Built on the opposite premise
We started with a peer-reviewed baseline: the Generative Engine Optimization research published at ACM KDD 2024. That gave us a scientifically grounded framework for what should drive AI citations. We treat that paper as a hypothesis, not gospel, and continually retest its recommendations against current evidence.
DataLab tests the framework against measured citation data and re-anchors it wherever the evidence disagrees. Pre-registered hypotheses, real significance thresholds, and corrections for multiple comparisons bring the scientific method to search optimization.
The data that powers it
When a page is analyzed, it enters the tracking pool. RankAbove assembles real search queries anchored in the Google searches the page already receives, runs those queries against major AI engines with live web search enabled, and reads the structured sources each engine reports using.
We match your domain exactly against those sources. A mention without a source is recorded separately and is never counted as a real citation.
A citation rate you can watch
The result is a per-page, per-engine citation rate you can monitor over time: improve your content, then measure whether answer engines begin citing it.
A real statistical bar
We hold our own findings to a real statistical standard before showing them to clients. Until a finding clears that bar, we treat it as unproven, internally and externally.
Our standard
Nothing is shown in RankAbove unless it meets our significance standards. No one should change content strategy on a whisper.