We scanned 500 brands across 6 AI engines. Here’s what moved scores.

Over the past quarter we ran repeated visibility scans across 500 tracked brands, spanning six AI engines, to see which content changes actually correlated with a measurable score jump between scans.

The two strongest predictors, by a wide margin, were structured FAQ content answering the exact prompts an engine was asked in that category, and third-party citations — independent write-ups, comparison articles, and review sites that corroborate a brand’s claims rather than the brand’s own marketing copy repeating them.

Brands that shipped both saw visibility gains within one to two tracking cycles. Brands that only optimized on-page copy without backing it up externally saw far smaller, slower-moving gains — the models seemed to weight independent corroboration heavily when deciding what to cite.

The weakest signal, somewhat surprisingly, was raw content volume. Publishing more pages without addressing specific gap prompts had almost no effect on score. Precision beat volume across every engine we measured.