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Content Marketing in the Machine Age: How to Make Your Content More Automated and Intelligent

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Content Marketing World 2016 Presentation:

This session is an exploration of what's possible as algorithms and artificial intelligence rapidly advance the industry. Attendees will leave inspired by a collection of case studies, and armed with an array of readily available technologies that marketers can use to make their content more automated and intelligent.

KEY TAKEAWAYS

* Understand what the disruption of other industries can teach us about the inevitable impact artificial intelligence will have on the marketing industry.
* Learn about the marketing technology companies that are leading the way in advanced automation, predictive analytics and machine-generated content.
* Apply new technologies and processes to make your content marketing more efficient and effective.

Published in: Marketing
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Content Marketing in the Machine Age: How to Make Your Content More Automated and Intelligent

  1. 1. @TwitterHandle • #CMWorld Content Marketing in the Machine Age Paul Roetzer Founder & CEO, PR 20/20 @paulroetzer @paulroetzer • #CMWorld Sept. 7, 2016 Copyright 2016 PR 20/20. All rights reserved.
  2. 2. Consider  how  much  !me  your  marke2ng  team  spends  .  .  . crea2ng  ad  copy   managing  digital  ad  campaigns   tes2ng  headlines,  landing  pages,  ads   scheduling/publishing  social  shares   predic2ng  opens,  clicks,  conversions   reviewing  analy!cs   wri2ng  performance  reports   recommending  content  strategies dra;ing  social  media  updates   discovering  keywords   planning  blog  post  topics   wri!ng  content   op!mizing  content   cura!ng  content   personalizing  content   automa!ng  content   building  email  workflows Copyright 2016 PR 20/20. All rights reserved.
  3. 3. Now imagine if machines performed the majority of those activities, and a marketer’s primary role was to enhance rather than create.
  4. 4. There is a relatively untapped technology that possesses the power to change everything…
  5. 5. artificial intelligence
  6. 6. “The  science  of  making  machines  smart.”     —  Demis  Hassabis,  Co-­‐Founder  &  CEO  of  DeepMind @paulroetzer • #CMWorld what  is  ar!ficial  intelligence? (which  in  turn  augments  human  knowledge  and  capabili5es) Source: Rolling Stone
  7. 7. a  set  of  instruc!ons  that  tells  the  machine  what  to  do.   @paulroetzer • #CMWorld what  is  an  algorithm? (except  with  AI  the  machine  can  create  its  own  algorithms,  determine  new  paths,   and  unlock  unlimited  poten5al  to  advance  marke5ng,  and  mankind.)
  8. 8. THE DISRUPTION OF INDUSTRIES
  9. 9. @paulroetzer www.pr2020.com 60%  of  all  trades  are  executed  by  computers     with  liKle  or  no  real-­‐2me  oversight  from  humans.   Source:  Christopher  Steiner,  Automate  This
  10. 10. @paulroetzer avg  120  stops/day
  11. 11. what  is  the  possible  number  of   alterna!ves  for  ordering  those  stops? @paulroetzer www.pr2020.com
  12. 12. 6,689,502,913,449,135,000,000,000,   000,000,000,000,000,000,000,000,   000,000,000,000,000,000,000,000,   000,000,000,000,000,000,000,000,   000,000,000,000,000,000,000,000,   000,000,000,000,000,000,000,000,   000,000,000,000,000,000,000,000,   000,000,000,000,000,000,000,000,   000,000 Source: Wall Street Journal
  13. 13. “Can  a  human  really  think  of  the   best  way  to  deliver  120  stops?  This   is  where  the  algorithm  will  come  in.   It  will  explore  paths  of  doing  things   you  would  not,  because  there  are   just  too  many  combina2ons.”   Jack  Levis     Senior  director  of  process  management,  UPS Source: Wall Street Journal
  14. 14. NETFLIX  uses  algorithms  to  suggest  content   and  manufacture  shows  based  on  subscriber   viewing  habits  and  preferences. Source:  NeUlix  Tech  Blog
  15. 15. 75%  of  what  people  watch  on  NeSlix  is  from  some   sort  of  algorithm-­‐generated  recommenda!on Source:  NeUlix  Tech  Blog
  16. 16. Epagogix  algorithms  analyze  movie  scripts  to     predict  how  much  money  they  will  make  at  the  box  office   and  offer  recommenda!ons  on  how  to  make  them  more   marketable  and  profitable,  including  through  changes  to   plot  lines,  seVngs,  character  roles  and  actors.
  17. 17. Source: Tesla
  18. 18. @paulroetzer www.pr2020.com
  19. 19. THE MARKETING MACHINE AGE
  20. 20. why marketing? why now?
  21. 21. POTENTIAL to disrupt + the REWARD for disruption @paulroetzer • #CMWorld
  22. 22. ExactTarget  IPO  (Mar  '12) Oracle  buys  Eloqua  (Dec  '12) SF  buys  ExactTarget  (Jun  '13) IBM  buys  Silverpop  (Apr  '14) Marketo  market  cap  (8-­‐30-­‐16) HubSpot  market  cap  (8-­‐30-­‐16) 0 5 10 15 20 25 $161.5M $871  M $2.5  B venture  funding,  mergers,  acquisi2ons  and  IPOs  have   fueled  the  marke!ng  automa!on  space   @paulroetzer www.pr2020.com $270  M $1.6  B $1.9  B @paulroetzer www.pr2020.com
  23. 23. marke2ng  automa2on  plaUorms   save  !me,  increase  efficiency  and   produc!vity,  and  drive   performance.  BUT  .  .  .
  24. 24. the marketing automation we see today is elementary, and, ironically, largely manual. . . @paulroetzer www.pr2020.com
  25. 25. marketing automation platforms generally do NOT provide deep insights into data, recommend actions, predict outcomes or create content. @paulroetzer www.pr2020.com
  26. 26. 90% of all data in the world has been created in the last 2 years Source:  IBM
  27. 27. marketers have access to data from dozens of sources: social monitoring, media monitoring, web analytics, email, call tracking, sales, advertising, remarketing, ecommerce, mobile apps. . .
  28. 28. We  have  a  finite  ability   to  process  informa2on,   build  strategies,  create   content  at  scale,  and   achieve  performance   poten!al.
  29. 29. Algorithms, in contrast, have an almost infinite ability to process data, and deliver predictions, recommendations and content better, faster and cheaper. Image:  Wikimedia  Commons
  30. 30. And  yet  content  marke2ng   remains  largely  human  powered,   with  a  bit  of  automa2on  mixed  in. @paulroetzer www.pr2020.com
  31. 31. The future may be closer than you think.
  32. 32. NATURAL LANGUAGE GENERATION (AKA MACHINE-ASSISTED CONTENT)
  33. 33. “Powered  by  Ar2ficial  Intelligence,  Quill  is  our  advanced  natural  language  genera!on   (Advanced  NLG)  plaSorm  for  enterprise  organiza2ons  that  goes  beyond  repor2ng  the   numbers—it  creates  perfectly  wriben,  meaningful  narra!ves  for  any  intended  audience.”
  34. 34. Image:  Franck  Calzada/YouTube The AP “writes” 10x more earnings reports using Automated Insights technology
  35. 35. NATURAL LANGUAGE GENERATION CASE STUDY
  36. 36. @paulroetzer
  37. 37. Define  Founda2on  Projects Subjective analysis Internal stakeholders 10 sections 27 profile fields 132 factors Sample  Marke5ng  Score  Factor  Slider  Scale
  38. 38. A  strong  marke!ng  technology  founda2on  is  cri2cal  to  driving  performance.  Core   technologies,  when  integrated,  improve  efficiencies,  maximize  produc2vity  and  ROI,   and  create  compe22ve  advantages.  The  company  should  priori2ze  CMS  (5),  CRM  (4),   email  marke2ng  (3),  marke2ng  analy2cs  (2)  and  marke2ng  automa2on  (2).   sample key finding
  39. 39. A  strong  marke!ng  technology  founda2on  is  cri2cal  to  driving   performance.  Core  technologies,  when  integrated,  improve   efficiencies,  maximize  produc2vity  and  ROI,  and  create   compe22ve  advantages.  The  company  should  priori2ze  CMS  (5),   CRM  (4),  email  marke2ng  (3),  marke2ng  analy2cs  (2)  and   marke2ng  automa2on  (2).  
  40. 40. * Requires human writers to develop and enhance templates. Using  Natural  Language  Genera!on  (aka  Machine  Assisted)*:   50  briefs  x  15  minutes  per  brief  =  12.5  hours/month The  Diff:   37.5  hours  (at  a  cost  of  $250/month  for  the  license.) Tradi!onal  Way:     50  briefs  x  1  hour  per  brief  =  50  hours/month
  41. 41. The  Benefits   More  accurate  (eliminates  human  error)   More  briefs  published  (enables  content  at  scale)   More  cost  efficient  (shi;s  2me  to  edi2ng  only)   More  engagement   More  value  crea!on  for  members   More  new  business  opportuni!es
  42. 42. MARKETING AI COMPANIES (PLAN, CREATE, OPTIMIZE, PERSONALIZE, PROMOTE & MEASURE CONTENT)
  43. 43. @paulroetzer “Tapping  into  the  power  of  big  data,  ar!ficial  intelligence,  and  machine  learning,  our   proprietary  so;ware  can  tell  your  editorial  team  exactly  what  to  write  about.”  
  44. 44. @paulroetzer Curata  u2lizes  informa!onal  retrieval  techniques,  machine  learning,  and  natural   language  processing  to  learn  users’  content  preferences,  detect  duplicate  content,   categorize  and  classify  content,  and  predict  content  contribu!on  to  marke2ng  goals.
  45. 45. @paulroetzer
  46. 46. @paulroetzer
  47. 47. @paulroetzer
  48. 48. @paulroetzer
  49. 49. @paulroetzer Marke!ng  success  powered  by  machine  learning   Advanced  data  analy2cs  and  intelligent  tools  to  help  marketers  produce  the  right  content,     in  the  right  format,  to  target  the  right  audience  at  the  right  2me.
  50. 50. @paulroetzer
  51. 51. @paulroetzer “Cortex’s  brain  is  an  Ar2ficial  Intelligence  plaUorm  that     understands  marke!ng  content  and  predicts  how  consumers  will  react  to  that  content.”
  52. 52. “At  the  heart  of  all  of  these   algorithm-­‐enabled   revolu2ons  on  Wall  Street   and  elsewhere,  there  exists   one  persistent  goal:   predic!on—to  be  more   exact,  predic2on  of  what   other  humans  will  do.”  
  53. 53. “Imagine  a  world  where  you  can   predict  with  above  85%  accuracy   who  will  buy,  what  they  will  buy,  how   much,  what  channel  will  reach  them,   what  message  will  resonate.”       —  Amanda  Kahlow,  6sense  founder  and  CEO Source:  VentureBeat
  54. 54. “6sense  predic!ons  power  all  downstream  sales  and  marke2ng  systems  with   intelligence  on  who  is  in  market  to  buy,  what  products,  when  they  will  buy  and  where   they  are  in  the  buyer’s  journey.”
  55. 55. THE NEXT FRONTIER
  56. 56. Private investment in the AI sector has grown from $1.7B in 2010 to $14.9B in 2014 The market for AI based analytics could grow from $8.2B to $70B by 2020. — Source: BofA Merrill Lynch: Robot Revolution — Global Robot & AI Primer
  57. 57. $29.4 M $36.0 M $9.5 M Source:  Crunchbase Artificial Intelligence + Marketing $266+ M $80.0 M* $66.0 M $14.5 M $13.9 M $11.0 M $5.4 M Not  shown  above:  Cortex  =  $500k,  MarketMuse  =  $245k,  Curata=  N/A
  58. 58. “We’re in an AI spring. For our company, and I think for every company, the revolution in data science will fundamentally change how we run our business because we’re going to have computers aiding us in how we’re interacting with our customers.” — Marc Benioff Source:  FortuneImage:  Wikipedia
  59. 59. Source: Social Media Frontiers Facebook  uses  “deep  learning,”  an  AI  subfield,  to  filter  your   Newsfeed  and  recognize  faces  in  photos  you  upload,     but  that’s  only  the  beginning  .  .  .
  60. 60. Source: Social Media Frontiers hKps://research.facebook.com/ai “We’re  commiKed  to  advancing  the  field  of   machine  intelligence  and  developing  technologies   that  give  people  beber  ways  to  communicate.  In   the  long  term,  we  seek  to  understand  intelligence   and  make  intelligent  machines.”
  61. 61. search,  voice  recogni!on,  language  transla!on,  robots,  driverless  cars  .  .  .
  62. 62. Image:  Wikimedia  CommonsSource:  Business  Insider The  story  of  ar2ficial  intelligence  can’t  be  told  without  IBM  ,   which  possesses  an  es!mated  500  AI-­‐related  patents.
  63. 63. IBM  Watson  is  a  technology  plaUorm  that  uses     natural  language  processing  and  machine  learning  to  reveal  insights     from  large  amounts  of  unstructured  data Source: IBM
  64. 64. Source: Popular Science “IBM  used  machine  learning  and  experimental  Watson  APIs,   parsing  out  the  trailers  of  100  horror  movies.  It  did  visual,  audio,   and  composi2on  analysis  of  individual  scenes.  .  .  .  Watson  was  then   fed  the  full  film,  and  it  chose  scenes  for  the  trailer.  .  .  .  A  process   that  would  normally  take  weeks  was  reduced  to  hours.”  
  65. 65. "Cogni2ve  technology  is  there  to  extend  and  amplify   human  exper!se,  not  replace  it.”   —  Rob  High,  Chief  Technology  Officer,  IBM  Watson @paulroetzer • #CMWorld
  66. 66. Rather  than  simply  automa2ng  manual   tasks,  ar!ficial  intelligence  adds  a   cogni!ve  layer  that  infinitely  expands   marketers’  ability  to  process  data,   iden2fy  paKerns,  predict  outcomes,   and  build  intelligent  strategies  and   content  beber,  faster  and  cheaper. @paulroetzer • #CMWorld
  67. 67. dra;ing  social  media  updates  *  discovering  keywords  *  planning  blog  post  topics  *  wri!ng  content  *             op!mizing  content  *  cura!ng  content  *  personalizing  content  *  automa!ng  content  *  building  email   workflows  *  crea2ng  ad  copy  *  managing  digital  ad  campaigns  *  tes2ng  headlines,  landing  pages,  ads  *   scheduling/publishing  social  shares  *  predic2ng  opens,  clicks,  conversions  *  reviewing  analy!cs  *       wri2ng  performance  reports  *  recommending  content  strategies
  68. 68. and imagine if that was only the beginning . . .
  69. 69. OK, NOW WHAT? WHERE DO I GO TO LEARN MORE? HOW DO I GET STARTED WITH AI?
  70. 70. @paulroetzer Our mission is to educate modern marketers on the present and future potential of artificial intelligence, and connect them with AI-powered technologies that can drive marketing performance and transform their careers. Go to: bit.ly/CMW16-MAII
  71. 71. @paulroetzer Go to: bit.ly/CMW16-MAII
  72. 72. @TwitterHandle • #CMWorld Paul Roetzer Founder & CEO, PR 20/20 @paulroetzer • #CMWorld www.pr2020.com Copyright 2016 PR 20/20. All rights reserved.

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