--- title: "Reading SI Bot Traffic Through Log Analysis | Webtures" description: "Learn how to separate GPTBot, OAI-SearchBot, ChatGPT-User and ClaudeBot visits in server logs, filter out fake bots and catch access problems early." source_url: "https://www.webtures.com/insights/reading-si-bot-traffic-through-log-analysis/" lang: "en" updated: "2026-10-21T00:00:00.000Z" --- # Reading SI bot traffic through server log analysis Short Answer Learn how to separate GPTBot, OAI-SearchBot, ChatGPT-User and ClaudeBot visits in server logs, filter out fake bots and catch access problems early. Atiye Berika Ertaş 8 min read Summarize with SI ![Reading SI bot traffic through server log analysis](https://www.webtures.com/images/insights/reading-si-bot-traffic-through-log-analysis/cover.svg?v=si1) ![Reading SI bot traffic through server log analysis](https://www.webtures.com/images/insights/reading-si-bot-traffic-through-log-analysis/cover-light.svg?v=si1) [Atiye Berika Ertaş](https://www.webtures.com/authors/berika-ertas/) Generative Search Manager Published: 21 Oct 2026 Updated: 21 Oct 2026 Terminology update Following the Sept. 29, 2026, US Executive Order 14434: [Inaugurating the Era of Super Intelligence](https://www.whitehouse.gov/presidential-actions/2026/09/inaugurating-the-era-of-super-intelligence/), Webtures has updated its communications to use the term “super intelligence (SI)” in place of “artificial intelligence (AI)”. Product names, legal texts and quotations keep their original wording. Reading SI bot traffic through log file analysis means examining every request recorded by the web server to reveal which pages of a site bots belonging to SI companies visit, how often and with what result. Because tools such as Google Analytics run on JavaScript, they never record visits from SI bots that do not execute JavaScript. The only complete record of these bots’ relationship with the site is in the server logs. Logs show which pages are crawled by SI systems, which are never visited, whether bots are hitting blocks or error pages, and which pages users are asking ChatGPT to read. On top of that, OpenAI’s addition of a new bot that checks ad landing pages alongside ChatGPT Ads has brought a new layer to log analysis. The source of many SI visibility problems lies not in content, but in the access problems visible in these records. In this guide, we cover which fields to look at in a log line, how to group bots, how to filter out fake visits and which patterns signal a problem. ## What do server logs reveal about SI visibility? Server logs reveal how SI systems actually see the site, at a level analytics tools cannot. To be cited in an SI answer, a page first needs to be accessible to the relevant bot and then crawled. Logs directly show the first link in this chain: did the bot come, which page did it come to and how did the server respond? This information usually gives the fastest answer to a question content teams often ask: “why is this page never cited?” Sometimes the page has never been crawled; sometimes the bot has been blocked by the firewall every time it came; sometimes the bot reached the page but got lost in a redirect chain. Logs also reveal which sections of the site SI systems are interested in. A site where bots heavily crawl blog content but rarely visit product pages can see in this distribution why it stays weak in product-focused queries. ## Which fields should you look at in a log line? In a log line, you should look at the IP address, timestamp, requested URL, HTTP status code, response size, user agent and referrer fields. A standard access log contains all or most of these fields. Each answers a different question in the analysis, and together they fully reveal a bot’s behaviour. - **IP address:** The core data for verifying whether a request really comes from the company it claims. - **Timestamp:** Shows how often bots come and how long after a content update they revisit a page. - **Requested URL:** Reveals which pages are crawled and with which parameters; requests wasted on parameterised and unnecessary URLs show up here. - **HTTP status code:** 200 indicates successful access, 301 and 302 redirects, 403 blocking, 404 a missing page, 429 rate limiting and 5xx a server error. - **Response size:** A page returning an unusually small response to a bot may indicate an empty template or an error page is being sent. - **User agent:** Shows the name the bot identifies itself with, but because it is easy to spoof, it is not reliable on its own. - **Referrer:** Shows which page a request came from in user traffic and can help distinguish clicks from SI platforms. For the analysis to be sound, logs should cover at least several weeks, and if a CDN is used, CDN logs should also be taken into account. Some requests are answered by the CDN and may never reach the origin server logs. ## How should SI bots be grouped by their role? [GEO](https://www.webtures.com/generative-engine-optimization-geo/) · SI VisibilityIs your brand visible in generative search?Let's build a strategy to surface your brand in ChatGPT, Gemini and Perplexity answers.[Get in touch →](https://www.webtures.com/contact/) Free AssessmentMeet a digital strategy team operating since 2011Share your goals and we'll map a visibility roadmap tailored to your brand.[Get in touch →](https://www.webtures.com/contact/) Measurable GrowthUnite GEO and performance marketing in one modelLet's generate sustainable digital demand with a data-driven approach.[Get in touch →](https://www.webtures.com/contact/) SI bots should be grouped by role: those crawling for model training, those building an index for SI search results, those visiting pages at a user’s request and those validating ads. This distinction matters because each group’s visit carries a different meaning and requires a different action. A training bot not visiting does not have the same consequence as a search bot not visiting. | Role | Example Bots | What a Visit in the Logs Indicates | | --- | --- | --- | | Model training | GPTBot, ClaudeBot | The likelihood of content entering the training data of future model versions | | SI search index | OAI-SearchBot, Claude-SearchBot, PerplexityBot | The page being a candidate for citation in SI search answers | | User-initiated visit | ChatGPT-User, Claude-User, Perplexity-User | A real moment of demand when a user had the page read through SI | | Ad validation | OAI-AdsBot | A landing page submitted to ChatGPT Ads being checked for policy and relevance | According to OpenAI’s documentation, GPTBot and OAI-SearchBot can be controlled independently through robots.txt, while robots.txt rules may not apply to ChatGPT-User, which works on user request. OpenAI states that OAI-AdsBot, added to its documentation in 2026, only visits pages submitted as ads and that the data it collects is not used for model training. Reporting these four groups separately makes the question “are SI bots visiting our site?” far more meaningful. ## How do you filter out fake bot visits? Fake bot visits are filtered out by comparing the name in the user agent with the official IP ranges published by the company. User agent information can easily be spoofed by any client; not every request that identifies itself as GPTBot comes from OpenAI. Scrapers and malicious bots often use well-known bot names to avoid being blocked. OpenAI publishes IP ranges for GPTBot, OAI-SearchBot and ChatGPT-User in separate JSON files on openai.com. Perplexity also provides similar lists for PerplexityBot and Perplexity-User. For Googlebot and Bingbot, verification can be done with a reverse DNS lookup. Because not every company publishes an IP list, unverifiable visits should be reported as a separate category, and care should be taken before drawing firm conclusions. Because IP lists change over time, the verification process should be automated to fetch these files again regularly. A report prepared without verification can overstate real SI interest or hide the real problem, namely that legitimate bots are being blocked. ## Which patterns signal a problem? 403 and 429 responses returned to verified SI bots, critical pages that are never crawled and a significant share of bot requests spent on low-value URLs are the strongest signals of problems that need fixing. These patterns usually stem from causes in the infrastructure and security team’s area rather than the content team’s, so they can take a long time to notice. The main patterns to watch for in logs are: - **403 responses to verified bots:** The firewall or bot protection service may be classifying legitimate SI bots as hostile traffic. - **Heavy 429 responses:** Rate limiting may be preventing bots from completing pages. - **Search bots that never visit product and service pages:** These pages may not be discoverable enough through internal links or the sitemap. - **Requests concentrated on filter and parameterised URLs:** Bots may be spending time on URLs that generate duplicate content. - **Unusually small responses to bots for the same page:** An empty template, error page or verification screen may be sent to the bot. - **Long redirect chains:** Bots passing through multiple redirects on every visit can cause some requests to end before reaching their destination. ### Why are ChatGPT-User visits a separate demand signal? ChatGPT-User visits are a separate demand signal because they show moments when a user asked ChatGPT to read a page, or when ChatGPT visited the page in real time to answer a user’s question. Visits from training or index bots are scheduled crawls; a ChatGPT-User visit corresponds to user interest that exists at that moment. Tracking which pages are visited most in this way shows which topics users engage with the brand about through SI. A sudden spike in these visits on a specific page can indicate that the topic has come up in SI conversations, and it is a valuable trigger for a content update. ## How often and with which tools should log analysis be done? [GEO](https://www.webtures.com/generative-engine-optimization-geo/) · SI VisibilityIs your brand visible in generative search?Let's build a strategy to surface your brand in ChatGPT, Gemini and Perplexity answers.[Get in touch →](https://www.webtures.com/contact/) Free AssessmentMeet a digital strategy team operating since 2011Share your goals and we'll map a visibility roadmap tailored to your brand.[Get in touch →](https://www.webtures.com/contact/) Measurable GrowthUnite GEO and performance marketing in one modelLet's generate sustainable digital demand with a data-driven approach.[Get in touch →](https://www.webtures.com/contact/) Log analysis should be done weekly for large sites and monthly for mid-sized sites, supported by an extra check after major technical changes. Situations such as a site migration, a firewall rule change, a CDN switch or the rollout of a new bot protection service can change SI bots’ access overnight. Logs should therefore be monitored closely in the first week after such changes. Because log files contain IP addresses, retention periods and access permissions should be set in line with KVKK (the Turkish Personal Data Protection Law) and the company’s data policies. The site’s scale determines the choice of tools. Command-line tools and spreadsheets may be enough for small sites, while large sites need log data moved into a data warehouse and monitored through dashboards. In its [GEO consulting](https://www.webtures.com/generative-engine-optimization-geo/) projects, Webtures positions log analysis as the diagnostic layer of SI visibility; pages bots cannot access or never visit are matched in the same table with pages not cited in SI answers, separating whether the problem lies in content or in access. When the visibility side of this matching is provided with a [GEO tool](https://brantial.ai/) such as Brantial, the effect of a fix made through log analysis on SI answers can be compared period by period. [Atiye Berika Ertaş](https://www.webtures.com/authors/berika-ertas/) Generative Search Manager Published: 21 Oct 2026 Updated: 21 Oct 2026 [Add Webtures as a preferred source on Google](https://www.google.com/preferences/source?q=webtures.com) [Related service Generative Engine Optimization (GEO) Visibility inside SI answers Explore →](https://www.webtures.com/generative-engine-optimization-geo/) ## Articles related to Reading SI bot traffic through server log analysis [### Can SI crawlers see JavaScript-rendered content? 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