> ## Documentation Index
> Fetch the complete documentation index at: https://docs.erlin.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Landing pages
> Every URL on your site classified by type, enriched with Google Search Console and Google Analytics data to show which pages drive traffic and which AI can cite.
Landing Pages shows every URL on your site, classified by type, alongside real search and analytics data from Google Search Console and Google Analytics. It answers one question: which of your pages already pull traffic, and which are strong candidates for AI to cite?
## What Landing Pages tracks
Erlin reads your sitemap, classifies each URL by type (product, collection, blog, page), and enriches each row with two data sources when connected:
| Data source | Columns it populates |
| ------------------------------- | ------------------------------------------------- |
| **Google Search Console (GSC)** | Clicks and top keyword for each URL |
| **Google Analytics 4 (GA4)** | Sessions, engagement rate, pageviews, bounce rate |
The combination tells you three things:
1. Which pages already have organic reach and engagement (high clicks, good sessions)
2. Which pages are high-value targets for AI citation but currently underperforming (good content, low traffic)
3. Which pages have traffic but no keyword coverage (opportunities for optimization)
## Why it sits in AI visibility tracking
Citations close the loop between AI mentioning your brand and users actually reaching your website. Landing Pages is the inventory view of what AI can cite back to.
The connection between this page and the rest of the section:
* [Citations](/ai-visibility/citations/publications) tells you which third-party sources AI cites
* **Landing Pages** tells you which of your own pages are strong enough to become citation targets
* [Citation Rate](/ai-visibility/metrics/citation-rate) measures how often AI actually links to your domain
A page with strong organic traffic, good engagement, and relevant keyword coverage is more likely to be cited by AI as a source. A page with zero traffic and no keyword relevance is unlikely to be cited even if it exists on your site.
Use Landing Pages to identify which of your pages deserve more AI citation coverage, then combine with the Citations view to see whether AI is actually finding and citing them.
## Connecting GSC and GA4
Landing Pages requires active connections to Google Search Console and Google Analytics to populate the analytics columns. Without them, the grid still shows your sitemap URLs and their type classifications, but the GSC and GA4 columns display dashes.
**If you have not connected yet**: Erlin shows a blue informational banner with a link to the [Integrations](/integrations/overview) page where you can connect both services.
**If connected but property not found**: if your website is connected to a GSC or GA4 account but not added as a property within those accounts, Erlin shows a specific message with a direct link to Google Search Console or Google Analytics where you can add the property.
Once connected, Erlin automatically fetches analytics data for your sitemap URLs in the background. A progress banner shows the fetch percentage. The fetch persists across navigation: if you leave the page and come back, the progress continues and data will be waiting when it completes.
GSC data has a 2-day lag from Google. The date range indicator in the page header shows exactly which period the data covers (typically the last 28 days). GA4 data is more current, usually lagging by only a few hours.
## URL types
Erlin classifies each sitemap URL into a type based on URL patterns and page structure:
| Type | What it represents | Examples |
| -------------- | --------------------------- | ------------------------------------------- |
| **Product** | Individual product pages | /products/widget-pro, /shop/item-123 |
| **Collection** | Category or listing pages | /collections/summer-sale, /category/tools |
| **Blog** | Blog posts and articles | /blog/how-to-guide, /articles/industry-news |
| **Page** | General informational pages | /about, /pricing, /faq |
Use the URL type filter above the grid to focus on one category at a time. For example, filtering to "Blog" lets you audit which articles have keyword coverage and which do not, helping you prioritize content optimization work.
## Navigating the grid
The Landing Pages grid supports:
* **Search**: type a URL fragment to filter the grid to matching pages
* **URL type filter**: narrow to a specific page type (product, collection, blog, page)
* **Pagination**: the grid loads in pages (default 100 URLs per page) with navigation controls at the bottom
* **CSV export**: export the full grid (with analytics data) for offline analysis
Analytics columns that have not loaded yet show a loading indicator. Columns for which no data exists show a dash.
## Refreshing analytics data
Two ways to update the analytics data:
**Automatic on first load**: when you visit Landing Pages for the first time (or after connecting GSC/GA4), Erlin checks whether analytics data already exists. If not, it starts a background fetch covering all sitemap URLs sequentially in batches.
**Manual refresh**: click **Load fresh data** in the page toolbar to re-fetch GSC and GA4 data for all your URLs. Erlin processes them in batches and shows a progress percentage in the banner. This is useful when you want to see updated data after a content campaign, for example without waiting for the next automatic refresh.
The background fetch continues even if you navigate away from the page. When you return, completed data is already populated in the grid.
## Recommendations tab
Switch to the **Recommendations** tab for prioritized, page-level actions that Erlin generates based on your analytics data and content signals. Each recommendation includes:
| Field | What it tells you |
| -------------- | --------------------------------------------------------------------------------------------------------------------------------- |
| Page URL | The specific page the recommendation targets |
| Action type | What to do: refresh, merge, differentiate, optimize CTR, improve depth, or optimize CTA |
| Priority score | 0-100 score based on potential impact (higher = more impactful) |
| Description | Plain-language explanation of why this recommendation was generated |
| Signals | The underlying data that triggered it (decay rate, impression trends, position changes, core web vitals, keyword cannibalization) |
**Action types explained**:
* **Refresh**: content is decaying (losing impressions or position). Update and republish.
* **Merge**: multiple pages compete for the same keyword (cannibalization). Combine them into one authoritative page.
* **Differentiate**: pages overlap in topic but are not identical. Sharpen each page's focus so they target distinct queries.
* **Optimize CTR**: the page has impressions but low click-through rate. Improve the title and meta description.
* **Improve depth**: the page ranks but does not satisfy the query fully. Add more comprehensive content.
* **Optimize CTA**: the page gets traffic but does not convert. Improve calls to action.
Click any recommendation row to expand the full description and see the specific signal metrics that triggered it. Use the priority filter pills at the top of the tab to focus on the highest-impact actions first.
## Related
See which of your pages AI currently cites and which third-party sources reference you.
Connect GA4 to populate sessions and engagement data.
Connect GSC to populate clicks and keyword data.
The dashboard that rolls all this data into five metrics.
The metric that measures how often AI cites your own pages.