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5 Emerging Trends in Search

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I 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.

Publicada em: Marketing
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5 Emerging Trends in Search

  1. 1. FIVE EMERGING TRENDS IN ONLINE SEARCH Tom Anthony SearchLove London 2015
  2. 2. 5 TRENDS
  3. 3. COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
  4. 4. 1 IMPLICIT QUERY SIGNALS 1
  5. 5. search query “london tube stations”
  6. 6. explicit aspect of query implicit aspect of query iPhone user, on street in London “london tube stations”
  7. 7. TIME TOTALSIGNALINFORMATION explicit signal implicit signal
  8. 8. Device Location Browser Social Connections Time of Day Search History Language
  9. 9. • NBED - WEARABLES IMPLICIT SIGNALS: WEARABLES
  10. 10. IMPLICIT SIGNALS: MODE OF TRANSPORT
  11. 11. • NBED - PHYSICAL WEB IMPLICIT SIGNALS: HYPER-LOCAL (BEACONS)
  12. 12. Mockup: Jack Morgan IMPLICIT SIGNALS: READING SIGNS
  13. 13. TIME TOTALSIGNALINFORMATION explicit signal implicit signal
  14. 14. 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
  15. 15. 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?
  16. 16. COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
  17. 17. COMPOUND QUERIES 2
  18. 18. Query Algorithm Response Revised Query Algorithm Response A SEARCH QUERY
  19. 19. Query Algorithm Response Revised Query Algorithm Response OLD MODEL: INDEPENDENT QUERIES
  20. 20. HUMMINGBIRD Credit: mikebaird on Flickr
  21. 21. brought to you by… https://youtu.be/JfJOFvKDNu4
  22. 22. brought to you by… https://youtu.be/X8K2ccNBZYU
  23. 23. NEW MODEL: DEPENDENT QUERIES Query Algorithm Response Additional Input Algorithm Revised Response
  24. 24. https://youtu.be/M1ONXea0mXg
  25. 25. https://youtu.be/M1ONXea0mXg
  26. 26. COMPOUND QUERIES ARE LIKE FACETED SEARCH
  27. 27. FACT Queries are no longer single expressions of intent followed by static responses. QUESTION What compound queries might your visitors be trying?
  28. 28. COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
  29. 29. KEYWORD FOCUS TO INTENT FOCUS 3
  30. 30. Example from: Rand Fishkin, Moz KEYWORDS & INTENTS
  31. 31. Source: /u/UpboatOarKnotUpboat SEARCH HISTORY OF A 5 YEAR OLD
  32. 32. KEYWORDS INTENT
  33. 33. KEYWORDS INTENT IMPLICIT SIGNALS COMPOUND QUERIES
  34. 34. brought to you by… https://youtu.be/Cv_EzsI7x34
  35. 35. CONTEXTUAL SEARCHES http://selnd.com/1MnLlF8
  36. 36. 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?
  37. 37. COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
  38. 38. WEB SEARCH TO DATA DRIVEN SEARCH 4
  39. 39. SHIFT AWAY FROM ‘WEB SEARCH’: ENTITIES
  40. 40. SHIFT AWAY FROM ‘WEB SEARCH’: DIRECT ANSWERS
  41. 41. SHIFT AWAY FROM ‘WEB SEARCH’: GOOGLE NOW
  42. 42. FROM WEB TO APP INDEXING & DEEP LINKS
  43. 43. WHERE ARE WE HEADED? ?
  44. 44. CROSS DEVICE TASKS & SEARCHES source: http://services.google.com/fh/files/misc/multiscreenworld_final.pdf (thanks, Dr Pete)
  45. 45. CROSS DEVICE: APPLE HANDOFF
  46. 46. CROSS DEVICE: SHARED SCREENS
  47. 47. DIRECT ANSWERS & CARDS
  48. 48. CARDS: UNITS OF DATA
  49. 49. CARDS: ADAPT EASILY CROSS DEVICE dicddic
  50. 50. CARDS: NEW MOBILE INTERFACE
  51. 51. CARDS: DATA SOURCES Knowledge Graph Data Partnerships Everything Else ?
  52. 52. CARDS: DATA SOURCES Knowledge Graph Data Partnerships Everything Else YOU!
  53. 53. DIRECT ANSWERS: FEATURED SNIPPETS
  54. 54. FACETED SEARCH 2.0: CROSS DEVICE CARDS?
  55. 55. 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?
  56. 56. COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
  57. 57. PERSONAL ASSISTANTS 5
  58. 58. GOOGLE’S MISSION
  59. 59. ‘PERSONAL INDEX’: PHOTOS
  60. 60. ‘PERSONAL INDEX’: CALENDAR
  61. 61. ‘PERSONAL INDEX’: DEVICES
  62. 62. ‘PERSONAL INDEX’: EMAILS
  63. 63. EMAIL STRUCTURED MARKUP
  64. 64. A single interface for all searches.
  65. 65. NOT JUST GOOGLE
  66. 66. MICROSOFT CORTANA
  67. 67. PROACTIVE SIRI
  68. 68. FACEBOOK ‘M’
  69. 69. HOUND
  70. 70. We are in a Post-PageRank world.
  71. 71. 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?
  72. 72. TAKEAWAYS
  73. 73. COMPOUND QUERIES IMPLICIT SIGNALS PERSONAL ASSISTANTS 1 2 5 WEB SEARCH TO DATA SEARCH 4 KEYWORDS VS INTENTS 3
  74. 74. 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). 1 2 3
  75. 75. THANKS@TomAnthonySEO

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