AIO is reshaping click distribution on SERPs
AI overviews change the way clicks flow through search results. Position 1 organic results that previously received a 30-35% CTR can see rates drop to 15-20% when AI overviews appear above them.
Industry observations indicate that AI observations appear 60-80% of the time for certain query types. For these keywords, traditional CTR models and traffic predictions become meaningless. The entire click distribution curve shifts, but we lack the data to accurately model this.
Brands and agencies need to know: How often AIO appears for their keywords
Knowing how often AI observations appear for your keywords can help guide your strategic planning.
Without this data, teams may optimize aimlessly, potentially focusing resources on keywords dominated by AI observations or missing opportunities where traditional SEO may perform better.
Check citations as a metric
Being cited can increase brand authority even without direct clicks, as people see your domain as a trusted source by Google.
Many domains with average traditional rankings are ahead in AI observation citations. However, without citation data, sites may struggle to understand what they’re doing well.
How CTR changes when AIO is present
The impact on click-through rate can vary depending on the type of query and the format of the AI observation.
To accurately model CTR, it is useful to understand:
- Whether AI observation exists for each question.
- The format of the overview (such as expanded, abridged, or with sources).
- Your quote status under Overview.
Unfortunately, Search Console doesn’t provide any of these data points.
Without visibility, customer reporting and strategy are based on guesswork
Currently, reporting relies on assumptions and observed correlations rather than direct measurements. Teams make educated guesses about the impact of AI observations based on changes in CTR, but they cannot definitively prove cause and effect.
Without solid data, any choice we make is somewhat like guesswork, and we miss out on the confidence that clear data can provide.
How to Create Your Own AIO Impression Dashboard
One approach: manual SERP checking
Since Google Search Console won’t show you AI observation data, you’ll need to collect it yourself. The most straightforward method is manual verification. Yes, by searching for virtually every keyword and documenting what you see.
This method requires no technical skills or API access. Anyone with a spreadsheet and a browser can do it. But that access comes with a significant time investment and limitations. You’re becoming a human web scraper, manually recording data that should be available through GSC.
Here’s how to manually track AI observations:
Step 1: Set up your tracking infrastructure
- Create a Google Sheet with columns: Keywords, Date Checked, Location, Device Type, AI Observations Current (Y/N), AI Observations Extended (Y/N), Your Site Cited (Y/N), Competitor Citations (List), Screenshot URL.
- Create a second sheet for historical tracking with the same columns and week number.
- Create a third sheet for CTR correlation using GSC data export.
Step 2: Configure your browser for consistent results
- Open Chrome in incognito mode.
- Install a VPN if tracking multiple locations (you’ll need to clear cookies and change locations between each check).
- Set up a screenshot tool that captures the length of the entire page.
- Disable any ad blockers or extensions that may alter the SERP display.
Step 3: Perform weekly checks (budget 2-3 minutes per keyword)
- Search for your keyword secretly.
- Wait for the page to load completely (AI observations sometimes load one to two seconds after the initial results).
- Check if the AI overview appears – note that some are collapsed by default.
- If collapsed, click and show Expand.
- Enumerate and document all cited sources.
- Take a screenshot of the entire page.
- Upload a screenshot to cloud storage and add a link to the spreadsheet.
- Clear all cookies and cache before the next search.
Step 4: Handle location-specific searches
- Close all browser windows.
- Connect to the VPN for the target location.
- Verify IP location using Whatismyipaddress.com.
- Open a new incognito window.
- Add the “&gl=us&hl=en” parameter (adjust the country/language code as needed).
- Repeat step 3 for each keyword.
- Disconnect the VPN and repeat for the next location.
Step 5: Process and analyze your data
- Export the previous week’s GSC data (wait two to three days for the data to complete).
- Match keywords between your tracking sheet and the GSC export using VLOOKUP.
- Calculate AI observation attendance rate: COUNT(IF(D:D=”Y”))/COUNTA(D:D)
- Calculate Quote Rate: COUNT(IF(F:F=”Y”))/COUNT(IF(D:D=”Y”))
- Compare the average CTR for keywords with an AI overview versus those without.
- Create a pivot table to identify patterns based on keyword category.
Step 6: Maintain data quality
- Double-check 10% of keywords to verify consistency.
- Document any SERP layout changes that may affect tracking.
- Archive screenshots weekly (they will quickly consume storage).
- Update your VPN locations if Google starts detecting and blocking them.
For 100 keywords in three locations, this process takes about 15 hours per week.
The Easy Way: Pull This Data With an API
If ~15 hours a week of manual SERP checking isn’t realistic, automate it. An API call gives you the same AIO signals in seconds, on a schedule, and without human error. The tradeoff is a slight setup and usage cost, but once you’re tracking ~50+ keywords, automation is cheaper than humans.
Here is the flow:
Step 1: Set up your API access
- Sign up for SerpApp (free tier includes 250 searches/month ).
- Get your API key from the dashboard and store it safely (env var, not in the screenshot).
- Install the client library for your preferred language.
Step 2, Easy Version: Verify it works (no code)
Paste this into your browser to pull only the AI overview for the test query:
https://serpapi.com/search.json?engine=google&q=best+laptop+2026&location=United+States&json_restrictor=ai_overview&api_key=YOUR_API_KEY
If Google returns the page_token instead of the full text, run this second request:
https://serpapi.com/search.json?engine=google_ai_overview&page_token=PAGE_TOKEN&api_key=YOUR_API_KEY
- Replace YOUR_API_KEY with your key.
- Replace PAGE_TOKEN with the value from the first response.
- Replace spaces in questions and spaces with +.
Step 2, the low-code version
If you don’t want to write code, you can call it from Google Sheets (see tutorial) , make or n8n and log three fields per keyword: AIO present (true/false), AIO status, and AIO source.
No matter which option you choose,:
- Total setup time: two to three hours.
- Ongoing time: Five minutes weekly to review results.
What data becomes available
The API returns comprehensive AI observation data that GSC does not provide:
- PresenceDetection : Boolean flag for AI observation presence.
- Content Extraction : Full AI-generated text.
- Citation Tracking : All source URLs with titles and snippets.
- Positioning data : Where the AI appears on the overview page.
- Interactive elements : Follow-up questions and expandable sections.
This structured data integrates directly into existing SEO workflows. Export to Google Sheets for quick analysis, push to BigQuery for historical tracking, or feed into dashboard tools for client reporting.
Demo Tool: Building an AIO Reporting Tool
Understanding the data pipeline
Whether you build your own tracker or use an existing tool, the data pipeline follows this pattern:
- Input : Your keyword list (from GSC, rank trackers, or keyword research).
- Collection : Retrieve SERP data (manually or via API).
- Processing : Extract AI observation information.
- Storage : Save to a database or spreadsheet.
- Analysis : Calculate metrics and identify patterns.
Let’s walk through implementing this pipeline.
You need: Your keyword list
Start with a prioritized keyword set.
Include classification to identify AI observation patterns based on intent type. Informational queries typically show higher AI observation rates than navigational queries.
Step 1: Call SerpaAP to find out the AIO block
For manual tracking, you’ll check each SERP:
- Individually. (This tutorial takes 2-3 minutes per manual check.)
- Instantly. (It returns structured data immediately.)
Step 2: Store the results in Sheets, BigQuery, or a database
Check out the full tutorial for:
Step 3: Report on KPIs
Calculate the following key metrics from your collected data:
- AI observation attendance rate.
- Quote success rate.
- CTR impact analysis.
Combine this with GSC data to measure the CTR difference between keywords with and without AI observation.
These metrics provide the visibility that GSC lacks, enabling data-driven optimization decisions.
Clear, transparent ROI reporting for clients
With AI observation tracking data, you can provide customers with concrete answers about their search performance.
Instead of vague statements, you can present specific metrics, such as: “AI observations appear for 47% of your tracked keywords, your citation rate is 23% compared to your main competitor’s 31%.”
This transparency transforms customer relationships. When they ask why impressions increased 40% but clicks only increased 5%, you can show them how many queries now trigger an AI overview above their organic listings.
More importantly, this data justifies strategic pivots and budget allocations. If AI insights dominate your client’s industry, you can make a case for content optimization targeting AI insights.
Early detection of AIO instability in your industry
Google’s AI Observation rollout is uneven, happening in waves that test different industries and query types at different times.
Without proper tracking, you might not notice these updates for weeks or months, leading to missed opportunities for critical optimization during competitive optimization.
Continuous monitoring of AI observations turns you into an early warning system for your customers or organization.
A data-backed strategy to optimize AIO quotes
By carefully tracking your content, you’ll quickly notice patterns, such as content types that consistently earn citations.
The data also reveals competitive advantages. For example, traditional ranking factors don’t always predict whether a page will be cited in an AI review. Sometimes, a page ranked fifth is consistently cited, while the top result is ignored.
Additionally, tracking helps you understand how citations relate to your business metrics. You may find that being cited in AI observations improves your brand visibility and direct traffic over time, even if those citations don’t result in immediate clicks.
Stop waiting for GSC to provide visibility – it will never come
Google has shown no signs of adding AI overview filtering to Search Console. The API roadmap doesn’t mention it. Waiting for official support means flying blind indefinitely.
Start testing SerapAP’s Google AI Observation API today
If manual tracking isn’t sustainable, we offer a free tier with 250 searches/month so you can validate your pipeline. For scale, our published limits are clear: 20% of plan volume per hour on plans under 1M/month, and 100,000 + 1% of plan volume per hour on plans ≥1M/month.
We also support enterprise plans up to 100 million searches/month. Same production infrastructure, no setup.
Build your own AIO analytics dashboard and give your team or customers the insights they need
Whether you choose manual tracking, build your own scraping solution, or use an existing API, the important thing is to start measuring. Every day without AI observational visibility is a day of missed optimization opportunities.
The tools and methods exist. The patterns are identifiable. You just need to implement tracking that fills the gaps that Google won’t address.
Get started here →
For those interested in an automated approach, access SerpAP’s documentation and test the playground to see what data becomes available. For manual trackers, download our spreadsheet template to start tracking immediately.
