How to Track AI Traffic on Google Analytics (Saved View): A Step-by-Step Guide

ChatGPT, Perplexity, Claude, Gemini, and Copilot are sending visitors to your site right now. Google Analytics is quietly burying them inside the “Referral” channel, and a meaningful chunk isn’t showing up at all. Industry estimates suggest visible AI referrals represent just 30 to 40% of actual AI-driven visits, and the rest disappears into what analysts now call dark AI traffic.

The kicker? AI referral traffic converts at 4.4 times the rate of traditional search traffic, with visitors spending 68% longer on sites and viewing more than three times as many pages per session. If you can’t see this channel, you can’t prove the ROI of every GEO and LLM SEO investment your team is making.

Here’s what we’ll go through in detail:

• Why GA4 hides AI traffic by default and what’s actually in your data
• How to build a custom AI/LLM Traffic channel group with copy-paste regex
• Building a dedicated AI Traffic report and adding it to your sidebar
• How to set the AI Traffic report as your saved default view
• Saved explorations, BigQuery queries, and Looker Studio dashboards
• The “dark AI traffic” problem and how to estimate what GA4 can’t show

This is exactly the visibility gap Doc Digital SEM closes for clients every day. Through our LLM SEO services and AI search optimization work, we set up the tracking infrastructure that makes AI traffic measurable, attributable, and reportable, so the channel you’re investing in actually shows up in your dashboards.

Why GA4 Hides AI Traffic by Default

Google Analytics 4 was built before ChatGPT existed. The default channel group still doesn’t recognize AI tools as their own category, which means every visit from an AI platform gets misclassified the moment it lands on your site.

Out of the box, GA4 ships with 18 channel groupings. None of them says “AI.” So when ChatGPT, Perplexity, Claude, Gemini, or Copilot sends you a visitor, GA4 has nowhere clean to put it.

Where Your AI Traffic Is Actually Hiding

Most AI traffic in GA4 ends up in one of three places:

This is the data display problem. Your traffic acquisition report shows AI driven traffic dispersed across at least three channels, with no way to isolate it without configuration.

Why This Matters Right Now

If you’re investing in LLM SEO or Generative Engine Optimization, you need to prove the channel exists. Without a custom AI channel group, you’re stuck filtering by source on every report, every time. That’s not scalable, and it’s not how data driven decisions get made.

The fix is straightforward. Build a custom AI traffic channel group using regex, then layer reports and dashboards on top of it. That’s exactly what we’ll walk through next.

Build a Custom AI/LLM Traffic Channel Group

This is the foundation. Before any reports, dashboards, or BigQuery queries can pull AI traffic cleanly, you need a custom channel group that tells Google Analytics, “Treat this list of AI tools as its own channel.”

Here’s the step by step setup.

Step 1: Open Channel Groups in Admin

Go to your GA4 property, click Admin (the gear icon, bottom-left), then under “Data display,” click Channel groups.

You’ll see one default channel group already in place. GA4 lets you create up to two custom channel groups in addition to the default. We’ll use one of them for AI.

Step 2: Create a New Channel Group

Click Create new channel group in the top right. Name it something clear and brand-friendly. We did:

Channel group name: AI/LLM Traffic

The reason we don’t just call it “AI” is search behavior inside GA4. The string “AI” matches words like “email” or “available” when you use the search feature in any data table. “AI/LLM Traffic” is unique, easy to filter, and reads cleanly in client reports.

Step 3: Add a New Channel Inside the Group

GA4 will show you the existing default channels (Organic Search, Paid Search, Direct, Referral, etc.). Click Add new channel at the top.

Step 4: Name the New Channel and Set the Condition

Inside the new channel:

• Channel name: AI/LLM Traffic
• Channel conditions: Match if AT LEAST ONE of the following is true
• Source → matches regex → paste the regex below

Step 5: Paste the Full Regex

This is the comprehensive regex covering 90+ AI platforms as of 2026. Copy and paste this exactly:

chatgpt\.com|chat\.openai\.com|gemini\.google\.com|deepseek\.com|perplexity(?:\.ai)?|claude\.ai|copilot\.microsoft\.com|deepl\.com|character\.ai|(?:\w+\.)?meta\.ai|grok\.x\.com|grok\.com|x\.ai|bard\.google\.com|(?:\w+\.)?mistral\.ai|writesonic\.com|quillbot\.com|chat\.suno\.com|turing\.microsoft\.com|cosmos\.microsoft\.com|orca\.microsoft\.com|phi\.microsoft\.com|megatron\.microsoft\.com|jarvis\.microsoft\.com|maia\.microsoft\.com|aitastic\.app|bnngpt\.com|chat-gpt\.org|(?:\w+\.)?edgepilot|firefly\.adobe\.com|edgeservices|iask\.ai|(?:\w+\.)?neeva|nimble\.ai|open-assistant\.io|(?:\w+\.)?copy\.ai|openchat\.so|blackbox\.ai|ex\.ai|cohere\.ai|anthropic\.com|(?:\w+\.)?palm-ai\.google\.com|chatglm\.cn|gemini-api\.google\.com|palm\.google\.com|deeplearning\.google\.com|vertexai\.google\.com|ai\.google\.com|deepmind\.google\.com|ml\.googleapis\.com|tensor\.google\.com|t5\.google\.com|my-ai\.snapchat\.com|ai\.baidu\.com|xiaoice\.com|anthropic-api\.com|huggingchat\.com|deepmind\.com|alphacode\.google\.com|copilot\.azure\.com|felo\.ai|chat\.qwen\.ai|(?:\w+\.)?qwenlm\.ai|(?:\w+\.)?outlier\.ai|chat\.hotmart\.ai|customgpt\.ai|venice\.ai|bot\.ivy\.ai|chat\.chatbotapp\.ai|lmarena\.ai|wrtn\.ai|chat\.chaton\.ai|app\.chatboxapp\.ai|duck\.ai|sider\.ai|webpilot\.ai|ai21\.com|pi\.ai|zhipu\.ai|huggingface\.co|wordtune\.com|reka\.ai|syntesia\.io|jasper\.ai|uminal\.org|ai-coustics\.com|magical\.team|vicuna\.ai|floydhub\.com|forefront\.ai|komo\.ai|wav\.ai|d-id\.com|sap\.ai|useblackbox\.io|you\.com|chinchilla\.ai|openrouter\.ai|waldo|coze\.com|exa\.ai|spellbook\.rossintelligence\.com|yiyan\.baidu\.com|lighton\.ai|baichuan-ai\.com|hyperwriteai\.com|phind\.com|app\.loora\.ai

Click Apply, then Save channel.

Step 6: Reorder the Channels (Critical Step)

This step is where most setups break. GA4 evaluates channel rules top to bottom. The first match wins. If your AI/LLM Traffic channel sits below Referral, every AI visit gets classified as Referral first and never reaches your custom rule.

Click Reorder, then drag AI/LLM Traffic above Referral. Even better, move it near the top of the list.

Click Apply, then Save group.

Step 7: Wait for the Data to Populate

Here’s something most tutorials skip: the new custom channel group can take up to an hour or more to populate, depending on traffic volume. The more data your site processes, the longer it takes. If you check the traffic acquisition report immediately and see “(other)” or an empty channel, that’s the system catching up.

Come back in an hour. The AI/LLM Traffic channel will appear with sessions, users, and conversions broken out cleanly.

💡 Pro tip: GA4 applies custom channel groups retroactively. Once your group is live, you’ll immediately see historical AI traffic data once processing completes.

Build a Dedicated AI Traffic Report

A custom channel group is great, but it’s still buried inside the standard traffic acquisition report. To make AI tracking effortless for your team and your clients, you need a dedicated AI traffic report living in the sidebar.

Step 1: Open the Traffic Acquisition Report

Go to Reports → Acquisition → Traffic Acquisition. By default, this report uses the session default channel group.

In the dimension dropdown above the data table, switch to Session custom channel group and select your new AI/LLM Traffic group.

You’ll now see your AI driven visits broken out alongside other channels.

Step 2: Customize the Report

Click the pencil icon in the top right to open the customization panel. If you don’t see the pencil, you don’t have edit permissions on the property. Reach out to your GA4 admin.

Step 3: Add a Filter for AI/LLM Traffic Only

Inside the customization panel:

• Click Add filter
• Dimension: Session Primary channel group
• Match type: exactly matches
• Value: AI/LLM Traffic
• Click Apply

The report now shows only AI traffic. Other channels are filtered out completely.

Step 4: Set the Primary Dimension to Session Source

The current report still shows your custom channel group as the row dimension. To see which AI tools are driving traffic, switch the primary dimension.

• Click Dimensions in the customization panel
• Add Session source (or Session source/medium for more detail)
• Set it as the default dimension
• Drag it to the top of the dimension list
• Click Apply

Now the report displays each AI tool individually. You’ll see chatgpt.com, perplexity.ai, gemini.google.com, claude.ai, and any other source matching your regex.

Step 5: Save as a New Report

Click Save → Save as a new report. Name it.

Step 6: Add the Report to Your Sidebar

The report exists, but it’s not in the navigation yet. You need to add it manually.

• Go to Reports → Library (bottom-left)
• Find the Life Cycle collection
• Click the three dots next to it → Edit collection

In the edit screen:

• Find AI Traffic in the right-hand list of available reports
• Drag it into the Acquisition section (or wherever you want it)
• Click Save → Save changes to current collection

Now your AI Traffic report appears in the sidebar under Reports → Acquisition → AI Traffic, accessible to every user with access to your GA4 property.

Set the AI Traffic Report as Your Saved Default View

You can configure your AI Traffic report to load with your preferred dimensions, filters, and date range every single time, so anyone on your team can open it and immediately see AI driven visits without changing a single setting.

Step 1: Open Your AI Traffic Report

Go to Reports → Acquisition → AI/LLM Traffic. The report loads, but the date range and dimensions might revert to defaults each time.

Step 2: Set Your Preferred View

Configure the report exactly how you want it to look every time it loads:

• Date range: Last 30 days (or whatever period your team prefers)
• Primary dimension: Session source
• Filter: Session custom channel group exactly matches AI/LLM Traffic
• Charts: Line chart on (we recommend disabling bar charts for cleaner reads)

Step 3: Open the Customization Panel Again

Click the pencil icon in the top right.

Step 4: Confirm Everything Is Selected

Double-check that the date range, primary dimension, and filter are all set the way you want them to load every time.

Step 5: Save the Configuration

Click Save → Save changes to current report.

That’s it. From now on, every time you (or anyone on your team) navigates to Reports → Acquisition → AI/LLM Traffic, the report will auto-load with your saved default view: last 30 days, AI/LLM Traffic filter applied, Session source as the primary dimension.

💡 Pro tip: This saved view is property-wide. Anyone with access to the GA4 property will see the same default view, which makes it perfect for agency teams managing client reports or in-house teams sharing dashboards across departments.

One Important Note

Once you’ve saved the default view, don’t expect it to populate instantly. The custom channel group and saved report can take up to an hour or more to fully load, depending on how much traffic your website processes. The more data flowing through your property, the longer it takes for the system to catch up.

If you go to Reports → Acquisition → Traffic Acquisition right after setup and see something like “archived channel group” or “(other)” in the data table, don’t panic. That’s GA4 telling you the data is still populating in the background.

The fix is simple: come back in an hour. Once processing finishes, your AI/LLM Traffic channel group will appear with sessions, users, and key events broken out cleanly. From that point forward, the saved view loads instantly every time.

What This Setup Looks Like in Practice

When you click into your AI Traffic report each morning, you’ll instantly see:

• Which AI platforms drove traffic in the last 30 days
• How many sessions, users, and key events each AI source generated
• Engagement metrics (engagement rate, average engagement time, events per session)
• Conversion data tied directly to AI driven visits

No filtering. No dimension switching. No date range adjusting. Just open and read.

Explorations, BigQuery, and Looker Studio

Custom channel groups and saved reports cover most use cases. But for advanced AI traffic analysis, you’ll want explorations, BigQuery queries, and a dedicated Looker Studio dashboard. Here’s how to layer them on.

Explorations: Deeper Custom Reports

Explorations are GA4’s flexible analysis workspace. They’re perfect when you want to slice AI traffic by landing page, device, or user behavior in ways the standard report doesn’t allow.

The fastest way to build an exploration:

1. Open your AI Traffic report
2. Click the explore icon (top right)
3. GA4 auto-generates a free-form exploration mirroring your report
4. Add or remove dimensions, segments, and visualizations as needed
5. Save the exploration with a clear name like AI Traffic Deep Dive

Common explorations worth building:

BigQuery: When You Need Real Query Power

If your property has the BigQuery export enabled, you can run SQL queries directly against raw GA4 event data. This is overkill for most teams but essential for agencies managing high-volume properties.

Enabling the BigQuery Export

Go to Admin → Product links → BigQuery links → Link. Select your Google Cloud project, choose Daily export (and Streaming if you want real-time data), then save.

The AI Traffic Query

Once your data lands in BigQuery, this query pulls AI traffic for any date range:

WITH ai_sessions AS (    SELECT      PARSE_DATE('%Y%m%d', event_date) AS session_date,      user_pseudo_id,      (SELECT value.int_value FROM UNNEST(event_params) WHERE key = 'ga_session_id') AS session_id,      traffic_source.source AS source,      traffic_source.medium AS medium,      CASE         WHEN REGEXP_CONTAINS(traffic_source.source, r'chatgpt\.com|chat\.openai\.com|openai\.com') THEN 'ChatGPT'        WHEN REGEXP_CONTAINS(traffic_source.source, r'perplexity') THEN 'Perplexity'        WHEN REGEXP_CONTAINS(traffic_source.source, r'gemini\.google\.com|bard\.google\.com') THEN 'Gemini'        WHEN REGEXP_CONTAINS(traffic_source.source, r'claude\.ai|anthropic\.com') THEN 'Claude'        WHEN REGEXP_CONTAINS(traffic_source.source, r'copilot\.microsoft\.com|copilot\.com') THEN 'Copilot'        WHEN REGEXP_CONTAINS(traffic_source.source, r'meta\.ai|grok\.com|x\.ai|deepseek\.com|mistral\.ai|you\.com|phind\.com') THEN 'Other AI'        ELSE NULL      END AS ai_source    FROM `your-project.analytics_XXXXXXXX.events_*`    WHERE _TABLE_SUFFIX BETWEEN FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 90 DAY))                            AND FORMAT_DATE('%Y%m%d', CURRENT_DATE())  )  SELECT    ai_source,    COUNT(DISTINCT CONCAT(user_pseudo_id, CAST(session_id AS STRING))) AS sessions,    COUNT(DISTINCT user_pseudo_id) AS users  FROM ai_sessions  WHERE ai_source IS NOT NULL  GROUP BY ai_source  ORDER BY sessions DESC;

Replace your-project.analytics_XXXXXXXX.events_* with your actual project ID and dataset.

Save as a BigQuery View

To use this query as a live data source for Looker Studio, save it as a View in BigQuery:

1. Run the query in the BigQuery SQL workspace
2. Click Save → Save view
3. Name it ai_traffic_summary
4. Choose your dataset and save

The view will refresh every time it’s queried, so your dashboards stay current.

💡 Pro tip: Don’t connect Looker Studio directly to the raw GA4 events tables with a custom query. It can rack up serious BigQuery costs. Always create a summary view first and connect Looker Studio to that.

Looker Studio: The Client-Ready Dashboard

For client reporting or executive dashboards, Looker Studio is the right move. Here’s how to build a clean AI traffic dashboard.

Connect Your Data Source

1. Open Looker Studio → Create → Data Source
2. Select BigQuery (if you set up the view above) or Google Analytics (if pulling from GA4 directly)
3. Authorize access and select your project, dataset, and view/property
4. Click Connect

Build the Core Visualizations

For a complete AI traffic dashboard, include:

Add Filters and Date Controls

Add a date range control at the top so users can adjust the time window. Add a filter control for AI source so users can drill into specific platforms.

The result: a self-service AI traffic dashboard your team or clients can refresh anytime, with no GA4 access required.

This is the kind of full-stack tracking infrastructure we build into every LLM SEO engagement and AI search optimization project. If your team is short on bandwidth to wire all of this up, we’ll do it for you.

The Dark AI Traffic Problem

Here’s the uncomfortable truth nobody puts in the headline. Even with a perfect GA4 setup, custom channel groups, BigQuery views, and Looker Studio dashboards, you’re still only seeing 30 to 40% of your actual AI driven traffic. The rest is invisible.

Industry analysts call this dark AI traffic. It’s the chunk of AI-influenced visits that never get attributed to AI in any analytics platform. Knowing it exists is the difference between treating GA4 numbers as gospel versus treating them as directional.

Where AI Traffic Disappears

These are the seven scenarios where AI traffic vanishes from your reports, no matter how perfect your setup:

What You Can Actually Track

To set realistic expectations:

• ✅ Direct ChatGPT, Perplexity, Claude, Gemini referrals (when referrer is intact)
• ✅ Landing pages receiving AI driven traffic
• ✅ Engagement and conversions from those visible visits
• ✅ Trends in AI traffic share over time
• ❌ Total AI influence on your traffic
• ❌ AI Overviews and Gemini clicks (lumped into Google Organic)
• ❌ Copilot AI clicks (lumped into Bing Organic)
• ❌ Mobile app referrals
• ❌ Copy-paste link visits
• ❌ AI-assisted conversions where the user later searched directly

How to Estimate the Real Number

Since GA4 only shows the visible portion, smart agencies triangulate using multiple data sources:

1. Google Search Console branded search data. A spike in branded searches without a corresponding spike in organic clicks often signals AI exposure driving demand.
2. Direct traffic anomalies. A sudden lift in direct traffic that correlates with content publications or AI citation gains is a strong indicator of dark AI traffic.
3. AI citation tracking tools. Platforms like Profound, Goose, Rankeo, or Yoast AI Brand Insights tell you when you’re being cited, even if the click never converts to an attributed visit.
4. Server log analysis. Tools like Screaming Frog and Cloudflare logs show when AI bots (GPTBot, ClaudeBot, PerplexityBot, OAI-SearchBot) crawl your site in real time.
5. Multiplier estimates. A working rule of thumb: multiply your visible AI traffic by 2.5 to 3x for a more realistic estimate of total AI influence.

What This Means for Your Reporting

When you present AI traffic numbers to stakeholders or clients, frame them honestly:

“These are the AI driven visits we can attribute directly. Industry benchmarks suggest actual AI influence is 2 to 3x what GA4 shows, since referrer stripping, mobile apps, and Google’s own AI overview placement all hide a significant portion of AI-driven discovery from analytics platforms.”

That framing protects your credibility, sets realistic expectations, and positions GA4 numbers as a floor, not a ceiling.

The bottom line is this. Tracking AI traffic in Google Analytics is necessary, but it’s not sufficient. The brands winning the AI search era pair GA4 setup with citation tracking, server log analysis, and consistent measurement frameworks across multiple data sources. Anything less is flying half-blind through the most important search shift in 25 years.

How to Use Your AI Traffic Data

Setting up tracking is the easy part. The harder, more valuable question: what do you actually do with the AI traffic data once it’s flowing into your reports? This is where most teams stall. They build the dashboards, then never use them to make a single decision.

Here’s how to turn your saved AI traffic report into a strategic engine for growth.

Step 1: Identify Your Significant Traffic Sources

Open your AI Traffic report. Look at the AI sources column and identify your top three to five significant traffic sources. For most B2B brands in 2026, this lineup tends to be:

Your top sources reveal where your content is winning citations right now. That’s where to double down.

Step 2: Spot the Pages AI Tools Love

Add a landing page as a secondary dimension in your saved report or build a custom report focused on landing pages. The pages getting the most AI driven traffic tell you exactly what AI engines are extracting from your site.

Look for patterns:

• Long-form, deeply-structured guides usually outperform short blog posts
• FAQ-heavy pages get cited more often than narrative content
• Pages with comparison tables and clear bullet points dominate
• Original data and proprietary research punch well above their weight

When you see a page winning AI citations, ask: what about this page is working? Then replicate that structure across your next 10 articles. That’s how you turn a single data point into a content strategy.

Step 3: Compare AI Traffic to Other Channels

Switch your traffic acquisition report to the default channel group view and compare AI/LLM Traffic against:

• Organic Search (your traditional search results performance)
• Direct (a likely hiding place for additional AI traffic)
• Google Ads (paid acquisition cost vs. AI’s free recommendation engine)
• Referral (the rest of your referring domains)

This comparison reframes the conversation internally. AI/LLM Traffic might be your fourth-largest channel by volume, but your first by conversion rate. That’s a story worth telling at every stakeholder meeting.

Step 4: Track Conversion Quality, Not Just Volume

Total users matters less than what those users do. In your saved report, look at:

• Engagement rate by AI source (Perplexity users tend to engage longer than ChatGPT users)
• Average engagement time per session
• Key events triggered (form fills, demo requests, purchases)
• Conversion rate vs. other channels

This is where data driven decisions get made. If ChatGPT traffic converts at 12% and Google Organic converts at 2%, your content strategy should prioritize being cited in ChatGPT over ranking #1 on Google for the same query.

Step 5: Use AI Mode Data Cautiously

Google AI Mode (the agentic, multi-query AI experience inside Google Search) is bleeding into your traffic data, but Google still attributes those clicks as Google / organic. There’s no clean way to separate AI Overview and AI Mode traffic from regular organic search inside GA4 alone.

Workaround: cross-reference Google Search Console’s performance report with your AI traffic report. If your impressions are flat but clicks are dropping, AI Overview is likely intercepting clicks. If impressions are climbing on long-tail conversational queries, you’re likely surfacing in AI Mode summaries.

💡 Pro tip: Until Google releases AI Overview data in Search Console as its own channel, treat any sudden CTR drops on informational queries as a signal that AI Overview placement is happening. Track citation rates in third-party tools like Profound or Goose to confirm.

Step 6: Build a Saved Report for Each Major AI Tool

Beyond the master AI Traffic report, consider building one saved report per major source. For example:

• ChatGPT Performance (filtered to chatgpt.com only)
• Perplexity Performance (filtered to perplexity.ai only)
• Gemini Performance (filtered to gemini.google.com)

Each gets its own channel and its own page in your sidebar. This makes deep analysis fast and gives you a custom report ready for client presentations or internal QBRs.

Step 7: Layer in Server-Side Tagging for Cleaner Data

If you’re serious about tracking AI traffic at scale, server side tagging fixes a lot of the referrer-stripping problems that hide AI visits. By moving your tracking from the client browser to your own server, you can preserve referrer data that mobile apps and certain AI platforms strip out.

Server-side GTM is a longer setup, but it’s the most effective way to recover dark AI traffic that traditional client-side GA4 misses. For agency teams managing high-traffic sites, the ROI is real.

Step 8: Use the Data to Win Internal Buy-In

The single biggest reason AI traffic tracking matters? Internal credibility. When you walk into a meeting and say, “AI/LLM Traffic now drives 8% of our sessions, converts at 4x our organic rate, and grew 156% quarter over quarter,” you have ammunition to:

• Justify continued investment in LLM SEO
• Reallocate budget from low-ROI paid channels
• Push leadership to fund GEO and AEO work
• Make the case for content restructuring, schema implementation, and AI assistant optimization

Without the data, every AI search investment is a leap of faith. With it, you have proof.

What to Do Each Month

Make AI traffic review a recurring 30-minute session every month. The agenda:

1. Pull last month’s AI Traffic saved report
2. Identify the top 5 AI sources by sessions
3. Identify the top 10 landing pages by AI traffic
4. Compare conversion rate vs. other channels
5. Document month-over-month growth or decline
6. Cross-reference with citation tracking tools (Profound, Goose, etc.)
7. Decide on next month’s content priorities

Thirty minutes a month. That’s the time investment that turns your tracking setup into actual growth.

💡 Pro tip: If you’re not actively reviewing AI traffic monthly, you’re collecting data you’ll never use. The setup is worth nothing without the discipline of analysis.

The teams winning the AI search era aren’t the ones with the prettiest dashboards. They’re the ones using their AI traffic data to make smarter content, schema, and channel decisions every single month. Doc Digital SEM builds these review systems into every engagement, so your AI investments compound month after month, instead of disappearing into a tracking tool nobody opens.

Track AI Traffic the Right Way With Doc Digital SEM

AI traffic is the highest-converting channel most brands aren’t measuring. Once your custom channel group, saved report, and dashboards are live, you stop guessing about AI’s impact and start proving it with real numbers.

Here’s what to remember:

• GA4 hides AI traffic in Referral and Direct by default
• A custom channel group with proper regex fixes the visibility gap
• Save your AI Traffic report as the default view for one-click access
• Layer BigQuery and Looker Studio for advanced analysis
• Visible AI traffic is roughly 30 to 40% of actual influence
• Monthly review turns tracking into real strategic wins

Tracking AI traffic in Google Analytics is just the start. Turning that data into more citations, better content, and higher conversions takes the kind of full-stack optimization Doc Digital SEM ships every day. Get your free AI visibility audit (valued at $1,500) or explore our LLM SEO services and start owning your AI channel.

FAQs

How to track AI traffic in Google Analytics?

Create a custom channel group in GA4 with a regex matching AI sources. This separates AI website visits from general referral traffic and lets you measure AI traffic accurately.

How to check bot traffic in Google Analytics?

GA4 auto-filters known bots, but server logs reveal the rest. Cross-reference Cloudflare or Screaming Frog data to identify artificial intelligence crawlers like GPTBot and ClaudeBot.

How to see AI referral traffic in GA4?

Build a custom channel group, then filter the Traffic Acquisition report by Session source matching ChatGPT, Perplexity, Claude, or Gemini to identify AI sources sending traffic coming to your site.

How to track traffic source in Google Analytics?

Open Reports → Acquisition → Traffic Acquisition. Use the Session source/medium to see how users arrive, separating search engine traffic from artificial intelligence referrals and only referral traffic.