Get Cited by ChatGPT, Claude, Perplexity & Gemini

The citation economy is a genuinely new channel

When a buyer asks ChatGPT, Claude, Perplexity, or Gemini for the best option in a category, the model does not return a ranked list of links. It composes a single answer from a small pool of sources it retrieved for that topic, and it names a handful of brands inside that answer. That naming is the new visibility, and it is invisible to every tool built for classic search. Generative engine optimization is the discipline of getting your brand into that retrieval pool and staying there. It matters now because a growing share of high-intent research, especially in B2B and considered purchases, begins inside an assistant rather than a search box, and the brands that get named in the shortlist prompt are shaping the decision before a SERP is ever seen. The reassuring part is that GEO is fully measurable: fix a set of buyer prompts, run them across the platforms on a schedule, and count exactly where you and your competitors appear. Anyone who cannot show you that scoreboard is selling activity, not outcomes.

How retrieval-augmented answers are actually built

Under the hood, engines like Perplexity and the search-grounded modes of ChatGPT and Gemini run a retrieval step before they generate. The prompt is turned into one or more searches, a set of candidate pages is pulled, and the model synthesizes its answer from passages within those pages, citing the sources it leaned on. Two consequences follow directly. First, if your page is not in the retrieved set, nothing else you do matters, which makes crawler access and retrievability the non-negotiable foundation. Second, the model quotes specifics far more readily than it quotes vague claims, so pages built around a defensible statistic, a clear definition, or a named comparison get lifted repeatedly while pages of soft marketing language are passed over. Understanding this pipeline is what separates real GEO from the superstition that has grown up around it. You are not trying to trick a model; you are trying to be the clearest, most quotable, most trusted source on the specific question your buyers ask.

The grounding research behind the practice

The commercial discipline rests on published research, most notably a Princeton-led study presented at the ACM SIGKDD 2024 conference, which ran controlled experiments on how content changes affect visibility inside generative answers. The headline finding was that targeted optimization methods could raise a source's visibility in generative responses by up to forty percent, with the addition of statistics, direct quotations, and clear citations among the strongest levers. The study also documented what practitioners now call the Equalizer Effect: pages sitting around position five in classic results saw visibility inside generative answers rise by more than a hundred and fifteen percent after optimization. In plain terms, generative search compresses the advantage that incumbents enjoy in classic rankings, giving well-structured mid-authority sites a genuine path to being cited alongside household names. That is the opportunity our GEO engagement is built to capture, and it is why a smaller specialist brand can win here even when it cannot outrank a giant in the classic index.

What our GEO engagement actually delivers

We start by engineering a Money Prompt Set: ten to thirty natural-language prompts that mirror how your real buyers ask, replacing keyword research with prompt research. We run that set across ChatGPT, Claude, Perplexity, and Gemini and log every citation against named competitors, which becomes your baseline scoreboard. From the citations we build a source-pool map, the domains each platform actually pulls for your queries ranked by frequency, and treat earning presence on those exact domains as the outreach plan rather than chasing generic links. On your own pages we engineer quotable content: specific claims, statistics, and definitions the models can lift verbatim. We lock one canonical description of what you do and for whom and deploy it identically across your site, profiles, and third-party mentions, because inconsistent entity signals make models hedge and cite someone clearer. We verify AI crawler access in robots, CDN, and firewall rules, deploy a standards-based llms.txt guide at your root, and confirm in server logs that the agents actually crawl.

Reporting a board can audit, and pricing that fits

GEO earned a reputation for hand-waving because too many vendors reported effort instead of evidence. We report six reproducible numbers: citation count on the fixed prompt set, share of voice against named competitors, query coverage, mention sentiment, source-domain wins, and an on-page readiness score, with the raw model answers logged as evidence for every figure. You can reproduce any number yourself in minutes, which is the whole point. Because the work is concentrated on retrievability, a defined prompt set, and a specific list of pages and domains, we price it hourly against a written estimate rather than as an open-ended retainer. Most clients start with a baseline scan and the first round of quotable-content and entity work, then scale into source-pool outreach only where the scoreboard shows movement. You approve the hours, you see them logged, and you can pause the moment the numbers stop moving.