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Search Console Performance: Metrics, Filters, and SEO Decisions

検索アナリティクス(Search Console)の使い方|指標の見方と改善活用法

Published: 06/23/2026

Last Updated: 10/11/2026

Category: Web Analytics

Authors: Shusaku Yosa

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Search Console Performance reports show how your site appears in Google Search and receives clicks. If you know the older name Search Analytics, start with the current search-results report. Understand the metrics and connect query evidence to a specific page before proposing an editorial change. This guide follows official documentation checked on October 11, 2026.

Find Search Analytics in the current Performance report

Choose the intended property and open the search-results Performance report. Check dates, search type, comparisons, and existing filters. A site-wide increase is not automatically an improvement for an individual article.

Keep Web, Image, and other search types distinct. Record any additional Web subdivisions available in your interface. For article analysis, fix the precise URL, including language, before comparing results.

Read clicks, impressions, CTR, and average position

Metric

Interpretation

Important limit

Clicks

Measured actions from results to the site

Not GA4 sessions or registrations

Impressions

Measured appearances in results

Visibility rules vary by result format

CTR

Clicks divided by impressions

Use matching numerator and denominator

Average position

Average recorded position for the included impressions

Not a fixed current rank for every searcher

Google’s impression and position definitions depend on result format and presentation. Do not assume that every listed result always counts without scrolling. Position reflects the relevant topmost result under the site or page aggregation being used.

The fictional table below illustrates weighting. Combined CTR is 14 divided by 1,000, or 1.4%, not the simple average of 1% and 5%. If the rows share the same position definition, their weighted position is (900 × 10 + 100 × 50) divided by 1,000, or 14. Check aggregation before applying this to real exports.

Row

Impressions

Clicks

CTR

Average position

A

900

9

1%

10

B

100

5

5%

50

Matching aggregation

1,000

14

1.4%

14

Link query evidence to a filtered page

  1. Record dates, search type, country, device, and other conditions.
  2. Select the intended URL in Pages or set an exact page filter.
  3. Keep the page filter active while opening Queries.
  4. Save visible queries and their metrics with the associated URL.
  5. Check remaining filters before changing page or language.

A query in the site-wide table does not prove that a particular article appeared for it. Follow the grouping and filtering guidance and inspect page-filtered queries. Some data is attributed to canonical URLs, so investigate canonicalization when similar URLs appear.

Use regex, country, device, and search-type filters

Search Console regex filters use RE2 syntax and are normally case-insensitive. Consult the documented syntax if case matters. Test expected matches and nonmatches before relying on a complex expression.

Fictional purpose

Expression

Check

Select a guides directory

^https://www[.]example[.]com/guides/

Anchored prefix; confirm host and language scope

Find either topic term

analytics|measurement

Partial matches, not necessarily entire queries

Match only guide

^guide$

Anchors exclude longer phrases

Change one comparison condition at a time. A shift toward mobile impressions can affect aggregate CTR or position even without a direct editorial effect. Mixing language URLs or changing search type midway makes the comparison harder to interpret.

Turn performance patterns into testable hypotheses

Observation

Alternative explanation

Next check

More impressions, few clicks

Query intent, rank, or device mix changed

Inspect page-specific queries and answer relevance

Lower CTR

More impressions occurred at lower positions

Compare similar queries and device conditions

Changed average position

The impression mix changed

Track relevant page-query combinations

No visible row

Period, anonymization, row limits, or aggregation

Check current indexing separately

Do not adopt a universal position cutoff for clicks or promise that a title edit will raise CTR. Compare visible intent with the page’s answer, then propose a clearer introduction, comparison, or worked example. Keep technical conditions and changing search demand among the possible explanations.

Compare changes while accounting for data and attribution limits

Record the edit date, equal-length before-and-after periods, fixed URLs and languages, search type, country, device, and filters. Seasonality and other changes prevent a simple difference from establishing that the rewrite caused it. With small counts, report actual impressions, clicks, and the number of pages receiving impressions before emphasizing percentage growth.

Document anonymization and row limitations using Search Console data guidance and export guidance. Visible query totals may differ from page totals; do not infer hidden terms. Report visible site: searches separately without treating subtraction as a complete general-search total.

Search Console daily data uses Pacific time, whereas GA4 uses its property reporting timezone. Search clicks and GA4 organic landing sessions also differ in definition, collection, and consent conditions. Their difference is not a calculated abandonment or registration rate. Evaluate registrations only after verifying success conditions, duplicates, production hosts, and authentication or app handoffs; otherwise mark the outcome unmeasured.

Continue with the relevant guide

  • Google SEO Basics: Launch Checks and Your First Improvements
  • How to Improve Search Rankings: Diagnose the Cause Before You Rewrite
  • How to Find Traffic Sources in GA4: Source, Medium, and Scope

 

 

 

 

Table of Contents

  1. Find Search Analytics in the current Performance report
  2. Read clicks, impressions, CTR, and average position
  3. Link query evidence to a filtered page
  4. Use regex, country, device, and search-type filters
  5. Turn performance patterns into testable hypotheses
  6. Compare changes while accounting for data and attribution limits

 

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