Key Takeaways

1. Content Audit Process:

   • Organize your database (crawl, content, metrics)
   • Understand the data (categorize your inventory)
   • Evaluate performance and assign action items
   • Organize your deliverable (prioritized recommendations)

2. Data Collection and Organization:

   • Crawl and scrape content efficiently, especially for large sites
   • Map important performance metrics (user engagement, traffic, search data)
   • Include custom metrics for deeper insights

3. Data Understanding and Categorization:

   • Use ML APIs for content classification (e.g., Google's Natural Language API)
   • Implement topic modeling techniques like LDA or BERTopic for subtopic identification
   • Utilize entity recognition for mapping entities to topics

4. Content Evaluation:

   • Automate checks for content helpfulness and EEAT (Expertise, Experience, Authoritativeness, Trustworthiness)
   • Implement semantic analysis for better content understanding
   • Use custom metrics like keyword density, entity density, and topic relevance

5. Performance Evaluation and Action Items:

   • Create a system of if/else logic for consistent evaluation
   • Assign action items and responsible persons/departments for each assessment
   • Utilize tools like Looker Studio for visualizations and Zapier for automations

6. Deliverable Organization:

   • Create immediately actionable, extensive, and insightful reports
   • Contextualize findings for multiple stakeholder groups
   • Include downloadable lists with all relevant data, actions, and roles

Action Items

1. Implement ML APIs:

   • Set up Google's Natural Language API for content classification
   • Explore topic modeling techniques like LDA or BERTopic
   • Implement entity recognition for improved content understanding

2. Enhance Data Collection:

   • Review and optimize crawling processes, especially for large sites
   • Expand metric collection to include custom and advanced metrics

3. Develop Automated Checks:

   • Create a checklist of best practices for content evaluation
   • Translate checklist items into if/else statements and code
   • Implement automated checks for EEAT factors where possible

4. Improve Semantic Analysis:

   • Develop custom metrics for keyword density, entity density, and topic relevance
   • Implement tools like KeyBert for query-content matching

5. Set Up Visualization Tools:

   • Create Looker Studio dashboards for ongoing content performance monitoring
   • Use Zapier to set up automated notifications for underperforming content

6. Refine Deliverable Format:

   • Review and optimize audit report structure for actionability and stakeholder relevance
   • Include clear sections on importance, responsible parties, and downloadable action lists

7. Continuous Improvement:

   • Aim to make the auditing process 1% better with each iteration
   • Explore advanced techniques like SERP analysis, competitor content audits, and cross-platform opportunity analysis

8. Upskill in ML for SEO:

   • Explore resources at MLforSEO.com for further learning and templates

Remember: The goal is to create a better, quicker audit process through automation and machine learning, while ensuring the output remains actionable and valuable for all stakeholders.

For more information:

• Website: www.mlforseo.com
• Academy: academy.mlforseo.com
• Twitter: @lazarinastoy
• Resources: lazarinastoy.com/resources/conference-decks-and-presentations/