Google Search Console provides insight into how your website performs in search results. The most valuable data for content production sits in the Performance report: which search terms lead to impressions and clicks, at what position your website ranks for those terms and through which URLs visitors arrive.

Search terms that generate many impressions but few clicks are particularly interesting. They indicate that Google considers your page relevant, but that the page is not compelling enough to click on yet. These are opportunities for improvement or new content.

Export the search terms from the Performance report in Search Console, preferably covering the last three to six months. You get a list of queries with impressions, clicks, average position and CTR.

Sort this list by impressions and identify two categories: queries for which you score well but where your content can still improve, and queries for which you have impressions but no dedicated page yet. The first category is input for content improvement, the second for new content.

A practical next step is clustering related queries. Sometimes you see ten variants of the same search question in your data: "using AI for marketing", "marketing with AI", "how do you use AI for marketing", and so on. These are all signals for the same information need.

Provide this cluster as input to an AI model and ask it to write an article that addresses all these variants naturally. The model can then produce text that matches the full breadth of the search intent, rather than just one specific phrasing.

Search terms with many impressions but low CTR indicate a mismatch between what the user is searching for and what your snippet shows. AI can help you rewrite page titles and meta descriptions based on the exact search terms generating impressions.

Provide the model with the current title, the current meta description and the top queries generating impressions for that URL. Ask the model to produce three alternative titles and descriptions that better match the search intent of those queries.

Search terms for which you have impressions but no dedicated landing page are direct indicators of missing content. These are topics users are searching for and for which Google considers you somewhat relevant, but not enough to rank highly.

Export those queries, group them by theme and have AI create content briefings based on those themes. This way you build a content calendar based entirely on proven search demand rather than assumed interest.

GSC data over longer periods reveals seasonal patterns in search behaviour. Certain topics peak in specific months. If you know those patterns, you can use AI to produce content in time to be ready for peak moments.

Compare impression data per month for your key keywords and build a publication calendar that responds to those peaks. This makes your content planning more responsive to the actual demand of your target audience.

GSC only shows data for queries for which you already have impressions. It tells you nothing about search terms for which you have no visibility at all. For discovering completely new opportunities, you need additional tools, such as keyword research tools or competitive analysis.

Use GSC as the basis for refining and optimising existing content directions. Combine it with external keyword research to discover new growth opportunities.

Google Search Console data is one of the most direct and reliable sources for AI content production. It replaces assumptions with evidence and ensures new content matches what your target audience is actually searching for.

At Mach8, we use GSC data as a structural part of our SEO content processes. View our SEO content service or get in touch.