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Hummingbird unleashed. Understanding the new Google Search Algorithm
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Hummingbird unleashed. Understanding the new Google Search Algorithm


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How does Hummingbird work? We cannot tell it and very few has been explicitly told about it by Amit Singhal and others Google spokespersons. …

How does Hummingbird work? We cannot tell it and very few has been explicitly told about it by Amit Singhal and others Google spokespersons.
But we can reasonably try to figure out the basis of its functioning and, therefore, understand how SEO is definitively changed.

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  • 1. Hummingbird Unleashed Sugges&ng  a  new  SEO  methodology   Gianluca Fiorelli - @gfiorelli1 Global  Associate  
  • 2. Hummingbird is a complete rewrite of our search system
  • 3. It’s not me saying it, it’s this guy
  • 4. Before talking about
  • 5. we should talk about
  • 6. and
  • 7. Caffeine   Panda   Penguin   Because a logic in the Google Updates sequence exists
  • 8. The mobile revolution forced us to change how we think
  • 9. Mobile may overtake desktop for Google searches within a year (SMXW 2014) It’s not me saying it, it’s this guy
  • 10. Do you remember when Google what showing us “searches similar to…” in the SERPs?
  • 11. Usually it was for queries like: “The best way of cooking a pizza with antichokes in a electric oven”
  • 12. (Long) Long Tails Verbose Queries
  • 13. (Long) Long Tails Verbose Queries
  • 14. Hummingbird =/ Humminguin
  • 15. How Hummingbird (possibly) works
  • 16. To take synonyms and Knowledge Graph and other things
  • 17. It’s not me saying it, it’s (again) this guy
  • 18. SYNONYMS
  • 19. Google is dealing with them since a long time
  • 20. Read  this  post  by  Vanessa  Fox  on  Search  Engine  Land:  hDp://     Keyphrases don’t need to be in their original form. We do a lot of synonym work, so we can find good pages that don’t happen to use the same words a the user typed (Matt Cutts)
  • 21. The issue is that a word can be a synonym or not depending on the Context Coche Automóvil Carro
  • 22. That Contest was the problem was clear since the beginning, as we can understand reading this patent by Amit Singhal: The issue is that a word can be a synonym or not depending on the Context
  • 23. Hummingbird is how Google solves the Contest issue, thanks to Search Entities and Semantics Search Entities:
  • 24. Search Entities • A query a searcher submits; • The documents responsive to the query; • The search session during which the searcher submits the query; • The time at which the query is submitted; • Advertisements presented in response to the query; • Anchor text in a link in a document; • The domain associated with a document. Suggested read: this post by Bill Slawski
  • 25. Words =/ Things
  • 26. Words = Verbal Representation of Things
  • 27. Google transforms Words into Concepts thanks to Search Entities
  • 28. And Concepts can be disambiguated over the base of their Context
  • 29. This is what Google already started to do with Knowledge Graph
  • 30. BEWARE! SEMANTIC SEO =/ SCHEMA.ORG is instrumental to Semantic, it’s not SEMANTIC
  • 31. OTHERS THINGS… I suspect that the third factor are co- occurrences
  • 32. Consequences
  • 33. Google understands better the queries and their intentions
  • 34. Google may expand the number of documents that respond significantly to a query
  • 35. If verbose query A = simplier query C and If verbose query B = simplier query C and similar to verbose query A then I’ll show just the SERPs answering to query C
  • 36. Tl;dr: Simpyfing the queries, Google also reduces the number of unnecessary SERPs
  • 37. And that’s good also in term of Adwords…
  • 38. What about links? Won’t they be an essential factor anymore?
  • 39. Links are clearly an important signal about the importance of your content. They’re still very valuable
  • 40. It’s not me saying it, it’s (again!) this guy
  • 41. From theory to practice. For a new model of SEO
  • 42. Mario has a small pizzerias’ chain in NYC
  • 43. He has only a very small difficulty
  • 44. The old way (not considering Local Search) 1) Pizzeria Tribeca; 2) Best pizzeria in NoLiTa; 3) Calzone Theater District; 4) Pizza Special Chelsea; 5) Where to eat the best pizza in Manhattan 6) etc etc
  • 45. #FAIL (not provided)
  • 46. #FAIL Penguin (monster)
  • 47. #FAIL Bounce Rate (tons of it)
  • 48. #FAIL Hummingbird (killing the long tail)
  • 49. Il Nuovo Metodo We identify the Entities related to our niche and how they are connected We match them with our Audience interests We creat Content Architecture based on Content Hub using Ontology We conducts a Keywords Research and Mapping with Entities in mind
  • 50. Entities identification Freebase APIs:
  • 51. Entities identification Yahoo Glimmer:
  • 52. Entities identification Bottlenose:
  • 53. Entities identification RelFinder:
  • 54. Audience Matching Read this:
  • 55. Audience Matching (audience personas) Followerwonk first
  • 56. Audience Matching (audience personas) And after we use Tribalytics:
  • 57. Ontology & Taxonomy Read twice this deck by Abby Covert:
  • 58. Ontology & Taxonomy (based on Entities Search and Audience Matching Pizza Thin Thick Regular crust Organic Rossa Bianca Napoletana Romana
  • 59. Content Hub Creation Home Tribeca Our Stories From the oven People of Tribeca Why we love Tribeca SOCIAL
  • 60. From Content Strategy to Content Marketing Recipes > > Rich Snippets Recipes > Video Marketing > VideoObject > Rich Snippets Infografics – Data Visualization – Charts (passive link building opportunities) Guides > Long Form > Authorship > In-Depth Articles UGC Q&A
  • 61. Protip – Newsjacking & Unconventional Marketing as a Plus
  • 62. Keyword Research based on Entities Much more ideas in this post by Dan Shure:
  • 63. And if someone tells you that SEO is dead…