ChatGPT, Perplexity, Claude, and Gemini combined.
Evidence-led growth
Real AI visibility work. Documented openly.
TruboRankAI is used across our own web properties to test workflows, monitor discovery signals, and turn search and AI visibility data into practical next steps.
We do not publish invented customer stories or exaggerated outcomes. Each study below is based on a real website, a real workflow, and evidence we can review over time.
Founder-led studies
Real websites and real data
Clear separation between evidence and assumptions
Measured portfolio snapshot
AI discovery produced measurable referral traffic.
Across the two owner-operated properties in the supplied referrer exports, AI answer platforms generated 1,781 attributed visits and 2,303 pageviews. These are observed referrals, not estimated visibility.
Attributed across Plinkod and eFootballLab.
Measured in the two aggregate referrer exports.
Data snapshot captured 6 August 2026.
Study library
Explore the studies
Plinkod AI Visibility Case Study
990 attributed visits from AI platforms, including 967 from ChatGPT, plus a 56,081-event crawler evidence set with transparent confidence labels.
990AI-platform visits
View study
eFootballLab Search Opportunity Study
791 attributed visits from AI platforms, with ChatGPT ranking sixth among all referral sources in the supplied export.
791AI-platform visits
View workflow
How We Use TruboRankAI on TruboRankAI
A transparent look at how we use our own product data to prioritize pages, improve documentation, and test AI visibility workflows.
View workflow
Evidence standards
Why these studies are different
AI visibility is still evolving. Search engines, crawlers, and answer engines do not always expose complete information about why a website appears or disappears.
That is why these studies focus on what can be documented: page improvements, crawler activity, Search Console context, observed AI answer appearances, and the actions taken next.
Evidence standards
How we document these studies
We separate what was changed, what was observed, and what cannot yet be attributed with certainty. This keeps each study useful without turning incomplete signals into exaggerated claims.