Notes on GEO
How AI assistants pick who to name, how to measure it, and what the numbers actually mean. Written by the people who build Teddit.
Case study · 15 Oct 2026 · 7 minCase study: nine weeks of a software services company in ChatGPT, Claude and GeminiAbout 400 buyer questions, asked every week for nine weeks. The company was named in about 3 answers in 100, but almost all of that came from a few narrow questions in its own industries. Here is what the numbers showed, and what they could not.Read ›
Case study · 15 Oct 2026 · 5 minCase study: where 110,000 citations wentBehind 10,344 answers about one software services company sit 110,850 cited sources. Less than one in a hundred pointed at the company’s own site. Which pages those were, which sites took the rest, and how differently three assistants chose them.Guides · 15 Oct 2026 · 5 minFrom numbers to a plan: working with your own AI through the MCP serverTeddit measures and stops there. The plan is better written by an AI that also knows your product, your content and your constraints. This guide connects your AI to Teddit and walks through one planning session, question by question.Guides · 15 Oct 2026 · 5 minRunning several clients in Teddit as an agencyOne brand per site, one budget per site, and people who see only the sites they work on. This guide covers how to lay out clients in workspaces and sites, who gets which role, and how to keep each client’s spend separate.Method · 14 Oct 2026 · 5 minOne scan is a sample: how to read a trend over weeksA scan asks each question once per assistant. That answer is one draw from many possible answers. Read one scan as a fact and you will chase noise; read nine in a row and the noise has a size you can see.Guides · 14 Oct 2026 · 6 minSetting up your first site: the choices that matter laterAdding a site takes a few minutes. A handful of the choices you make on the way decide how useful the numbers are in two months. This guide walks through the setup in order and says which choices to slow down for.How assistants work · 13 Oct 2026 · 6 minHow an AI assistant decides which brands to name and which pages to citeWhen a buyer asks an assistant for a recommendation, the answer is usually written after a web search: the assistant writes its own queries, reads some of what comes back, and then decides what to say. Each step is a place where your brand can enter the answer or drop out of it.Method · 13 Oct 2026 · 5 minGEO and SEO: what carries over, and what does notGetting named by AI assistants is often sold as something entirely new. Much of it is search work you already know. Some of it is not, and the part that changes most is how you measure.Method · 12 Oct 2026 · 5 minNamed, named first, linked: the states we track, and why not one scoreOne answer from one assistant can go six ways for your brand. Teddit draws each of them as a square instead of folding them into a number, and this is how to read the squares.How assistants work · 6 Oct 2026 · 4 minWhy the same question gets different answers, and how to measure anywayAsk five assistants the same question and you get five answers; ask one of them again next week and you may get a sixth. That is how these systems work, and it decides how visibility in them has to be measured.Guides · 29 Sep 2026 · 5 minHow to choose the prompts worth trackingWhat you learn is decided by the questions you ask. A short, stable list written the way buyers talk to an assistant tells you more than a long list of keywords.Guides · 22 Sep 2026 · 5 minLinked is not named: how to read the pages assistants citeAn assistant can recommend you without linking to you, and link to you without recommending you. The Pages screen shows the second half of that picture: which of your pages get cited, and for which questions.