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Strings to Things - The move to Semantic SEO - MozCon 2013

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My presentation at MozCon 2013 - I go into the latest information from Google, Bing and Yahoo and what tools to use to align SEO strategy with where the search engines are headed.

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Strings to Things - The move to Semantic SEO - MozCon 2013

  1. 1. Strings to Things: The Move to Semantic SEO by Matthew Brown – Moz #MozCon @MatthewJBrown
  2. 2. The 2011 me was a different SEO
  3. 3. 3 The rise of Panda
  4. 4. The writing was on the wall
  5. 5. Adios, Keyword-based site architecture RIP: Industrial-Strength “Query SEO”
  6. 6. Semantic SEO: The Pitch The market corrected
  7. 7. 7 The solution? Use the semantic web!
  8. 8. 8 Entity-based SEO to increase relevancy
  9. 9. 9 Turns out that‟s where Google was headed
  10. 10. “Search is dramatically changing right before our eyes” Amit Singhal Google I/O 2013 Source: Flickr: JD Hancock
  11. 11. “This is our flagship product used by billions of people, and yet we‟re saying it‟s changing fundamentally.” Jason Douglas Knowledge Graph Product Manager Google I/O 2013 http://bit.ly/17WMS1G
  12. 12. Desktop PC sales: Freefall
  13. 13. 13 Mobile. (source: http://slidesha.re/11aymBx)
  14. 14. 14Or rather, Mobile ARPU (source: http://slidesha.re/11aymBx)
  15. 15. “The end of search as we know it?”
  16. 16. 16 Source: Flickr: David Masters SEO is NOT dead
  17. 17. 17 Source: LinkedData.org Links aren‟t going anywhere
  18. 18. 18 Truth: The best SEOs make a lot of bets Source: Flickr: SLGCKGC
  19. 19. Are sites implementing structured data? Markup Percent of URLs Open graph 36.9% schema.org 9.9% G+ publisher 7.1% G+ author 2.2% And it‟s still plenty early to make this bet…
  20. 20. How to level up in semantic SEO Source: Flickr: Rob Boudon
  21. 21. Step 1: What problem are the engines trying to solve? #MozCon @MatthewJBrown
  22. 22. Entity extraction from web documents http://bit.ly/17WMS1G
  23. 23. Co-reference and the WikiLinks Corpus Reading List: UMass Wikilinks Project - SEO by the Sea - Google Research
  24. 24. It‟s easy to extract entities from this.
  25. 25. This? Not so much.
  26. 26. Search engines need to do this at web scale http://bit.ly/17WMS1G
  27. 27. We see this in their presentations http://bit.ly/17WMS1G
  28. 28. We see this in the evolution of Schema.org
  29. 29. We see this in “conversational search”
  30. 30. We see this in Bing Research http://bit.ly/LxwYgh
  31. 31. And they‟re carefully measuring intent http://slidesha.re/17mS0OM
  32. 32. Step 2: Freebase (and other tools) #MozCon @MatthewJBrown
  33. 33. Freebase presentation from Google I/O http://bit.ly/YZt6C4
  34. 34. Using the Freebase API to get ranked entities http://bit.ly/12aetM0
  35. 35. Using the Freebase API to roll your own http://bit.ly/13sg2aW
  36. 36. Google‟s tilde search operator?
  37. 37. Entity search from Bing http://explicit.bing.net/entities/search?q=adidas
  38. 38. Bottlenose www.bottlenose.com
  39. 39. Yahoo Glimmer http://glimmer.research.yahoo.com
  40. 40. Fresh Web Explorer http://freshwebexplorer.moz.com/
  41. 41. RelFinder http://www.visualdataweb.org/relfinder.php
  42. 42. Step 3: Target the entity long tail #MozCon @MatthewJBrown
  43. 43. Avoid targeting Entity-based SERPs like this
  44. 44. Find the longer tail entity-based queries
  45. 45. Use Freebase and social tools to map entities
  46. 46. 46 „Entity KW‟ stuffing will not look natural
  47. 47. Create a semantic content model http://bit.ly/11drfnY This is where you add Freebase and other semantic tools
  48. 48. 48 Step 4: Profit?!?! Source: Flickr: Rob Boudon
  49. 49. @MatthewJBrown

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