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. 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
- 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
Editor's Notes
- ENTITY EXTRACTION – DISAMBIGUATION ENTITIES OUT OF QUERIES – IF THEY CAN’T DISAMBIGUATE, THEY CAN’T SERVE SEMANTIC RESULTSTHEY’VE GOT TO BE ABLE TO RECOGNIZE THERE IS AN ENTITY IN THERE. DEEPER QUERIES WITH MULTIPLE ENTITIES PRESENT TOUGHER QUERY CHALLENGESEXISTING DATA SETS NOW THAT HAVE BEEN THE BACKBONE COMPILED BY HUMANS (WIKIPEDIA, DBPEDIA, WORDNET, FREEBASE). SUMMARIZE DATA AND LOOKUPS. SCHEMA IS A SHORTCUT TO A DIFFICULT DISAMBIGUATION CHALLENGE.