Tom Anthony outline 5 key changes in technologies and trends which are changing the landscape of search. Some of these trends are here now, but some are trends which will emerge in the next 12-24 months.

1. FIVE EMERGING TRENDS IN
ONLINE SEARCH
Tom Anthony
SearchLove London 2015

3. 5 TRENDS

4. COMPOUND
QUERIES
IMPLICIT
SIGNALS
PERSONAL
ASSISTANTS
1 2
5
WEB SEARCH TO
DATA SEARCH
4
KEYWORDS
VS INTENTS
3

5. 1
IMPLICIT QUERY SIGNALS
1

6. search query
“london tube stations”

7. explicit aspect of query
implicit aspect of query
iPhone user, on street in London
“london tube stations”

8. TIME
TOTALSIGNALINFORMATION
explicit signal
implicit signal

9. Device
Location Browser
Social Connections
Time of Day
Search History
Language

10. • NBED - WEARABLES
IMPLICIT SIGNALS: WEARABLES

11. IMPLICIT SIGNALS: MODE OF TRANSPORT

12. • NBED - PHYSICAL WEB
IMPLICIT SIGNALS: HYPER-LOCAL (BEACONS)

13. Mockup: Jack Morgan
IMPLICIT SIGNALS: READING SIGNS

14. TIME
TOTALSIGNALINFORMATION
explicit signal
implicit signal

15. My vision when we started Google 15 years ago was
that eventually you wouldn't have to have
a search query at all.
SERGEY BRIN
GOOGLE

16. FACT
Explosion of implicit signals is leading to more
complex queries and more granular results.
QUESTION
Which implicit signals could impact searchers
trying to find your clients?

17. COMPOUND
QUERIES
IMPLICIT
SIGNALS
PERSONAL
ASSISTANTS
1 2
5
WEB SEARCH TO
DATA SEARCH
4
KEYWORDS
VS INTENTS
3

18. COMPOUND QUERIES
2

19. Query
Algorithm
Response
Revised
Query Algorithm
Response
A SEARCH QUERY

20. Query
Algorithm
Response
Revised
Query Algorithm
Response
OLD MODEL: INDEPENDENT QUERIES

21. HUMMINGBIRD
Credit: mikebaird on Flickr

22. brought to you by…
https://youtu.be/JfJOFvKDNu4

23. brought to you by…
https://youtu.be/X8K2ccNBZYU

24. NEW MODEL: DEPENDENT QUERIES
Query
Algorithm
Response
Additional
Input
Algorithm
Revised
Response

26. https://youtu.be/M1ONXea0mXg

27. https://youtu.be/M1ONXea0mXg

28. COMPOUND QUERIES ARE LIKE FACETED SEARCH

29. FACT
Queries are no longer single expressions of
intent followed by static responses.
QUESTION
What compound queries might your
visitors be trying?

30. COMPOUND
QUERIES
IMPLICIT
SIGNALS
PERSONAL
ASSISTANTS
1 2
5
WEB SEARCH TO
DATA SEARCH
4
KEYWORDS
VS INTENTS
3

31. KEYWORD FOCUS TO
INTENT FOCUS
3

32. Example from: Rand Fishkin, Moz
KEYWORDS & INTENTS

33. Source: /u/UpboatOarKnotUpboat
SEARCH HISTORY OF A 5 YEAR OLD

34. KEYWORDS
INTENT

35. KEYWORDS
INTENT
IMPLICIT
SIGNALS
COMPOUND
QUERIES

36. brought to you by…
https://youtu.be/Cv_EzsI7x34

37. CONTEXTUAL SEARCHES
http://selnd.com/1MnLlF8

38. FACT
Intent is not just ‘better keywords’; it is determined
from implicit signals and across multiple queries.
QUESTION
Do you know which landing pages serve which
intents on your site?

39. COMPOUND
QUERIES
IMPLICIT
SIGNALS
PERSONAL
ASSISTANTS
1 2
5
WEB SEARCH TO
DATA SEARCH
4
KEYWORDS
VS INTENTS
3

40. WEB SEARCH TO
DATA DRIVEN SEARCH
4

41. SHIFT AWAY FROM ‘WEB SEARCH’: ENTITIES

42. SHIFT AWAY FROM ‘WEB SEARCH’: DIRECT ANSWERS

43. SHIFT AWAY FROM ‘WEB SEARCH’: GOOGLE NOW

44. FROM WEB TO APP INDEXING & DEEP LINKS

45. WHERE ARE WE HEADED?
?

46. CROSS DEVICE TASKS & SEARCHES
source: http://services.google.com/fh/files/misc/multiscreenworld_final.pdf (thanks, Dr Pete)

47. CROSS DEVICE: APPLE HANDOFF

48. CROSS DEVICE: SHARED SCREENS

49. DIRECT ANSWERS & CARDS

50. CARDS: UNITS OF DATA

51. CARDS: ADAPT EASILY CROSS DEVICE
dicddic

52. CARDS: NEW MOBILE INTERFACE

53. CARDS: DATA SOURCES
Knowledge
Graph
Data
Partnerships
Everything Else
?

54. CARDS: DATA SOURCES
Knowledge
Graph
Data
Partnerships
Everything Else
YOU!

55. DIRECT ANSWERS: FEATURED SNIPPETS

56. FACETED SEARCH 2.0: CROSS DEVICE CARDS?

57. FACT
Direct answers and cross device search are driving us
towards a ‘data driven’ model where cards are key.
QUESTIONS
Is your data accessible to Google?
Why should Google choose you as a data source?

58. COMPOUND
QUERIES
IMPLICIT
SIGNALS
PERSONAL
ASSISTANTS
1 2
5
WEB SEARCH TO
DATA SEARCH
4
KEYWORDS
VS INTENTS
3

59. PERSONAL ASSISTANTS
5

60. GOOGLE’S MISSION

61. ‘PERSONAL INDEX’: PHOTOS

62. ‘PERSONAL INDEX’: CALENDAR

63. ‘PERSONAL INDEX’: DEVICES

64. ‘PERSONAL INDEX’: EMAILS

65. EMAIL STRUCTURED MARKUP

66. A single interface for all searches.

67. NOT JUST GOOGLE

68. MICROSOFT CORTANA

69. PROACTIVE SIRI

70. FACEBOOK ‘M’

71. HOUND

72. We are in a Post-PageRank world.

73. FACT
We will increasingly search both personal and
public indexes via a single interface.
QUESTION
How can we prepare to be the most useful source
from a personal assistant app’s perspective?

74. TAKEAWAYS

75. COMPOUND
QUERIES
IMPLICIT
SIGNALS
PERSONAL
ASSISTANTS
1 2
5
WEB SEARCH TO
DATA SEARCH
4
KEYWORDS
VS INTENTS
3

76. Intent is more than just ‘keywords done better’;
consider the implicit signals and compound queries.
Data Driven Search is coming;
start considering what steps to take to prepare.
The rise of ‘Personal Assistants’ is an opportunity;
optimise on another axis (that isn’t PageRank based).
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2
3

78. THANKS@TomAnthonySEO