Jan, who hails from a background in physics, has been able to successfully prove a number of his own personal theories about the inner workings of Google's Hummingbird algorithm and how its has evolved in the months since its launch. During these 45 minutes you will be informed how you can build a better website in the eyes of the search engine's most recent major update. Patents, publications and announcements over the past five years can all be used to your advantage.

1. Taming the Hummingbird
Performance Marketing Insights Berlin, 2014
Jan-Willem Bobbink - @jbobbink
#PMIEUR http://bit.ly/pmi-hummingbird

2. WHO SAW IT COMING?

3. ALGORITHM UPDATE

4. “ACCORDING TO GOOGLE, THIS
NEW ALGORITHM IMPACTS 90%
OF ALL QUERIES”
90% OF
ALL SEARCH QUERIES!

6. GOOGLE STARTED USING
HUMMINGBIRD ABOUT A
MONTH AGO, IT SAID. GOOGLE
ONLY ANNOUNCED TODAY.
ADJUSTMENTS WERE ALREADY
LIVE FOR MULTIPLE WEEKS

8. Performance Marketing Insights Berlin, 2014

13. Director of SEO @ Acronym Media – Blogging at www.notprovided.eu

14. WHAT CHANGED?

16. WHY SO MUCH
CONFUSION?

17. Back to the basics

22. CONVERSATIONAL SEARCH
EVEN MORE AWESOME!

26. That’s the knowledge graph!

27. "Hummingbird is focused more on ranking
information based on a more intelligent
understanding of search requests, unlike its
predecessor, Caffeine, which was targeted at
better indexing of websites."
GOOGLE:
“TRY TO UNDERSTAND” RELATIONS

29. WHAT IS THE DIFFERENCE?

30. REWRITING THE QUERIES

31. HOW ABOUT ORGANIC RESULTS?
[how old is the president of the United States, Barack Obama]
Biography is not in the query!

32. HOW ABOUT ORGANIC RESULTS?
[age obama]

33. Keyword based!?
[age obama]
RESULTING IN MORE RELEVANT SERPS
Semantically, related phrases will be those that
are commonly used to discuss or describe a
given topic or concept, such as “President of
the United States” and “White House.”

34. MONITOR SEO PATENTS

35. FIFA, ARE YOU WATCHING?

36. SEO PATENTS, NOT ONLY FOR THE NERDS!
- Learn from the past
- Predict future changes
- Get an idea about the inner working of search
engines
- Get an idea what certain features take to exist
WHAT CAN YOU LEARN FROM PATENTS?

37. PREDECESSOR - 2004
PHRASE-BASED VS SINGLE KEYWORDS

38. KEYWORD BASED SCORING
“A document is retrieved in response
to a query containing a number of
query terms, typically based on
having some number of query
terms present in the document.”

39. Google research has shown that on more difficult queries, people start to type their
searches as natural language questions. They also searched longer queries on average. This
study also stated that, at the time of the study (2010), most of the time the question
queries failed to give users the information they were looking for and they would revert
back to keyword queries.
WHY DEVELOP HUMMINGBIRD?

40. DISTRIBUTION OF WEB SEARCH QUERIES
[Lin et al. 2011]

41. THE HUMMINGBIRD PATENT?
REVISING SEARCH QUERIES
http://www.google.com/patents/US8538984

42. IT’S ALL ABOUT CONCEPTS
“The goal is that pages matching the
meaning do better, rather than pages
matching just a few words.”

43. CAR VERSUS AUTO

44. CAR VERSUS AUTO

45. FULL QUESTION NOT NEEDED

46. Already filed by Google in 2005
DETERMINING QUERY TERM SYNONYMS
WITHIN QUERY CONTEXT
http://www.google.com/patents/US7636714

48. HOW IS THE KNOWLEDGE GRAPH WORKING?

49. HOW ABOUT SCALE?
-YAGO: 10 million entities and 120 million facts
-Freebase: 37 million topics, 1,998 types, and more than 30,000
properties
- DBpedia: 3.77 million things, 2.35 million classified in Ontology,
including:
- 764,000 persons, 573,000 places,
- 333,000 creative works, 192,000 organizations,
- 202,000 species and 5,500 diseases.
-111 languages, together 20.8 million things
Source: WSDM’14 conference, http://ejmeij.github.io/entity-linking-and-retrieval-tutorial/

50. INTERNATIONAL DIFFERENCES
CURRENT STATUS

51. GOOGLE.DE (GERMAN)

52. GOOGLE.ES (SPANISH)

53. GOOGLE.NL (DUTCH)

54. KNOWLEDGE GRAPH LOCALISED?
German
Spanish
Dutch

55. GOOGLE.DE (GERMAN)

56. GOOGLE.NL (DUTCH)

57. PRERENDERED QUERIES?

58. HOW CAN YOU DEAL
WITH HUMMINGBIRD?
AS AN AFFILIATE?

59. HUMMINGBIRD MYTHS

60. GOOGLE KNOWS WHAT QUALITY IS

61. ADD MORE TEXT TO YOUR PAGES

62. LITERALLY ADD MORE QUESTIONS & ANSWERS

63. TEXTS IN THE FORM OF QUESTIONS

64. PUT MORE FOCUS ON LONGTAIL!

66. OK, LETS TURN IT AROUND

67. SRC: Searchmetrics.com 2014 US Ranking factors study

68. DETERMINE TARGET AUDIENCE

69. DEFINE INTENTION PER PERSONA

70. BUILD ENTITY SPECIFIC PAGES
Using natural and semantically rich language:
Use entities in copy: 5 facts you have to
know about Jan-Willem Bobbink being in
Berlin at Performance marketing Insights
Entity attributes: 1987, Utrecht, SEO, Acronym, Physics etc.
So start with attribute stuffing instead of
keyword stuffing

71. ORGANISE YOUR PAGES TOPICALLY

72. ENTITY BASED KEYWORD RESEARCH

74. GENERATE SYNONYM LISTS

75. http://www.performancemarketinginsights.com/14/europe/agenda/2/
SRC: http://www.alchemyapi.com/

76. Use Google’s Freebase API
https://developers.google.com/freebase/

77. RELATE CONTENT TO ENTITY
SRC: http://www.blindfiveyearold.com/knowledge-graph-optimization

78. sameAS EXAMPLE

79. GET LINKS FROM
SEMANTICALLY RELEVANT SOURCES
http://semantic-link.com/#/berlin

80. FILL FREEBASE WITH RELEVANT INFORMATION

81. Google may present better SERPs also in terms
of better ads
FROM ADVERTISING PERSPECTIVE

82. How to get in their?

83. HOW DOES GOOGLE
DECIDE ON SOURCE?
SRC: Bill Slawski
http://www.seobythesea.com/2013/05/google-knowledge-graph-results/

84. HOW TO DEAL WITH KNOWLEDGE GRAPH?

85. NO PATTERN FOUND YET

86. GOOGLE GETTING YOUR TRAFFIC?

88. https://class.coursera.org/nlangp-001
https://www.coursera.org/course/nlp

89. PDF: HTTP://NLP.STANFORD.EDU/IR-
BOOK/PDF/IRBOOKPRINT.PDF
If you are interested in Natural language processing, read it:
AN INTRODUCTION TO
INFORMATION RETRIEVAL

90. WANT TO KNOW MORE ABOUT
ENTITY RETRIEVAL AND LINKING?
http://ejmeij.github.io/entity-linking-and-retrieval-tutorial/

92. Questions?
Don’t hesitate to ask! Or find me at the bar 
http://bit.ly/pmi-hummingbird & @jbobbink

93. Image Credits
Thanks for the images!
http://community.qlik.com/blogs/theqlikviewblog/2013/02/21/visualizations-the-tip-of-the-iceberg-of-
understanding
http://asset5.instanthumour.com/wp-content/uploads/2013/11/is-google-boy-or-girl-2.jpg
https://encrypted-
tbn2.gstatic.com/images?q=tbn:ANd9GcQovn4u6HtBbDB6uceJQLk7WyBNvRFKQLt2lYxF3gy94HRzosYG
Images: http://img3.wikia.nocookie.net/__cb20130815124007/transformers-legends/images/c/c4/Triple-
facepalm.jpg
http://www.verticalresponse.com/blog/how-to-find-your-target-market/
http://footage.shutterstock.com/clip-2399522-stock-footage-reading-a-book-or-bible.html
http://www.searchengineguide.com/matt-bailey/keyword-strategies-the-long-tail.php
Europe: http://www.ezilon.com/maps/images/Europe-physical-map.gif
Devices: http://www.google.com/insidesearch/features/search/assets/img/devices-preview.png
Postcard: https://plus.google.com/u/0/+AmitSinghal/posts/AtndBA1pzNg
Entity: http://www.entitythemovie.com/gallery
Cutts meme: http://www.jacobking.com/affiliate-link-cloaking