What Is GEO: Getting Cited in AI Search Answers

When ChatGPT searches, it crawls the web in real time, pulls the answer together from several sources, and lists them under a 'Sources' section beneath the reply, exactly as OpenAI describes in its own announcement of the search feature.

Perplexity works on a similar principle: it interprets the question, looks for reliable sources on the web, builds the answer from them, and attaches a numbered footnote to each claim linking back to its source. Google AI Mode runs the same logic over Google's own index, aimed at comparison and multi-step questions.

GEO means writing a page so it can be summarised and quoted by a model, not only read by a person. The difference is one of form rather than technique: clear definition sentences, paragraphs that stand on their own, visible and current dates.

In classic SEO, an answer arriving in the second paragraph is rarely fatal. In GEO it raises the risk that a model quotes a different source instead, which is why the opening paragraph remains the single most important part of the page.

The first step is one clear answer page for every topic the brand speaks to. The second is making sure that page carries a real date, author or organisation, since these tools weigh recency. The third is backing the page with structured data, which we cover in a separate article.

• One clear answer page per core topic
• Definition first, detail after
• Visible, current dates and sourcing on the page
• Structured data confirming the topic to a machine
• No contradicting version of the same fact elsewhere on the site

There is no single dashboard for GEO yet; all three tools run inside their own closed interface. The most reliable method is asking the ten to fifteen real questions a brand's audience asks, across ChatGPT, Perplexity and Google AI Mode, at regular intervals, and recording by hand which source gets shown.

Alongside that, Search Console's AI features reporting shows whether a page appears inside Google's own summaries. Together, the two give a concrete picture of where a brand is being cited.

A spa chain repeating identical wording for the same treatment across every branch page is a common one; a model choosing which page to cite gets no benefit from the repetition, and the duplication makes it harder to tell which version is the original.

The other common mistake is writing purely for keyword density. A model is not counting keywords; it is checking whether the sentence actually answers the question.

A common one on a workwear manufacturer's product pages is repeating the same safety standard in slightly different wording on every product description, each time at the same shallow level. When a model cannot tell which page actually explains the subject, it does not favour any of them.

Another is leaving a page unrefreshed. Once a standard or regulation changes and the page keeps carrying the old version, a model stops treating it as a current source and picks an updated competitor page instead.

A useful decision rule: if a page has not been reviewed in the last six months and its topic is one the brand gets asked about often, it should move to the top of the update list.

Getting started with GEO does not need a complicated toolkit, a simple routine repeated regularly is enough.

• List the ten to fifteen topics the brand's audience asks about most.
• Check whether each topic already has one clear answer page on the site.
• For any gap, write a new page that opens with a definition sentence before adding detail.
• Add missing date, author or source information to pages that already exist.
• Ask those same ten to fifteen questions to ChatGPT, Perplexity and Google AI Mode once a month and log which source gets shown.