When someone asks ChatGPT to recommend a service in your category, your brand either shows up in the answer or it doesn't. There's no page two, no ad slot to buy your way in. This is the reality behind GEO, Generative Engine Optimization, and it's worth understanding before spending a budget on it.

Why this is different from ranking on Google

A Google results page shows ten links and lets the user decide. An AI answer synthesises a handful of sources into a single recommendation, and most people don't scroll past it to check the sources. That means the competition isn't for a spot on a list anymore, it's for being one of the small number of sources the model decided to trust when forming its answer.

The good news is that the underlying signals overlap heavily with good SEO and good content marketing. The brands getting cited aren't running some secret playbook, they're the ones with genuine authority, clear positioning and content that's structured well enough for a model to parse and trust.

The signals that actually correlate with AI citations

Where to actually start

Start by finding out where you currently stand. Ask ChatGPT and Perplexity the questions your potential customers would ask, the ones without your brand name in them, and see whether you show up. Do this for five to ten realistic queries. This baseline matters more than any theoretical framework, because it tells you whether the gap is about visibility (you're simply not on the radar) or about trust (you're known but not cited as an authority).

From there, the highest-leverage work is usually content that directly answers specific questions your audience asks, written with genuine expertise rather than surface-level coverage. Generic "what is X" content rarely gets cited when there are already a thousand versions of it. Content answering a specific, less obvious question has a much better shot.

What doesn't work

Trying to game this the way old-school SEO used to be gamed. Keyword stuffing, thin content dressed up with schema markup, or buying mentions from low-quality sites. AI models are trained partly to recognise and downweight exactly this kind of content, and the field is too new for shortcuts to have a long shelf life anyway.

Setting realistic expectations

This is a genuinely new area, and anyone who claims to have it fully figured out is overselling. What a serious approach looks like is applying the signals known to correlate with citations, monitoring visibility consistently over time, and adjusting based on what's actually moving the needle rather than following a fixed playbook. Early movers in most industries are still building this from scratch, which is itself an opportunity if you start now instead of waiting for it to become obvious.

How to actually track whether it's working

There's no equivalent of Google Search Console for AI citations yet, which makes measurement genuinely harder than traditional SEO. The practical approach is running the same set of representative queries against ChatGPT, Perplexity and Gemini on a regular cadence, monthly is usually enough, and logging whether your brand appears, how it's described, and which competitors show up alongside or instead of you. It's manual and a little tedious right now, but it's the only reliable way to see whether the underlying content and authority work is actually translating into visibility, rather than guessing based on traffic alone.