Search Console screenshot · 30 Jun–29 Sep 2026.
Live AI visibility studies
eFootballLAB: AI visibility with results you can inspect.
All featured figures belong to one website only, efootballlab.com. This study brings together three months of Google AI Overview appearances, UTM-attributed traffic, and crawler activity. Explore the original evidence, then compare the other studies.
The featured figures come from owner-supplied evidence received on 3 October 2026. Each image opens at its original size, and the detailed study includes the source tables.
Founder-led studies
Real websites and real data
Clear separation between evidence and assumptions
One website · efootballlab.com
Three months of measurable AI discovery.
All figures in this study belong to one website only: efootballlab.com. Google AI Overview appearances, UTM-attributed views, and crawler requests each keep their own source and measurement period.
UTM source report · three months · rounded display.
Share displayed in the supplied UTM source breakdown.
Crawler overview screenshot · three months · rounded display.
The daily line rises during August and reaches a higher range in September. The screenshot supplies the trend; no daily Google values have been reconstructed.
13.6k views, accounting for the displayed 66%. These are UTM-attributed views, not unique visitors or sessions.
The screenshot shows 1M total, 782k allowed, and 576k unsuccessful requests. These provider metrics are not added together or treated as disjoint categories.
Website: efootballlab.com only. Owner-supplied evidence received 3 October 2026. UTM and crawler screenshots cover three months, as confirmed by the owner. Rounded labels are preserved exactly as shown. Click any image to inspect the original.
Live study library
Browse SEO, AEO, and GEO case studies
eFootballLAB AI Visibility Case Study
164,000 Google AI Overview appearances, 13.6k ChatGPT-attributed views, and a detailed crawler export. Inspect the original screenshots and see what each result measures.
13.6kChatGPT-attributed views · UTM
View study
Plinkod AI Visibility Case Study
27,067 attributed visits from AI platforms, including 6,444 from ChatGPT, plus a 109,509-event crawler evidence set with transparent confidence labels.
27,067AI-platform visits
View study
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.
6Workflow steps
View workflow
Live case study data
Live AI visibility case studies with real numbers, analytics, and charts
This library is built for people looking for documented AI visibility results—not generic advice. Every study connects real website evidence with a clear SEO, AEO, or GEO workflow.
Real traffic and referral numbers
Review UTM-attributed views for efootballlab.com and the separately reported visits in the Plinkod study. Source traffic stays separate from crawler requests.
Historical bot and crawler evidence
Review named crawler request counts and daily activity. Search, training, and user-triggered agents stay individually named so their different roles remain visible.
Percentage charts and comparisons
Compare the displayed UTM source shares, inspect the original screenshots, and review daily crawler counts from the supplied CSV. Plinkod retains its own separately published analytics.
Documented SEO, AEO, and GEO analysis
Follow the starting point, the action taken, the evidence collected, and the next decision. The studies show how technical SEO, answer-ready content, generative search clarity, and crawler monitoring fit into one measurable workflow.
From data to action
How to use live case study analysis for SEO, AEO, and GEO decisions
A useful case study should help you understand what happened, what the numbers mean, and what can be tested next on your own website.
Check the evidence source
Start with the publication date and evidence type. Search Console data, referral exports, crawler logs, and saved answer-engine observations answer different questions and should not be combined into one visibility claim.
Compare the live numbers
Use percentages and trend context to see which AI platforms or crawler groups account for the largest share. A change in bot activity can guide investigation, but it does not by itself prove ranking or citation impact.
Turn analysis into the next test
Connect the observed signal to a practical action: improve crawl access, clarify a page answer, strengthen entity context, build an intent page, or monitor whether the next published snapshot changes.
Explore the Plinkod live AI visibility data, the eFootballLAB AI visibility results, or the TruboRankAI SEO, AEO, and GEO 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.
Case study questions
How to read these live AI visibility studies
Short answers about the evidence, charts, and update process used across this case study library.
What is a live AI visibility case study?
It is a documented analysis of a real website using published referral, crawler, search, and answer-engine evidence. Each study separates observed data from assumptions and explains the workflow behind the result.
What do the case study charts measure?
The featured eFootballLAB study shows UTM-attributed source views, Google AI Overview appearances, and daily crawler requests. Each source has a separate measurement period.
How often are the live case study statistics updated?
eFootballLAB uses the owner-supplied screenshots and CSV received on 3 October 2026. Its sources show their own measurement periods. Plinkod retains its frozen historical evidence snapshot.
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.