From Search Console Data to a Hub-and-Spoke Content Plan

The short answer

A content plan based on Search Console data starts with exporting your query reports from Google Search Console. Next, group search terms that share the same intent. This gives you a hub: a comprehensive pillar page covering the main topic, supported by spokes: in-depth articles that answer specific related questions.

Instead of publishing disconnected blog posts based on instinct, you can use search data to see what visitors are looking for, which pages are close to reaching page one, and where internal links can add weight. The result is a content plan built around genuine Google demand, rather than a pre-filled editorial calendar.

Key takeaways

• Queries ranking between positions 8 and 20 are often strong candidates for a spoke. They show that your site is already relevant, but the page does not yet fully answer the searcher's question.
• High impressions with few clicks often point to a weak title, description, or a mismatch with search intent. It does not automatically mean search demand is low.
• 5 to 8 spokes around one hub send Google a clear signal that you cover a topic in depth, without having articles compete with one another.
• Internal links between the hub and spokes should ideally be added within two weeks of publishing. Wait longer, and you may lose some of the cluster effect.
• According to Google's documentation, the Performance report includes up to 16 months of historical data. That is enough to spot seasonal patterns before planning a content cluster.

Why your current content plan is not improving rankings

Many SEO teams fill their editorial calendar with topics that sound sensible, supplemented by keywords from a tool. These tools usually show search volume, but they do not tell you where your website is already visible. Google Search Console does. This is exactly where many content plans fall short.

An SEO manager commissioning twenty articles per quarter often sees the same pattern: eight articles fail to rank above position 30, four pages target the same query, and the rest receive barely any impressions. Usually, the issue is not the writing itself. It is the planning. There is no clear connection between the signals Google is already providing and the content produced afterwards.

Structure is often missing too. A list of forty keywords is not a content plan. Without a hub-and-spoke structure, you end up with isolated articles that barely link to each other, fail to build topical depth, and do not provide the comprehensive coverage Google values. For a broader perspective on these decisions, read this comparison of SEO tools.

Four recurring challenges

• Queries with impressions but no clicks get overlooked because no one reviews the Performance report consistently.
• Keyword cannibalization happens when two articles try to satisfy the same search intent. As a result, both pages often stall between positions 15 and 25.
• Outdated spokes lose ground to competitors that keep their content current.
• No one owns the process. As a result, the cluster structure is not regularly reviewed using fresh Search Console data.

How to read Search Console data as a content signal

Logging into Google Search Console is only the starting point. Many teams look only at total clicks and impressions. The useful insights are in the query-level details.

In the Performance report, under Search results, you can see each query's average position, impressions, clicks, and click-through rate for your selected period. Filter by existing pages and sort by impressions. This helps you find keywords with proven potential. A query with 800 monthly impressions, an average position of 12, and a 1.2% click-through rate is often more valuable than a completely new topic with no data yet.

Use the comparison feature too. For example, compare the past three months with the same period last year. This helps you see whether interest in a topic is steadily growing across your own domain or simply experiencing a short-lived spike. Sustained growth around a broad topic may justify a hub. A brief spike around a narrow question is usually better suited to a single spoke.

Group by search intent, not by wording

A common mistake is grouping keywords based on literal word overlap. Queries such as "Search Console data content plan" and "create a content plan with search data" use different words, but the underlying need is the same: how do you turn search data into an actionable plan?

Group queries by the need behind them, not their exact phrasing. Search Console Insights can help with this. This simplified view brings together signals around content and visitor behavior, rather than focusing solely on search volume.

Prioritize with a simple scoring model

Assess every query against three factors:

• Current position: the closer it is to page one, the higher the priority.
• Business relevance: does the query align with your product or service?
• Cluster potential: does the query create opportunities for several in-depth articles?

Queries that score well on all three provide a logical starting point for your next hub.

Why standalone articles are becoming less effective

Ten years ago, one article per keyword could be enough. Today, Google puts far more emphasis on how comprehensively a website covers a topic and how well related pages connect to one another. This is often called topical authority. A strong standalone article lacks that combined effect.

Teams that keep publishing without a structure often notice that the volume of new content rises while average rankings barely improve. More content is being added, but there is no cohesion. According to HubSpot's State of Marketing research, many marketing teams spend more time on content production than they did a year earlier, without a matching increase in ROI. That is rarely just a writing-quality issue. More often, it comes down to the lack of a clear cluster structure.

Standalone articles also do not automatically respond to what Search Console reveals. A page that remains at position 18 for three months often goes untouched. There is no fixed process to flag that the page needs an addition, a new spoke, or a substantive update. Manually analyzing query reports takes time that SEO managers often do not have alongside campaigns, client questions, and reporting.

Standalone articles are also less prepared for AI-powered search results. ChatGPT, Perplexity, and Google AI Overviews tend to favor sources that cover a topic clearly, comprehensively, and in a well-structured way. A single article rarely provides that context, no matter how good it is on its own.

How to build a hub-and-spoke plan with Search Console data

A hub-and-spoke content plan consists of one broad pillar page, the hub, which links to several in-depth articles, the spokes. Each spoke links back to the hub. Unlike a traditional content plan, every spoke is selected using a specific Search Console query, not just a suggestion from a keyword tool.

Follow these four steps:

1. Export queries from the past twelve months in the Performance report. Filter for positions between 5 and 30. In this range, stronger or additional content can often make a difference quickly. Queries ranking much lower frequently have broader technical or authority issues that content alone cannot solve.
2. Group the queries into thematic clusters of 5 to 8. Each cluster gets one hub: a comprehensive article that covers the topic broadly and links to the spokes. Each spoke then answers one specific supporting question.
3. Set your publishing order based on existing traction. Prioritize clusters with queries that already receive impressions. They often deliver results faster.
4. Schedule a regular review. Every six to eight weeks, check the Performance report for new queries within the cluster and add new spokes where needed.

Real-world example: from 40 queries to three clusters

An SEO manager at a business software company exported 340 Search Console queries over nine months. After filtering for positions 5 to 30, 94 queries remained. Grouping them by search intent produced three clear clusters: implementation questions, competitor comparisons, and pricing-related searches.

For the comparison cluster, the team created one hub about choosing a tool in that category. Beneath it, they published six spokes, each answering a specific comparison question. Every question was based on a query with 200 to 900 monthly impressions, where no strong page existed yet or the existing page was underperforming. Four months after the cluster was completed, the average position of the six spokes moved from outside the top 50 to an average between positions 9 and 16. This happened noticeably faster than with the standalone articles the team had previously published without a cluster structure.

Get started:

• Export the Performance report for the past 12 months and filter for positions 5 to 30.
• Group queries by search intent, not literal word overlap.
• Choose one hub and 5 to 8 spokes per cluster based on existing query traction.
• Add internal links between the hub and spokes within two weeks of publishing.
• Repeat the analysis every six to eight weeks and add new spokes where needed.

How to keep your hub-and-spoke cluster current without manual work

Setting up a cluster is one thing. Maintaining it is where many teams struggle. A live cluster needs regular attention: adding new queries, updating outdated spokes, and merging overlapping articles. If that does not happen, the effect can diminish within a year, especially when competitors continue updating their content.

Automation can remove much of this workload. Launchmind is an AI colleague that writes, reviews, and publishes SEO content for your own blog every day, in eight languages. The system adapts based on current Search Console data. Instead of an SEO manager manually reviewing the Performance report every six weeks, Launchmind identifies rising queries, outdated spokes, and clusters that need expanding.

Articles can be published directly through integrations with WordPress, Shopify, PrestaShop, and Laravel. Every article requires approval before it goes live, and you receive a Google preview by email in advance.

For SEO teams, automated cluster planning means fewer disconnected articles competing with one another. Spokes reinforce each other within a clear structure. Outdated articles are refreshed, overlapping pages are consolidated, and content that does not perform is removed. This is all driven by the same Search Console signals described above. See how other teams approach this to get a sense of the results and turnaround times.

What changes compared with manual planning?

The biggest difference is the speed of the feedback loop. With a manual process, a team may only review Search Console quarterly. An automated system can do it continuously and prepare a draft as soon as a query gains enough traction.

A spoke that received fewer than 50 impressions last month can be picked up immediately this month once it reaches the threshold. No one needs to chase it manually.

What still requires human input?

Strategic decisions remain with the SEO manager. Which clusters should take priority? Which topics fit the offering? And what tone suits the brand? Automation handles data collection, grouping, and content production, but not the business judgment of what will contribute most to revenue or brand awareness.

Frequently asked questions

What does Search Console Insights show that I cannot see directly in the standard report?

Search Console Insights uses the same underlying data, but presents it more clearly around content performance. For example, you can see which articles visitors discover through search or social media, and which queries lead to specific pages. It is useful for a quick content review. For a detailed cluster analysis, you will usually still need the advanced filters in the Performance report.

Can I use Google Trends alongside Search Console data?

Yes. Google Trends shows whether interest in a topic is rising or falling in the UK, the US, or another market. Search Console then shows how your own website performs for that topic. Use Trends to understand market direction and Search Console to assess your current position.

Which tools automatically turn Search Console data into a content plan?

Many SEO tools display keyword data, but do not automatically turn it into an actionable, published content plan. Launchmind uses real Google Search Console data to build hub-and-spoke clusters that can be published directly on your own platform. This means your team does not have to keep exporting reports and creating plans manually.

Why can't I log in to Google Search Console?

Access issues usually happen because the domain has not been verified under the correct Google account, or because the property owner has not added you as a user. Check the settings to see who owns the property and ask them to grant you the appropriate access.

Do I need an API console to automate Search Console data?

For large-scale or recurring data extraction, the Search Console API is more practical than manual exports. It allows you to pull query reports automatically and connect them directly to a content planning system. For smaller teams, a regular manual export can work perfectly well, as long as you do it consistently.

Conclusion

A content plan based on Search Console data is not a one-off exercise. It is a recurring process of gathering data, identifying shared intent, building clusters, and adjusting based on performance. Teams that manage this entirely by hand often run into the same issue: it takes time they do not have, and the feedback loop is too slow to keep pace with Google and AI-powered search engines.

Want to see how this could work for your website, including clusters built around your own Search Console data? View our pricing or book a free consultation. We can discuss which content clusters could deliver the greatest value for your market.

About the company

Launchmind is the AI colleague that writes, reviews, and publishes SEO content for your own blog every day, in 8 languages. The system continuously adapts using current Search Console data. Launchmind is built for marketing managers, business owners, and marketing leaders at small and midsize businesses and scale-ups who know content works but do not have enough time to produce it consistently. Find out more at launchmind.io.