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.

1. Strings to Things: The Move to Semantic SEO
by Matthew Brown – Moz
#MozCon @MatthewJBrown

2. The 2011 me was a different SEO

3. 3
The rise of Panda

4. The writing was on the wall

5. Adios, Keyword-based site architecture
RIP: Industrial-Strength “Query SEO”

6. Semantic SEO: The Pitch
The market corrected

7. 7
The solution? Use the semantic web!

8. 8
Entity-based SEO to increase relevancy

9. 9
Turns out that‟s where Google was headed

10. “Search is dramatically changing right before
our eyes”
Amit Singhal
Google I/O 2013
Source: Flickr: JD Hancock

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. Desktop PC sales: Freefall

13. 13 Mobile. (source: http://slidesha.re/11aymBx)

14. 14Or rather, Mobile ARPU (source: http://slidesha.re/11aymBx)

15. “The end of search as we know it?”

16. 16
Source: Flickr: David Masters
SEO is NOT dead

17. 17 Source: LinkedData.org
Links aren‟t going anywhere

18. 18
Truth: The best SEOs make a lot of bets
Source: Flickr: SLGCKGC

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. How to level up in semantic SEO
Source: Flickr: Rob Boudon

21. Step 1: What problem are the engines trying
to solve?
#MozCon @MatthewJBrown

22. Entity extraction from web documents
http://bit.ly/17WMS1G

23. Co-reference and the WikiLinks Corpus
Reading List: UMass Wikilinks Project - SEO by the Sea - Google Research

24. It‟s easy to extract entities from this.

25. This? Not so much.

26. Search engines need to do this at web scale
http://bit.ly/17WMS1G

27. We see this in their presentations
http://bit.ly/17WMS1G

28. We see this in the evolution of Schema.org

29. We see this in “conversational search”

30. We see this in Bing Research
http://bit.ly/LxwYgh

31. And they‟re carefully measuring intent
http://slidesha.re/17mS0OM

32. Step 2: Freebase (and other tools)
#MozCon @MatthewJBrown

33. Freebase presentation from Google I/O
http://bit.ly/YZt6C4

34. Using the Freebase API to get ranked entities
http://bit.ly/12aetM0

35. Using the Freebase API to roll your own
http://bit.ly/13sg2aW

36. Google‟s tilde search operator?

37. Entity search from Bing
http://explicit.bing.net/entities/search?q=adidas

38. Bottlenose
www.bottlenose.com

39. Yahoo Glimmer
http://glimmer.research.yahoo.com

40. Fresh Web Explorer
http://freshwebexplorer.moz.com/

41. RelFinder
http://www.visualdataweb.org/relfinder.php

42. Step 3: Target the entity long tail
#MozCon @MatthewJBrown

43. Avoid targeting Entity-based SERPs like this

44. Find the longer tail entity-based queries

45. Use Freebase and social tools to map entities

46. 46
„Entity KW‟ stuffing will not look natural

47. Create a semantic content model
http://bit.ly/11drfnY
This is where you
add Freebase and
other semantic tools

48. 48
Step 4: Profit?!?!
Source: Flickr: Rob Boudon

49. @MatthewJBrown