The levers

Not every “AI optimization” tactic works. Lokrix recommends only levers with measured impact on how AI engines cite and recommend sources — grounded in the Princeton GEO study (KDD 2024) and observed engine behaviour, not folklore.

Content levers and their measured visibility liftHorizontal bars showing measured visibility lift: cited sources about 41 percent, quotations 37, statistics 34, earned media about 30, and llms.txt with no measured effect shown as an empty bar.Visibility lift · Princeton GEOCited sources+41%Quotations+37%Statistics+34%Earned media (Reddit/Wikipedia/G2)+30%llms.txtno measured effect

Quotations, statistics and cited sources

The strongest on-page levers are adding quotations, concrete statistics and cited sources. In the GEO study these lifted a page’s visibility in AI answers by roughly 30–41%, and adding citations lifted low-ranked pages by around 115%. The mechanism is intuitive: engines synthesise answers from verifiable, quotable material, so pages that supply it are easier to cite.

Earned-media corroboration

Being corroborated off-site — Reddit, Wikipedia, G2 and similar — is a top driver of AI visibility. It matters most on engines that run live search and over-weight community sources: Perplexity draws roughly 47% of its top citations from Reddit. Earned mentions give the engine independent evidence that your brand is a credible answer, which no amount of on-page copy can fully substitute.

Freshness and index presence

Because engines ground on live indexes and search, freshness and where you sit in the underlying index carry through. ChatGPT tracks the Bing index closely (about 87% of its citations match Bing’s top-10), while Gemini and Google’s AI surfaces follow Google’s index. See Answer Engines for how each engine is grounded and which levers move it most.

What we won’t sell you: llms.txt

llms.txt has no measured effect on whether AI engines cite or recommend you. It is harmless to publish and Lokrix treats it as optional, but we will never present it as a visibility lever. Statistical and evidential honesty is a product rule: Lokrix only recommends changes it can attribute to real, observed impact.

From lever to plan

These levers are the vocabulary of Lokrix’s recommendations. For any target prompt, the engine picks the levers with the highest predicted uplift for your specific gaps, simulates them, and sequences them into a path to #1.