On a recent Thursday, I logged into Google Search Console expecting the usual link report, only to discover a significant issue—it had broken. For some, it displayed zero links, while others saw their reported links drop by nearly 90% from the previous week.
Google acknowledged the problem and decided to revert to older data temporarily as they worked on a fix. This means the link data you’re seeing might be weeks old.
Google’s Response: John Mueller of Google mentioned, “Thanks for the heads-up, Barry. We’ll take a look to see if there’s anything unexpected happening (given the long weekends, it might take a bit of time).”
By Saturday, the links seemed to reappear, but as Mueller explained, they had merely switched back to previous data as a temporary measure. “They’re working on resolving the actual issue and in the meantime switched back to the data from the week before.”
Old Data: If you check your link report now, it displays old information. This is crucial to keep in mind if you’re using this data for reports to clients or stakeholders.
The Bug’s Impact: Many folks noticed either zero links or a drastic drop exceeding 85%. Here’s a screenshot highlighting the problem:
OK, this takes the cake. Hahaha. Yeah, something is very off with the links reporting in GSC. pic.twitter.com/KIYmFPm1fX— Glenn Gabe (@glenngabe) May 21, 2026
Why It Matters: For those relying on this link data for generating reports, the inaccuracy can be problematic. Data pulled on that Thursday might not be reliable.
While Google is addressing the issue, be prepared to work with data that’s temporarily outdated.
I’ve always found SEO reporting to be a bit of a hassle. It used to mean spending hours exporting data from Google Search Console (GSC), tidying it up in spreadsheets, and then trying to make sense of it all in Data Studio.
Now, with AI tools like Claude Code, my workflow has completely changed. I can instantly create customized data visuals and reports in a fraction of the time it used to take.
Let me walk you through the journey of transforming GSC data into tailored reports, streamlining the entire process.
Using Claude Code is different from the standard Claude experience. While the regular Claude.ai acts like a chatbot, Claude Code functions as an AI coding assistant right on my computer. It’s capable of reading GSC CSV files, analyzing large datasets, and transforming raw data into clear, visual reports.
Initially, setting up Claude Code can be daunting, especially if you aren’t familiar with technical tasks. But don’t worry, the setup is a one-time effort. Once it’s up and running, generating reports takes just minutes.
The real magic happens after you connect Claude to GSC. Whether you’re in an enterprise environment or you’re an independent SEO consultant, having Claude Code set up is invaluable.
Starting your journey with Claude Code begins by creating an account on Claude.ai. Even without a paid subscription, I find the platform extremely helpful for generating SEO reports.
A crucial step in using Claude Code is installing Node.js on your machine. For this tutorial, I used a Mac, but it’s compatible with other operating systems too. Once Node.js is installed, I am able to install Claude Code and verify my setup through simple terminal commands.
After setting everything up, I navigated a series of prompts in Claude, choosing how to access GSC data and defining key parameters for my reporting.
Connecting Claude to GSC involves interacting with the Search Console API, albeit a bit technical. But Claude guides me through each step, ensuring a smooth setup.
The exciting part comes after the connection is established. I can now rapidly create focused reports, such as identifying top-performing pages or tracking keyword trends over time, tailor-made for my needs.
Overall, Claude Code redefines how I manage SEO reporting. It offers the perfect balance of speed, flexibility, and control. Once the groundwork is laid, it makes my reporting both dynamic and precise, adapting to the demands of my stakeholders with ease.
Have you recently noticed a decline in clicks and impressions around May 7th to May 8th? Don’t worry; it’s just a reporting glitch.
I discovered that Google has confirmed a bug affecting the Discover report in Google Search Console. It turns out there was a ‘logging’ error with the data, which has resulted in a drop in clicks and impressions during May 7th to May 8th, 2026.
Google assures us that this is merely a ‘data logging only’ issue, and it hasn’t impacted the actual positioning in Google Discover.
The issue: Google stated once again that a data logging error caused the discrepancies in the Discover report between May 7th and 8th, 2026.
As per Google’s post, this bug might have caused a ‘decrease in clicks and impressions in the Discover performance report.’
Why it matters: Numerous publishers, possibly including myself, saw a dip in performance metrics. It’s crucial to note that this is likely due to this bug.
Make sure to annotate your reports and inform your stakeholders that the Discover data from May 7th to May 8th is inaccurate and should be disregarded.
It feels like a moment of relief as Google recently announced a resolution to a longstanding data logging issue within Google Search Console. This glitch affected data between May 13, 2025, and April 27, 2026, spanning approximately 50 weeks. However, it’s important to note that while the root cause has been addressed, historical data from this period remains unfixed.
Google shared this update in a rather understated post, bringing light to a problem that many of us have been grappling with for quite some time. According to their post, “A logging error prevented Search Console from accurately reporting impressions from May 13, 2025, until April 27, 2026. This issue has been resolved.” It was a relief to hear, but also a bit frustrating knowing that impressions, CTR, and average position data were affected for such a significant period. Thankfully, clicks weren’t influenced by this error, which was some consolation.
As I sift through my Search Console data, I must remind myself of this anomaly, particularly when analyzing metrics from that problematic timeframe. The good news is that any data collected from this point forward should be accurate.
Further confirmation came from John Mueller on Bluesky, who reiterated that past data would not be retroactively corrected, but the issue has indeed been resolved going forward.
This development is crucial for all of us who rely heavily on precise data for SEO strategies. If your impressions appear lower and, consequently, your CTR and average position figures seem skewed during this period, this is likely why.
I’ve noticed that Google is currently investigating an issue with the Google Search Console. Specifically, this concerns the data logging and reporting of “Job listing” and “Job details” search appearance filters.
On April 16th, a bug began affecting how this data is logged, causing Google to report zero clicks and impressions for job-related reports. Although traffic is still being received, it’s not being recorded correctly.
What Google said. According to an update from Google, “A logging error is preventing Search Console from reporting impressions and clicks for ‘Job listing’ and ‘Job details’ Search appearance types from April 16, 2026 onward. We’re working to resolve this issue. This issue affects data logging only.”
Complaints. I’ve also seen numerous SEOs voicing their concerns on social media, as shared in a tweet by Max Peters. The bug seems to impact impressions and clicks, but the traffic still comes through other measurement methods like google_jobs_apply UTM.
Why we care. If you’ve noticed a decrease in search data for job listings, rest assured, it’s due to this bug on Google’s side. Your listings are likely still active and receiving traffic, although this isn’t reflected in Search Console at the moment.
I recently discovered a fantastic update from Google Search Console that’s now available for all eligible sites. This new feature shows exactly how much traffic comes from branded versus non-branded search queries, and I couldn’t wait to explore its potential.
Google’s branded queries filter, which was announced on November 20, allows us to separate branded and non-branded search traffic in the Performance report. This is a game-changer for anyone who’s struggled with manual regex filters or keyword lists to achieve similar results.
Why I care. As someone deeply invested in understanding brand demand versus discovery traffic, this new native segmentation in Search Console makes life so much easier. Finally, I can accurately measure and compare these insights.
What Google announced. Today, Google confirmed through a LinkedIn post that this branded queries filter is accessible to us all. It helps analyze the queries driving traffic by autofiltering between branded and non-branded ones.
Exploring the details. This filter can be found in the Search results Performance report and allows queries to be segmented into two main groups:
Branded: These queries include our brand name, its variations, any misspellings, and brand-related products and services.
Non-branded: This group covers all other types of queries.
When applying the filter, Search Console restricts metrics like impressions, clicks, CTR, and average position, focusing solely on the selected group. The filter works across all search types including Web, Image, Video, and News.
Notable insights. Google also enriched the Insights report with a new card that breaks down clicks between branded and non-branded traffic, providing a clearer picture of brand recognition.
As Google explained, this feature helps us measure the traffic from users already familiar with our brand compared to those discovering it for the first time.
Understanding Google’s classification. Google employs an AI-driven system to classify queries as branded. This system can adeptly recognize brand names in various languages, handle misspellings or variations, and detect queries that mention unique brand products or services.
There might be occasional misclassifications due to the contextual nature of brand detection, and Google clarifies that this filter doesn’t impact search rankings.
Keeping an eye out. With today’s announcement, this feature is supposedly available for all eligible sites. However, some sites might not qualify yet due to specific query and impression volume requirements.
I’ve been asked numerous times about how to track prompts effectively, especially by those using tools like Profound, Athena, and Peec. The big question on everyone’s mind is, “Which prompts are worth tracking?” In this ever-evolving landscape, it’s challenging to determine what buyers are querying about my company when they use LLMs.
Currently, there isn’t a reliable data source that puts my mind at ease. Unlike traditional search with publicly available Keyword Planner data, it’s unlikely that OpenAI or Google will fully release this kind of data for analysis. Though there have been recent proposals by the UK CMA about Google and data transparency, I’m not holding my breath for significant change.
Long story short, LLM tracking feels like navigating a black box. So, are there any alternative data sources we can use to track which prompts? Perhaps.
Back in November, Jason Packer published an interesting report highlighting how ChatGPT searches accidentally leaked into Google Search Console reports, featuring PII. When this was confirmed by Ars Technica, OpenAI stated the problem affected only a small number of queries.
This confirmed, for me, that ChatGPT queries do appear in some Search Console profiles. While privacy implications are significant and beyond this article’s scope, it shows that LLM queries are not impossible to capture.
Additionally, Barry Schwartz has reported that AI Mode data is available in Search Console. This supports the idea that Search Console can track how users interact with LLMs.
Based on my analysis, it seems that AI data appears to come from this area. By applying specific filters, I’ve noted steady increases in impressions over recent months, coinciding with Google’s roll-out of AI Mode features.
So, how can I access user prompt data in Search Console? The key is focusing on longer queries. Using regex, we can filter queries with 10 or more words, unveiling prompt-like behavior:
1. Navigate to Search Console Performance > Search Queries
2. Select Add Filter > Query
3. Choose Custom Regex
4. Input: ^(?:S+s+){9,}S+$
This method revealed understandable, prompt-styled queries when applied to various properties. Though the actual data cannot be shared, examples such as “Map out a full day in Glacier National Park…” highlight the trend.
Mind you, there’s no direct evidence these queries originate from ChatGPT or similar AI platforms. It’s possible they reflect new user behavior patterns within Google.
Regardless, analyzing these conversational query patterns provides invaluable insight into how customers search using longer strings.
Will Critchlow wisely said, “we’re doing business, not science.” In our shift toward less attributed, zero-click data collection, the choice to leverage this available data is up to us.
Currently, my preferred tool for prompt analysis is Claude. Its results are reliably robust, and its visualizations are effective. Integrating Claude into existing frameworks streamlines the process.
After export, uploading prompt lists to Claude lets it perform behavioral analysis, identifying data themes and trends for better prompt tracking.
Posing specific questions to Claude about customer behavior opens a treasure trove of insights. Analyzing this data reveals learning opportunities I would not have anticipated.
For instance, I discovered searches probing a PR issue from over three years ago are still frequent and that searches often use one company as a benchmark against its competitors.
Finally, leveraging Claude to suggest new prompt-tracking methods, based on this data, offers an informed way to continually hone tracking efforts.
While there’s no definitive system for selecting which prompts to track, incorporating Search Console data provides a clearer direction. The insights derived can help unearth unique user prompts and discern scalable themes for ongoing data tracking.
As an SEO professional, Google Search Console is like a trusty sidekick for me. It’s no secret that this free tool from Google provides an in-depth look at how my website performs. It’s like having a pair of X-ray glasses to see through the web’s layers.
With its robust data, I can delve into reports to uncover hidden treasures like clicks, impressions, and Core Web Vitals. It’s like exploring a digital gold mine inside my site.
Search Console’s custom regex filters are my guide through my vast website, ensuring I navigate it seamlessly, page by page.
While I hope to sidestep any SEO-related disasters, especially with Google’s AI advancements, it’s always best to be prepared. That’s why diving into this Search Console guide is essential.
This guide has been crafted for those times when the SEO world becomes unpredictable, much like a thrilling adventure in a post-apocalyptic world.
For instance, as an SEO director, I rely on Search Console daily. It’s my go-to for monitoring content performance, validating technical enhancements, and tracking grows in branded and non-branded queries. It’s integral to my SEO strategy, helping me prioritize tasks with precision.
What does Search Console do? And how does it help SEO?
Search Console stands as Google’s free website analytics and diagnostic platform. It tracks how a site performs in search results, potentially expanding soon into Gemini and AI Mode, offering us what feels closest to first-party search truth.
To set it up, it’s as simple as having a Google account and visiting the website. If profiles aren’t visible, simply verify ownership via a domain or prefix URL.
Domain property is the default recommendation
By default, I prefer setting up a domain property. It offers a holistic overview of my site’s search performance, autonomously including HTTP, HTTPS, www, and non-www versions.
With a verified domain property, I enjoy an uncomplicated setup, often via a DNS TXT record through my hosting provider.
URL prefix property allows you to dissect sections of a site
For more detailed insights, the URL prefix property lets me focus on specific sections like subfolders or subdomains. This is especially handy for producing targeted reports and troubleshooting.
Working with colleagues, such as customer support teams, becomes seamless when I can provide detailed data on specific site sections their work influences.
Key moments in Search Console history
The journey of Search Console has been quite eventful. Launched as Google Webmaster Tools in 2005, it evolved significantly over the years, adding key functionalities like mobile usability reports, security issue improvements, and Core Web Vitals report.
The enhancements continue as we advance into an era increasingly intertwined with AI, making Search Console a dynamic tool for SEO professionals like myself.
Was Google preparing us for AI through Search Console all along?
Reflecting on its evolution, I see a clear narrative. Search Console is transitioning from a mere technical tool into an AI visibility intelligence platform. Google’s approach suggests a future-bound strategy where not just queries but topic clusters define our analysis.
Breakdown of Search Console for SEOs
Within Search Console, I explore various features like URL inspection, search results, Core Web Vitals, and sitemaps, each offering unique insights into the health and performance of my sites.
With advanced tools like regex filters and manual action alerts, Search Console stands as a fortress of data, informing my SEO tactics with precision.
Overview
The Overview section quickly outlines key data sets, setting the stage for deeper dives into performance metrics across my websites.
I’ve noticed a peculiar issue with the Google Search Console’s page indexing report—it seems to be missing data prior to December 15th. Many of us are likely scratching our heads over this, and it appears to be some kind of reporting glitch affecting everyone.
So far, Google hasn’t provided any comments on this widespread issue. The absence of this data is creating challenges for all of us trying to analyze our website performance accurately.
What it looks like. To give you a clearer picture, Vijay shared a screenshot on X. You can verify this by checking your own page indexing report, and you’ll likely see the same gaps.
Why it matters to us. I plan to check back in the next few days to see if the data returns or if Google releases any updates about this problem. Currently, we’re all in the same boat, unable to access the prior data, which hinders our ability to run accurate reports and analyses.
Let’s hope Google resolves the issue soon, enabling us to resume our regular reporting and analysis for those missing data ranges.
Recently, I discovered that Google’s AI-powered configuration tool for the Search Console is available to everyone, and it’s been quite an exciting update! This tool allows us to interact with the performance reports by asking AI-driven questions and receiving detailed insights in return.
I found out about this rollout on LinkedIn where Google enthusiastically announced, “The Search Console’s new AI-powered configuration is now available to everyone!” This means we can all experience this amazing functionality firsthand.
AI-Powered Configuration: With this tool, I can describe the type of analysis I want in plain language. Google’s AI then converts my inputs into specific filters and settings, creating a customized report immediately.
Rolling Out Now: When I logged into my Search Console account and checked the performance report, a new note caught my eye: “New! Customize your Performance report using AI.” By clicking on it, I gained access to this innovative AI tool.
More Details: This AI-powered configuration is designed to simplify our analysis by managing three key tasks: selecting metrics, applying filters, and configuring comparisons.
Selecting Metrics: I can choose from metrics like Clicks, Impressions, Average CTR, and Average Position based on my queries.
Applying Filters: This allows me to refine data by various parameters such as query, page, country, device, or date.
Configuring Comparisons: I can establish intricate comparisons, like custom date ranges, without manual configuration.
Why We Care: While currently limited to the Performance report for Search results, I’m excited to see how AI might soon enhance reports for Discover and News. Even though the AI might not always provide perfect answers, exploring its potential has been an enlightening experience, sparking new ideas.
