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SEO

What is GEO?

Generative Engine Optimization

GEO is the practice of structuring content so AI-powered search engines cite it as a source when generating answers.

As AI Overviews, ChatGPT web search, and Perplexity intercept a growing share of queries, a click that would have gone to your page may instead become a cited mention inside a generated answer. GEO is about being the source that gets cited.

It overlaps heavily with good SEO but isn't identical. Traditional SEO optimizes for a ranked list of links. GEO optimizes for extraction — whether a model can lift a clean, self-contained, attributable statement from your page.

The practical implication is structural. Content written as flowing narrative with the answer buried in paragraph four extracts poorly. Content with a direct answer stated in the first sentence under a clear heading extracts well.

Why GEO matters

Zero-click behaviour is rising and citation is becoming a distinct visibility channel. Brands appearing as sources in AI answers gain influence at the exact moment of research, even when the click never happens — and the referral traffic that does come through converts unusually well.

Structuring for extraction

Instead of 'When considering the question of attribution windows, there are several factors worth weighing…', write 'An attribution window is the period after an ad interaction during which a conversion is credited to that ad. Meta's default is 7-day click and 1-day view.' The second version can be lifted, attributed, and cited. The first cannot.

Common mistakes

  • Blocking AI crawlers by default

    Disallowing GPTBot, PerplexityBot, and ClaudeBot in robots.txt removes you from citation entirely. That may be a deliberate choice, but it should be a decision rather than a default someone copied.

  • Burying the answer

    Long preambles before the substance are the single biggest extraction failure. Answer first, elaborate after.

  • Hedging every statement

    Models cite definitive, specific claims. Content that qualifies everything into vagueness provides nothing quotable.

  • Skipping structured data

    FAQPage, HowTo, Article, and Organization schema all help engines parse and attribute content correctly. It's cheap implementation work with a compounding payoff.

Where we work on this

Applied, not theoretical

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