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All lessons in Technical SEO Auditing Lesson 10.1 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

Reading Crawl Reports and Exports

What we will go through

  • What crawl overviews and issue reports show
  • Which export columns matter for analysis
  • How to join crawl, Search Console, and analytics data
  • How to set up a clean working spreadsheet

Short answer

Crawl reports summarize issues, but analysis happens in exports. Export all internal HTML URLs with status, indexability, canonical, titles, depth, inlinks, word count, and Search Console clicks and impressions. Filter to the URLs that matter, join other data sources by URL, add a page type column, and keep raw exports untouched in a separate sheet.

Modules 2 to 9 taught you how to find issues. Module 10 teaches you to make sense of them. It starts with turning a crawl into a spreadsheet you can actually analyze.

Reports vs. exports

  • Overview and Issues reports tell you what the tool noticed and roughly how many URLs.
  • Exports let you ask why, where, and how much it matters.

The columns that matter

From Internal, HTML, keep:

  • Address, Status Code, Indexability, Indexability Status
  • Canonical Link Element, Meta Robots
  • Title, Meta Description, H1 (with lengths and counts)
  • Crawl Depth, Unique Inlinks, Word Count
  • Response Time
  • Search Console Clicks, Impressions (if connected)
  • Analytics Sessions or Conversions (if connected)

Drop columns you will not use. Fewer columns, clearer thinking.

Build the working sheet

  1. Raw tab: paste the untouched export.
  2. Working tab: copy, then filter to HTML URLs on the in-scope host.
  3. Add a page type column from URL folders.
  4. Join other data by URL: Search Console Pages reasons, sitemap presence, backlink counts.
  5. Add issue columns (TRUE/FALSE) for checks like “duplicate title” or “non-200 inlinks.”

Practice: keep or drop this column?

Sort each item into the right group.

  • Indexability Status

  • Search Console Impressions

  • Content-Type for HTML pages

  • Unique Inlinks

  • Hash of the response body

Common mistakes

  • Copying the tool’s issue list into the report as is.
  • Editing raw exports. You lose the original.
  • Not joining traffic data. Impact cannot be judged without it.
1. What is the main difference between a report and an export?
2. What column is usually the join key?
3. Why keep a raw tab?

Your action

Next, you will group URLs by issue type.

Key terms

Crawl overview
A summary dashboard of URL counts, response codes, and issues found in a crawl.
Issues report
A crawler's list of detected problems, often with priority labels and affected URL counts.
Bulk export
A CSV or spreadsheet export of URLs and their data, or of relationships like inlinks.
Join key
The shared column, usually the URL, used to combine data from different tools.

Questions beginners ask

Should I trust the crawler's issue priorities?

Use them as a starting point. Tools do not know your business, traffic, or intended index states, so you rank issues yourself.

Which export is most useful?

Internal HTML with all columns, plus link exports for inlinks. Most analysis starts there.

Why keep raw exports separate?

So you can always trace back to the original data and redo analysis if a filter or formula was wrong.

Spreadsheet or database?

Spreadsheets work for most sites under 100,000 URLs. Larger sites benefit from BigQuery, Python, or Looker Studio.

Related lessons

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