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Find where Meta ad clicks drop off before the landing page loads

Compares link clicks with landing page views per Meta ad, then checks each weak ad's destination for status, redirects, message match and mobile LCP.

When to use it

When you pay for Meta link clicks but many people seem to leave before your landing page loads.

What you get

A table per weak ad with spend, link clicks, landing page views, ratio, destination status, redirects and mobile LCP, plus the 3 fixes that recover the most paid clicks.

Does it change anything in my account?

No. The assistant only reads your data and reports back.

Works with

Meta Ads, SEO Intelligence

Fill in before sending

[ad account name][minimum spend, e.g. 500 TL]

On Meta, I pay for link clicks but many people may leave before my page loads. Check this for my ad account [ad account name]. 1. List the ads and keep the ones whose effective_status is ACTIVE. For the last 14 days, pull spend, inline_link_clicks and actions at ad level (with ad_id and ad_name), and read landing page views from the landing_page_view action. Calculate landing page views divided by link clicks. Flag any ad below 70% that has spent more than [minimum spend, e.g. 500 TL]. 2. For each flagged ad, read the creative and get the destination link, the headline and the primary text, plus any URL parameters the creative carries. 3. Open each destination URL as a visitor would. Report the HTTP status. If the response is a redirect (a 3xx status or a Location header), open the target too and keep going until you reach a 200 or an error, so you can show the redirect chain. Read the final page with outline=true and text=true and say whether its heading and content match the ad's headline and offer, and whether the URL parameters survived to the final URL. 4. Run core_web_vitals with strategy=mobile on each final destination and report LCP. Deliver a table with these columns: ad name, spend, link clicks, landing page views, ratio, destination URL, status, redirects, LCP, and the likely cause. Finish with the 3 fixes that would recover the most paid clicks. This is analysis only, so do not pause or edit any ad.

On Meta, I pay for link clicks but many people may leave before my page loads. Check this for my ad account [ad account name].

1. List the ads and keep the ones whose effective_status is ACTIVE. For the last 14 days, pull spend, inline_link_clicks and actions at ad level (with ad_id and ad_name), and read landing page views from the landing_page_view action. Calculate landing page views divided by link clicks. Flag any ad below 70% that has spent more than [minimum spend, e.g. 500 TL].
2. For each flagged ad, read the creative and get the destination link, the headline and the primary text, plus any URL parameters the creative carries.
3. Open each destination URL as a visitor would. Report the HTTP status. If the response is a redirect (a 3xx status or a Location header), open the target too and keep going until you reach a 200 or an error, so you can show the redirect chain. Read the final page with outline=true and text=true and say whether its heading and content match the ad's headline and offer, and whether the URL parameters survived to the final URL.
4. Run core_web_vitals with strategy=mobile on each final destination and report LCP.

Deliver a table with these columns: ad name, spend, link clicks, landing page views, ratio, destination URL, status, redirects, LCP, and the likely cause. Finish with the 3 fixes that would recover the most paid clicks. This is analysis only, so do not pause or edit any ad.

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WebsiteChanges after your approval

Rewrite meta titles and descriptions for pages with low organic CTR

Finds page-one pages that get impressions but few clicks, compares them to your site-wide CTR, and rewrites their meta title and description around the queries that actually bring them traffic.

When to use itWhen your pages rank on page one and get impressions but few clicks, so your titles and descriptions are probably not convincing.

Use Search Console property [Search Console property] and WordPress site [WordPress site].

Step 1. Baseline. Pull the last 90 days with dimension "date" and add up total clicks and total impressions. Site average CTR = total clicks / total impressions. Show this number first.

Step 2. Candidates. Pull the last 90 days by page, sorted by impressions. Keep pages with at least 500 impressions, an average position between 1 and 10, and a CTR below 2%. Take the top 10 by impressions.

Step 3. For each of those 10 pages:
- Pull the queries for that page only (dimension "query", filtered to the page URL, sorted by impressions) and keep the top 5.
- Find the matching WordPress post or page ID by searching for its slug. If a URL has no clear match (archive, category, home page), mark it and move on.
- Read its current meta title and meta description from the SEO plugin.

Skip any page whose current title already contains its main query AND whose CTR is within 20% of the site average from Step 1. Say why you skipped it.

Deliver a table with these columns: URL, post ID, impressions, CTR, position, main queries, current title, current description, proposed title, proposed description.
- Proposed title: max 60 characters, main query near the start.
- Proposed description: max 155 characters, one concrete benefit and a call to action.
- Use only facts that are on the page. Do not invent prices, guarantees or numbers.

This table is the preview. Do not write any SEO field until I approve. After I approve, write only the approved rows (overwrite the existing values only for those rows), then purge the cache so the new tags go live, and read the SEO fields back for each changed page to confirm they landed.

WebsiteChanges after your approval

Rebuild the site menu around pages that actually convert

Matches GA4 landing-page performance against your WordPress menus, flags valuable pages missing from the navbar, dead weight and broken links, and proposes a leaner main menu.

When to use itWhen your site menu feels cluttered or outdated and you suspect it does not point visitors to the pages that actually bring conversions.

Compare my navigation menu with what actually converts.

From GA4 property [GA4 property], pull the last 90 days by landing page: sessions and key events. Calculate key event rate as key events / sessions.

Then read every menu on [WordPress site], including the main navbar and the footer, with all their links.

Match menu links to GA4 rows by URL path (ignore the domain, trailing slashes and query strings). Where a link has no GA4 row, treat it as zero sessions and say so.

Check every menu link for problems:
- Fetch each linked URL and record its HTTP status. Anything 4xx or 5xx is broken; redirects are worth noting.
- Flag links that point to draft or private pages, to old slugs, or to http instead of https.

Deliver three lists:
1. Pages with at least 20 key events that are not in the main menu.
2. Menu links pointing to pages with fewer than 50 sessions or zero key events in 90 days.
3. Broken or outdated links, with the reason for each.

Then propose a new main menu:
- Max 7 top-level items, ordered by commercial importance.
- Exact labels of 2 to 3 words, in plain language a customer would use.
- The contact page stays as the last item.
- Move low-value pages to the footer menu instead of deleting them.

Show the current menu and the proposed menu side by side, with the exact list of menu actions you would run (add, rename, relink, reorder, remove), as a preview. Do not edit anything until I approve. After approval, apply the changes, purge the cache and read the menus back to confirm the final structure.

WebsiteChanges after your approval

Plugin and tracking health check before it breaks your conversions

A plugin-by-plugin action list that flags outdated, duplicate and conflicting plugins and double-firing tags.

When to use itWhen your WordPress site has too many plugins, updates piling up, or you fear duplicate tags are inflating the conversions your ads optimize toward.

WebsiteChanges after your approval

Replace an old phone number everywhere on the site, safely

A full map of where the old number appears, a dry-run diff of the bulk replace, and a list of places that need manual fixes.

When to use itWhen your phone number has changed and you need to be sure the old one no longer shows anywhere on your website.