Upgrading insights: how and why we’re improving docs analytics
Upgrading insights: how and why we’re improving docs analytics
Product updates
Product updates
Product updates
15 May,2025
We recently shipped a huge upgrade that gives you a much deeper understanding of how people use your documentation. In this post, I’ll walk through what’s new, why we made these changes, and some of the technical details behind the rebuild.
👋 Hi there! I’m Rémi, Head of Data at GitBook. I’ve been spearheading the recent overhaul of our insights system at GitBook so that you can better understand the details of who is reading your docs, which docs they’re reading, where they’re clicking, and more.
Why we rebuilt insights from the ground up
When we first launched site analytics back in 2021, our approach was straightforward but limited. We tracked basic page views using BigQuery, which was great initially, but then led to significant limitations for a growing documentation platform.
For starters, it wasn’t easily scalable as your documentation grew. It had no concept of aggregation, making complex queries expensive both in performance and cost. We were limited to tracking only basic pageviews, search, and feedback — missing out on a wealth of other valuable user interactions.
Another critical issue was that we stored different types of analytics in separate databases, creating silos of information that couldn’t easily be connected. The system offered no way to filter or segment your data dynamically. This made it difficult to answer specific questions about your documentation.
And perhaps most frustrating, we had almost 500ms latency regardless of the query complexity — that wasn’t ideal for an interactive analytics dashboard.
Research shows that docs creators want more from documentation analytics, and we’ve been hearing that from you, too! We knew we needed a foundation that could support both what you need today and what you’ll want tomorrow. Especially as the landscape of tech and docs continues to grow and change.
A new technical foundation for better analytics
Our new insights system is built on Clickhouse, a database specifically designed for analytical workloads. This change might sound purely technical, but it fundamentally transforms what’s possible with your documentation analytics.
With Clickhouse as our foundation, we can now deliver lightning-fast results even for complex queries. This consistent performance means you can explore your data interactively without waiting for results to load.
We’ve also unified our analytics, bringing all your data into one place instead of spreading it across different systems. This integration enables connections between different types of user behaviors that were impossible to see before.
The system now offers flexible filtering through dynamic query generation for comprehensive data analysis. Want to see how users from a specific country interact with a particular section of your docs? Or how mobile users differ from desktop users? Now you can get those answers with just a few clicks.
All of this adds up to significantly better performance, especially for large documentation sites with extensive content and substantial traffic. Where our previous system would struggle under heavy load, the new Insights system scales smoothly with your needs.
New metrics to transform how you understand your docs
The new insights system isn’t just an upgrade — it’s a complete re-imagining of what documentation analytics can be. Let’s explore the new metrics we’ve added and how they transform the way you understand your documentation.
Page analytics: beyond simple pageviews
Gone are the days when documentation analytics meant simply counting pageviews. Our enhanced page analytics reveal the full story of how people interact with your content.
With page analytics, you can now track not just how many people visit your docs, but what they do when they get there. Which pages are getting the most traffic? Where are those visitors coming from? What devices are they using? How do they navigate through your site?
These questions form the foundation of understanding user journeys through your documentation, and the new insights system answers them all.
By seeing these patterns, you can identify which parts of your documentation are serving users well and which might need improvement. You might discover that mobile users consistently struggle with certain pages, or that people coming from your marketing site have different needs than those arriving from your product.
Search and Ask AI: Uncovering user questions
One of the most valuable insights comes from seeing what users are actively looking for. Our new search and Ask AI analytics reveal exactly what information your users are seeking — and often, what they’re not finding.
What terms do people search for most frequently? What questions are they asking the AI assistant? Where is search happening most within your docs? By answering these questions, you can identify gaps in your documentation structure and content.
For example, if users are frequently searching for terms that don’t appear in your navigation, that might indicate a mismatch between your terminology and theirs. Or if certain features generate a disproportionate number of questions to the AI assistant, that could highlight areas where your documentation needs expansion or clarification.
By analyzing search queries and AI questions, you can identify gaps in your documentation that might not be obvious from content analysis alone.
This data can reveal which features cause the most confusion among users and helps you discover the terminology your audience is actually using. You might find that users are searching for concepts using different words than you’ve used in your headings and navigation, making content hard to find even when it exists.
You’ll also see what information is difficult to locate in your current structure, helping you refocus your documentation efforts where they’ll have the biggest impact.
For example, if users frequently ask the AI assistant about a particular workflow, but that workflow is buried deep in your documentation, you might want to elevate it to a more prominent position.
Link Clicks: Following user pathways
Understanding which links actually get clicked gives you unprecedented visibility into how users navigate your documentation. Now you can track clicks on both internal and external links, monitor header navigation usage, and see when links get clicked and by whom.
This data reveals whether users are finding your cross-references helpful, if they’re following your suggested learning paths, and which external resources they find valuable. You might discover that certain navigation patterns are more effective than others, or that users are consistently overlooking important related content.
Identifying and addressing broken links
Nothing frustrates users more than hitting a 404 ‘Page Not Found’ error. The new insights system automatically detects and reports broken URLs that have been visited by users, giving you visibility into navigation issues that might otherwise go unnoticed.
With this data, you can quickly identify which redirects to set up first based on actual user impact. Instead of guessing which broken links are most important to fix, you can prioritize based on how many users are encountering each one. This means you can focus your efforts where they’ll have the biggest impact on user experience.
By systematically addressing broken links based on usage data, you create a smoother, more reliable documentation experience. Users who previously would have hit dead ends can now continue their learning journey without interruption.
API Usage: Serving your developer audience
If you’re documenting an API with GitBook, the new insights into API documentation usage are invaluable. You can now see analytics around how developers interact with your API docs.
Which API endpoints receive the most interest? Which operations do users click on most? How are developers exploring your API? Understanding these patterns helps you prioritize your documentation efforts where they’ll have the greatest impact for your developer audience.
For example, you might find that certain endpoints are viewed far more frequently than others, suggesting where to focus your examples and explanations. Or you might discover that users spend a lot of time on error documentation for particular operations, indicating potential issues with those areas of your API.
The power of flexible filtering
What truly sets the new insights apart isn’t just what we track — it’s how you can explore and analyze that data. The filtering capabilities transform raw analytics into actionable insights.
You can filter by country, language, device, browser, and operating system to understand your international audience. Analyze traffic sources and UTM parameters to see where visitors are coming from. Exclude bot traffic for more accurate analytics, and compare data across different time periods to track trends.
The system also includes powerful "Group by" capabilities that help you identify drivers and patterns in your data. Group by traffic source to see which channels bring the most engaged visitors, or by page type to understand which kinds of content perform best.
This flexibility means you can identify high-value pages that deserve more attention and spot underperforming content that needs improvement. You can see which external links drive traffic to your site and correlate page feedback with usage data to understand which pages truly serve your audience well.
These insights create a virtuous cycle where you continuously improve your documentation based on actual usage patterns. And thanks to Clickhouse, all this filtering and analysis happens at impressive speed.
🐰🛠️ Technical rabbit hole: One of the things that makes Clickhouse special is how it handles aggregations. Instead of processing the entire dataset for each query, it pre-calculates many metrics and only processes new data incrementally. When you run a count query, for example, it doesn’t count every row again — it knows what was already calculated and just updates with new data. This makes even complex queries consistently fast, regardless of how much historical data you have.
Looking ahead: The future of documentation analytics
While the new insights system already transforms how you understand your documentation, we’re just getting started. Here’s a glimpse into what’s coming next:
Adaptive content analytics
We’re currently testing an exciting new feature called adaptive content, which lets you build tailored documentation experiences based on who’s reading — like only showing certain pages to enterprise users. Soon, we’ll be rolling this out more widely and combining it with Insights to create powerful new analytics capabilities.
Once available, this integration will let you filter analytics based on customer segments, giving you unprecedented visibility into how different types of users interact with your documentation. You’ll be able to see how enterprise customers use your docs compared to other customers, or how experienced developers navigate compared to newcomers.
This granular understanding will help you tailor your documentation strategy to meet the specific needs of your diverse user base. We’ll be sharing more details about adaptive content and its analytics capabilities in the coming weeks — stay tuned for a dedicated post about this feature.
Expanding our analytics roadmap
We’re exploring several other exciting enhancements to the insights system, such as:
Expanding our export capabilities to send more event types to external analytics platforms. Currently limited to page views, we plan to support exporting search events, link clicks, and other interaction data to your preferred analytics tools.
Adding automatic redirect creation from broken URL data. This would streamline the process of fixing navigation issues by suggesting or even implementing redirects based on detected broken links.
Creating simple funnels for tracking conversion paths. This would help you understand how documentation usage relates to key business outcomes like signups, feature adoption, or support ticket reduction.
And as our AI features continue to evolve, we’re developing more advanced analytics specifically for understanding AI interactions. These insights will help you optimize both your documentation content and the AI’s responses to user questions.
Experience the new insights today
The new insights system is available now to all users with Premium and Ultimate site plans. Just head to the insights tab in your site’s dashboard to start exploring your documentation analytics in a whole new way.
We believe that good documentation isn’t just about writing great content — it’s also about understanding how people use that content. With the new insights, you now have the tools you need to measure, analyze, and improve your documentation in ways that weren’t possible before.
Have questions about the new insights? Join our GitHub community and let us know, or check out our documentation for more details on how to get the most from these new features.
We recently shipped a huge upgrade that gives you a much deeper understanding of how people use your documentation. In this post, I’ll walk through what’s new, why we made these changes, and some of the technical details behind the rebuild.
👋 Hi there! I’m Rémi, Head of Data at GitBook. I’ve been spearheading the recent overhaul of our insights system at GitBook so that you can better understand the details of who is reading your docs, which docs they’re reading, where they’re clicking, and more.
Why we rebuilt insights from the ground up
When we first launched site analytics back in 2021, our approach was straightforward but limited. We tracked basic page views using BigQuery, which was great initially, but then led to significant limitations for a growing documentation platform.
For starters, it wasn’t easily scalable as your documentation grew. It had no concept of aggregation, making complex queries expensive both in performance and cost. We were limited to tracking only basic pageviews, search, and feedback — missing out on a wealth of other valuable user interactions.
Another critical issue was that we stored different types of analytics in separate databases, creating silos of information that couldn’t easily be connected. The system offered no way to filter or segment your data dynamically. This made it difficult to answer specific questions about your documentation.
And perhaps most frustrating, we had almost 500ms latency regardless of the query complexity — that wasn’t ideal for an interactive analytics dashboard.
Research shows that docs creators want more from documentation analytics, and we’ve been hearing that from you, too! We knew we needed a foundation that could support both what you need today and what you’ll want tomorrow. Especially as the landscape of tech and docs continues to grow and change.
A new technical foundation for better analytics
Our new insights system is built on Clickhouse, a database specifically designed for analytical workloads. This change might sound purely technical, but it fundamentally transforms what’s possible with your documentation analytics.
With Clickhouse as our foundation, we can now deliver lightning-fast results even for complex queries. This consistent performance means you can explore your data interactively without waiting for results to load.
We’ve also unified our analytics, bringing all your data into one place instead of spreading it across different systems. This integration enables connections between different types of user behaviors that were impossible to see before.
The system now offers flexible filtering through dynamic query generation for comprehensive data analysis. Want to see how users from a specific country interact with a particular section of your docs? Or how mobile users differ from desktop users? Now you can get those answers with just a few clicks.
All of this adds up to significantly better performance, especially for large documentation sites with extensive content and substantial traffic. Where our previous system would struggle under heavy load, the new Insights system scales smoothly with your needs.
New metrics to transform how you understand your docs
The new insights system isn’t just an upgrade — it’s a complete re-imagining of what documentation analytics can be. Let’s explore the new metrics we’ve added and how they transform the way you understand your documentation.
Page analytics: beyond simple pageviews
Gone are the days when documentation analytics meant simply counting pageviews. Our enhanced page analytics reveal the full story of how people interact with your content.
With page analytics, you can now track not just how many people visit your docs, but what they do when they get there. Which pages are getting the most traffic? Where are those visitors coming from? What devices are they using? How do they navigate through your site?
These questions form the foundation of understanding user journeys through your documentation, and the new insights system answers them all.
By seeing these patterns, you can identify which parts of your documentation are serving users well and which might need improvement. You might discover that mobile users consistently struggle with certain pages, or that people coming from your marketing site have different needs than those arriving from your product.
Search and Ask AI: Uncovering user questions
One of the most valuable insights comes from seeing what users are actively looking for. Our new search and Ask AI analytics reveal exactly what information your users are seeking — and often, what they’re not finding.
What terms do people search for most frequently? What questions are they asking the AI assistant? Where is search happening most within your docs? By answering these questions, you can identify gaps in your documentation structure and content.
For example, if users are frequently searching for terms that don’t appear in your navigation, that might indicate a mismatch between your terminology and theirs. Or if certain features generate a disproportionate number of questions to the AI assistant, that could highlight areas where your documentation needs expansion or clarification.
By analyzing search queries and AI questions, you can identify gaps in your documentation that might not be obvious from content analysis alone.
This data can reveal which features cause the most confusion among users and helps you discover the terminology your audience is actually using. You might find that users are searching for concepts using different words than you’ve used in your headings and navigation, making content hard to find even when it exists.
You’ll also see what information is difficult to locate in your current structure, helping you refocus your documentation efforts where they’ll have the biggest impact.
For example, if users frequently ask the AI assistant about a particular workflow, but that workflow is buried deep in your documentation, you might want to elevate it to a more prominent position.
Link Clicks: Following user pathways
Understanding which links actually get clicked gives you unprecedented visibility into how users navigate your documentation. Now you can track clicks on both internal and external links, monitor header navigation usage, and see when links get clicked and by whom.
This data reveals whether users are finding your cross-references helpful, if they’re following your suggested learning paths, and which external resources they find valuable. You might discover that certain navigation patterns are more effective than others, or that users are consistently overlooking important related content.
Identifying and addressing broken links
Nothing frustrates users more than hitting a 404 ‘Page Not Found’ error. The new insights system automatically detects and reports broken URLs that have been visited by users, giving you visibility into navigation issues that might otherwise go unnoticed.
With this data, you can quickly identify which redirects to set up first based on actual user impact. Instead of guessing which broken links are most important to fix, you can prioritize based on how many users are encountering each one. This means you can focus your efforts where they’ll have the biggest impact on user experience.
By systematically addressing broken links based on usage data, you create a smoother, more reliable documentation experience. Users who previously would have hit dead ends can now continue their learning journey without interruption.
API Usage: Serving your developer audience
If you’re documenting an API with GitBook, the new insights into API documentation usage are invaluable. You can now see analytics around how developers interact with your API docs.
Which API endpoints receive the most interest? Which operations do users click on most? How are developers exploring your API? Understanding these patterns helps you prioritize your documentation efforts where they’ll have the greatest impact for your developer audience.
For example, you might find that certain endpoints are viewed far more frequently than others, suggesting where to focus your examples and explanations. Or you might discover that users spend a lot of time on error documentation for particular operations, indicating potential issues with those areas of your API.
The power of flexible filtering
What truly sets the new insights apart isn’t just what we track — it’s how you can explore and analyze that data. The filtering capabilities transform raw analytics into actionable insights.
You can filter by country, language, device, browser, and operating system to understand your international audience. Analyze traffic sources and UTM parameters to see where visitors are coming from. Exclude bot traffic for more accurate analytics, and compare data across different time periods to track trends.
The system also includes powerful "Group by" capabilities that help you identify drivers and patterns in your data. Group by traffic source to see which channels bring the most engaged visitors, or by page type to understand which kinds of content perform best.
This flexibility means you can identify high-value pages that deserve more attention and spot underperforming content that needs improvement. You can see which external links drive traffic to your site and correlate page feedback with usage data to understand which pages truly serve your audience well.
These insights create a virtuous cycle where you continuously improve your documentation based on actual usage patterns. And thanks to Clickhouse, all this filtering and analysis happens at impressive speed.
🐰🛠️ Technical rabbit hole: One of the things that makes Clickhouse special is how it handles aggregations. Instead of processing the entire dataset for each query, it pre-calculates many metrics and only processes new data incrementally. When you run a count query, for example, it doesn’t count every row again — it knows what was already calculated and just updates with new data. This makes even complex queries consistently fast, regardless of how much historical data you have.
Looking ahead: The future of documentation analytics
While the new insights system already transforms how you understand your documentation, we’re just getting started. Here’s a glimpse into what’s coming next:
Adaptive content analytics
We’re currently testing an exciting new feature called adaptive content, which lets you build tailored documentation experiences based on who’s reading — like only showing certain pages to enterprise users. Soon, we’ll be rolling this out more widely and combining it with Insights to create powerful new analytics capabilities.
Once available, this integration will let you filter analytics based on customer segments, giving you unprecedented visibility into how different types of users interact with your documentation. You’ll be able to see how enterprise customers use your docs compared to other customers, or how experienced developers navigate compared to newcomers.
This granular understanding will help you tailor your documentation strategy to meet the specific needs of your diverse user base. We’ll be sharing more details about adaptive content and its analytics capabilities in the coming weeks — stay tuned for a dedicated post about this feature.
Expanding our analytics roadmap
We’re exploring several other exciting enhancements to the insights system, such as:
Expanding our export capabilities to send more event types to external analytics platforms. Currently limited to page views, we plan to support exporting search events, link clicks, and other interaction data to your preferred analytics tools.
Adding automatic redirect creation from broken URL data. This would streamline the process of fixing navigation issues by suggesting or even implementing redirects based on detected broken links.
Creating simple funnels for tracking conversion paths. This would help you understand how documentation usage relates to key business outcomes like signups, feature adoption, or support ticket reduction.
And as our AI features continue to evolve, we’re developing more advanced analytics specifically for understanding AI interactions. These insights will help you optimize both your documentation content and the AI’s responses to user questions.
Experience the new insights today
The new insights system is available now to all users with Premium and Ultimate site plans. Just head to the insights tab in your site’s dashboard to start exploring your documentation analytics in a whole new way.
We believe that good documentation isn’t just about writing great content — it’s also about understanding how people use that content. With the new insights, you now have the tools you need to measure, analyze, and improve your documentation in ways that weren’t possible before.
Have questions about the new insights? Join our GitHub community and let us know, or check out our documentation for more details on how to get the most from these new features.
We recently shipped a huge upgrade that gives you a much deeper understanding of how people use your documentation. In this post, I’ll walk through what’s new, why we made these changes, and some of the technical details behind the rebuild.
👋 Hi there! I’m Rémi, Head of Data at GitBook. I’ve been spearheading the recent overhaul of our insights system at GitBook so that you can better understand the details of who is reading your docs, which docs they’re reading, where they’re clicking, and more.
Why we rebuilt insights from the ground up
When we first launched site analytics back in 2021, our approach was straightforward but limited. We tracked basic page views using BigQuery, which was great initially, but then led to significant limitations for a growing documentation platform.
For starters, it wasn’t easily scalable as your documentation grew. It had no concept of aggregation, making complex queries expensive both in performance and cost. We were limited to tracking only basic pageviews, search, and feedback — missing out on a wealth of other valuable user interactions.
Another critical issue was that we stored different types of analytics in separate databases, creating silos of information that couldn’t easily be connected. The system offered no way to filter or segment your data dynamically. This made it difficult to answer specific questions about your documentation.
And perhaps most frustrating, we had almost 500ms latency regardless of the query complexity — that wasn’t ideal for an interactive analytics dashboard.
Research shows that docs creators want more from documentation analytics, and we’ve been hearing that from you, too! We knew we needed a foundation that could support both what you need today and what you’ll want tomorrow. Especially as the landscape of tech and docs continues to grow and change.
A new technical foundation for better analytics
Our new insights system is built on Clickhouse, a database specifically designed for analytical workloads. This change might sound purely technical, but it fundamentally transforms what’s possible with your documentation analytics.
With Clickhouse as our foundation, we can now deliver lightning-fast results even for complex queries. This consistent performance means you can explore your data interactively without waiting for results to load.
We’ve also unified our analytics, bringing all your data into one place instead of spreading it across different systems. This integration enables connections between different types of user behaviors that were impossible to see before.
The system now offers flexible filtering through dynamic query generation for comprehensive data analysis. Want to see how users from a specific country interact with a particular section of your docs? Or how mobile users differ from desktop users? Now you can get those answers with just a few clicks.
All of this adds up to significantly better performance, especially for large documentation sites with extensive content and substantial traffic. Where our previous system would struggle under heavy load, the new Insights system scales smoothly with your needs.
New metrics to transform how you understand your docs
The new insights system isn’t just an upgrade — it’s a complete re-imagining of what documentation analytics can be. Let’s explore the new metrics we’ve added and how they transform the way you understand your documentation.
Page analytics: beyond simple pageviews
Gone are the days when documentation analytics meant simply counting pageviews. Our enhanced page analytics reveal the full story of how people interact with your content.
With page analytics, you can now track not just how many people visit your docs, but what they do when they get there. Which pages are getting the most traffic? Where are those visitors coming from? What devices are they using? How do they navigate through your site?
These questions form the foundation of understanding user journeys through your documentation, and the new insights system answers them all.
By seeing these patterns, you can identify which parts of your documentation are serving users well and which might need improvement. You might discover that mobile users consistently struggle with certain pages, or that people coming from your marketing site have different needs than those arriving from your product.
Search and Ask AI: Uncovering user questions
One of the most valuable insights comes from seeing what users are actively looking for. Our new search and Ask AI analytics reveal exactly what information your users are seeking — and often, what they’re not finding.
What terms do people search for most frequently? What questions are they asking the AI assistant? Where is search happening most within your docs? By answering these questions, you can identify gaps in your documentation structure and content.
For example, if users are frequently searching for terms that don’t appear in your navigation, that might indicate a mismatch between your terminology and theirs. Or if certain features generate a disproportionate number of questions to the AI assistant, that could highlight areas where your documentation needs expansion or clarification.
By analyzing search queries and AI questions, you can identify gaps in your documentation that might not be obvious from content analysis alone.
This data can reveal which features cause the most confusion among users and helps you discover the terminology your audience is actually using. You might find that users are searching for concepts using different words than you’ve used in your headings and navigation, making content hard to find even when it exists.
You’ll also see what information is difficult to locate in your current structure, helping you refocus your documentation efforts where they’ll have the biggest impact.
For example, if users frequently ask the AI assistant about a particular workflow, but that workflow is buried deep in your documentation, you might want to elevate it to a more prominent position.
Link Clicks: Following user pathways
Understanding which links actually get clicked gives you unprecedented visibility into how users navigate your documentation. Now you can track clicks on both internal and external links, monitor header navigation usage, and see when links get clicked and by whom.
This data reveals whether users are finding your cross-references helpful, if they’re following your suggested learning paths, and which external resources they find valuable. You might discover that certain navigation patterns are more effective than others, or that users are consistently overlooking important related content.
Identifying and addressing broken links
Nothing frustrates users more than hitting a 404 ‘Page Not Found’ error. The new insights system automatically detects and reports broken URLs that have been visited by users, giving you visibility into navigation issues that might otherwise go unnoticed.
With this data, you can quickly identify which redirects to set up first based on actual user impact. Instead of guessing which broken links are most important to fix, you can prioritize based on how many users are encountering each one. This means you can focus your efforts where they’ll have the biggest impact on user experience.
By systematically addressing broken links based on usage data, you create a smoother, more reliable documentation experience. Users who previously would have hit dead ends can now continue their learning journey without interruption.
API Usage: Serving your developer audience
If you’re documenting an API with GitBook, the new insights into API documentation usage are invaluable. You can now see analytics around how developers interact with your API docs.
Which API endpoints receive the most interest? Which operations do users click on most? How are developers exploring your API? Understanding these patterns helps you prioritize your documentation efforts where they’ll have the greatest impact for your developer audience.
For example, you might find that certain endpoints are viewed far more frequently than others, suggesting where to focus your examples and explanations. Or you might discover that users spend a lot of time on error documentation for particular operations, indicating potential issues with those areas of your API.
The power of flexible filtering
What truly sets the new insights apart isn’t just what we track — it’s how you can explore and analyze that data. The filtering capabilities transform raw analytics into actionable insights.
You can filter by country, language, device, browser, and operating system to understand your international audience. Analyze traffic sources and UTM parameters to see where visitors are coming from. Exclude bot traffic for more accurate analytics, and compare data across different time periods to track trends.
The system also includes powerful "Group by" capabilities that help you identify drivers and patterns in your data. Group by traffic source to see which channels bring the most engaged visitors, or by page type to understand which kinds of content perform best.
This flexibility means you can identify high-value pages that deserve more attention and spot underperforming content that needs improvement. You can see which external links drive traffic to your site and correlate page feedback with usage data to understand which pages truly serve your audience well.
These insights create a virtuous cycle where you continuously improve your documentation based on actual usage patterns. And thanks to Clickhouse, all this filtering and analysis happens at impressive speed.
🐰🛠️ Technical rabbit hole: One of the things that makes Clickhouse special is how it handles aggregations. Instead of processing the entire dataset for each query, it pre-calculates many metrics and only processes new data incrementally. When you run a count query, for example, it doesn’t count every row again — it knows what was already calculated and just updates with new data. This makes even complex queries consistently fast, regardless of how much historical data you have.
Looking ahead: The future of documentation analytics
While the new insights system already transforms how you understand your documentation, we’re just getting started. Here’s a glimpse into what’s coming next:
Adaptive content analytics
We’re currently testing an exciting new feature called adaptive content, which lets you build tailored documentation experiences based on who’s reading — like only showing certain pages to enterprise users. Soon, we’ll be rolling this out more widely and combining it with Insights to create powerful new analytics capabilities.
Once available, this integration will let you filter analytics based on customer segments, giving you unprecedented visibility into how different types of users interact with your documentation. You’ll be able to see how enterprise customers use your docs compared to other customers, or how experienced developers navigate compared to newcomers.
This granular understanding will help you tailor your documentation strategy to meet the specific needs of your diverse user base. We’ll be sharing more details about adaptive content and its analytics capabilities in the coming weeks — stay tuned for a dedicated post about this feature.
Expanding our analytics roadmap
We’re exploring several other exciting enhancements to the insights system, such as:
Expanding our export capabilities to send more event types to external analytics platforms. Currently limited to page views, we plan to support exporting search events, link clicks, and other interaction data to your preferred analytics tools.
Adding automatic redirect creation from broken URL data. This would streamline the process of fixing navigation issues by suggesting or even implementing redirects based on detected broken links.
Creating simple funnels for tracking conversion paths. This would help you understand how documentation usage relates to key business outcomes like signups, feature adoption, or support ticket reduction.
And as our AI features continue to evolve, we’re developing more advanced analytics specifically for understanding AI interactions. These insights will help you optimize both your documentation content and the AI’s responses to user questions.
Experience the new insights today
The new insights system is available now to all users with Premium and Ultimate site plans. Just head to the insights tab in your site’s dashboard to start exploring your documentation analytics in a whole new way.
We believe that good documentation isn’t just about writing great content — it’s also about understanding how people use that content. With the new insights, you now have the tools you need to measure, analyze, and improve your documentation in ways that weren’t possible before.
Have questions about the new insights? Join our GitHub community and let us know, or check out our documentation for more details on how to get the most from these new features.
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