Google's Hummingbird update was a major rewrite of its search algorithm focused on understanding search queries through entities and relationships rather than just keywords. This has implications for e-commerce sites, which should optimize to be recognized as entities, build relationships between products and categories, and focus on answering queries through in-depth content rather than just keywords. They also need to optimize for voice and mobile search through measures like prioritizing local search results and ensuring their content is accessible across devices.

1. Hummingbird Proof
How Conversational based search is set to shape
eCommerce in a post Hummingbird World
eCommerce SEO Planning

2. @KunleTCampbell
What was Hummingbird all about?
“A Major Change in the Way Google Interprets or
Rewrites Long, Complex Search Queries”

3. @KunleTCampbell
What was
Hummingbird all
about?
…it was a rewrite of
Google’s Entire Search
Engine or Algorithm for
voice and mobile search
…biggest ever since 2000
–
Amit Singhal

4. @KunleTCampbell
“…a new engine built on
both existing and new
parts, organized in a way
to especially serve the
search demands of today
(from mobiles), rather than
ten years ago”
What was
Hummingbird all
about?

5. @KunleTCampbell
The Translation of a Search Query
Google Search Timeline
EMD

6. @KunleTCampbell
What was
Hummingbird all
about?
Precision & Speed of a
Hummingbird

7. @KunleTCampbell
What was Hummingbird all about?
Precision
& Speed
“answer your questions about the world”
- Tamar Yehoshua, VP, Search
Answers
Queries
Knowledge
Graph
Conversational
Queries
Voice
Search
Anticipate
Queries
Google Now
follow up
context queries

8. @KunleTCampbell
Entities
Classes
Micro-data
schema.org
Freebase
Object Oriented Approach
metawebThings
Nodes & Edges
(in Facebook) Wikipedia data
Labeled data
Semantic network
Topic modeling
Sets of topics
Resource Description Framework (RDF)
Understanding of THINGS not just STRINGS
Answers
Queries
topics
Knowledge
Graph

9. @KunleTCampbell
Remember relational databases?
Understanding ENTITIES and RELATIONSHIP
between entities
Knowledge
Graph

10. @KunleTCampbell
Understanding ENTITIES and RELATIONSHIP
between entities
Knowledge
Graph

11. @KunleTCampbell
Understanding ENTITIES and RELATIONSHIP
between entities
actionSubject Object
has aENTITY PROPERTY
Knowledge
Graph

12. @KunleTCampbell
Context of a Query rather than String Match
Information Card
A major change in
the way Google
Interprets the way
we Search
Knowledge
Graph

13. @KunleTCampbell
Context of a Query rather than String Match
Information
Card
Knowledge
Graph

14. @KunleTCampbell
Context of a Query rather than String Match
Knowledge
Graph

15. @KunleTCampbell
Context of a Query rather than String Match
Knowledge
Graph

16. @KunleTCampbell
Context of a Query rather than String Match
Knowledge
Graph

17. @KunleTCampbell
Context of a Query rather than String Match
Knowledge
Graph

18. @KunleTCampbell
Answer
Cards
Knowledge
Graph

19. @KunleTCampbell
Is Google not a
scraper site?
No…a search engine like
Google is ‘an amazing Swiss
Army Knife’ ;)
h#ps://www.youtube.com/watch?v=HViSQjZxhnY

20. @KunleTCampbell
Knowledge Graph is Not Perfect…
Vs

21. @KunleTCampbell
Conversational‘Voice’Search
“…someday, having to pull out a cell phone
from your pocket and search would feel as
archaic as a dial-up modem”
- Amit Singhal
– Head of Google’s Core Ranking Team
Conversational
Queries
Voice
Search

22. @KunleTCampbell
Conversational Queries…
Algo rewrite…for conversational search from: mobile
devices and wearable tech i.e. ‘google glass’
Conversational
Queries
Voice
Search

23. @KunleTCampbell
Search used to be about
using queries that hopefully
matched content that was
out there…
Conversational Queries…
Search today is also
about asking complex
questions in a conversational
format with the hope of
getting a direct answer ?
Conversational
Queries
Voice
Search

24. @KunleTCampbell
Talk to Google…
Siri Google Now Cortana
Conversational
Queries
Voice
Search

25. @KunleTCampbell
Hot-wording Google
“Okay Google”
Conversational
Queries
Voice
Search

26. @KunleTCampbell
Google is also teaching us a new set of commands
Read
more:
h#p://bit.ly/PQg3zq
Conversational
Queries
Voice
Search

27. @KunleTCampbell
As we learn these commands, Google might
better Anticipate our follow up Queries...
Anticipate
Queries
Google Now
follow up
context queries

28. @KunleTCampbell
Query Reviser Re-Writing Engine Based on
Identifying ENTITIES and the SYNONYM ENGINE...
Anticipate
Queries
Google Now
follow up
context queries
via:
h#p://www.seobythesea.com/2013/09/google-­‐hummingbird-­‐patent/
SYNONYM IDENTIFICATION
BASED ON CO-OCCURRING
TERMS
United States Patent: 8,538,984
Filled on: September 17, 2013
Assignee: Google Inc.
(Mountain View, CA)
http://1.usa.gov/1i900HL

29. @KunleTCampbell
The Vast and Ever Expanding Size of Knowledge Graph and
the Semantic Web is Constantly Improving Query Re-Writing
Anticipate
Queries
Google Now
follow up
context queries
via:
h#p://www.seobythesea.com/2013/09/google-­‐hummingbird-­‐patent/
SEARCH QUERIES IMPROVED
BASED ON QUERY SEMANTIC
INFORMATION
United States Patent: 8,577,907
Filled on: November 5, 2013
Assignee: Google Inc.
(Mountain View, CA)
http://1.usa.gov/1nosfFP

30. @KunleTCampbell
Anticipate
Queries
Google Now
follow up
context queries
The Vast and Ever Expanding Size of Knowledge Graph and
the Semantic Web is Constantly Improving Query Re-Writing

31. @KunleTCampbell
Advances with Google Now, shows
Google’s Ambitious long-term goal
of progressing from a search engine
to an ubiquitous artificial-
intelligence answer machine
Anticipate
Queries
Google Now
follow up
context queries

32. @KunleTCampbell
How Should e-Tailers
Prepare for the Impending
Change?

33. @KunleTCampbell
Understand
the Context
of a Query

34. @KunleTCampbell
User Data from Query logs
Here’s How Google Attempts to Understand the‘Layers
of Context’in a Query
Search Entity information – Knowledge Graph
has 570 million objects with data on 18 billion+
relationships
Clicks and CTR history on SERPs
Co-occurrences of words within
queries and query sessions
Queries and query refinements with a
query session
Location and device cues
Was the search via Voice or typed in?

35. @KunleTCampbell
Here’s How Google Attempts to Understand the‘Layers of
Context’in a Query
“A search query for a search engine may be
improved by incorporating alternate terms into the
search query that are semantically similar to terms
of the search query, taking into account information
derived from the search query.”
- U.S. Patent 8,577,907 Abstract
Search queries improved based on query semantic information
http://1.usa.gov/1nosfFP

36. @KunleTCampbell
“the context for a particular query term included at the
beginning of the search query may be defined by a
query term located at the end of the search query”
Co-occurrences of words within queries and
query sessions
SYNONYM IDENTIFICATION BASED ON CO-OCCURRING TERMS
United States Patent: 8,538,984
September 17, 2013
Assignee: Google Inc. (Mountain View, CA)
http://1.usa.gov/1i900HL
where can I buy a playstation 4

37. @KunleTCampbell
Mobile OR Desktop?
Local business OR on an e-Tailer?
Context might be different…
Co-occurrences of words within queries and
query sessions
The defining query
where can I buy a playstation 4

38. @KunleTCampbell
Non local Results from
a mobile device
“where can I buy a playstation 4”
eCommerce AND article results

39. @KunleTCampbell
Query String Match
Results from a
mobile device
“where can I buy a playstation 4 in oxford”

40. @KunleTCampbell
Search from a mobile
device
“where can I buy coffee”
Prominent Local results

41. @KunleTCampbell
Search from a desktop
on Google.com
“where can I buy coffee”
Prominent Local results

42. @KunleTCampbell
Strive to
become an
ENTITY

43. @KunleTCampbell
Work on Your Brand Until it Earns the Right
to Become a Global‘Entity’

44. @KunleTCampbell
Which means striving to ethically earn a
Wikipedia Page

45. @KunleTCampbell
Which Gets You Into Freebase

46. @KunleTCampbell
Understand
the Context
of a Query
And an
Answer
Card…
You also get to
become an entity in
your retail niche!
It is not just the preserve of the‘big boys’

47. @KunleTCampbell
Don’t GAME Wikipedia
From the Wiki page of
a prominent UK and
Global Fashion

48. @KunleTCampbell
Understand
How ENTITY
ATTRIBUTES
Influence
Rankings

49. @KunleTCampbell
Don’t Just List your Retail Business on
Wikipedia; ensure that it is in the right
category and that it has as many
schema attributes are completed

50. @KunleTCampbell
Complete
Schema
Profile

51. @KunleTCampbell
Check Out
Amazon’s Freebase
Listing to see how
detailed Attributes
can get
Also Check out
Google’s Freebase
Listing
http://www.freebase.com/m/045c7b
http://www.freebase.com/m/0mgkg

52. @KunleTCampbell
A UK e-tailer that Deserves a Wikipedia Page
Listed on the AIM

53. @KunleTCampbell
No Information Card or Knowledge Graph Data…

54. @KunleTCampbell
Build
RELATIONSHIPS
with other
ENTITIES
On Freebase

55. @KunleTCampbell
Added as Supplier’s
of ASOS
On
Freebase
Added as ASOS as
‘Major Customer’
On
Freebase

56. @KunleTCampbell
Build ENTITIES
within your
Store with
Marked-Up
Data

57. @KunleTCampbell
Avoid Keyword Cannibalisation
URL Singularity Is Key
Especially on Category and Product Pages
Rethink the excessive use of tag pages
What THING does your Category Page
Represent?
Mark-up Product & Category pages
with Schema.org, Microformats, Open
Graph

58. @KunleTCampbell
With Schema.org – Go Over and Beyond mark-up
Required by Google
http://schema.org/Product
Also consider the
data highlighter
tool to help
establish entities

59. @KunleTCampbell
Establish Connections between ENTITIES with
HYPERLINKS
http://schema.org/Product
Ensure URL
Singularity to
maximum potential
Internal-link
building 101

60. @KunleTCampbell
Optimise Product and Category Pages for Open Graph
and the Social Web
Social Media
Markups are
essential

61. @KunleTCampbell
Multichannel
Retailers
should take
their Local
Presence
Seriously

62. @KunleTCampbell
A UK e-tailer that Deserves a Wikipedia Page

63. @KunleTCampbell
BUT saved by their Google+ and Google Places
Presence…
Most recent
Google+ Post
Google Local
Other Local
Related Entities

64. @KunleTCampbell
Multichannel
Retailers Tend to
have a more
competitive edge
due to their High
Street Local
Presence
Contextual
Alternatives
powered by Local
Search

65. @KunleTCampbell
Be Prepared
and Ready for
the Mobile
Web
think beyond a
Responsive
Website

66. @KunleTCampbell
If Google Changed its Engine in
preparation for voice and mobile
search, prepare for the storm
ahead by going
mobile

67. @KunleTCampbell
Check the growth and share of
mobile traffic and study your
Multi-Device Attribution
i.e. with Universal Analytics
+
+

68. @KunleTCampbell
Google is striving to become an
Answers’Engine – rather than a
Search Engine
with is gear to cover any and every
computing device
+
+
servers, mobile phones, tablet computers, notebook computers, music players, e-book readers, laptop or
desktop computers, PDAs, smart phones, or other stationary or portable devices

69. @KunleTCampbell
Start
Optimising
for
Questions
both on-site
and off-site

70. @KunleTCampbell
People Ask Search Engines Questions
Infuse your
brand in
conversations
offsite – i.e.
reviews,
press, video
EARNED
MEDIA

71. @KunleTCampbell
People Ask Search Engines Questions
Infuse your brand in
conversations offsite
– i.e. reviews, press,
video
EARNED MEDIA

72. @KunleTCampbell
STOP
Optimising
for STRINGS
and
START
Optimising
for
THINGS,
CONCEPTS
& Subjects

73. @KunleTCampbell
Keyword Research
is NOT Dead
in the water
RIP

74. @KunleTCampbell
Infuse
Keyword Research into:
CONCEPT RESEARCH
Or
SUBJECT MATTER
RESEARCH

75. @KunleTCampbell
Align On-site Content Marketing with Content that Addresses
Pain Points at Each Stage of the Purchase Funnel
A
I
D
A
AWARENESS
INTEREST
DESIRE
ACTION
Brand Awareness Efforts: Viral
Video, Image, Advertising,
Sponsorship, Social
Create Interest: PR, Events,
Guides, Blog, YouTube Video
Series, eNewsletter, Q&As
Desire for Your Products: Brand
Name Search, Product Search,
Direct Traffic
Action: Buy Product, Voucher
Codes
THE AIDA MODEL

76. @KunleTCampbell
Answer Specific Queries that align with user needs
?

77. @KunleTCampbell
Go deep…

78. @KunleTCampbell
Optimize your on-site content for
“in-depth articles”

79. @KunleTCampbell
eBay Goes
Quite detailed
in their
User Guides

80. @KunleTCampbell
Argos on the
other hand is
quite thin on
for it’s Pools
Buying Guide

81. @KunleTCampbell
Invest in
PLA Ads

82. @KunleTCampbell
Searchers are being
trained to interact
with Visual Answer
Cards….
Yes SEOs, CTRs are Higher…

83. @KunleTCampbell
Small Screens and
PLA ads are
swipeable
Mobiles are worse…
J

84. @KunleTCampbell
Highly Targeted
outreach gets Highly
Relevant links matter
even more now
Continue to do great SEO…
J

85. @KunleTCampbell
Contact Me
to chat more…
about
eCommerce
Marketing
email: kc@2x.co
twitter: @KunleTCampbell
web: www.2xmedia.co