SEO and content

Fix organic landing pages that get traffic but fail to engage

Finds high-traffic landing pages with weak engagement or zero key events in GA4, checks their Search Console queries and mobile Core Web Vitals, inspects how each WordPress page is built, diagnoses the main problem and previews exact page edits for approval.

When to use it

When some pages get plenty of organic visitors but those visitors bounce, barely engage or never convert.

What you get

A ranked table of problem landing pages with the main issue and 3 fixes each, plus exact edits for the top 3 pages applied only after your approval.

Does it change anything in my account?

Only with your approval. The assistant first shows a preview of every change and waits for your go-ahead.

Works with

GA4, Search Console, WordPress, SEO Intelligence

Fill in before sending

[GA4 property][property][site]

For the GA4 property [GA4 property], the Search Console property [property] and the WordPress site [site], find landing pages that attract visitors but lose them. 1. Pull the site-wide GA4 overview for the last 28 days to get the average engagement rate. Then pull a landing page report for the same 28 days with sessions and key events. Keep pages with at least 300 sessions where either: - the engagement rate is 15 or more points below the site average (if the report does not give engagement rate per page, use key events per session against the site average instead and tell me you did), or - key events are zero. Cap the list at the 10 pages with the most sessions. 2. For each page, pull its top 5 Search Console queries for the last 28 days, filtered to that page URL, and judge whether the content answers what people searched for. 3. Run a mobile Core Web Vitals check on each page, one call per page. Note LCP, CLS and INP and the LCP element. 4. Match each URL to its WordPress page or post by slug. Inspect how it is built: - On an Elementor page, read the design elements: what sits in the first section, where the first button or CTA appears, and how far down the answer to the main query starts. - On other builders or the block editor, read the raw content and judge the same points from the block or shortcode order. If a URL does not map to a WordPress page, say so and skip step 4 for it. 5. Deliver one row per page with these columns: sessions, engagement rate (or key events per session), key events, top queries, main problem, and 3 specific fixes. The main problem must be one of: intent mismatch, buried answer, weak or missing CTA, slow LCP, or layout shift. Rank the rows by sessions. For the top 3 pages, propose exact edits: heading text, button label, link, and block order. For each edit, show the element or block, the current value and the new value. Do not change anything until I approve each page. After I approve, apply only the approved edits (design edits on Elementor pages, text replacements in the content on other pages) and then purge the site cache. If a page looks wrong afterwards, roll it back to the previous version.

For the GA4 property [GA4 property], the Search Console property [property] and the WordPress site [site], find landing pages that attract visitors but lose them.

1. Pull the site-wide GA4 overview for the last 28 days to get the average engagement rate. Then pull a landing page report for the same 28 days with sessions and key events. Keep pages with at least 300 sessions where either:
   - the engagement rate is 15 or more points below the site average (if the report does not give engagement rate per page, use key events per session against the site average instead and tell me you did), or
   - key events are zero.
   Cap the list at the 10 pages with the most sessions.
2. For each page, pull its top 5 Search Console queries for the last 28 days, filtered to that page URL, and judge whether the content answers what people searched for.
3. Run a mobile Core Web Vitals check on each page, one call per page. Note LCP, CLS and INP and the LCP element.
4. Match each URL to its WordPress page or post by slug. Inspect how it is built:
   - On an Elementor page, read the design elements: what sits in the first section, where the first button or CTA appears, and how far down the answer to the main query starts.
   - On other builders or the block editor, read the raw content and judge the same points from the block or shortcode order.
   If a URL does not map to a WordPress page, say so and skip step 4 for it.
5. Deliver one row per page with these columns: sessions, engagement rate (or key events per session), key events, top queries, main problem, and 3 specific fixes. The main problem must be one of: intent mismatch, buried answer, weak or missing CTA, slow LCP, or layout shift. Rank the rows by sessions.

For the top 3 pages, propose exact edits: heading text, button label, link, and block order. For each edit, show the element or block, the current value and the new value. Do not change anything until I approve each page. After I approve, apply only the approved edits (design edits on Elementor pages, text replacements in the content on other pages) and then purge the site cache. If a page looks wrong afterwards, roll it back to the previous version.

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A ranked list of keyword clusters with volume, difficulty and the right page type or ad group for each.

When to use itWhen you are starting keyword research for a business and only have a few seed keywords.

I sell [product or service] in [city or country]. Start from these seed keywords: [3 to 5 seed keywords].

First check seo_history so you reuse earlier results instead of paying for the same query twice. Then use Keyword Planner and SEO keyword research to collect ideas with average monthly searches, competition and keyword difficulty.

Clean the list:
- remove keywords under 30 monthly searches
- remove job, free, DIY, course and competitor-brand terms unless they clearly fit my business
- merge close variants and plurals

Cluster the rest by search intent, with one cluster per distinct need a searcher has. For each cluster give:
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- 5 to 10 supporting keywords
- combined monthly volume and average difficulty
- intent: informational, commercial or transactional
- best use: service page, blog post or a Google Ads ad group

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Uses 90 days of converting Google Ads and Microsoft Ads search terms to find topics where you pay for conversions but have weak or no organic visibility. Returns a prioritized content plan and a preview-only list of keyword additions.

When to use itWhen you pay for conversions on search terms but are unsure which topics deserve organic content so you can rely less on ads.

I want to use my ad data to decide what to write about. Use the last 90 days on every source.

1. Pull my Google Ads search terms for the last 90 days (days=90, or an explicit start and end date), sorted by conversions. Keep only terms with at least 1 conversion. If the response is truncated, page through until you have every converting term.
2. If Microsoft Ads is connected, find the default account and pull its search terms for the same 90 days. Keep only terms with at least 1 conversion and add them to the pool, marking which platform each term came from.
3. Group all converting terms into topic clusters by search intent. For each cluster show total cost, conversions and cost per conversion, split by platform where both are present.
4. Find my Search Console property (use [site property] if I named one) and pull organic data for the last 90 days with dimension query, plus a page,query pull so you can see which page ranks for each query. Use a high enough limit to cover the long tail.
5. Match each cluster to the Search Console queries that express the same intent. Use your judgement for close variants and wording differences, and say which queries you counted. Report organic clicks, impressions and average position per cluster, and the page that ranks best for it if there is one.

Classify each cluster:
- Content gap: converts in ads, organic average position worse than 10 or no organic impressions. I should build a page.
- Improve: converts in ads, organic position 4 to 10. Name the existing page that needs strengthening.
- Covered: organic position 1 to 3. Note it as a possible place to test lower ad spend later.

Deliver a table sorted by ad conversions, then the top 5 content-gap clusters with a suggested page title and URL slug for each.

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When to use itWhen your Business Profile gets views but you suspect your services and categories do not match what people really search for on Google and Maps.

For my Business Profile location [location name], pull the search terms people used on Google Search and Maps to find the listing over the last 3 months.

Cluster the terms into:
- brand searches
- service searches, with one cluster per service
- "near me" and neighborhood or district searches
- problem-based searches, such as a symptom or an issue the customer has

For each cluster show total impressions and the top 5 terms.

Then read my listing details: primary and additional categories, and the services list. Compare them with the clusters and tell me:
- service clusters with real demand that are missing from my services list
- services I list that get almost no searches
- whether an additional category would match a strong cluster. Search the category names to confirm they exist.

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Show me the exact changes as a preview first. Do not update the listing until I approve.

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A 12-month calendar showing when each keyword cluster peaks, when to publish content and when to raise or lower ad budgets.

When to use itWhen you want to time content and ad budgets around real seasonal demand instead of guessing when interest peaks.