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”Voice	
  Search	
  
SEO	
  &	
  Assistive	
  
Systems...	
  
Challenges	
  &	
  
Opportunities”	
  
“The	
  current	
  si...
WHO
IS
DAWN
ANDERSON
@dawnieando
dawn.anderson@@move-it-
marketing.co.uk
move-it-marketing.co.uk
linkedin.com/in/msdawnand...
So,	
  just	
  what	
  is	
  conversational	
  
assistance	
  &	
  where’s	
  the	
  
opportunity?
Evolution	
  of	
  
Information
Retrieval
Classic	
  
Information	
  
Retrieval	
  (IR)
Interactive	
  
Information	
  
Re...
Something’s	
  brewing…‘A	
  Call	
  to	
  
Arms’	
  in	
  ‘Assistive	
  AI’
…	
  and	
  some	
  names
Subordinate	
  
systems
Conducive	
  
systems
Decisive	
  
systems
A	
  Trio	
  of	
  assistive	
  systems
But…	
  we	
  will	
  look	
  at	
  only	
  2	
  types	
  today…	
  which	
  
are	
  a	
  hybrid	
  within	
  the	
  assis...
Ok	
  Google,	
  Hello	
  Siri,	
  
Greetings	
  Cortana
Phones,	
  Desktop,	
  Laptops	
  &	
  Smart	
  Speakers	
  
&	
  Watches
Joe	
  Public	
  is	
  in	
  awe	
  
and	
  wonder	
  at	
  Smart	
  
Speakers
Interest	
  over	
  time	
  for	
  Google	
  Home	
  &	
  Amazon	
  Alexa
Stepping	
  out	
  of	
  the	
  SEO	
  bubble
Source:	
  SISTRIX.	
  2018. Stepping	
  out	
  of	
  the	
  SEO	
  Bubble	
...
Why	
  do	
  people	
  use	
  voice	
  search?
Source:	
  Higher	
  visibility	
  study	
  on	
  2000	
  people	
  (opport...
When	
  do	
  people	
  use	
  voice	
  search?
Source:	
  Higher	
  visibility	
  study	
  on	
  2000	
  people	
  (oppor...
What	
  do	
  people	
  do	
  when	
  using	
  voice	
  search?
We	
  are	
  still	
  on	
  
‘Day	
  One’	
  with	
  
this	
  stuff
We	
  are	
  like	
  prospecting	
  
gold	
  miners…	
  future	
  facing
All	
  signals	
  point	
  to	
  the	
  future
By	
  2020	
  30%	
  of	
  web	
  
browsing	
  sessions	
  will	
  be	
  
done	
  without	
  a	
  screen	
  
(Gartner,	
  ...
Search	
  engines	
  &	
  IR	
  researchers	
  compete	
  over	
  voice	
  recognition
How	
  can	
  we	
  maximise conversation	
  search	
  &	
  
conversation	
  actions	
  opportunities?
Accuracy	
  of	
  
results	
  is	
  more	
  
important	
  
than	
  quantity
Let	
  us	
  first	
  look	
  
at	
  ‘conversation	
  
Search’
In	
  2017	
  we	
  asked	
  ”How”	
  more	
  than	
  anything	
  else
Since	
  voice	
  
search	
  is	
  mostly	
  
on	
  mobile	
  
devices	
  
(including	
  
phones)…	
  be	
  
VERY	
  mobil...
We	
  have	
  some	
  
guidance
Google’s	
  human	
  quality	
  
raters	
  guidelines
And	
  also	
  some	
  of	
  the	
  researchers	
  who	
  work	
  on	
  
the	
  Conversational	
  Search	
  team	
  at	
  ...
Machine	
  Learning	
  
Word2Vec	
  &	
  Concept2Vec
What	
  did	
  
they	
  say?
Tip	
  1	
  – Meet	
  informational	
  needs…	
  in	
  the	
  right	
  
context
What	
  are	
  the	
  questions?
Who? What?
Where? When?
Why?
Transactional
Navigational
Informational
A	
  Taxonomy	
  
of	
  Web	
  Search	
  
(Broder,	
  2002)
Map	
  Different	
  
Question	
  
Answering	
  
Content	
  To	
  
Informational	
  
Needs
Informational
Navigational
Trans...
Think	
  often	
  ‘On	
  the	
  Go’	
  location	
  intent	
  focus
Tip	
  2	
  – Keep	
  answers	
  short	
  &	
  get	
  to	
  the	
  point	
  
early	
  – prosody	
  modifications	
  &	
  s...
Keep	
  it	
  brief	
  &	
  concise
Tip	
  3	
  – Watch	
  	
  out	
  for	
  grammar,	
  spelling	
  &	
  
pronunciation
Soundex,	
  Metaphone,	
  Double	
  Metaphone
(or	
  similar)	
  Algorithms
Tip	
  4	
  – Watch	
  out	
  for	
  pesky	
  pronouns
Linguisitics are	
  
Complicated	
  –
Watch	
  out	
  for	
  
anaphora	
  &	
  
cataphora
resolution
It’s	
  raining	
  pronouns	
  – many	
  types	
  of	
  pronouns
So	
  many	
  ways	
  to	
  misunderstand	
  natural	
  language
Intensive Reciprocal Reflexive Personal Relative Indefini...
Computer	
  
programs	
  lose	
  
track	
  of	
  who	
  
is	
  who	
  easily
I’m	
  confused…	
  Here…	
  Have	
  
some	
 ...
They
Us
She
He Them
I
You
Him Her
Me
E.g.	
  
Minimize	
  
these	
  
personal	
  
pronouns…
That Those
These This
Time	
  &	
  Space	
  confuses	
  
things	
  further
Instead…	
  refer	
  to	
  entities	
  by	
  name	
  (where	
  
possible)
Dis…	
  Ambiguate
Unstructured	
  
data	
  (text)
Semi-­‐
structured	
  
data
Relational	
  
databases
Structured	
  
data
XML	
  sitemaps O...
Structured	
  
data	
  explosion
2017
2014
Over	
  half	
  of	
  voice	
  
search	
  results	
  
hold	
  featured	
  
snippets	
  (Dr	
  Pete	
  
Myers,	
  Moz,	
  
...
Tip	
  5	
  – Cover	
  all	
  bases	
  due	
  to	
  paraphrasing	
  
absence
• Well	
  structured	
  long	
  form	
  
informational	
  content	
  (where	
  
appropriate)
• Semantic	
  headings
• Writ...
Tip	
  6	
  -­‐ Avoid	
  Tables
You	
  may	
  need	
  
a	
  dual	
  or	
  
triple	
  content	
  
strategy
2%
Now	
  let’s	
  look	
  at	
  ‘conversation	
  actions’
Many	
  subtasks	
  towards	
  a	
  major	
  task
Google	
  Assistant	
  – Actions,	
  
Entities,	
  Dialog	
  flows	
  &	
  Intents
Many	
  built-­‐in	
  intents	
  &	
  many	
  ‘coming	
  soon’
Extend	
  Actions	
  on	
  Google	
  using	
  Machine	
  
Learning
Extend	
  Actions	
  
on	
  Google	
  
using	
  Machine	
  
Learning
Understand	
  your	
  customers	
  to	
  assist	
  with	
  AI
Customer	
  
Service	
  Data
Customer	
  
Panels
Email	
  
q...
Understand	
  your	
  customers	
  to	
  assist	
  with	
  AI
Perceived	
  
Information	
  need
Micro-­‐task
Micro-­‐task ...
Paraphrase	
  handling	
  on	
  ‘Actions’	
  appears	
  to	
  
be	
  programmable
Hotel	
  Booking	
  
Dialogflow
Book	
  hotel	
  
intent
When	
  do	
  you	
  
want	
  to	
  stay?
dates
dates
How	
  many	
  
nights?
3	
  nights 2	
  ni...
We	
  are	
  at	
  ’Day	
  One’	
  but	
  the	
  
future	
  is	
  ’Assistive’
Thank	
  you
Keep	
  in	
  touch
@DawnieAndo
@MoveItMarketing
References,	
  Sources	
  &	
  
Further	
  Reading
References
• Broder,	
  A.,	
  2002,	
  September.	
  A	
  taxonomy	
  of	
  web	
  search.	
  In ACM	
  Sigir forum (Vol....
References
• Mitkov,	
  R.,	
  2014. Anaphora	
  resolution.	
  Routledge.
• NLP	
  Department	
  -­‐ Stanford	
  Universi...
References
• The	
  Stanford	
  Question	
  Answering	
  Dataset.	
  2018. The	
  Stanford	
  
Question	
  Answering	
  Da...
Voice Search and Conversation Action Assistive Systems - Challenges & Opportunities
Voice Search and Conversation Action Assistive Systems - Challenges & Opportunities
Voice Search and Conversation Action Assistive Systems - Challenges & Opportunities
Voice Search and Conversation Action Assistive Systems - Challenges & Opportunities
Voice Search and Conversation Action Assistive Systems - Challenges & Opportunities
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Voice Search and Conversation Action Assistive Systems - Challenges & Opportunities

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We are headed to the age of assistive task driven search where the user needs help to 'do' things as well as learn things. Smart speakers, mobile phones, assistive systems and conversational search and action devices are where the buck is headed for now. Where are we at in this wave? What are the challenges? What are the opportunities right now? Here we look at some of the ways we can start to prepare our tactics and strategy to be pioneering search marketers with conversation search and conversation action.

Published in: Marketing

Voice Search and Conversation Action Assistive Systems - Challenges & Opportunities

  1. 1. ”Voice  Search   SEO  &  Assistive   Systems...   Challenges  &   Opportunities”   “The  current  situation  for   voice  search  &  SEO  and   overcoming  challenges“ Dawn  Anderson @DawnieAndo from   @MoveItMarketing
  2. 2. WHO IS DAWN ANDERSON @dawnieando dawn.anderson@@move-it- marketing.co.uk move-it-marketing.co.uk linkedin.com/in/msdawnanderson 11+  years  SEO  &  Digital  Marketing  Consultant &  Pracademic: Contributor: Speaker  &  Trainer: Fellow  of:
  3. 3. So,  just  what  is  conversational   assistance  &  where’s  the   opportunity?
  4. 4. Evolution  of   Information Retrieval Classic   Information   Retrieval  (IR) Interactive   Information   Retrieval  (IIR) Mobile   Information   Retrieval  (MIR) Machine   Learning
  5. 5. Something’s  brewing…‘A  Call  to   Arms’  in  ‘Assistive  AI’
  6. 6. …  and  some  names Subordinate   systems Conducive   systems Decisive   systems
  7. 7. A  Trio  of  assistive  systems
  8. 8. But…  we  will  look  at  only  2  types  today…  which   are  a  hybrid  within  the  assistive  systems Provide   answers   /  search Conversation     Search Help   with   activities   /  tasks Conversation   Actions
  9. 9. Ok  Google,  Hello  Siri,   Greetings  Cortana
  10. 10. Phones,  Desktop,  Laptops  &  Smart  Speakers   &  Watches
  11. 11. Joe  Public  is  in  awe   and  wonder  at  Smart   Speakers
  12. 12. Interest  over  time  for  Google  Home  &  Amazon  Alexa
  13. 13. Stepping  out  of  the  SEO  bubble Source:  SISTRIX.  2018. Stepping  out  of  the  SEO  Bubble  -­‐ SISTRIX.  [ONLINE]  Available   at: https://www.sistrix.com/blog/stepping-­‐out-­‐of-­‐the-­‐seo-­‐bubble/. 26,700+  respondents
  14. 14. Why  do  people  use  voice  search? Source:  Higher  visibility  study  on  2000  people  (opportunity  sampling)
  15. 15. When  do  people  use  voice  search? Source:  Higher  visibility  study  on  2000  people  (opportunity  sampling)
  16. 16. What  do  people  do  when  using  voice  search?
  17. 17. We  are  still  on   ‘Day  One’  with   this  stuff
  18. 18. We  are  like  prospecting   gold  miners…  future  facing
  19. 19. All  signals  point  to  the  future
  20. 20. By  2020  30%  of  web   browsing  sessions  will  be   done  without  a  screen   (Gartner,  2016) 30% 70% Web  browser  sessions Without  a  screen With  a  screen
  21. 21. Search  engines  &  IR  researchers  compete  over  voice  recognition
  22. 22. How  can  we  maximise conversation  search  &   conversation  actions  opportunities?
  23. 23. Accuracy  of   results  is  more   important   than  quantity
  24. 24. Let  us  first  look   at  ‘conversation   Search’
  25. 25. In  2017  we  asked  ”How”  more  than  anything  else
  26. 26. Since  voice   search  is  mostly   on  mobile   devices   (including   phones)…  be   VERY  mobile   friendly
  27. 27. We  have  some   guidance
  28. 28. Google’s  human  quality   raters  guidelines
  29. 29. And  also  some  of  the  researchers  who  work  on   the  Conversational  Search  team  at  Google   Switzerland
  30. 30. Machine  Learning   Word2Vec  &  Concept2Vec
  31. 31. What  did   they  say?
  32. 32. Tip  1  – Meet  informational  needs…  in  the  right   context
  33. 33. What  are  the  questions? Who? What? Where? When? Why?
  34. 34. Transactional Navigational Informational A  Taxonomy   of  Web  Search   (Broder,  2002)
  35. 35. Map  Different   Question   Answering   Content  To   Informational   Needs Informational Navigational Transactional Guides,  FAQs,  Quick   Answers,  How  to,   Articles Directions,   Branch  locations,   Meet  the  Team,   Avout Case  Studies,   Product  Reviews,   Testimonials,   Product  videos,   360  images,  specs
  36. 36. Think  often  ‘On  the  Go’  location  intent  focus
  37. 37. Tip  2  – Keep  answers  short  &  get  to  the  point   early  – prosody  modifications  &  sentence  stress
  38. 38. Keep  it  brief  &  concise
  39. 39. Tip  3  – Watch    out  for  grammar,  spelling  &   pronunciation
  40. 40. Soundex,  Metaphone,  Double  Metaphone (or  similar)  Algorithms
  41. 41. Tip  4  – Watch  out  for  pesky  pronouns
  42. 42. Linguisitics are   Complicated  – Watch  out  for   anaphora  &   cataphora resolution
  43. 43. It’s  raining  pronouns  – many  types  of  pronouns
  44. 44. So  many  ways  to  misunderstand  natural  language Intensive Reciprocal Reflexive Personal Relative Indefinite Demonstrativ e Possessive Interrogative Myself Each  other Herself I Who Anything This Mine Who Himself One   another Himself You Whom Everybody That His Whom Herself Myself He Whose few Those Theirs Which Itself Ourselves She Which many These Hers What Ourselves Yourself We That none Ours Whatever Yourself They What some Yours Whichever Me Whatever Whomever Him Whoever Her Whomever Us whichever
  45. 45. Computer   programs  lose   track  of  who   is  who  easily I’m  confused…  Here…  Have   some  flowers  instead  ;P  ;P
  46. 46. They Us She He Them I You Him Her Me E.g.   Minimize   these   personal   pronouns…
  47. 47. That Those These This Time  &  Space  confuses   things  further
  48. 48. Instead…  refer  to  entities  by  name  (where   possible)
  49. 49. Dis…  Ambiguate
  50. 50. Unstructured   data  (text) Semi-­‐ structured   data Relational   databases Structured   data XML  sitemaps Ordered  lists Unordered   lists Tabular  data Data  Feeds Turn  ‘fluffy’  web  pages  into  machine-­‐ understandable  formats  – add  signals
  51. 51. Structured   data  explosion 2017 2014
  52. 52. Over  half  of  voice   search  results   hold  featured   snippets  (Dr  Pete   Myers,  Moz,   2017) Work  on  building  out  the  Knowledge  Graph
  53. 53. Tip  5  – Cover  all  bases  due  to  paraphrasing   absence
  54. 54. • Well  structured  long  form   informational  content  (where   appropriate) • Semantic  headings • Write  for  a  featured  snippet   win  (few  exceptions) • Cover  the  bases  because  of   extraction  &  compression  (no   paraphrasing)
  55. 55. Tip  6  -­‐ Avoid  Tables
  56. 56. You  may  need   a  dual  or   triple  content   strategy 2%
  57. 57. Now  let’s  look  at  ‘conversation  actions’
  58. 58. Many  subtasks  towards  a  major  task
  59. 59. Google  Assistant  – Actions,   Entities,  Dialog  flows  &  Intents
  60. 60. Many  built-­‐in  intents  &  many  ‘coming  soon’
  61. 61. Extend  Actions  on  Google  using  Machine   Learning
  62. 62. Extend  Actions   on  Google   using  Machine   Learning
  63. 63. Understand  your  customers  to  assist  with  AI Customer   Service  Data Customer   Panels Email   questions FAQs Build   Assistant  App
  64. 64. Understand  your  customers  to  assist  with  AI Perceived   Information  need Micro-­‐task Micro-­‐task Micro-­‐task Micro-­‐task Micro-­‐task Task Micro-­‐task Micro-­‐task Micro-­‐task Micro-­‐task Task Micro-­‐task Micro-­‐task Task Micro-­‐task Micro-­‐task Micro-­‐task Task Micro-­‐task Micro-­‐task Task Micro-­‐task Task We  can  identify  the   user’s  probable  top   tasks  &  subtasks Identify  their  needs  &   what  info  they  need   along  the  way
  65. 65. Paraphrase  handling  on  ‘Actions’  appears  to   be  programmable
  66. 66. Hotel  Booking   Dialogflow
  67. 67. Book  hotel   intent When  do  you   want  to  stay? dates dates How  many   nights? 3  nights 2  nights Overnight A  week Single  or   double  room? Single  room Double  room Programme your   own  expected   questions  and   answers
  68. 68. We  are  at  ’Day  One’  but  the   future  is  ’Assistive’
  69. 69. Thank  you Keep  in  touch @DawnieAndo @MoveItMarketing
  70. 70. References,  Sources  &   Further  Reading
  71. 71. References • Broder,  A.,  2002,  September.  A  taxonomy  of  web  search.  In ACM  Sigir forum (Vol.  36,  No.   2,  pp.  3-­‐10).  ACM. • Chuklin,  A.,  Severyn,  A.,  Trippas,  J.,  Alfonseca,  E.,  Silen,  H.  and  Spina,  D.,  2018.  Prosody   Modifications  for  Question-­‐Answering  in  Voice-­‐Only  Settings. arXiv preprint   arXiv:1806.03957. • HigherVisibility.  2018. How  Popular  is  Voice  Search?  |  HigherVisibility.  [ONLINE]  Available   at: https://www.highervisibility.com/blog/how-­‐popular-­‐is-­‐voice-­‐search/ • Filippova,  K.,  Alfonseca,  E.,  Colmenares,  C.A.,  Kaiser,  L.  and  Vinyals,  O.,  2015.  Sentence   compression  by  deletion  with  lstms.  In Proceedings  of  the  2015  Conference  on  Empirical   Methods  in  Natural  Language  Processing (pp.  360-­‐368). • Filippova,  K.  and  Alfonseca,  E.,  2015.  Fast  k-­‐best  sentence  compression. arXiv preprint   arXiv:1510.08418. • Google  Developers.  2018. Content-­‐based  Actions   | Actions  on  Google   | Google   Developers.  [ONLINE]  Available  at: https://developers.google.com/actions/content-­‐ actions/.  [Accessed  18  June  2018]
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