Answers that name a competitor

If your main question is “when do GPT-style crawlers hit my site, and how often?”, I’d look at these:

• developers.cloudflare.com — best overall if you already use Cloudflare. It gives you request-over-time charts, crawler breakdowns, paths, bandwidth, and filters for individual crawlers such as GPTBot, OAI-SearchBot, ClaudeBot, and PerplexityBot. Cloudflare Docs Cloudflare Docs
• help.ahrefs.com — good if you're already using Ahrefs. It tracks which bots visit, how frequently, and which pages they crawl; its Bot Analytics is currently in beta. Ahrefs Help Center
• kitbase.dev — purpose-built for this. It emphasizes per-URL crawl frequency and distinguishes verified crawlers from spoofed User-Agent strings. Kitbase
• surva.ai — another dedicated option. It provides a 30-day trend chart, page-level crawl counts, real-time activity, and crawler error reporting. Surva.ai
• Your server/CDN logs + a log analyzer — cheapest and most authoritative if you have access to them. GPT-style crawlers identify themselves through HTTP User-Agent strings, so you can count requests from GPTBot, OAI-SearchBot, ClaudeBot, etc. Cloudflare

My pick

If your site is behind Cloudflare, use Cloudflare AI Crawl Control first. It directly answers the “crawl frequency over time” question without adding another analytics script, and it can break activity down by crawler and URL. Cloudflare Docs

One important distinction: Google Analytics won't reliably show this traffic, because these crawlers generally fetch pages server-side rather than executing your analytics JavaScript. DataEase AI

Also, don't lump all “GPT traffic” together: GPTBot, OAI-SearchBot, and ChatGPT-User represent different OpenAI use cases, so tracking them separately is much more informative. Cloudflare Docs

If you tell me what your site runs on (Cloudflare, Vercel, WordPress, Shopify, AWS, etc.), I can recommend the simplest setup and what dashboard I'd use.

If you want to track GPT-style crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended, etc.) hitting your website and graph crawl frequency over time, you generally need server-side bot analytics, not Google Analytics (AI crawlers usually do not execute JavaScript). www.dataease.aiwww.crawlerlogs.com

Good options:

A DIY approach is often enough:

1. Capture requests from your web server/CDN:
   • User-Agent
   • URL requested
   • Timestamp
   • Status code
   • IP (optional)

2. Identify crawler user agents:
   • GPTBot
   • ChatGPT-User
   • OAI-SearchBot
   • ClaudeBot
   • PerplexityBot
   • Google-Extended
   • others

3. Aggregate:
   • crawls/day by bot
   • crawls/week/month
   • pages most frequently fetched
   • time between revisits

If you already use Cloudflare, that is usually the cleanest place to collect this data because it sees requests before they reach your origin. Tools like CrawlerLogs and similar services often build on edge/CDN logging for this reason. www.crawlerlogs.com

For a typical site, I’d choose:

• No engineering effort: CrawlerLogs or DataEase AI www.dataease.aiwww.crawlerlogs.com
• SEO-focused: Ahrefs Bot Analytics help.ahrefs.com
• Large/custom site: Cloudflare logs → warehouse → Grafana/Looker dashboard

One important distinction: crawl frequency ≠ citation frequency. A GPTBot hit means an AI system fetched your content; it does not guarantee that ChatGPT or another assistant will use or cite it later. www.dataease.aiwww.crawlerlogs.com

If your goal is specifically “which AI assistants are crawling my site, how often, and which pages they’re taking”, the best options are a bit different from traditional SEO tools.

My picks

1. developers.cloudflare.com — best overall

• Shows activity from AI crawlers such as GPTBot, ClaudeBot, PerplexityBot, etc.
• Breaks activity down by crawler/operator, URL path, status code, bandwidth and time period.
• Lets you distinguish AI Search, Agent and Training behavior.
• Can also allow/block individual crawlers and monitor robots.txt compliance. Cloudflare Docs Cloudflare Docs Cloudflare Docs
• Particularly compelling if your site already runs through Cloudflare: AI Crawl Control is available on all Cloudflare plans, although the free tier has a limited analytics window. Cloudflare Docs
• ahrefs.com — best if you already use Ahrefs

• Tracks bots server-side rather than relying on JavaScript.
• Lets you isolate AI crawler traffic and see which pages they're crawling.
• Also puts AI crawlers alongside search engines, SEO crawlers and other bots, which is useful for comparing your overall crawl budget. Ahrefs Help Center Ahrefs
• Currently in beta and free according to Ahrefs. Ahrefs Help Center
• promptwatch.com — best for “crawl → citation”

• Goes beyond raw crawler logs.
• Claims to connect which pages AI systems crawl with which pages subsequently get cited in ChatGPT, Claude, Gemini, Perplexity and other AI search systems. Promptwatch
• Interesting if your real KPI isn't crawling, but “AI read my page → AI actually cited my page.”
• dataease.ai — worth looking at for lightweight monitoring

• Focuses specifically on AI crawler logs, including GPTBot and ClaudeBot.
• Its approach is particularly useful if you want page-level crawl frequency without adopting a big SEO platform. DataEase AI

One important distinction

I'd separate AI crawling/indexing from AI visibility.

For example:

GPTBot → crawled /best-running-shoes/

does not necessarily mean:

ChatGPT → indexed /best-running-shoes/ → cited it to a user.

AI systems have multiple crawler types. Cloudflare's current classification is particularly useful here: Search crawlers collect/index content for later answers, Agent crawlers act on behalf of users in real time, and Training crawlers collect content for model training. Cloudflare Docs

For example, Cloudflare identifies OpenAI's GPTBot, ChatGPT-User, and OAI-SearchBot as distinct crawler/assistant/search identities, with equivalent distinctions for Anthropic and Perplexity. Cloudflare Docs

What I'd use

If I were setting this up today, I'd do:

Cloudflare AI Crawl Control + Ahrefs Bot Analytics

Cloudflare gives you the raw edge-level truth about who is hitting which URLs, while Ahrefs gives you a more SEO-oriented way to analyze bot activity. Then, if you're serious about measuring AI SEO, add a tool such as Promptwatch that tracks AI mentions/citations.

The resulting dashboard should answer four separate questions:

If you tell me your stack (Cloudflare/Vercel/AWS/etc.) and whether you care more about ChatGPT/Claude/Perplexity crawling or actually citing your pages, I can narrow this down to the 2–3 best choices and compare pricing/features.

If by “monitoring how AI assistants crawl and index my site pages” you mean which AI bots actually fetch which URLs, plus whether those pages subsequently get cited in AI answers, I’d separate the market into two categories. Crawl activity and AI visibility are related, but they are not the same thing. Tracemetry

My top picks

1. Botify — best if you have a serious SEO operation

This is probably my #1 choice for a large site. Botify's Analytics Suite combines its own crawling with server-log data, and its new AI Visibility/Discoverability functionality specifically analyzes LLM crawler behavior at the URL level. Botify Knowledge Base Botify Knowledge Base

The interesting part is that you can get closer to:

“These 40,000 important URLs received Google traffic, but only 2,300 have been fetched by AI crawlers.”

That's much more actionable than a generic “AI visibility score.”

support.botify.com

2. Profound — best for “are AI assistants actually using me?”

If your real objective is AI search visibility rather than raw crawling, I'd look very seriously at Profound.

The distinction matters: a crawler visiting /pricing doesn't necessarily mean ChatGPT or Gemini will cite /pricing. Crawl logs are evidence of access, not evidence of visibility. Tracemetry

Profound is oriented more toward monitoring AI answers, citations, competitors, and the emerging answer-engine ecosystem.

3. OtterlyAI — best accessible option

Otterly is attractive if you don't need enterprise-grade server-log analysis. It monitors generated answers across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, including which URLs are cited. Otterly

otterly.ai

I'd use this for the question:

“When people ask AI systems about topics we care about, which of our pages get cited?”

rather than:

“Exactly which AI crawler requested /foo/bar at 03:17?”

4. Cloudflare — surprisingly good if you want raw data

If your site already runs through Cloudflare, don't overlook it.

For a technical team, edge/server logs can actually be preferable to another SaaS dashboard. You can identify things such as OpenAI's GPTBot and OAI-SearchBot, Anthropic's crawlers, Perplexity's crawler, etc., and analyze URL-level requests yourself. Crawlytics

One important wrinkle: Google-Extended isn't a crawler you should expect to see in your access logs. It's a robots.txt control applied to Google's crawling infrastructure, rather than a separate HTTP user agent. Crawlix

5. Surva.ai — closest to your exact question

Surva is particularly interesting if your primary requirement is:

“Show me which AI crawlers are visiting my site, how frequently, and which pages they're reading.”

It explicitly tracks AI crawler activity and reports which pages are being visited versus missed. Surva.ai

surva.ai

What I'd actually build

For a serious AI SEO / GEO monitoring stack, I'd combine two layers:

Layer 1 — Crawl telemetry

• GPTBot / OAI-SearchBot
• ClaudeBot / Claude-SearchBot
• PerplexityBot
• Googlebot / Google AI ecosystem
• Bingbot
• other AI/search crawlers
• URL requested
• timestamp
• HTTP status
• response size
• robots.txt status
• crawl frequency

Layer 2 — AI visibility

• Which prompts trigger your brand?
• Which of your URLs are cited?
• Which competitors are cited instead?
• Citation frequency by URL
• Citation frequency by AI engine
• Changes over time
• AI referral traffic

That's important because “AI crawled my page” ≠ “AI indexed my page” ≠ “AI cited my page.” The tools that only count crawler hits can give you a misleading picture of visibility. Tracemetry Botify Knowledge Base

My recommendation by situation

• Large enterprise site: Botify + Profound
• Mid-size site / SEO team: Botify or Tracemetry + Otterly
• Small site / startup: Surva + Otterly
• Technical team already on Cloudflare: Cloudflare logs + Otterly
• You primarily care about individual URLs being cited: Otterly
• You primarily care about exactly what AI bots are crawling: Botify or Surva
• You want the most complete “crawl → citation → traffic” picture: Profound/Tracemetry-style platform

If you tell me roughly how many pages your site has (1K / 10K / 100K / 1M+) and whether you have Cloudflare/server-log access, I can narrow this to the 3 best options and compare pricing, API access, crawler coverage, and URL-level reporting.

That's much more actionable than a generic “AI visibility score.”

support.botify.com

2. Profound — best for “are AI assistants actually using me?”

If your real objective is AI search visibility rather than raw crawling, I'd look very seriously at Profound.

The distinction matters: a crawler visiting /pricing doesn't necessarily mean ChatGPT or Gemini will cite /pricing. Crawl logs are evidence of access, not evidence of visibility. Tracemetry

Profound is oriented more toward monitoring AI answers, citations, competitors, and the emerging answer-engine ecosystem.

3. OtterlyAI — best accessible option

Otterly is attractive if you don't need enterprise-grade server-log analysis. It monitors generated answers across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, including which URLs are cited. Otterly

otterly.ai

I'd use this for the question:

“When people ask AI systems about topics we care about, which of our pages get cited?”

rather than:

“Exactly which AI crawler requested /foo/bar at 03:17?”

4. Cloudflare — surprisingly good if you want raw data

If your site already runs through Cloudflare, don't overlook it.

For a technical team, edge/server logs can actually be preferable to another SaaS dashboard. You can identify things such as OpenAI's GPTBot and OAI-SearchBot, Anthropic's crawlers, Perplexity's crawler, etc., and analyze URL-level requests yourself. Crawlytics

One important wrinkle: Google-Extended isn't a crawler you should expect to see in your access logs. It's a robots.txt control applied to Google's crawling infrastructure, rather than a separate HTTP user agent. crawlix.app

5. Surva.ai — closest to your exact question

Surva is particularly interesting if your primary requirement is:

“Show me which AI crawlers are visiting my site, how frequently, and which pages they're reading.”

It explicitly tracks AI crawler activity and reports which pages are being visited versus missed.

Yes. There are platforms that can alert you when AI crawlers hit specific URLs (for example, high-margin product pages, pricing pages, or proprietary content pages). The category is usually called AI crawler monitoring, LLM bot analytics, or AI visibility monitoring.

Some options:

For an ecommerce site, the setup I’d look for is:

1. Connect to your CDN/server logs

• Cloudflare, AWS CloudFront, Fastly, Nginx, Shopify edge logs, etc.
• Avoid relying only on JavaScript analytics because many crawlers do not execute JS. Honeyb CrawlerLogs
• Create URL-based alerts

Examples:

• “Alert me if GPTBot accesses /products/high-margin-widget”
• “Alert me when ClaudeBot hits /pricing”
• “Daily digest of AI crawlers touching our top 100 SKUs”
• “Notify me if AI crawler traffic to product pages spikes 5×”
• Verify the crawler identity

User-agent strings can be spoofed. Better tools validate crawlers against known IP ranges or infrastructure signals. LogLens Everfound

If your store is on Shopify, Magento, WooCommerce, or a custom stack, the best option may differ. The key question is whether you need:

• real-time Slack/email alerts when a valuable page is crawled, or
• analytics dashboards showing AI crawler trends and citations.

Yes. Cloudflare is probably the closest off-the-shelf fit for exactly this use case.

Best fit: Cloudflare AI Crawl Control

cloudflare.com can identify AI crawlers and show:

• Which AI crawler accessed the site — e.g. GPTBot, ClaudeBot, Bytespider.
• Which specific URL/path it requested.
• Request volume and data transferred.
• Which AI operator is behind the crawler.
• Filters by crawler, operator, hostname, and path. Cloudflare Docs

So you could monitor something like:

/products/rare-widget
/collections/luxury-*
/pages/brand-story

and determine when AI crawlers are hitting those high-value areas.

The interesting part is that Cloudflare now supports AI Crawl Control on all plans, although the depth of bot identification and historical analytics varies by plan. Cloudflare Docs Cloudflare Docs

If you specifically want an instant alert

There's a distinction worth making:

Cloudflare's native product is primarily an analytics/control system, not a "send me a Slack notification every time GPTBot hits /product/X" product.

However, Cloudflare gives you the underlying request data and APIs, so you can build that alerting layer. Its bot-alert system can also send notifications by email, webhook, or PagerDuty, although the documented custom bot alerts are an Enterprise feature. Cloudflare Docs

There's also an open-source Cloudflare Worker called AI Traffic Alerts for Cloudflare that specifically implements crawler/referral notifications and can send alerts to services such as Telegram, WhatsApp, Discord, Pushover, and ntfy. GitHub

Another option: Ahrefs Bot Analytics

help.ahrefs.com is worth looking at if you mainly want analytics rather than real-time alerts. It tracks AI assistants, individual bots, and the specific pages they crawl, with filtering by bot and URL. It's currently free during beta. Ahrefs Help Center

What I'd do for an ecommerce site

If your actual goal is:

"Tell me immediately when an AI company starts crawling one of my commercially valuable product pages."

I'd use Cloudflare + a lightweight alerting rule rather than installing an ecommerce analytics app.

For example:

GPTBot / ClaudeBot / PerplexityBot → /products/* → send Slack/email alert

You can make it even more useful by assigning tiers:

• Tier 1: individual high-margin product URLs → alert immediately
• Tier 2: product/category pages → aggregate alerts hourly
• Tier 3: blog/help pages → analytics only
• Known search crawlers: ignore
• Unknown/impersonating bots: flag separately

One caveat: AI crawler identification isn't perfect. Cloudflare's basic detection relies on crawler identity/user-agent information; its more advanced Bot Management detection adds behavioral/fingerprinting signals. Cloudflare Docs

If you tell me what your ecommerce stack is (Shopify, WooCommerce, BigCommerce, custom, etc.), I can tell you the simplest way to get a real-time alert for specific URLs, including what I'd use and roughly what it would cost.

There's a distinction worth making:

Cloudflare's native product is primarily an analytics/control system, not a "send me a Slack notification every time GPTBot hits /product/X" product.

However, Cloudflare gives you the underlying request data and APIs, so you can build that alerting layer. Its bot-alert system can also send notifications by email, webhook, or PagerDuty, although the documented custom bot alerts are an Enterprise feature. Cloudflare Docs

There's also an open-source Cloudflare Worker called AI Traffic Alerts for Cloudflare that specifically implements crawler/referral notifications and can send alerts to services such as Telegram, WhatsApp, Discord, Pushover, and ntfy. GitHub

Another option: Ahrefs Bot Analytics

help.ahrefs.com is worth looking at if you mainly want analytics rather than real-time alerts. It tracks AI assistants, individual bots, and the specific pages they crawl, with filtering by bot and URL. It's currently free during beta. help.ahrefs.com

What I'd do for an ecommerce site

If your actual goal is:

"Tell me immediately when an AI company starts crawling one of my commercially valuable product pages."

I'd use Cloudflare + a lightweight alerting rule rather than installing an ecommerce analytics app.

For example:

GPTBot / ClaudeBot / PerplexityBot → /products/* → send Slack/email alert

You can make it even more useful by assigning tiers:

Yes—but there's an important distinction.

Most AI crawler analytics tools show which pages AI bots visit, but very few reconstruct complete crawl sessions with entry and exit paths. AI crawlers don't behave like human visitors, so "sessions" are harder to infer. Most products stop at page-level analytics. A handful are starting to visualize crawl sequences. Cloudflare Docs Ahrefs Help Center

If your goal is "show me the paths GPTBot, ClaudeBot, PerplexityBot, etc. take through my site", here's how the landscape looks:

What you're asking for is more like a Sankey graph

Ideally you'd see something like:

GPTBot

robots.txt
      │
      ▼
sitemap.xml
      │
      ▼
/blog/
      │
 ┌────┴─────┐
 ▼          ▼
/pricing   /docs
 │            │
 ▼            ▼
/api      /about
 │
 ▼
EXIT

or

ClaudeBot

Homepage
   │
   ▼
Features
   │
   ▼
Pricing
   │
   ▼
Case Study
   │
   ▼
Exit

That's still uncommon in commercial dashboards.

If you really want entry → path → exit

The best approach is often to analyze server logs instead of relying on analytics.

You can reconstruct sessions by:

• grouping requests by crawler IP + User-Agent
• ordering requests by timestamp
• breaking sessions after ~5–10 minutes of inactivity
• generating: - entry pages
• transition matrix
• exit pages
• Sankey diagrams
• crawl depth
• loops
• abandoned branches

This produces exactly the visualization you're describing.

I'd build it differently

If I were building this today, I'd create a dashboard showing:

• Entry pages by AI crawler
• Top crawl flows (Sankey diagram)
• Exit pages
• Average crawl depth
• Pages that every crawler reaches
• Pages only one crawler reaches
• Dead-end pages where crawlers stop
• Comparison between GPTBot, ClaudeBot, Google-Extended, PerplexityBot, etc.

That kind of report is much more actionable than simple "top pages crawled."

If your site runs behind Cloudflare, NGINX, Apache, or another server where you have access to logs, this is very feasible to build. The raw data already contains almost everything needed—you mainly need the session reconstruction and visualization layer.

Yes—but there's an important distinction.

Most AI crawler analytics tools show which pages AI bots visit, but very few reconstruct complete crawl sessions with entry and exit paths. AI crawlers don't behave like human visitors, so "sessions" are harder to infer. Most products stop at page-level analytics. A handful are starting to visualize crawl sequences. Cloudflare Docs Ahrefs Help Center

If your goal is "show me the paths GPTBot, ClaudeBot, PerplexityBot, etc. take through my site", here's how the landscape looks:

What you're asking for is more like a Sankey graph

Ideally you'd see something like:

GPTBot

robots.txt
      │
      ▼
sitemap.xml
      │
      ▼
/blog/
      │
 ┌────┴─────┐
 ▼          ▼
/pricing   /docs
 │            │
 ▼            ▼
/api      /about
 │
 ▼
EXIT

or

ClaudeBot

Homepage
   │
   ▼
Features
   │
   ▼
Pricing
   │
   ▼
Case Study
   │
   ▼
Exit

That's still uncommon in commercial dashboards.

If you really want entry → path → exit

The best approach is often to analyze server logs instead of relying on analytics.

You can reconstruct sessions by:

• grouping requests by crawler IP + User-Agent
• ordering requests by timestamp
• breaking sessions after ~5–10 minutes of inactivity
• generating: - entry pages
• transition matrix
• exit pages
• Sankey diagrams
• crawl depth
• loops
• abandoned branches

This produces exactly the visualization you're describing.

I'd build it differently

If I were building this today, I'd create a dashboard showing:

• Entry pages by AI crawler
• Top crawl flows (Sankey diagram)
• Exit pages
• Average crawl depth
• Pages that every crawler reaches
• Pages only one crawler reaches
• Dead-end pages where crawlers stop
• Comparison between GPTBot, ClaudeBot, Google-Extended, PerplexityBot, etc.

That kind of report is much more actionable than simple "top pages crawled."

If your site runs behind Cloudflare, NGINX, Apache, or another server where you have access to logs, this is very feasible to build. The raw data already contains almost everything needed—you mainly need the session reconstruction and visualization layer.

If your goal is specifically to correlate AI crawler activity with changes in organic traffic and conversions, I’d shortlist these:

Best fit: Botify

botify.com is probably the strongest fit for this exact analysis.

It can combine:

• Server logs → actual AI crawler activity, including GPTBot, ChatGPT-User, OAI-SearchBot, ClaudeBot, PerplexityBot, etc.
• Google Search Console → impressions, clicks and keyword/page performance.
• Analytics/conversion data → visits, conversions and revenue.
• URL-level SEO/crawl data → so you can determine whether pages crawled by AI bots subsequently gain or lose organic performance.

Botify specifically has an “AI Bots in Search” report that combines AI-bot behavior with user visits, and its broader Analytics suite overlays crawl, GSC, visit and conversion data. Botify Knowledge Base Botify Knowledge Base

That lets you ask questions such as:

“Pages heavily crawled by ChatGPT/Perplexity in January—did their Google clicks, organic sessions and conversions change in February/March?”

Best alternative: Oncrawl

oncrawl.com is particularly good if you want to work directly from server logs.

Its AI Search Lens tracks AI-bot crawling, citation-related crawling and AI referral traffic, and lets you cross-reference that with crawl metrics and custom metrics. Its Log Analyzer also covers AI bots, search-engine crawlers and organic traffic. Oncrawl - Technical SEO Data Oncrawl - Technical SEO Data

I'd favor Oncrawl if your SEO team is already heavily invested in log-file analysis.

Easiest/cheapest bot visibility: Ahrefs

ahrefs.com is worth considering if you already use Ahrefs. Its Bot Analytics uses Cloudflare data to identify AI crawlers and the URLs they visit. It currently covers categories such as AI crawlers, AI assistants, AI search and traditional search engines. Ahrefs Help Center Ahrefs

The limitation is that Bot Analytics itself isn't the complete causal/correlation layer I'd choose for connecting crawler activity to conversions. You'd likely combine it with your analytics/GSC data.

My recommendation

If you're trying to prove or disprove an actual relationship, I'd choose Botify. The important thing isn't merely measuring “AI bots crawled 20% more.” You want a dataset keyed by URL × date containing AI crawler hits, Google impressions/clicks, organic sessions, conversions/revenue, and ideally page/content changes. Botify is unusually well suited to putting those datasets together. Botify Knowledge Base Botify Knowledge Base

One important caveat: correlation isn't necessarily causation. An AI crawler may preferentially crawl pages that are already becoming more popular. For a stronger analysis, I'd use crawl events as a time-series/event variable and compare affected pages against similar pages that weren't crawled, controlling for seasonality, rankings, content changes, links, etc.

If you tell me what you're currently using (GA4 + GSC + Cloudflare/Akamai/CDN + Ahrefs/Semrush/etc.), I can also recommend the lowest-cost setup to build this correlation without buying Botify/Oncrawl.

Yes. If your goal is specifically “Did increased AI crawler activity coincide with changes in Google organic traffic and conversions?”, I’d look at tools that can join server-side crawler logs + Google Search Console/GA4 data rather than a tool that only reports AI referrals.

Best fits

• conductor.com — probably the closest match if you want an enterprise SEO dashboard. It integrates with GA4 and puts AI-sourced sessions, engagement, conversions and revenue alongside traditional organic performance. Conductor
• ahrefs.com — excellent for the crawler side. It identifies individual AI crawlers, pages crawled and activity over time, using server-side Cloudflare data. You can export the data and correlate it with GSC/GA4 yourself. Ahrefs Help Center Ahrefs
• developers.cloudflare.com — best if you already use Cloudflare. It gives you crawler-level and page-level activity, trends and CSV exports, and exposes the data programmatically through its GraphQL Analytics API. Cloudflare Docs
• searchable.com — interesting if you want a lighter-weight analytics layer. It explicitly combines crawler activity with GA4/GSC data and compares crawler/referral/page movement over the same reporting periods. Searchable

What I'd use

For a serious analysis, I'd build this data model:

AI crawler activity
→ GPTBot / OAI-SearchBot / ClaudeBot / PerplexityBot / Google AI crawlers
→ URL + date + crawl frequency

SEO performance
→ GSC impressions + clicks + CTR + average position
→ ideally at the URL/query level

Business outcome
→ GA4 organic sessions
→ conversions
→ conversion rate
→ revenue/value

Then analyze things like:

“When GPTBot/PerplexityBot activity increased on these 50 pages, did their Google impressions, rankings, organic clicks, and conversions subsequently change?”

That's more useful than simply comparing total AI crawls against total organic traffic, because correlation can be heavily confounded by seasonality, algorithm updates, content releases, backlinks, and demand changes.

If you tell me whether you're using Cloudflare + GA4 + Google Search Console, I can recommend the simplest stack and show you exactly how I'd structure the correlation analysis.

If you mean AI Share of Voice (AI SOV) — measuring how often your brand/content is surfaced, mentioned, or cited in AI-generated answers after AI engines retrieve information — you’re looking for GEO (Generative Engine Optimization) / AI visibility tracking platforms rather than traditional SEO crawlers. These tools typically run a set of prompts against AI engines, capture responses and citations, and calculate metrics like mention rate, citation share, competitor visibility, and source URLs. Daily.dev Shadow

Some of the main options:

What to look for specifically

For your use case (“after crawling” and “how often our content is surfaced”), prioritize tools that provide:

• Citation-level tracking: “Did ChatGPT cite our URL?” rather than only “Did it mention our brand?”
• Prompt panels: a fixed set of buyer queries tracked over time.
• Engine coverage: - ChatGPT
• Perplexity
• Gemini
• Claude
• Google AI Overviews / AI Mode
• Copilot (if relevant)
• Competitor share comparison: your citation share vs. competitors.
• Source attribution: which pages, articles, reviews, or third-party sites are being pulled into answers. Shadow cloro

If you are coming from an SEO/content background

The closest mental model is:

• SEO ranking tools → “Are we ranking for keywords?”
• AI SOV tools → “When someone asks an AI assistant a relevant question, does it recommend or cite us?”

A typical KPI would be:

AI Citation Share = (AI answers citing your brand/content ÷ total relevant AI answers tracked) × 100

Most mature teams also separate:

• Brand mention share (named in the answer)
• Citation share (your URL/source used)
• Recommendation share (AI says you are a preferred option)
• Competitive displacement (competitor cited instead of you) organikpi.com

For a marketing team, I’d usually shortlist Profound, Ahrefs Brand Radar, Semrush, Peec AI, and Otterly.AI; for an enterprise content/GEO program, look harder at Profound or Scrunch. Geo Software Rankings Foglift

Yes. The category you’re looking for is usually called AI search visibility / AI visibility / GEO monitoring, and several tools now calculate something very close to “AI share of voice.”

The important distinction is that there are two different measurements:

1. AI answer SOV: How often your brand/content is mentioned or cited in AI-generated answers relative to competitors.
2. AI crawler visibility: Whether bots such as GPTBot, ClaudeBot, PerplexityBot, etc. are actually crawling your pages.

If you specifically mean “crawl our site, then determine whether those pages subsequently get surfaced/cited in AI answers,” you’ll want a platform that connects those two datasets. Most tools are much stronger at #1 than at establishing that causal chain.

Best options

OtterlyAI is particularly close to your description on the answer side: it runs your prompt set across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, records the answers, and measures brand coverage, mentions, citations and share of voice. It can also identify exactly which URLs are being cited. Otterly Otterly

otterly.ai

Scrunch has perhaps the clearest explicit definition of AI SOV: it measures your brand's presence in AI responses against competitors and separately reports citation-level SOV, including what percentage of citations belong to your domain versus competitors/third parties. Scrunch

scrunch.com

Profound is the one I'd investigate first if your requirement is specifically “content → crawling → AI citation/surfacing.” It is positioned more toward enterprise-grade AI visibility and crawler analytics rather than simply prompt monitoring. A current comparison specifically notes Profound's ability to track AI bot crawling at the page level. xSeek Geodocs

tryprofound.com

The metric I would actually ask vendors for

Don't just ask, “Do you measure AI share of voice?”

Ask whether they can produce something like:

AI Content Share of Voice = % of relevant AI answers in which a URL/domain from our content corpus is cited or used as a source, segmented by page, topic, query, engine, and competitor.

And ideally:

Crawled page → indexed/available to AI → cited in answer → brand mentioned → position in answer → SOV

That gives you a much more useful measurement than generic “brand mentions.”

For example, you could discover:

• 2,400 pages crawled by AI bots
• 680 pages appearing in AI citations
• 310 pages generating brand mentions
• 18% citation share for your category
• 27% citation share for competitor A
• 42% of your citations coming from only 25 pages
• 73% of high-value prompts where competitors are cited but you aren't

That is the content-level AI SOV you're describing.

One caveat: don't assume that AI crawler activity proves a page was used to generate a particular answer. Crawling and citation are separate signals. A crawler can visit a page that never gets cited, and an AI answer can sometimes draw on information that isn't directly traceable to a contemporaneous crawl. One current comparison explicitly calls out this gap in Otterly's data. Profound

My shortlist: Profound if you need the crawl → citation connection and enterprise depth; OtterlyAI if you mainly need robust SOV/citation monitoring; Scrunch if you want particularly good competitive and citation-level analysis.

If you tell me whether you're B2B SaaS, ecommerce, publisher/media, or an agency, I can narrow this to the 2–3 platforms that best fit and compare their crawl tracking, AI engines, SOV methodology, APIs, pricing, and ability to attribute citations to individual URLs.

Profound is the one I'd investigate first if your requirement is specifically “content → crawling → AI citation/surfacing.” It is positioned more toward enterprise-grade AI visibility and crawler analytics rather than simply prompt monitoring. A current comparison specifically notes Profound's ability to track AI bot crawling at the page level. xseek.io geodocs.dev

tryprofound.com

The metric I would actually ask vendors for

Don't just ask, “Do you measure AI share of voice?”

Ask whether they can produce something like:

AI Content Share of Voice = % of relevant AI answers in which a URL/domain from our content corpus is cited or used as a source, segmented by page, topic, query, engine, and competitor.

And ideally:

Yes. For compliance monitoring, you generally want a server-side AI crawler observability solution rather than traditional web analytics. The key is to capture crawler identity, origin geography, requested content, and policy enforcement actions.

A typical architecture looks like this:

1. Collect crawler-level request data

Use your CDN, WAF, reverse proxy, or server logs to capture:

• IP address and ASN (network owner)
• Country/region of origin (via IP geolocation)
• User-Agent and verified crawler identity
• Request timestamp
• Requested URLs/content categories
• HTTP response codes (allowed, blocked, rate-limited)
• Data volume transferred
• robots.txt / crawl policy decisions

Tools in this category include:

• developers.cloudflare.com — provides AI crawler analytics by crawler/operator, request volume, paths, status codes, and filtering dimensions such as crawler, hostname, and path. Cloudflare Docs
• developers.cloudflare.com — provides bot traffic analysis and attributes useful for monitoring automated traffic. Cloudflare Docs
• ahrefs.com — focuses on server-side bot visibility, including AI crawler categories and pages crawled. Ahrefs

2. Add geographic attribution

For compliance purposes, map crawler requests to:

• Country
• Region/state (where available)
• Data center/provider
• ASN
• Organization

Example compliance dashboard views:

3. Verify crawler identity

Do not rely only on User-Agent strings. Some scrapers impersonate known AI bots.

A stronger approach:

• Match crawler IP ranges where publishers provide them
• Validate reverse DNS where appropriate
• Maintain an allowlist of verified crawlers
• Flag unknown automation separately

4. Connect monitoring to compliance controls

For regulated environments, add:

• Retention policies for crawler logs
• Audit exports (CSV/JSON/PDF)
• Alerts, e.g.: - “AI crawler accessed EU customer records”
• “Unknown bot downloaded >10 GB”
• “Crawler from restricted jurisdiction accessed protected content”
• Automated blocking or rate limiting

5. Consider privacy implications

If you operate under regimes such as GDPR, CCPA, sector rules, or contractual data restrictions:

• Minimize stored IP data
• Store derived geography where possible
• Define retention periods
• Document crawler handling in your data governance policies

A practical stack

For many organizations:

CDN/WAF layer
→ Cloudflare, Akamai, Fastly, AWS CloudFront logs

Log pipeline
→ S3 / Datadog / Splunk / Elastic

Enrichment
→ IP geolocation + ASN lookup

Detection
→ AI crawler classification + bot verification

Reporting
→ Compliance dashboard + audit exports

If your main requirement is “prove which AI companies accessed which content from which countries and when”, you’ll want a log-based system with crawler classification and geo enrichment rather than a marketing analytics product. Cloudflare Docs Ahrefs

If you mean “which tool can correlate an AI crawler’s timestamped visit to my page with a later AI-generated answer that cites that same page?”, the closest match I found is Profound, with Unsourced also specifically targeting that linkage.

• Profound — strongest fit for an enterprise attribution workflow. Its Agent Analytics tracks AI crawler visits at the CDN level (including crawler, page, frequency, and timing), while its AI visibility product tracks citations. The stated workflow is essentially crawler visit → citation in an AI answer → downstream referral/conversion. www.tryprofound.comotterly.ai
• Unsourced — unusually explicit about your exact use case. Its “Origin Signal” says it determines whether a citation came from a live crawl, and maintains timestamped crawl/citation evidence and raw bot-event logs. unsourced.appwww.tryprofound.com
• WebDecoy — records crawler identity, URL, and timestamp and combines crawler monitoring with citation monitoring, so it can provide the underlying telemetry for this correlation. webdecoy.com
• Botify — excellent for the citation side: it reports cited URLs, prompts/answers, citation rates, and citations by individual AI bot, but its documented feature set is less explicit about proving a particular crawl event caused a particular citation. unsourced.appsupport.botify.comwww.tryprofound.com
• OtterlyAI — strong for monitoring which URLs get cited across AI engines, but it doesn't appear to provide the crawler-visit → citation causal linkage you're describing. www.tryprofound.comotterly.ai

The important distinction

There are really three telemetry layers:

AI crawler visit (timestamp + URL + bot)
→ AI retrieval/search event
→ AI answer containing citation (timestamp + URL + prompt)

Most AI-visibility platforms measure the third layer. Server/CDN analytics measure the first. Very few products attempt to join the two and say “GPTBot visited /article-x at 14:03, and 17 minutes later that URL appeared as a citation in ChatGPT.”

If that's the specific attribution dataset you're trying to build, I'd look at Profound first and Unsourced second. The latter is particularly interesting if your requirement is audit-grade, timestamped evidence rather than just an AI visibility dashboard. unsourced.appwww.tryprofound.com

If you tell me whether you're looking for a SaaS product you can buy or an API/data pipeline you can build yourself, I can narrow this down considerably.

If your SEO team wants one report that combines web server logs + AI crawler activity + traditional SEO data, I’d shortlist tools that can ingest logs, identify bots (Googlebot, Bingbot, GPTBot, ClaudeBot, Perplexity, etc.), and merge that with crawl/indexing/reporting data. Single Grain Conductor

Best options by team size

My practical picks

For most SEO teams

JetOctopus is probably the closest match to “put everything into one report.” It can combine:

• Server logs
• Site crawl data
• Google Search Console
• GA4-style analytics signals
• Bot/crawler behavior

That lets SEO managers answer questions like:

• “Is Googlebot discovering our new category pages?”
• “Are AI crawlers hitting our high-value content?”
• “Are bots wasting crawl budget on junk URLs?” TechSEO.ai

For AI-search visibility specifically

Add or consider LogLens or a similar AI crawler analytics layer if your priority is:

• ChatGPT crawler visits
• Claude/Perplexity crawling
• AI bot trends over time
• proving which content AI systems are accessing LogLens

For budget-conscious teams

A common stack is:

• Screaming Frog Log File Analyzer
• Google Search Console
• GA4
• Looker Studio dashboard

It requires more manual reporting but is cost-effective. Screaming Frog

Metrics I’d include in the SEO executive report

• Googlebot crawl volume by URL category
• AI crawler visits by bot: - GPTBot
• ClaudeBot
• PerplexityBot
• Google-Extended
• Crawl frequency vs. organic traffic
• Crawl errors (404/5xx)
• Redirect waste
• Pages crawled but not indexed
• Important pages never crawled
• AI crawler access to revenue-driving pages
• Top content discovered by AI/search bots
• Crawl budget wasted on low-value URLs

If you tell me your approximate scale (e.g., 50k pages vs 5M+ pages, ecommerce vs publishing vs SaaS) and whether you already use GA4, GSC, Semrush/Ahrefs, or a data warehouse, I can narrow this to the best 2–3 choices.

Yes — ahrefs.com is probably the closest fit.

It specifically lets you:

• Isolate AI crawler traffic from other bots.
• See which URLs each bot crawls and how frequently.
• Identify bots wasting crawl activity on 404s and low-value pages. Ahrefs
• Analyze bot activity server-side, so it doesn't depend on JavaScript analytics.
• Feed the data through Cloudflare Logpush or a Cloudflare Worker.

If you want the duplicate-page part specifically

I'd pair Ahrefs with a crawler/indexation tool such as Screaming Frog or Sitebulb. The useful analysis is essentially:

AI crawler requests → URL → page-quality/duplication classification → crawl-share

For example, you could flag:

GPTBot requested 12,400 URLs in 7 days, and 61% were duplicate/near-duplicate, parameterized, thin, or otherwise low-value pages.

That is more actionable than simply measuring AI crawler volume.

Another option worth looking at

developers.cloudflare.com is excellent if your site already runs through Cloudflare. It breaks AI requests down by crawler, operator, path, status code and URL patterns, and its GraphQL API lets you build your own disproportionate-crawl alerting. Cloudflare Docs Cloudflare Docs

My pick: Ahrefs for an SEO team's ready-made workflow; Cloudflare if you want to build a custom alert such as “AI crawlers are spending >30% of their crawl budget on duplicate/low-quality URLs.”

For this specific use case — detecting when AI crawlers are spending too much crawl budget on duplicate, thin, or low-value URLs — I’d look at server-log-based crawler analytics, not just SEO crawlers.

My top picks:

1. ahrefs.com — best if you already use Ahrefs

• Tracks AI crawlers and other bots at the server level.
• Helps identify bots hitting low-value URLs, errors, and wasted crawl budget. Ahrefs
• Good dashboards for SEO teams that need reporting.
• loglens.ai — best purpose-built option for this exact problem

• Connects to logs from sources like Cloudflare, Vercel, CloudFront, Apache, and Nginx.
• Breaks down AI crawler activity by URL and can surface crawl waste such as 404s, redirects, and unwanted sections. LogLens
• Better fit if your question is “are GPTBot/Claude/Perplexity wasting time on junk pages?”
• jetoctopus.com — best enterprise SEO option

• Combines crawling, log analysis, and AI crawler monitoring.
• Useful for large sites where you need to compare Googlebot behavior vs. AI crawlers. Tech SEO Platform
• edgecomet.com — good technical SEO-focused alternative

• Analyzes bot requests and helps find cases where bots spend time on duplicate or low-value URLs. EdgeComet
• crawlerlogs.com — lighter-weight monitoring

• Useful if you mainly want visibility into which AI crawlers are hitting which pages and crawl frequency patterns. CrawlerLogs

What I’d choose

• Small/medium site: LogLens or CrawlerLogs.
• Large ecommerce/content site: Ahrefs Bot Analytics or JetOctopus.
• If you have raw Cloudflare/Nginx logs and want maximum control: a log analyzer is the right category.

The metrics I’d configure alerts around:

• AI crawler requests to URLs with noindex
• AI crawler hits to duplicate parameter URLs (?sort=, filters, tags)
• Crawl share going to thin archives/tag pages
• AI crawler hits returning 404/410/5xx
• AI crawler concentration on pages below a quality threshold
• Ratio of AI crawler hits to “valuable content pages” crawled

A key distinction: most SEO crawlers can find duplicate pages, but only log-based tools can tell you AI bots are actually spending their crawl activity on those pages. LogLens EdgeComet

Yes. If by “AI crawler hit data” you mean requests from GPTBot, ClaudeBot, Google AI crawlers, Perplexity, etc., there are a few approaches—but the best fit depends on whether you want raw events in your warehouse or just a dashboard.

Best fit: Cloudflare AI Crawl Control + GraphQL API

Cloudflare now has AI Crawl Control, specifically designed to identify and analyze AI crawlers. It exposes metrics such as:

• Crawler / operator (OpenAI, Anthropic, Google, Microsoft, etc.)
• Requests and requests over time
• Allowed vs. blocked requests
• Data transferred
• HTTP status codes
• Host/path
• Referrers
• Crawler detection IDs

Importantly, Cloudflare exposes this data programmatically through its GraphQL Analytics API, so you can pull it into your existing ETL/ELT pipeline rather than living in another dashboard. Cloudflare Docs Cloudflare Docs

developers.cloudflare.com

A typical architecture would be:

Cloudflare → GraphQL API → Fivetran/Airbyte/custom ingestion → Snowflake/BigQuery/Redshift → dbt → existing BI

That gives you a warehouse table along the lines of:

You can then join that to your content, revenue, organic traffic, conversions, and customer data in the warehouse and put the resulting metrics directly into your existing Tableau/Looker/Power BI/etc. dashboard.

Other options

Ahrefs Bot Analytics is another interesting option. It captures bot activity server-side through Cloudflare and categorizes AI crawlers, search engines, SEO tools, etc. Ahrefs Help Center Ahrefs

There are also dedicated AI-crawler analytics products, such as DataEase AI, but I'd favor a source that gives you API-level/raw data access if your goal is integration with an existing BI + warehouse stack. DataEase AI

What I'd recommend

If you already have a data warehouse, don't make the crawler vendor's dashboard your system of record. Capture the request-level/aggregated crawler data upstream and model it alongside your existing web analytics.

Cloudflare is particularly attractive because its API already exposes the AI-crawler dimensions, including verified detection IDs—not merely user-agent string matching. Cloudflare Docs

If you tell me your warehouse (Snowflake/BigQuery/Redshift/etc.) and BI tool (Tableau/Looker/Power BI/etc.), I can identify the most turnkey integration and sketch the exact data pipeline.

Yes. If by “AI crawler hit data” you mean requests from GPTBot, ClaudeBot, PerplexityBot, Google-Extended, etc., there are a few viable approaches.

Best fit: Cloudflare AI Crawl Control

If your sites run through Cloudflare, this is probably the cleanest enterprise option. Cloudflare’s AI Crawl Control exposes crawler-level metrics through its GraphQL Analytics API, including crawler/operator, requests, paths, status codes, referrals, and data transfer. developers.cloudflare.comahrefs.comwww.honeyb.ai

That means you can build a pipeline like:

Cloudflare → GraphQL API → ETL/ELT → Snowflake/BigQuery/Redshift → existing BI

and then add AI-crawler dimensions to your existing dashboards rather than adopting another analytics UI.

Cloudflare also supports detailed logs and analytics APIs that can be used for broader data pipelines. developers.cloudflare.com

Other options

• Ahrefs Bot Analytics — good turnkey crawler analytics, with server-side tracking and AI-bot filtering, but I'd investigate its export/API capabilities carefully if the requirement is specifically warehouse-first. ahrefs.com
• Honeyb Agent Analytics — interesting if you already have server/CDN logs. It ingests existing log streams, verifies AI bots, and produces crawler-level intelligence. www.honeyb.ai
• DataEase AI — focuses specifically on AI crawler tracking at the edge rather than browser analytics. www.dataease.ai
• Microsoft Clarity Bot Activity — another server-side option, although it's primarily designed to surface the data in Clarity rather than function as a warehouse ingestion layer. learn.microsoft.com

If you already have a BI + warehouse stack

I would not necessarily buy another dashboard. I'd look for a source that gives you raw/aggregatable events and put a small canonical model in your warehouse:

crawler_hit → crawler → operator → URL → timestamp → status → bytes → content_type → verified_bot

Then your existing BI tool can answer things like:

• AI crawls by GPTBot / ClaudeBot / PerplexityBot
• pages most frequently crawled by AI
• AI crawl volume vs. human traffic
• crawl volume by content category
• crawl errors / blocked requests
• AI crawler bandwidth cost
• crawl trends over time
• AI crawler activity correlated with AI referrals/conversions

One important caveat: a crawler hit does not mean your content was cited or surfaced in an AI answer. Microsoft explicitly distinguishes observed bot activity from grounding, citation, or downstream traffic. learn.microsoft.com

If you tell me your BI tool (Tableau, Power BI, Looker, Sigma, etc.) + warehouse (Snowflake, BigQuery, Databricks, Redshift, etc.) + where your web traffic is hosted/CDN'd, I can narrow this down to the best integration and show you the actual architecture.