How To Interpret SEO Correlation Studies ft. Erika Varangouli

In episode 129, Erika Varangouli shares the time, effort, and marketing discussions that went into Semrush's 2023 Ranking Factors study. Too often, uninformed SEOs will use statistics from these correlation studies and use them to serve their own agendas despite them not proving causation. Erika argues that the data still has value to inform and guide us. We can apply the insights to hypotheses and experiments to our own websites without using it purely as a prescriptive playbook.

She explains why the team landed on a study called 'Ranking Factors' and used their own metrics quantified as 'Content Quality.'

Resources: Semrush 2023 Ranking Factors Study - https://www.semrush.com/blog/ranking-factors-semrush-study/

[0:00] Intro

[1:30] The Semrush Ranking Factors Study - What is it?

[3:20] The methodology to address the correlation implications.

[6:20] How should SEOs remain skeptical yet find value in these SEO correlation studies?

[10:15] Highlighting limitations and the nature of correlation.

[12:20] How did you decide on the controversial title and the marketing of the study? The metrics created behind 'content quality.'

[19:45] Big insights and takeaways from the Ranking Factors Study

[22:00] What's your take on SGE and GenAI based on the study's findings?

[26:30] Do you think Brand recognition should trump content quality in search rankings?

[30:05] Rapid Fire Rankings