Plinkod AI Visibility Case Study
How a browser games platform moved from unclear AI visibility toward documented crawler activity, search context, and appearances in selected AI answer engines.
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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We do not publish invented customer stories or exaggerated outcomes.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
Study library
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eFootballLab Search Opportunity Study
How search signals, page intent, and technical priorities can be turned into a clearer content roadmap for an established eFootball website.
View workflowHow 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.
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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.