Using GSC to Find AI Questions Your Customers Ask

The New Search Landscape. Why AI Questions Matter

The way people find information online is undergoing a fundamental shift. For years, we were trained to think in keywords, typing short phrases into a search bar. Today, users are increasingly having conversations with AI. They are asking detailed, natural language questions to models like ChatGPT, Perplexity, and Google's AI Overviews. This evolution from keyword searches to conversational queries presents a new challenge for businesses. To remain visible, you must understand the specific questions your customers are asking, but this data can often feel like it's locked away in a black box.

This is where many small and medium-sized businesses (SMBs) feel stuck. How can you optimize for questions you don't know are being asked? The purpose of this guide is to show you a practical, step-by-step method for finding these valuable questions using a powerful tool you already have access to, Google Search Console (GSC).

It's important to set expectations. As confirmed by industry analysis and Google representatives, Google Search Console does not currently offer a dedicated filter to isolate traffic from AI Overviews. All performance metrics from these AI-driven features are aggregated with your standard web search data, creating what many marketers call a "data blind spot" [1]. However, the raw query data within GSC remains a goldmine. By learning how to mine it effectively, you can gain powerful data-driven insights into the user intent that fuels AI answers and begin building a robust AI visibility strategy.

Step 1. Exporting Your Query Goldmine from GSC

Your Google Search Console account contains thousands of real search queries that led users to your website. This is the most direct source of truth for what your audience is actually looking for. The first step in our process is to export this data so we can analyze it. While you can perform filtering directly within the GSC interface, exporting the data to a CSV file allows for more flexible analysis and record-keeping.

Follow these simple instructions to get your data:

1. Log in to your Google Search Console account and select the correct property for your website.
2. From the left-hand menu, navigate to the 'Performance' report and ensure you are viewing 'Search results'.
3. Select a relevant date range. To get a meaningful amount of data, we recommend choosing at least the last 3 to 6 months.
4. Below the performance graph, make sure the 'Queries' tab is selected. You will see a list of search terms that your site has appeared for.
5. In the top-right corner of this table, click the 'EXPORT' button and choose 'Download CSV'.

As noted by some SEO platform guides, the GSC user interface typically allows you to export up to 1,000 queries at a time [2]. For most SMBs, this provides more than enough raw material to identify key trends and customer questions. You now have a file filled with the exact language your customers use to find you.

Step 2. Using Regex to Isolate Customer Questions

With your query data in hand, the next step is to filter it to find the questions. Staring at a spreadsheet of a thousand queries can be overwhelming. We need a way to quickly isolate the conversational, question-based searches that are most likely to trigger an AI response. The best tool for this job is Regex, which stands for Regular Expressions.

In simple terms, Regex is a powerful way to find specific patterns in text. Think of it as a 'find and replace' feature on steroids. Instead of searching for a single word, you can search for patterns, like 'any query that starts with the word what' or 'any query that contains the word versus'.

You can apply these filters directly in GSC without exporting the data. Here’s how, as outlined by SEO experts:

• In your GSC 'Performance' report, click the '+ NEW' button above the graph.
• Select 'Query...' from the dropdown menu.
• In the filter box that appears, click the dropdown that says 'Queries containing' and change it to 'Custom (regex)'.
• Paste one of the Regex codes below into the text field and click 'Apply'.

Here are three powerful Regex patterns to get you started:

1. The Classic Question Filter

This pattern finds queries that begin with common question words, often called 'interrogators' [3]. These are the most direct questions your audience is asking.

^(who|what|where|when|why|how|can|does|is|are)\b

2. The Comparison Seeker Filter

AI Overviews are frequently triggered by queries where a user is comparing two or more options. This pattern helps you find those valuable comparison-based searches.

\b(vs|versus|compare|alternative|or|better|difference)\b

3. The Advanced Conversational AI Prompt Filter

To dig even deeper, you can combine patterns. The following Regex, shared by digital strategy analysts, identifies queries that both start with a question word and are at least eight words long. This is an excellent way to find long, conversational queries that closely mimic how a user would prompt an AI chatbot.

^(who|what|where|when|why|how|was|did|do|is|are|aren't|won't|does|if)\b.*([[^"\s]*\s){8,}

By applying these filters, you transform your raw data into a clean list of high-intent customer questions, which is the first step toward a better AI Search Optimization strategy.

Step 3. From Data to Strategy. Analyzing Your Findings

Now that you have a filtered list of questions, the real work begins. This list is the voice of your customer, telling you exactly what they need to know. The next step is to move from data collection to strategic analysis. Your goal is to identify themes, pain points, and opportunities within these questions.

Start by reading through the filtered queries. Look for patterns and recurring topics. Are customers frequently asking about a specific product feature? Are they confused about your return policy? Are they looking for guidance on how to use your product for a particular task? Group similar questions together to build a clear picture of your audience's top priorities.

For example, if you run an e-commerce store selling skincare and you see multiple questions like:

• 'is vitamin c serum good for sensitive skin'
• 'how to use vitamin c serum with retinol'
• 'what is the best vitamin c serum for beginners'

You have identified a clear content gap. Your audience needs a comprehensive guide on Vitamin C serum. By creating a detailed blog post, FAQ page, or video that directly answers these questions, you are not only serving your customers but also creating the perfect content for AI models to use as a source for their answers. This analysis forms the foundation of your content strategy, turning raw data into a playbook for what to create next. For a deeper dive into this process, you can review our playbook on what customers ask AI.

The Limits of Manual Analysis and the Path to Automation

The manual GSC method is an incredibly powerful and free way to begin your journey into AI visibility. It provides a concrete, data-backed starting point based on your own audience's behavior. However, for a growing business, this approach has significant limitations.

First, the process is time-consuming. To keep your insights fresh, you must manually repeat the export and filtering process regularly. Second, it's reactive. This method only shows you queries for which your site already has some impressions. It doesn't help you discover new questions or topics that your competitors are ranking for but you are missing entirely. Finally, it provides no insight into how your brand is perceived across different AI models or how that perception is changing over time.

To truly get ahead, you need a proactive and scalable solution. You need a system that automates the discovery process, provides competitive intelligence, and offers a complete view of your brand's visibility in the new AI-powered search landscape.

Upgrade Your Strategy. Automate AI Visibility with Searchify

This is precisely why we built Searchify. Searchify is an AI Search Optimization platform designed to automate and scale the work of improving your brand's visibility in AI-generated responses. Our platform moves beyond manual data pulls and reactive analysis.

Searchify continuously monitors how AI models like ChatGPT, Google AI Overview, and Perplexity perceive your brand. We track your competitors and simulate thousands of realistic user questions to uncover a complete map of your optimization opportunities. Our platform is built around a core principle of being action-oriented. We don't just report on data; our 'Action Center' delivers concrete, actionable recommendations to improve your AI visibility.

We also understand that many SMBs and their marketing teams are stretched thin. That's why we offer an optional full-service add-on. This service empowers you to offload the implementation of technical website fixes, targeted content creation, and outreach to a dedicated AI visibility expert. You get the value and output of a full agency but at a fraction of the cost, complete with a dedicated account manager to guide your strategy.

Stop guessing what questions your customers are asking. Start building a data-driven strategy for the new age of search. To see how your brand currently appears in AI answers and get a personalized analysis, request your free AI visibility one-pager from Searchify today.