#Explainer

10 posts in #Explainer

Sep 26, 2026 AI Visibility

AI Web Search vs Training Data: Why Brand Answers Differ

AI tools can describe your brand one way from memory and another way after searching the web. That gap is diagnostic if you know how to read it.

Sep 24, 2026 Tutorials

llms.txt Explained: Should Your Site Have One?

llms.txt is a proposed way to help AI systems understand your site’s most useful content. Here’s what to publish, what not to expect, and a template you can use.

Sep 2, 2026 AI Visibility

Generative Engine Optimization: A Practical Guide

Generative engine optimization helps your brand become visible, accurate, and citable in AI answers. This guide explains the foundations and gives you a first-week action plan.

Jun 6, 2026 AI Visibility

The Visibility Gap: Why Your Brand Scores Differently in AI's Memory vs Live Search

Ask ChatGPT about your brand with web browsing off and you get one answer — drawn from training data, the reputation baked into the model. Turn browsing on and you can get a different answer entirely, assembled from whatever the model finds on the live web in that moment. Most measurement programs only ever see one of these. The gap between them is diagnostic: it tells you whether the live web is rescuing a weak memory, or quietly eroding a strong one. This post is about why the gap exists, what its sign and size mean, and how to act on each case.

Apr 22, 2026 AI Visibility

What Is AI Brand Visibility? A 2026 Primer

For twenty-five years, the question marketers asked was simple: where do we rank? In 2026, the question has changed. Buyers now open ChatGPT, Claude, or Gemini, ask a question in plain language, and receive a single composed answer. There is no page of blue links to fight for. Either your brand appears in that answer, described accurately, or it does not. AI brand visibility is the measurable degree to which a language model surfaces and describes your company — and it is quickly becoming a primary discovery metric.

Apr 15, 2026 AI Visibility Brand Strategy

The Shift From Search to Answer: Four Years That Redefined Discovery

In late 2022, a buyer researching a product opened Google, scanned ten blue links, clicked two or three, and formed an opinion across several tabs. In 2026, the same buyer opens ChatGPT, types a question in a sentence, and reads one composed paragraph. The channel has not widened — it has compressed. This is the most consequential shift in discovery since the launch of Google itself, and it breaks several things marketers have treated as stable for two decades.

Apr 8, 2026 AI Visibility

Anatomy of an LLM Answer: Where Your Brand Fits In the Recipe

A large language model does not keep a database of brands. It does not look up your company the way a search engine queries an index. When someone asks ChatGPT or Claude about your category, the model assembles an answer from several overlapping sources — parametric memory, any available retrieval, and the running context of the conversation. Understanding how that assembly works is the difference between guessing at GEO tactics and choosing them deliberately. This post walks through the recipe.

Apr 1, 2026 AI Visibility

Training Data vs. Real-Time Retrieval: The Two Ways LLMs Know Your Brand

Ask ChatGPT about your brand twice — once with browsing enabled, once without — and you often get two different answers. That is not a bug. It is the visible surface of a deeper structure: language models hold brand knowledge in two distinct places, training data and real-time retrieval, with very different properties. Treating them as the same thing is how marketing teams end up applying the wrong fix to the wrong gap. This post walks through both paths and the tactical implications of each.

Mar 18, 2026 AI Visibility Tutorials

The Six Dimensions of AI Brand Visibility: A Practitioner's Explainer

A single AI visibility score is a tempting shortcut. It is also a lossy one. "Your brand scores 63/100 on ChatGPT" does not tell you what to fix, or whether to fix anything at all. A useful audit breaks the score into dimensions — component questions, each with its own diagnostic and its own remedy. BrandGEO scores on six dimensions across a 150-point scale, normalized to 0–100. This post is a practitioner's explainer of each dimension: what it measures, why it matters, and what moves it.

Mar 5, 2026 AI Visibility Tutorials

Recognition, Recall, and Reality: The Three Questions Every Audit Must Answer

Every AI brand visibility audit ever run, regardless of vendor or methodology, is trying to answer some combination of three questions. Do the models know you exist? Do they surface you when it matters? Do they describe you accurately? Each question has a different remedy, and tools that collapse them into a single score make it impossible to tell which problem you actually have. This post is a practical frame for interpreting audit results — Recognition, Recall, Reality — and what separates a useful report from a decorative one.