get from marketing leaders: What is LLM visibility? How is it different from SEO? How do you measure it? What does an engagement look like? Each answer is written the way I’d explain it to someone in a first conversation — plain language, no jargon, complete sentences.

It also signals to AI crawlers what my brand is actually about, beyond what appears on the homepage.

Decision 4: Updated the URL slug and added schema markup

Two smaller but important changes.

My “How I Help” page previously lived at /general-4. That’s a Wix default that tells search engines and AI crawlers absolutely nothing about what’s on the page. I updated the slug to /how-i-help — a small fix that makes the page’s purpose legible to anything crawling it.

I also added Organization schema markup to the site. Schema is structured data that lives in the code of your pages and explicitly tells AI tools who you are, what you do, and how different mentions of your brand connect to the same entity. It’s not visible to visitors, but it’s one of the clearest signals you can send to the systems that decide whether to cite you.

I validated it using Google’s Rich Results Test — one valid item detected, which confirmed it was reading correctly.

What I didn’t change

It’s worth being clear about what I left alone.

I didn’t overhaul the site design. I didn’t rewrite every page. I didn’t stuff keywords into copy or try to game anything. Every change I made was in service of one goal: making it easier for AI tools to understand what NextWise Studio does, who it’s for, and why it belongs in conversations about LLM visibility and AI readiness.

The on-site changes took about a day to implement. The harder work — building third-party citations, getting listed in directories, publishing content that earns its way into the conversations I want to be part of — that’s the longer game. And that’s what I’m tracking.

What comes next

My 30-day re-measurement is scheduled for May 20. I’ll re-run the full audit — same seven prompts, same four tools, same six measurement sources — and publish the results honestly, whatever they show.

If the on-site changes moved the needle, I’ll tell you what moved and by how much. If category visibility is still at zero, I’ll tell you that too, and what it suggests about the relative weight of citations versus on-page signals.

Either way, it’s useful data. That’s the point of doing this in public.

These four changes were the most strategically significant but they weren't the only ones. In parallel I've been building out directory listings on Clutch, Sortlist, and G2, tightening entity signals across profiles, and working through a set of off-site actions specifically designed to address the citation gap. The on-site changes were the foundation. The off-site work is the longer game. Post 3 will show the full picture with data behind all of it.

Post 3 publishes May 20. I’m working with 3-5 brands this spring to run this audit alongside my own. If you’re curious what your baseline looks like, get in touch.