Google PageSpeed Insights Report Dashboard
Unlock Website Performance Insights with the Power BI Template for PageSpeed Insights
Slow pages push customers away and cut conversions. Transform raw data from the Google PageSpeed Insights API into clear, practical findings that pinpoint where lag hits rankings, annoys users, and drops sales. Maya Insights brings it all together with a sharp view, custom reports, and full control over your analysis.
Trusted by
Without Maya
- Manually pull data from the Google PageSpeed Insights API, requiring coding and API knowledge.
- Complex and time-consuming ETL processes, often involving custom scripts and data cleaning.
- Building your own data model in Power BI, requiring extensive knowledge of PageSpeed Insights metrics and relationships.
- Manually creating reports and dashboards from scratch, requiring significant time and effort.
- Days or weeks to get actionable insights.
- Requires data engineering, API, and Power BI expertise.
With Maya
- Automated data extraction directly from the Google PageSpeed Insights API – no coding required.
- Pre-built ETL processes that automatically clean, normalize, and transform PageSpeed Insights data into a ready-to-use format.
- Pre-built semantic model specifically designed for PageSpeed Insights data, optimized for Power BI.
- Out-of-the-box dashboards and reports, plus easy customization with Power BI.
- Minutes to get actionable insights.
- Codeless solution – accessible to marketers, BI professionals, and data engineers without specialized coding skills.
What You Will Learn From the PageSpeed Analytics Dashboard
By leveraging Maya Insights and the Google PageSpeed Insights API, you’ll gain a deep understanding of your website’s performance and identify areas for improvement. You’ll be able to:
- Identify Slow Pages: Quickly pinpoint which pages are loading slowly and impacting user experience.
- Diagnose Performance Bottlenecks: Understand the why behind slow loading times, whether it’s server response time (TTFB), rendering issues (FCP, LCP), or large resource sizes.
- Track Core Web Vitals: Monitor your Core Web Vitals scores and see how they trend over time.
- Answer Critical Questions: Get answers to key questions like, “How is my Speed Index evolving?” and “Which pages are the slowest?”.
- Prioritize Optimization Efforts: Focus your resources on the areas that will have the biggest impact on your website’s speed and user experience.
How Maya’s Semantic Model Works
Simple 3-Step Process to Page Speed & SEO Analytics
-
#1
Unified Data Collection
Maya automatically pulls data from multiple key sources: Google Lighthouse (for lab-based performance testing), the Chrome UX Report (CrUX, for real-world user experience data), and your connected Google Analytics accounts (for site speed metrics).
-
#2
PageSpeed Data Integration & Marketing Data Unification
Our semantic model automatically cleans, normalizes, and structures the raw data from Lighthouse, CrUX, and Google Analytics. It connects your page speed data, including all Core Web Vitals (LCP, FID, CLS), with other marketing data for comprehensive, cross-channel analysis.
-
#3
Visualization & Reporting in Power BI
Access insightful dashboards showing the impact of page speed on SEO, user experience, and conversions. Build custom reports to answer your specific questions, leveraging the pre-defined measures and dimensions.
Go beyond pre-built dashboards. Tailor your reports to your specific needs.
While Maya Insights provides powerful out-of-the-box dashboards, the real power lies in its customization capabilities. Thanks to the pre-built semantic model and the flexibility of Power BI, you can:
- Unify all marketing data sources: Integrate your PageSpeed Insights data with other marketing data sources for a holistic view of performance.
- Group Pages for Meaningful Analysis: Create custom page groupings based on URL structure, content type, or business function (e.g., product pages, blog posts, landing pages). Analyze performance trends for each group to identify areas for targeted optimization.
- Create Mobile vs. Desktop Performance Comparisons: Isolate and compare page speed metrics (Speed Index, LCP, CLS, etc.) for mobile and desktop devices.
- Share Reports Easily: Share your customized dashboards and reports with colleagues and stakeholders.
- Monitor Speed Trends for Your Most Valuable Pages: Track the performance of your key landing pages, product pages, or high-traffic content over time.
Explore all of Maya’s functionalities
FAQs
What specific PageSpeed Insights metrics are included in the Maya semantic model?
The Maya Insights semantic model provides a comprehensive set of metrics, sourced directly from the Google PageSpeed Insights API (including data from both Google Lighthouse and the Chrome UX Report (CrUX)), all readily available for analysis within Power BI. These are categorized for easier understanding:
Core Web Vitals & Related Metrics:
- First Contentful Paint (FCP): Time until the first content is rendered.
Speed MS First Contentful Paint: Milliseconds to FCP (lab data).Speed Users MS First Contentful Paint: Milliseconds to FCP (real user data).Speed Score First Contentful Paint: Performance score for FCP (0-100).
- Largest Contentful Paint (LCP): Time until the largest content element is visible.
Speed MS Largest Contentful Paint: Milliseconds to LCP (lab data).Speed Users MS Largest Contentful Paint: Milliseconds to LCP (real user data).Speed Score Largest Contentful Paint: Performance score for LCP (0-100).
- Cumulative Layout Shift (CLS): Measures visual stability (unexpected layout shifts).
Speed Cumulative Layout Shift: Sum of all individual layout shifts (lab data).Speed Users Cumulative Layout Shift: CLS based on real user data.Speed Score Cumulative Layout Shift: Standardized CLS score (0-100).
- Total Blocking Time (TBT): Time the main thread was blocked, preventing responsiveness (lab data – proxy for FID/INP).
Speed MS Total Blocking Time: Total blocking time in milliseconds.Speed Score Total Blocking Time: Performance score for TBT.
- First Input Delay (FID) / Interaction to next Paint (INP). Measures Responsiveness (Field data)
Speed Users MS First Input Delay: Milliseconds to FID
Overall Speed & Performance:
- Speed Index: How quickly the page content is visibly populated.
Speed MS: Overall speed index in milliseconds.Speed MS Index: General/composite speed metric in milliseconds.Speed Users MS: Overall speed index in milliseconds. Field DataSpeed Score Index: Performance score for Speed Index.
Server Response Time:
- Time to First Byte (TTFB): How long the server takes to respond.
Speed Users MS Time To First Byte: TTFB in milliseconds (real user data).
Overall Audit Scores:
Speed Score Audit Total: Overall performance score across all audit categories.Speed Score Performance Audit/Speed Score Performance Latest: Score for the Performance audit category (and the latest value).Speed Score Accessibility Audit/Speed Score Accessibility Latest: Score for the Accessibility audit category (and the latest value).Speed Score Best Practices Audit/Speed Score Best Practices Latest: Score for the Best Practices audit category (and the latest value).Speed Score SEO Audit/Speed Score SEO Latest: Score for the SEO audit category (and the latest value).
User Experience Distribution (CrUX Data):
Speed Users High Proportion/Speed Users High Proportion Latest: Percentage of users with a “good” experience (and the latest value).Speed Users Average Proportion/Speed Users Average Proportion Latest: Percentage of users with an “average” experience (and the latest value).Speed Users Low Proportion/Speed Users Low Proportion Latest: Percentage of users with a “poor” experience (and the latest value).
PageSpeed Insights Data:
PageSpeed Insights User Sessions Examined #: Number of user sessions analyzed by Google.PageSpeed Insights Landing Pages Examined #: Number of landing pages analyzed by Google.
Metric Weighting:
Speed Metric Weight Towards Total Score: The weight used to calculate the total score.
Dimensions:
Track performance over time using date-related dimensions such as Year, Quarter, Month, Week, and specific Date. Dive deeper into device-specific performance with the Device dimension. Analyze individual page performance using the Landing Page title and gain insights into URL structure with Landing Page Url Link Domain (the complete base domain, including subdomain and protocol) and Landing Page Url Link Domain Base (the base domain without subdomains and protocols). Finally, leverage custom groupings of landing pages created within the Maya Insights web app, using dimensions like LPCx – {Landing Page Cluster x Name}, to analyze performance based on user-defined attributes (e.g., grouping by page title keywords).
What data sources does Maya use for Page Speed Analytics?
Maya Insights combines data from three essential sources to provide a complete picture of your website’s speed performance: Google Lighthouse (for lab testing), the Chrome UX Report (CrUX) (for real user data), and Google Analytics (GA4) (for site speed metrics and user behavior). This ensures you have a comprehensive view of how your website performs, combining different aspects and data points, all in one platform, and seeing how it ties to other marketing channels. Learn how to measure and monitor page speed effectively.
What types of questions can I answer with Maya Insights and PageSpeed data?
You can answer a wide range of questions, including: How is my Speed Index evolving? Which pages are the slowest? What is my Time to First Byte (TTFB)? How does my performance compare to competitors? How can I improve my Core Web Vitals (FID, CLS, INP)? You can analyze data from both Google Lighthouse (lab data) and the Chrome UX Report (real user data).
Can I track mobile performance separately?
Yes, absolutely. Maya Insights provides a dedicated view for tracking and comparing your mobile and desktop page speed performance metrics. Our dashboards let you analyze Core Web Vitals, load time, and user experience on mobile vs. desktop separately to pinpoint any specific issues or differences that might be impacting your conversions or rankings. You will finally understand how different devices affect user experience and marketing performance.
What is a good page speed for SEO?
Pages that load under 3 seconds generally perform best in search results. Maya Insights allows you to track all the key metrics that impact SEO, including Core Web Vitals, load time, First Contentful Paint (FCP), Largest Contentful Paint (LCP), and mobile performance to improve your overall SEO strategy. You can easily see the impact of page speed on your rankings, using real user data, all in one platform. This will allow you to make informed decisions and prioritize the actions that will have the highest impact.
How often is the speed data updated?
Maya Insights refreshes your page speed data daily, ensuring that you have the latest information. Our platform allows you to monitor up to 10 key URLs on a daily basis. CrUX data, which is based on real-user experience, is updated to provide a 28-day rolling average. Google Lighthouse, which provides lab testing data, is updated to show the most recent data. With Maya you will always have all the freshest data.
Which stakeholders can benefit from using Maya Insights for PageSpeed analysis?
Maya Insights is valuable for SEO analysts, web developers, BI engineers, data engineers, marketing managers, and CMOs – anyone involved in website performance optimization.
How does Maya Insights help improve my website’s performance?
Maya Insights helps by unifying your PageSpeed Insights data (from Google Lighthouse and CrUX), applying a consistent format, and making it easy to analyze, share insights, and cultivate a data-driven culture.
What is the “Speed Score” in the Maya Insights data model?
The “Speed Score” metrics provide standardized scores and overall performance evaluations based on various aspects of page speed, as measured by the Google PageSpeed Insights API. This allows for easy benchmarking and tracking of progress. The suffixes like “PERFORMANCE,” “ACCESSIBILITY,” “BEST_PRACTICES,” “SEO,” and “PWA” indicate scores related to specific categories.
What are the “Speed Use” metrics in the Maya Insights data model?
The “Speed Use” metrics provide insights into the visual progression of page loading and user experience, including timings for key rendering milestones and overall user session data. This helps you understand how users experience your website’s speed.
What is the difference between Google Lighthouse and the Chrome UX Report (CrUX)?
Google Lighthouse is a lab testing tool that simulates page loads under controlled conditions. The Chrome UX Report (CrUX) provides real-world user experience data collected from Chrome users who have opted in to sharing their browsing data. Maya Insights integrates data from both sources for a complete picture.
What is the difference between Speed Curve MS, and Speed MS?
‘Speed Curve MS’ in Google PageSpeed Insights typically refers to a detailed breakdown of loading times, showing how different parts of a page load over time. ‘Speed MS’ usually represents a single metric, like the time to first paint or overall load time in milliseconds.
What are Core Web Vitals, and why are they important?
Core Web Vitals are a set of specific factors that Google considers important for a webpage’s overall user experience. They include metrics like Largest Contentful Paint (LCP), First Input Delay (FID)/Interaction to Next Paint(INP), and Cumulative Layout Shift (CLS). Good Core Web Vitals scores are crucial for SEO and user satisfaction.