SEO Ranking Factors Insights
I attended the SEO Ranking Factors session at this year’s SMX West, enjoying the panelists’ presentations on their experiences and ideas.
The discussion of ranking factors often stirs emotions and controversy, and this session was no exception. It’s crucial to approach this information with caution: none of the data is fully conclusive and should be taken with a grain of salt.
Olga Andrienko of SEMrush
Olga Andrienko presented her company’s recent ranking factors study, examining top 100 positions across 600,000 keywords, segmented by competitiveness. Unlike traditional correlation studies, SEMrush used a machine learning model called Random Forest. This model uses random dataset sampling to build decision trees and averages the results across samples. It provides better fits for training data but carries a risk of "overfitting." The study focused on several on-page factors, including links and traffic.
Key Insights from Olga’s Presentation:
- Keywords in Title Tags: The study found keywords in title tags in only 35% of pages analyzed, with much higher usage in competitive keywords.
- Keyword-Rich Anchor Text: Usage of keyword-rich anchor text is infrequent in high-ranking content, even for high-volume terms. This suggests a decrease in link spamming.
- Content Length: Despite discussions on shorter content for mobile, longer content appears to help with rankings.
- Page Speed: Higher-ranking pages generally load faster, as indicated by charts on "time to first meaningful paint."
- Links: Links remain significant in determining webpage ranks, with a notable peak in the number two ranking position across all keyword groups.
Marcus Tober of Searchmetrics
Marcus Tober highlighted two main points: the potential harm of ranking studies to the search industry and the need for industry-specific ranking analyses.
- Harmful Ranking Studies: Blindly applying study implications can be harmful since faster pages, for instance, don’t necessarily drive rankings but indicate importance in ranking well.
- Industry-Specific Analyses: Using microdata to compare different segments like dating, recipes, and divorce, Marcus revealed the variance across market sectors. Recipes show high microdata usage due to structured data advantages.
Chanelle Harbin, Disney/ABC Television Group
Chanelle Harbin shared several real-world case studies from her experience.
- Structured Data Implementation: Implementing VideoObject schema and exposing closed captioning to search engines significantly increased visits and page views.
- Featured Snippets: Securing featured snippets yielded notable traffic increases for phrases like “Beyoncé guacamole recipe.”
- Link Building: Basic strategies such as converting mentions to links and fixing broken ones resulted in stellar outcomes.
Conclusion
The session provided valuable insights into ranking factors and industry trends. While not every piece of information is a direct ranking factor, there are actionable insights applicable to your website and business strategy.
