Generative Engine Optimization (GEO): What It Is and How to Start
By Keith Schilling · August 7, 2026 · 6 min read
GEO — generative engine optimization — entered the vocabulary through a 2023 academic paper and stuck, because it names something real: the practice of shaping how generative AI systems represent and recommend you. If AEO is the same discipline named from the answer side, GEO names it from the model side. The work is identical; we'll use GEO here and move on.
What the research actually found
The original GEO research tested which content modifications made sources more likely to be used in generated answers. The tactics that moved results: adding statistics, quotations, and citations to authoritative sources — in other words, giving engines concrete, attributable substance to lift. Fluent-sounding marketing copy without liftable facts underperformed. Keyword stuffing did nothing or hurt.
That finding matches what we see in category measurements: the pages engines cite are dense with specifics — prices, comparison tables, named criteria — while the beautifully vague thought-leadership post gets ignored. The generative web rewards being *quotable*, and quotable means concrete.
GEO in practice: three layers
Your site: crawlable to AI bots, server-rendered, schema-marked, with plain-language answers to your category's real questions — specifics stated in the first screenful, not paragraph nine. The third-party layer: engines assemble answers disproportionately from review platforms and comparison articles, so your G2/Capterra currency and your presence in the listicles engines cite are GEO work, arguably the highest-leverage kind. The measurement layer: a baseline of how often engines mention, recommend, and cite you today — because GEO without measurement is the new "we do SEO" of 2012, unfalsifiable and unfundable.
A 30-day starting plan
Week one: baseline your category — every core buying question, multiple engines, repeat runs; note where you never appear and which domains get cited. Week two: fix access — robots.txt, rendering, schema, llms.txt; it's mostly a sprint. Weeks three and four: ship direct-answer pages for your five worst prompts (the ones where competitors appear and you don't), stating the concrete facts engines can lift. Then re-measure monthly and let the trendline, not the folklore, decide what you do next. GEO rewards the patient and the specific; it's unusually kind to small teams willing to publish real numbers.
Treyci tracks your brand across ChatGPT, Perplexity, Gemini, and Grok — every prompt run three times, every month, from $99.
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