CONNECT GOOGLE PAGESPEED INSIGHTS TO MUSE
Set up Google PageSpeed Insights reporting in Muse
Choose the public research subject, then authorize Adzviser in Muse. No source account credentials are needed for this research.
Choose a research subject
Use an Adzviser account to access Google PageSpeed Insights research. You do not need a Google PageSpeed Insights account; choose a page URL and mobile or desktop analysis.
Open Adzviser setup →Authorize Adzviser in Muse
Open Muse.ai and send: “Can you connect to custom Adzviser MCP at https://mcp.adzviser.com/http?” Select Connect on the Adzviser card, sign in to Adzviser, and select Complete Authorization via MCP. Return to Muse.
https://mcp.adzviser.com/httpVerify the first result
Ask for a small sample using your chosen URL or advertiser and region. Check that Muse used the intended subject before continuing.
The Adzviser reporting connection is read-only. It can retrieve data for analysis; it cannot edit source records or campaigns.
A USEFUL FIRST GOOGLE PAGESPEED INSIGHTS REPORT
Review one page across mobile and desktop
Build a report you can check
Provide the complete page URL and ask for mobile and desktop checks separately. Return the performance score and available LCP, INP and CLS field measurements beside clearly labeled lab results. Record the device strategy and run time. If field data is missing, report it as unavailable rather than assigning a zero score.
Use lab and field data for different questions
Field data describes observed user experience; lab data comes from a controlled test and helps reproduce issues. A strong lab performance score does not establish that every visitor has a good experience. Total blocking time is a lab metric, not a substitute measurement for field INP.
Choose a measurable engineering follow-up
Ask Muse to identify the weakest available measurement and explain which page behavior should be investigated. Treat suggested fixes as hypotheses to verify in browser developer tools. Repeat the same device test after a change and compare like-for-like measurements.
Metrics for this report: Performance score; Largest contentful paint (LCP); Interaction to next paint (INP); Cumulative layout shift (CLS); Total blocking time (Lab test result).
Relevant breakdowns: Web page Url; Device type.
These are starting fields, not a promise that every combination belongs in one report. Use separate requests for different reporting levels and check the full field catalog for additional coverage.
COPY INTO MUSE
Run your first Google PageSpeed Insights analysis
Paste this after connecting. Change the period or research subject to match your question, and let Muse confirm the selection before retrieving results.
Use Adzviser to research Google PageSpeed Insights. Ask me to confirm a page URL and mobile or desktop analysis before you begin. Provide the complete page URL and ask for mobile and desktop checks separately. Return the performance score and available LCP, INP and CLS field measurements beside clearly labeled lab results. Record the device strategy and run time. If field data is missing, report it as unavailable rather than assigning a zero score. Use these metrics in compatible reports: Performance score, Largest contentful paint (LCP), Interaction to next paint (INP), Cumulative layout shift (CLS), Total blocking time (Lab test result). Relevant breakdowns: Web page Url, Device type. Check field compatibility and use separate tables for different reporting levels. State the actual reporting dates or observation window. Show the supporting rows, then give a short conclusion and one next investigation. Label missing data and separate observed changes from possible explanations.
