2013 Search Ranking Factors by Matthew Peters

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From SMX East 2013 #SMX #13B - What are the most important search ranking factors by @mattthemathman

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2013 Search Ranking Factors by Matthew Peters

  1. 1. SEARCH RANKING FACTORS 2013 # Matthew Peters Moz @MattTheMathMan #SMX #13B October 1, 2013 #
  2. 2. @mattthemathman Lead Data Scientist at Moz Data science is responsible for all of Moz’s metrics: Page/Domain/Social Authortity, etc.
  3. 3. @mattthemathman Different feature types include: On-page, links, anchor text, social signals and properties of the URL URL www.mrqe.com
  4. 4. @mattthemathman Different feature types include: On-page, links, anchor text, social signals and properties of the URL On-page
  5. 5. @mattthemathman Different feature types include: On-page, links, anchor text, social signals and properties of the URL Links
  6. 6. @mattthemathman Different feature types include: On-page, links, anchor text, social signals and properties of the URL “movie reviews” Anchor Text
  7. 7. @mattthemathman Different feature types include: On-page, links, anchor text, social signals and properties of the URL “movie reviews” Anchor Text Social
  8. 8. @mattthemathman Which factors are important? What Google says
  9. 9. @mattthemathman Which factors are important? What’s in the algorithmWhat Google says
  10. 10. @mattthemathman Which factors are important? What’s in the algorithmWhat Google says What SEOs say
  11. 11. @mattthemathman Which factors are important? What’s in the algorithmWhat Google says What SEOs say Characteristics of sites that rank well
  12. 12. @mattthemathman Survey Thanks to everyone who participated and Cyrus Shepard and Matt Brown for organizing 120 professional SEOs surveyed in mid-June 2013
  13. 13. @mattthemathman Survey
  14. 14. @mattthemathman Survey
  15. 15. @mattthemathman Correlations • 14,000+ keywords from Google Adwords, all categories/search volumes • Top 50 de-personalized, de-localized results from Google US • Mean Spearman Correlation – compute for each keyword then average • Measures extent to which increases in one factor are related to rank • Correlations between -1 and 1. Values of 0.1 - 0.3 are common.
  16. 16. @mattthemathman "Correlation is not causation but it sure is a hint" - Edward Tufte Links Correlation and causation Higher rank ??
  17. 17. @mattthemathman "Correlation is not causation but it sure is a hint" - Edward Tufte Links Correlation and causation Higher rank
  18. 18. @mattthemathman "Correlation is not causation but it sure is a hint" - Edward Tufte Links Higher rank Correlation and causation Correlation, but causation? Higher rank More words on page ??
  19. 19. @mattthemathman "Correlation is not causation but it sure is a hint" - Edward Tufte Links Higher rank Correlation and causation Correlation, but causation? Higher rank Higher quality More words on page ??
  20. 20. @mattthemathman "Correlation is not causation but it sure is a hint" - Edward Tufte Links Higher rank Correlation and causation Correlation, but causation? Higher rank Higher quality More words on page Links ??
  21. 21. @mattthemathman "Correlation is not causation but it sure is a hint" - Edward Tufte Links Higher rank Correlation and causation Correlation, but causation? Higher rank Higher quality More words on page Links
  22. 22. @mattthemathman Survey: Overall
  23. 23. @mattthemathman Survey: Links
  24. 24. @mattthemathman Correlations: Links Overall PA our highest correlated factor. Page link correlations higher then domain.
  25. 25. @mattthemathman Correlations: Anchor Text Partial and exact match have same correlation. Internal anchor text correlations significantly lower then external.
  26. 26. @mattthemathman Survey: On-page keyword usage
  27. 27. @mattthemathman Correlations: On-page keyword usage
  28. 28. @mattthemathman Relevance vs Ranking See http://moz.com/blog/determining-relevance-how-similarity-is-scored
  29. 29. @mattthemathman Relevance vs Ranking Relevance See http://moz.com/blog/determining-relevance-how-similarity-is-scored
  30. 30. @mattthemathman Relevance vs Ranking Relevance Ranking 1 2 See http://moz.com/blog/determining-relevance-how-similarity-is-scored
  31. 31. @mattthemathman Survey: On-page Keyword Agnostic
  32. 32. @mattthemathman Correlations: Site speed Zoompf to provided the speed data. Response time has negative correlation, but total load time does not! See: http://moz.com/blog/how-website-speed-actually-impacts-search-ranking
  33. 33. @mattthemathman Speed and Users Jonathon Colman: http://www.slideshare.net/jcolman/seo-site-speed-and-battlestar-galactica-searchfest-2012-11735155 • 40% of customers will abandon any site that takes longer than 3 seconds to load • Conversion rate drops by 7% for every 1 second of load time
  34. 34. @mattthemathman Survey: Brand metrics
  35. 35. @mattthemathman Correlations: Brand metrics
  36. 36. @mattthemathman Correlations: Brand metrics
  37. 37. @mattthemathman Survey: Exact/partial match domain
  38. 38. @mattthemathman Correlations: EMD/PMD Query: “adidas sneakers” Exact Match Domain (EMD): www.adidassneakers.com Partial Match Domain (PMD): www.adidas.com
  39. 39. @mattthemathman Exact match domain over time
  40. 40. @mattthemathman Exact match domain over time
  41. 41. @mattthemathman Exact match domain over time
  42. 42. @mattthemathman Exact match domain over time
  43. 43. @mattthemathman Exact match domain over time Removal of low quality EMDs??
  44. 44. @mattthemathman Survey: Social
  45. 45. @mattthemathman Correlations: Social Google +1’s second highest correlation metric (behind PA)!
  46. 46. @mattthemathman Correlations: Social, 2013 vs 2011
  47. 47. @mattthemathman +1’s are not used in ranking Similar to Facebook Shares, Google +1’s are not used in ranking: Matt Cutts: https://news.ycombinator.com/item?id=6243451
  48. 48. @mattthemathman Google+ provides SEO benefits Followed links, relevant anchor text, priority crawling Cyrus Shepard: http://moz.com/blog/google-plus-correlations
  49. 49. @mattthemathman Correlation vs Causation revisited Higher rank Higher quality More +1’s, Shares or Tweets Links
  50. 50. @mattthemathman Multivariate correlations Spearman correlations between links and social shares Page level links and social shares are correlated
  51. 51. @mattthemathman Partial correlations Partial correlations controlling for links, anchor text, keyword usage A simple linear model with a handful of factors removes much of the social correlation with search position.
  52. 52. @mattthemathman Overall algorithm Link factors still very important, followed by on-page page. SEO’s don’t think Social important, but it has high correlation.
  53. 53. @mattthemathman 1. Quality, authorship, structured data, social all predicted to increase in importance. Future predictions
  54. 54. @mattthemathman 1. Quality, authorship, structured data, social all predicted to increase in importance. 1. EMD, paid links, anchor text expected to decrease. Future predictions
  55. 55. @mattthemathman Final caution
  56. 56. Thanks for watching! Matthew Peters matt@moz.com @mattthemathman 56
  57. 57. http://www.slideshare.net/SearchMarketingExpo # see more presentations at: # 57

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