Rank Google Ads landing pages by speed problems and wasted spend
Joins Google Ads landing page cost and conversion data with real mobile Core Web Vitals, estimates the spend lost on slow pages and ranks which pages to fix first. Read-only.
When to use it
When your Google Ads leads are dropping and you suspect slow landing pages are wasting your ad budget.
What you get
A ranked table of landing pages with Core Web Vitals, estimated wasted spend, the main bottleneck and the top 3 fixes for the worst pages.
Does it change anything in my account?
No. The assistant only reads your data and reports back.
Works with
Google Ads, SEO Intelligence
Fill in before sending
[account]
I run a local service business and most of my leads come from Google Ads in account [account]. Find out which landing pages lose leads because they load slowly. Read only: do not change anything in the account.
1. Run google_ads_query on landing_page_view for the last 30 days (segments.date DURING LAST_30_DAYS): landing_page_view.unexpanded_final_url, clicks, cost, conversions, speed_score and mobile_friendly_clicks_percentage. Compute conversion rate as conversions divided by clicks per URL, and the account average as total conversions divided by total clicks across all URLs. If speed_score or mobile_friendly_clicks_percentage come back empty, mark them as not available and continue.
2. Take the top 8 URLs by cost and run core_web_vitals on each, strategy mobile, resources=true. Report LCP, INP and CLS from field data. If a page has no field data for INP, report lab TBT instead, mark INP as "no field data" and do not count it as poor. Say for each metric whether it is field or lab data.
3. Rate each metric as good, needs improvement or poor. LCP good at 2.5 s or less, poor above 4 s. INP good at 200 ms or less, poor above 500 ms. CLS good at 0.1 or less, poor above 0.25.
4. Name the main bottleneck per page from the resource lists: the LCP element, render-blocking files, unused CSS or JS, or oversized images.
5. Estimate wasted spend for pages converting below the account average: cost × (1 − page conversion rate ÷ account conversion rate). Pages at or above average get 0.
6. Build one table with these columns: URL, cost, conversions, conversion rate, speed score, LCP, INP, CLS, poor metric count, estimated wasted spend, main bottleneck.
7. Rank by priority: estimated wasted spend first, then poor metric count as the tie-breaker. If a page has few clicks (under 50), say the conversion rate is not reliable yet.
Flag any page where mobile LCP is above 4 s and conversion rate is below the account average. Those pages get fixed first. Finish with the top 3 concrete fixes for each flagged page, based on what Lighthouse actually reported.
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