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All lessons in Technical SEO Auditing Lesson 11.2 of 84

Module 1: Introduction to Technical SEO Auditing

  1. 1.1What Is a Technical SEO Audit?
  2. 1.2Technical SEO Audit vs. General SEO Audit
  3. 1.3When Should You Audit a Website?
  4. 1.4Types of Technical SEO Issues
  5. 1.5Defining Audit Scope and Objectives

Module 2: Website Crawling and URL Discovery

  1. 2.1How SEO Crawlers Discover URLs
  2. 2.2Configuring a Website Crawl
  3. 2.3Crawl Scope, Limits, and Exclusions
  4. 2.4Internal Links and Crawl Depth
  5. 2.5Orphan Pages and URL Discovery
  6. 2.6Crawl Data vs. Search Engine Data
  7. 2.7Identifying Crawl Coverage Gaps

Module 3: HTTP Status Codes and Redirect Auditing

  1. 3.1Understanding HTTP Status Codes
  2. 3.2Finding 4xx Errors and Broken Links
  3. 3.3Identifying 5xx Server Errors
  4. 3.4Redirect Chains and Redirect Loops
  5. 3.5Internal Links to Redirected URLs
  6. 3.6301 vs. 302 Redirects
  7. 3.7Auditing 404 Pages and Soft 404s

Module 4: Crawlability and Indexability Auditing

  1. 4.1Crawling vs. Indexing
  2. 4.2Robots.txt Audit
  3. 4.3Meta Robots and X-Robots-Tag
  4. 4.4Noindex and Canonical Conflicts
  5. 4.5XML Sitemap Validation
  6. 4.6Canonical URL Auditing
  7. 4.7Identifying Indexability Conflicts
  8. 4.8Comparing Crawl Data with Google Search Console

Module 5: URL Structure and Duplicate Content Issues

  1. 5.1URL Structure and Normalization
  2. 5.2Duplicate URLs and Duplicate Pages
  3. 5.3HTTP vs. HTTPS and Hostname Variations
  4. 5.4Trailing Slashes and URL Parameters
  5. 5.5Pagination and Faceted Navigation
  6. 5.6Canonicalization Strategies
  7. 5.7Internal Linking to Preferred URLs

Module 6: Technical On-Page Auditing

  1. 6.1Missing and Duplicate Title Tags
  2. 6.2Missing and Duplicate Meta Descriptions
  3. 6.3Missing, Duplicate, and Multiple H1 Headings
  4. 6.4Heading Hierarchy and HTML Structure
  5. 6.5Missing Image Alt Attributes
  6. 6.6Internal Link and Anchor Text Issues
  7. 6.7Empty, Thin, and Near-Duplicate Pages
  8. 6.8Auditing HTML Metadata at Scale

Module 7: Website Performance and Core Web Vitals

  1. 7.1Core Web Vitals: LCP, INP, and CLS
  2. 7.2Lab Data vs. Field Data
  3. 7.3Identifying Slow Pages
  4. 7.4Image and Resource Optimization Opportunities
  5. 7.5JavaScript and CSS Performance
  6. 7.6Mobile Usability and Responsive Rendering
  7. 7.7Prioritizing Performance Fixes

Module 8: JavaScript SEO and Rendering

  1. 8.1How Search Engines Process JavaScript
  2. 8.2HTML Source vs. Rendered HTML
  3. 8.3Client-Side vs. Server-Side Rendering
  4. 8.4JavaScript-Generated Content and Links
  5. 8.5Rendering Failures and Missing Content
  6. 8.6Lazy Loading and Crawl Accessibility
  7. 8.7Diagnosing JavaScript SEO Problems

Module 9: Structured Data and Schema Auditing

  1. 9.1Structured Data and Schema.org Basics
  2. 9.2JSON-LD and Structured Data Formats
  3. 9.3Finding Structured Data Across a Website
  4. 9.4Detecting Invalid or Incomplete Markup
  5. 9.5Schema Validation and Rich Result Eligibility
  6. 9.6Conflicting or Duplicate Structured Data
  7. 9.7Prioritizing Schema Fixes

Module 10: Analyzing Audit Data and Prioritizing Issues

  1. 10.1Reading Crawl Reports and Exports
  2. 10.2Grouping URLs by Issue Type
  3. 10.3Identifying Root Causes vs. Symptoms
  4. 10.4Evaluating Severity, Impact, and Effort
  5. 10.5Separating Sitewide and Isolated Issues
  6. 10.6Identifying False Positives
  7. 10.7Building an Actionable Issue Register

Module 11: Technical SEO Audit Reporting

  1. 11.1Structuring a Technical SEO Audit Report
  2. 11.2Documenting Evidence and Affected URLs
  3. 11.3Writing Developer-Ready Recommendations
  4. 11.4Mapping Issues to Business and Search Impact
  5. 11.5Creating a Prioritized Remediation Roadmap
  6. 11.6Presenting Findings to Stakeholders
  7. 11.7Tracking Fixes and Ownership

Module 12: Fix Verification and Technical QA

  1. 12.1Re-Crawling After Fixes
  2. 12.2Comparing Before-and-After Crawl Results
  3. 12.3Verifying Redirects, Canonicals, and Indexability
  4. 12.4Detecting Regressions and Newly Introduced Issues
  5. 12.5Testing Website Changes Before Deployment
  6. 12.6Confirming Fixes with Search Console and Other Evidence
  7. 12.7Closing Audit Findings and Recording Results

Documenting Evidence and Affected URLs

This lesson covers

  • What counts as strong evidence
  • How many example URLs to include
  • How to capture screenshots and code snippets
  • How to deliver full affected URL lists

Short answer

Strong audit evidence lets anyone reproduce a finding. For each issue, include three to five example URLs, a screenshot or code snippet showing the problem, supporting Search Console or analytics data, the date checked, and a link to the full affected URL list. Evidence turns opinions into facts developers can verify and act on.

“Your canonicals are wrong” starts an argument. “Here are four product URLs, the canonical tag from each page’s source, and Search Console showing Google chose a different canonical, checked on October 21” ends it.

Five pieces of evidence per finding

  1. Example URLs: 3 to 5 representative pages.
  2. What you saw: an annotated screenshot or a code snippet.
  3. Google’s view: URL Inspection, Pages report, or Crawl Stats.
  4. Scale: affected count and a link to the full URL list.
  5. Date and method: when, with which tool and settings.

Code snippets beat descriptions

Found on https://www.example.ph/rooms/deluxe/:

<link rel="canonical" href="http://example.ph/rooms/deluxe">

One snippet shows protocol, host, and trailing slash problems at once. Always write the source URL as a caption above the snippet, so readers know exactly where it came from.

Organizing URL lists

  • One tab or CSV per finding, named with the issue ID (IDX-03.csv).
  • Include useful columns: URL, page type, status, the problem value, clicks.
  • Keep them in a shared folder linked from the report.

Practice: strong or weak evidence?

Sort each item into the right group.

  • 'Many pages have issues'

  • 4 example URLs plus their canonical tags from source

  • URL Inspection showing Google-selected canonical

  • Unannotated screenshot of a whole tool dashboard

  • Linked CSV of all 312 affected URLs

Common mistakes

  • No examples, only counts.
  • Evidence from a logged-in browser.
  • No date, so later readers cannot tell if it is still true.
1. How many example URLs per finding?
2. Why include Google's data?
3. What helps developers reproduce an issue?

Your action

Next, you will write developer-ready recommendations.

Key terms

Reproducible evidence
Evidence detailed enough for someone else to see the same problem by following the same steps.
Example URLs
A small, representative sample of affected pages listed in the finding.
Code snippet
The relevant lines of HTML or headers showing the issue, such as a wrong canonical tag.
Affected URL list
The complete export of URLs with the issue, delivered as a linked file or tab.

Questions beginners ask

How many example URLs should I include?

Three to five, covering the main variations. Link the full list separately.

Why include the date checked?

Sites change. A date shows when the evidence was true and helps when the issue is fixed or reappears.

Should I annotate screenshots?

Yes. Circle or highlight the exact problem so readers do not have to search.

What if the developer cannot reproduce it?

Share exact steps: user agent, tool settings, and the URL Inspection result. Many disagreements come from testing in a logged-in browser.

Related lessons

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