Gianluca Fiorelli's presentation at The Inbounder New York, May 22 2017.

2. GIANLUCA FIORELLI
@gfiorelli1 #theinbounder
THE ALPHABET
OF GOOGLE

3. Let me start
with a
question
gfiorelli1 #theinbounder

4. What does any SEO
usually think when
asked about Google?
gfiorelli1 #theinbounder

9. gfiorelli1 #theinbounder
SHAME
gfiorelli1 #theinbounder

11. gfiorelli1 #theinbounder
The usual suspects
(nothing personal but…)

12. Inside Search Blog
Office Hours Videos
Virtual & not Talks
Patents/Papers Acquisitions
Rumors
Propaganda
Fandom
New
Employees

13. APP Indexing
Rich Cards
Real time
Indexing
API
Webmaster Blog
Interstitial
AMP Series
Reviews in
Local KGraph
New AMP
Tester
More Https
PWA
Mobile
1st
Rich Cards
New Mobile
Friendly Test API
UGC
Spam
Crawl Budget
Google Safe
Browsing’s
Site Status
#Nohacked
Similar
Item
How We Fought
Webspam

14. APP Indexing
Rich Cards
Interstitial
AMP Series New AMP
Tester
PWA
Mobile
1st
Rich Cards
New Mobile
Friendly Test API
May 2016 –
January 2017
MOBILE
MOBILE
MOBILE
Webmaster Blog

15. Real time
Indexing
API
Reviews in
Local KGraph
More Https
UGC
Spam
Crawl Budget
Google Safe
Browsing’s
Site Status
#Nohacked
Similar
Item
How We Fought
Webspam
Webmaster Blog

16. Research
Blog
More than 40 posts in
5 months (more than
the Webmaster Blog)
Only one topic
gfiorelli1 #theinbounder

17. PatentsSentence Compression Patent
Associating an Entity With a Search Query
Methods & Systems For Classifying Data Using a Hierarchical Taxonomy
Ranking Events
User-Context-Based Search Engine
Recommended News On Map With Geo Entities
Will Google Start Giving People Social Media Influencer Scores?
How Google May Rank Websites Based Upon Their Databases Answering Queries
Google’s Related QuestionsPatent or ‘People Also Ask’ Questions
Ranking Local BusinessesBased Upon Quality Measures including Travel Time
Google May Check to See if People Go to Geographic Locations Google May Recommend
Google Introduces a Social Where Next Suggestion Patent
Google Search Query Refinements Patent Updated
Google and Spoken Queries: Understanding Stressed Pronouns
A New Search Results Evaluation Model from Google
Answering Featured Snippets Timely, Using Sentence Compression on News
Google Patents Context Vectors to Improve Search
How Google May Respond to Reverse Engineering of Spam Detection
How Google May Map a Query to an Entity for Suggestions gfiorelli1 #theinbounder
http://www.seobythesea.com/

18. Sentence Compression Patent
Associating an Entity With a Search Query
Methods & Systems For Classifying Data Using a Hierarchical Taxonomy
Ranking Events
User-Context-Based Search Engine
Recommended News On Map With Geo Entities
Will Google Start Giving People Social Media Influencer Scores?
How Google May Rank Websites Based Upon Their Databases Answering Queries
Google’s Related Questions Patent or ‘People Also Ask’ Questions
Ranking Local Businesses Based Upon Quality Measures including Travel Time
Google May Check to See if People Go to Geographic Locations Google May Recommend
Google Introduces a Social Where Next Suggestion Patent
Google Search Query Refinements Patent Updated
Google and Spoken Queries: Understanding Stressed Pronouns
A New Search Results Evaluation Model from Google
Answering Featured Snippets Timely, Using Sentence Compression on News
Google Patents Context Vectors to Improve Search
How Google May Respond to Reverse Engineering of Spam Detection
How Google May Map a Query to an Entity for Suggestions
gfiorelli1 #theinbounder
http://www.seobythesea.com/
Entity Search
Voice Search
Informational Retrieval
Local Search / Geolocalization
Search User Experience
Patents

19. Learning from User Interactions in Personal Search via Attribute Parameterization
Related Event Discovery
Situational Context for Ranking in Personal Search
Improving topic clustering on search queries with word co-occurrence and
bipartite graph co-clustering
Incorporating Clicks, Attention and Satisfaction into a Search Engine
Result Page Evaluation Model
Large-Scale Analysis of Viewing Behavior: Towards Measuring Satisfaction with
Mobile Proactive Systems
Learning for Efficient Supervised Query Expansion via Two-stage Feature Selection
Learning to Rank with Selection Bias in Personal Search
M3A: Model, MetaModel, and Anomaly Detection in Web Searches
Using Machine Learning to Improve the Email Experience
Wide & Deep Learning for Recommender Systems
gfiorelli1 #theinbounder
Papers - Information Retrieval

20. Learning from User Interactions in Personal Search via Attribute Parameterization
Related Event Discovery
Situational Context for Ranking in Personal Search
Improving topic clustering on search queries with word co-occurrence and bipartite
graph co-clustering
Incorporating Clicks, Attention and Satisfaction into a Search Engine Result Page
Evaluation Model
Large-Scale Analysis of Viewing Behavior: Towards Measuring Satisfaction with
Mobile Proactive Systems
Learning for Efficient Supervised Query Expansion via Two-stage Feature Selection
Learning to Rank with Selection Bias in Personal Search
M3A: Model, MetaModel, and Anomaly Detection in Web Searches
Using Machine Learning to Improve the Email Experience
Wide & Deep Learning for Recommender Systems gfiorelli1 #theinbounder
Machine Learning
Context
Personal Search
Search User Experience
Papers - Information Retrieval

21. gfiorelli1 #theinbounder
Generating Long and Diverse Responses with Neural Conversation Models
Language Modeling in the Era of Abundant Data
Multilingual Metaphor Processing: Experiments with Semi-Supervised
and Unsupervised Learning
A Piggyback System for Joint Entity Mention Detection and Linking in
Web Queries
Collective Entity Resolution with Multi-Focal Attention
Conversational Contextual Cues: The Case of Personalization and
History for Response Ranking
Exploring the Steps of Verb Phrase Ellipsis
Papers - Natural Language
Processing

22. gfiorelli1 #theinbounder
About 45 Papers in just 1 year!
Generating Long and Diverse Responses with Neural Conversation Models
Language Modeling in the Era of Abundant Data
Multilingual Metaphor Processing: Experiments with Semi-Supervised and Unsupervised
Learning
A Piggyback System for Joint Entity Mention Detection and Linking in Web Queries
Collective Entity Resolution with Multi-Focal Attention
Conversational Contextual Cues: The Case of Personalization and History for Response
Ranking
Exploring the Steps of Verb Phrase Ellipsis
Entity Search Context
Rhetoric Personalization
Search User Experience
Papers - Natural Language
Processing

23. WebPass
Moodstock
Anvato
Kifi
Launch
Kit
Orbitera
Apigee
Eyefluence
AcquisitionsUrban
Engine
API.ai
Famebit
Kaggle

24. gfiorelli1 #theinbounder
Images
Video
Video Influencers
APP Link Sharing &
Recommendations
Local &
Geolocalization
AI
Chatbots
Vocal Search &
Natural Language
ML & Datasets
Entity Search
Collaborative Coding
API

25. ProductsGoogle Assistant
DayDream VR
Google Home
GBoard
Google Lens

27. Search User Experience
Search User Optimization
TECHNICAL SEO
HTTP/2
Mobile First
AMP / PWA
SEO as MARKETING
Video & Images
Local
Semantic Search

28. UNDERSTANDING
INFORMATION RETRIEVAL
FILTERING & CLUSTERING
RANKING
PAINTING
P
A
R
S
I
N
G
I
N
D
E
X
I
N
G
C
R
A
W
L
I
N
G

29. UNDERSTANDING
INFO RETRIEVAL
FILTERING &
CLUSTERING
RANKING
PAINTING
P
A
R
S
I
N
G
I
N
D
E
X
I
N
G
C
R
A
W
L
I
N
G
ML
NO
ML

30. MOBILE
FIRST
HTTP/2
AMP
PWA

31. MOBILE
FIRST

33. MOBILE
FIRST
CHECKLIST

34. #1
Check Mobile Agent / Client
Handling

35. #2
Follow the RAIL Model
https://developers.google.com/web/fundamentals/performance/rail

36. #3
Structured Data for Rich Cards on a
Domain and Page Level
https://youtu.be/B0BA7Tswavs

37. Page Level
https://youtu.be/B0BA7Tswavs

38. Domain Level
https://youtu.be/B0BA7Tswavs

39. #4
Beware the URL Hierarchy >
Hreflang!!

40. #5
Review Content UX to avoid higher
bounce rate
https://youtu.be/DIGfwUt53nI

41. #6
Review Customer Journey UX with
mobile tests

42. SPEED

44. SPEEDCHECKLIST

45. #1
Speed > Go for HTTP/2
Multiplexed resources Browser to Server
Prioritized by type & context Keep-Alive by default
https://developers.google.com/web/fundamentals/performance/http2/

46. #2
Speed Front-End with Image
Spriting

47. #3
Tag Handling - Use Tag Assistant
extension for Chrome
http://itseo.org/tagasstnt

48. #4
Use JSON-LD for Structured Data
https://moz.com/blog/using-google-tag-manager-to-dynamically-generate-
schema-org-json-ld-tags

49. #6
Service Workers (for solving the no-
connection issue)

50. CONTEXT

53. CONTEXT

56. Thinking of local search only as
MyBusiness optimization may limit the
opportunities businesses can have to
earn SEO visibility and traffic.

57. GBoard
CONTEXT

58. CONTEXT

59. PARSING

60. SEMANTICS

61. @gfiorelli1

62. @gfiorelli1

66. @gfiorelli1

67. Personalized
Search

70. @gfiorelli1

71. @gfiorelli1

72. PARSING
UNDERSTANDING
RELEVANCY
QUALITY

73. Video &
Images

74. My sons’ hero

75. 1.The average age kids start owning
a smartphone is 10.3 years;
2.Children from 5 to 13 years old
(and also young people up to 20
years old) tend to me more visual
than textual;
3.Their influence on the buying
habits of their parents has been
known for many years and, in 2012,
it was equal to $1.2 trillion USD in
spending.

78. Similar items:
Rich products feature on
Google Image Search

79. Google Lens

81. https://www.google.com/intl/en/about/

87. http://safecont.com/

90. Generic but non trivial knowledge all all
marketing disciplines
T
E
C
H
N
I
C
A
L
M
A
R
K
E
T
E
R
S

95. https://research.google.com/teams/nlu/

97. Buyer
Persona
KW
Research
Top 10
Ranking Sites
* Query
Intention
Entity
Recognition
via CNL API
Thesaurus
Creation