Nobody knows this about Google.

TLDR
The video introduces a new, little-known AI feature within Google Search Console, accessible through the "Performance Search Results" section. This AI tool allows users to quickly filter search queries based on user intent, distinguishing between "bottom of funnel" searches indicating a desire to purchase (e.g., "buy," "deal") and "informational" searches focused on learning (e.g., "how to," "what is"). Additionally, it can analyze the performance of specific website sections, such as blog articles, providing comparative data over different time periods for detailed insights.

Summary
The video unveils a recently launched, largely unrecognized AI feature integrated directly into Google Search Console. Users can access this powerful new tool by navigating to the "Performance Search Results" section and clicking on the distinct blue AI button. This functionality is designed to streamline the process of understanding search data, offering advanced filtering and analytical capabilities that were previously more complex to execute manually.

One of the key applications of this AI is its ability to categorize search queries based on the user's underlying intent. By simply instructing the AI with "show me bottom of funnel searches," it will automatically filter for keywords indicating a clear intent to purchase, identifying terms such as "buy," "price," "deal," "free trial," "get a quote," "sign up," "download," or "purchase." Conversely, if a user inputs "show me informational searches," the AI will filter for queries where individuals are seeking to learn, recognizing keywords like "how to," "what is," "guide," "tutorial," "why," "when," "where," or "who," providing valuable insights into user journey stages.

Beyond intent-based filtering, this AI in Google Search Console also facilitates sophisticated performance analysis for specific sections of a website. For example, if a website organizes its blog content within a `/articles` subdirectory, users can prompt the AI with a query like "Show me how forward/articles performed this week compared to the same time last year." This allows for a detailed comparison of performance, requiring users to specify a time range—such as "7 days versus same period last year"—and filter for URLs containing the specific path (e.g., `edward.com/articles`), with an option to break down the data by individual pages. This capability offers unprecedented ease in tracking and optimizing content categories over time.