AI Bot Visibility Across Five Matched Websites

The first AISymantix study found a narrow page-level discovery signal but no reliable sitewide prediction. The obvious next question was whether AISymantix was simply too small a sample. So I picked four other websites with similar launch timing, current page counts, GSC coverage, and validated crawler data. Then the comparison did something useful. It made the crawler story harder to defend.

Five Matched Websites in the AI Bot Visibility Study

The cohort was selected before calculating the result. First GSC observations fall within twenty-one days of one another. Current sitemaps remain in the same general size band. Every site supplies a complete GSC series from July 9 through October 6 and the same eighty-eight validated Good Bot days after the two unavailable cache dates are left as gaps.

How Site Changes Could Affect AI Bot and Search Activity

AISymantix received most of my attention during this period. That is not a subtle difference hiding in the data. Thirty-four of the cohort's forty-six logged SEO Events belong to AISymantix. It also generated about two-thirds of the measured impressions. If I worked on one site constantly and barely touched the others, of course the worked site should look different.

The explanation got tidier as the study ran. AISymantix logged thirty-four events and was the only site whose impressions rose in the fourteen-day comparison. The other four logged between two and five events each, and all four fell. That fits the work theory. It is also one outlier among five sites, so the 0.69 correlation between events and impression change describes the sites. It does not test the theory. Events vary wildly in scope, event logging is not work-hour tracking, and five sites are not a controlled test. Event count cannot be used as a dosage meter.

The fair reading is narrower. Sustained work probably contributed to AISymantix owning about two-thirds of cohort visibility. The current data cannot separate that contribution from topic demand, content quality, internal linking, query competition, or the unusually strong search-visibility cluster AISymantix developed during the same period.

Crawler Requests Rose Across Five Sites; Search Impressions Did Not

This is the contradiction I was looking for. Good Bot activity increased on all five sites, by 142 percent to 579 percent. Search impressions rose 6.3 percent on AISymantix and fell on the other four, from 9.9 percent on AITOAIConnect to 72.3 percent on SymatixAI. SymatixAI and CustomCakesOrlando each recorded about four-fifths as many Good Bots as AISymantix, yet each earned only about a tenth of its impressions.

If crawler volume were a practical leading indicator, those are difficult results to explain. If crawler volume measures machine access while search visibility depends on a larger system, they make perfect sense.

Daily AI Bot Counts Did Not Forecast Search Impressions

The cohort test normalizes daily bots and impressions by current sitemap size, removes each site's average, and compares the remaining within-site movement. That keeps AISymantix's larger impression total from swallowing the other four sites. The test then asks whether today's bot activity aligns with the change in impressions up to seven days later.

The strongest bot-leading growth relationship is 0.021 at six days. That is effectively zero, and it is the best of seven possible leading lags, so it flatters the result. At sixty-one days the same test read 0.119. Adding twenty-seven more days pulled it down, which is consistent with a chance result. The longer, broader test reaches the same conclusion as the original AISymantix analysis.

AI Bots Reached Some Pages Before Google Recorded Impressions

The sitewide theory failed twice. The page-level sequence did not. Across the retained raw-request window, twenty-one current pages received a Good Bot request before their first GSC impression. That is real discovery order. It is surrounded by seventy-three bot-only pages and six same-day, search-first, or search-only counterexamples. That is why discovery order cannot be promoted into ranking prediction.

What the Five-Site Study Supports

• Websites with similar age and page counts can produce radically different search visibility while receiving much closer Good Bot totals.
• Good Bot growth is common across the cohort. It ran from 142 to 579 percent on every site, including the four where impressions fell.
• AISymantix's work intensity is a credible part of its result, but event count is not a clean measurement of effort and does not isolate causation.
• Event count tracks impression change across the five sites, but one site holds 74 percent of the events, so the pattern rests on a single outlier.
• Crawler requests remain useful evidence of machine access and page discovery order.
• Neither crawler totals nor the current pooled lag test support using bot visibility as a ranking forecast.

AI Bot Cohort Study: Sources and Measurement Limits

• The sites were selected using current sitemap size, first GSC observation date, and overlapping validated Good Bot coverage before the cohort result was calculated.
• Study totals use only dates available for every site in both GSC device totals and the algorithm-version-2 Good Bot cache.
• Good Bots count successful content GET requests from active search, AI search, training, and user-retrieval crawler fingerprints.
• The pooled lag test normalizes by current sitemap size and removes each site's mean before calculating correlation.
• SEO Events are evidence that recorded work occurred. Their absence does not prove that nothing changed, and one event is not equal to another event.
• The five sites have similar age and size, but their subjects, competition, content, internal linking, and search demand remain different.
• Raw request retention is thirty-five days, so page timing and human-request comparisons use a shorter window than the eighty-eight-day site series.
• Crawler activity proves machine access. It does not prove indexing, citation, training use, a human prompt, ranking causation, or future visibility.

Public living dataset /data/research/ai-bot-visibility-cohort.json. It includes the cohort definition, daily site rows, crawler-purpose totals, lag tests, event windows, page timing, bot-first receipts, bot-only counterexamples, method, and limits.