> For the complete documentation index, see [llms.txt](https://docs.sageseo.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sageseo.ai/getting-started/seo-analytics.md).

# SEO Analytics

If the Performance Dashboard is the **summary**, SEO Analytics is the **deep dive**. This is where you investigate which specific queries are driving traffic, which pages are pulling weight, and which keyword movements explain the shifts you spotted upstream. It's also where the AI Suggestions Engine reads the data from when it generates the next round of content ideas.

All data comes straight from Google Search Console — what you see is exactly what Google reports.

{% hint style="info" %}
**Key Takeaways**

* Two main tables: Top Performing Pages and Top Keywords — both sortable, both live
* Trend charts for impressions and clicks — visualize what's happening over time
* Time-range filters (7d / 1mo / 3mo / 2yr) update everything instantly
* This is the data that powers the AI Suggestions Engine — better insights here = smarter suggestions there
* Use it to validate strategy weekly, diagnose dips immediately, and inform the next batch of articles
  {% endhint %}

## What you see

```mermaid
flowchart TD
  A[SEO Analytics page] --> B[Top Performing Pages table]
  A --> C[Top Keywords table]
  A --> D[Search Impression Trend chart]
  A --> E[Organic Traffic Trend chart]
  B --> F[Click any column to sort: clicks / impressions / CTR / position]
  C --> G[See the queries that are actually driving traffic]
  D --> H[Hover for daily impression counts]
  E --> I[Hover for daily click counts]
  F --> J[Spot which pages need internal links or rewrites]
  G --> K[Spot which queries to write more content for]
  H --> L[Identify ranking wins, algorithm shifts]
  I --> L
  classDef view fill:#F0F6FF,stroke:#0052CC,color:#091E42
  classDef action fill:#E3FCEF,stroke:#006644,color:#091E42
  class A,B,C,D,E view
  class F,G,H,I,J,K,L action
```

### Top Performing Pages table

Sortable table of every indexed URL on the domain:

| Column           | What it shows                                   |
| ---------------- | ----------------------------------------------- |
| **URL**          | The page path                                   |
| **Clicks**       | Total clicks in the selected time range         |
| **Impressions**  | Total times the page appeared in search results |
| **CTR**          | Click-through rate (clicks ÷ impressions)       |
| **Avg position** | Average ranking position (1 = top of page 1)    |

Sort by any column to see different views: clicks-sorted shows revenue-driving pages, impressions-sorted shows high-visibility-but-unclicked pages (a CTR optimization opportunity), position-sorted shows what's ranking well vs poorly.

### Top Keywords table

Same columns, but rows are queries instead of pages:

| Use case                              | How to spot it                                                                                                    |
| ------------------------------------- | ----------------------------------------------------------------------------------------------------------------- |
| **Queries doing all the work**        | Sort by clicks descending — usually 5-10 keywords drive >50% of traffic                                           |
| **Almost-there opportunities**        | Sort by position ascending, filter to positions 5–15 — these are the "one good update away from page one" queries |
| **High-impression / low-CTR queries** | Sort by impressions, look for CTR <2% — title + description rewrite opportunity                                   |
| **New movers**                        | Compare 7-day vs 1-month — keywords climbing rankings need supporting content; keywords falling need triage       |

### Trend charts

Two parallel charts:

* **Search Impression Trend** — how often the site appeared in search results, day by day
* **Organic Traffic Trend** — how often someone actually clicked through, day by day

Hover any point for exact numbers. Spot pattern types:

* **Step changes** = algorithm updates, sitewide technical fixes, big content drops
* **Gradual curves** = content compound interest working (or not working)
* **Sudden cliffs** = manual penalty, server issue, redirect mistake — investigate immediately
* **Seasonal waves** = expected ebb in some niches (B2B Q4 slowdown, ecom Q1 reset)

## How to use the tables

```mermaid
flowchart LR
  A[Open SEO Analytics] --> B{What are you investigating?}
  B -->|Why did traffic dip?| C[Sort Top Keywords by clicks delta]
  B -->|What's working?| D[Sort Top Pages by clicks descending]
  B -->|Where's the upside?| E[Sort Top Keywords by position 5-15]
  B -->|CTR opportunities?| F[Sort Top Pages by impressions, low CTR]
  C --> G[Find the 2-3 queries that dropped]
  D --> H[Replicate format/angle in next articles]
  E --> I[Strengthen content for almost-page-1 keywords]
  F --> J[Rewrite meta titles and descriptions]
  G --> K[Action plan for next week]
  H --> K
  I --> K
  J --> K
  classDef question fill:#F0F6FF,stroke:#0052CC,color:#091E42
  classDef analysis fill:#EAE6FF,stroke:#6554C0,color:#091E42
  classDef action fill:#E3FCEF,stroke:#006644,color:#091E42
  class A,B question
  class C,D,E,F,G,H,I,J analysis
  class K action
```

The pattern: **what are you investigating?** drives the **sort + filter** combination, which drives the **action plan**. SEO Analytics is the tool; the action is always content (write more, rewrite something, optimize titles).

## How this feeds the AI Suggestions Engine

Every time you request fresh AI suggestions for a domain, Sage reads from this same SEO data to inform the suggestions. Specifically:

1. **Almost-there queries** (positions 5-20) become candidate article topics — these are the keywords with proven demand where the client can credibly rank with the right content
2. **High-performing pages** become templates — the AI looks at what's working and suggests similar topics
3. **Content gaps** (queries the client ranks for poorly relative to competitors) become opportunity suggestions

This is why the better your SEO data, the better Sage's suggestions get. Old/stale GSC data = generic suggestions. Fresh, well-categorized data = targeted, high-upside suggestions.

## Time-range filters

| Range             | Best for                                        |
| ----------------- | ----------------------------------------------- |
| **Last 7 days**   | Recent shifts, catching new ranking movements   |
| **Last month**    | Standard weekly review window                   |
| **Last 3 months** | Quarterly performance, content compound effects |
| **Last 2 years**  | Long-term trends, year-over-year comparison     |

All metrics on the page update in place when you switch ranges — no full-page reload.

## When to use SEO Analytics

* **Weekly client review** — sort top keywords by position changes to see recent movements
* **Diagnosing a traffic dip** — first stop after spotting it on the Performance Dashboard
* **Identifying content opportunities** — find queries ranking 5-15 that need a strengthening pass
* **CTR optimization** — find pages with high impressions but low CTR (meta title + description rewrites)
* **Validating strategy** — confirm that the articles you've published are showing up where you expected

## Frequently asked questions

### Why don't I see all my queries?

Google Search Console hides queries with very low impression counts (privacy threshold). You'll see anything that gets at least a few dozen impressions in the selected time range; ultra-long-tail queries get aggregated into the "anonymized queries" bucket that GSC doesn't expose individually.

### Why does Google show me a different number than this dashboard?

You should see the same numbers as Google Search Console for the same date range. If there's a discrepancy, it's almost always a timezone difference or a date-range mismatch — Sage's "Last 7 days" is the rolling 7 days as of last GSC refresh, which may differ from GSC's "Last 7 days" by a few hours.

### Can I export this data?

Direct CSV export is on the roadmap. Until then, GSC's UI has full export — Sage doesn't duplicate that.

### How does this feed back into AI suggestions?

See "How this feeds the AI Suggestions Engine" above. The short version: this data is the input to the next batch of suggestions, so investing time investigating here pays dividends in suggestion quality.

### What's the difference between "Top Performing Pages" and "Top Keywords"?

* **Pages** — sorted by URL. Tells you which content is doing the work.
* **Keywords** — sorted by query. Tells you which searches are driving the work.

Both views are useful; they answer different questions. A page can rank for multiple keywords; a keyword can drive traffic to multiple pages.

## Related

* [Domain Performance Dashboard](/getting-started/dashboard.md) — the summary view; this is the drill-in
* [Google Index Status](/getting-started/google-index.md) — what Google has actually indexed for this domain
* [AI Content Suggestions Engine](/getting-started/content-calendar.md) — where SEO Analytics data turns into article ideas
* [How Sage Writes an Article](/reference/article-pipeline.md) — how Sage uses keywords from GSC during generation