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Marketing in the Machine Age: The Path to a More (Artificially) Intelligent Future

Presented at Emarsys Evolution, Aug. 3, 2017

Consider how much time your team spends reviewing marketing analytics, generating data-driven insights and recommendations, and devising intelligent strategies. Now imagine if a machine performed the majority of those activities and a marketer's primary role was to enhance rather than create.

Machines are not going to replace marketers in the near term, but artificial intelligence is accelerating us toward a more intelligently automated future. Come explore the present and future potential of artificial intelligence, and discover AI-powered technologies that can drive marketing performance and transform your career.

* 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.

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Marketing in the Machine Age: The Path to a More (Artificially) Intelligent Future

  1. 1. marketing in the machine age the path to a more (artificially) intelligent future 8-3-17 paul roetzer founder & CEO | PR 20/20 creator | Marketing Artificial Intelligence Institute@PaulRoetzer Emarsys Evolution #EmarsysEvolution
  2. 2. Can we automate content creation through artificial intelligence (AI)? @PaulRoetzer
  3. 3. Can we use machines to write blog posts at scale? Image: Franck Calzada/YouTube
  4. 4. The Associated Press “writes” 10x more earnings reports using Automated Insights NLG* technology.10x *NLG = natural language generation@PaulRoetzer
  5. 5. We implemented NLG with Google Analytics reports, cutting analysis and production time by more than 80%. @PaulRoetzer Image: Automated Insights
  6. 6. What we’ve learned has dramatically altered my view of what’s possible today, and in the near future. Image: Timothy Neesam
  7. 7. Consider how much !me your marke2ng team spends . . . crea%ng ad copy managing digital ad campaigns tes%ng headlines, landing pages, ads scheduling/publishing social shares predic%ng opens, clicks, conversions reviewing analy5cs wri%ng performance reports recommending content strategies dra7ing social media updates discovering keywords planning blog post topics wri5ng content op5mizing content cura5ng content personalizing content automa5ng content building email workflows Copyright 2017 PR 20/20. All rights reserved. @PaulRoetzer
  8. 8. Now imagine if machines performed the majority of those activities, and a marketer’s primary role was to enhance rather than create. @PaulRoetzer
  9. 9. Artificial intelligence is accelerating us toward a more intelligently automated future . . .
  10. 10. “The science of making machines smart.” — Demis Hassabis, Co-Founder & CEO of DeepMind (which in turn augments human knowledge and capabilities) Source: Rolling Stone
  11. 11. Source: John Koetsier
  12. 12. an algorithm is a set of instructions that tells the machine what to do. @PaulRoetzer
  13. 13. Except with AI the machine can create its own algorithms, determine new paths, and unlock unlimited potential to advance marketing, and mankind.
  14. 14. THEN send three-part email campaign. IF visitor downloads ebook, @PaulRoetzer
  15. 15. What if there are 10,000 downloads, across five personas, originating from multiple channels (social, organic, paid, direct) that require personalized emails and website experiences based on user history? @PaulRoetzer
  16. 16. the marketing automation we see today is, ironically, largely manual. @PaulRoetzer
  17. 17. Marketing automation platforms save time, increase efficiency and productivity, and drive performance. BUT . . . @PaulRoetzer
  18. 18. Marketing automation platforms generally do NOT provide deep insights into data, recommend actions, predict outcomes or create content. @PaulRoetzer
  19. 19. Source: BBC: Is A.I. the Problem or the Solution?
  20. 20. AI takes very specific (narrow) and complex data-driven problems, and then devises and executes solutions.
  21. 21. 90% of all data in the world has been created in the last 2 years Source: IBM
  22. 22. Marketers have access to data from dozens of sources: social monitoring, media monitoring, web analytics, email, call tracking, sales, advertising, remarketing, ecommerce, mobile apps. . .
  23. 23. We have a finite ability to process information, build strategies, create content at scale, and achieve performance potential. @PaulRoetzer
  24. 24. Image: Wikimedia Commons Algorithms, in contrast, have an almost infinite ability to process data, and deliver predictions, recommendations and content better, faster and cheaper.
  25. 25. @paulroetzer And yet marketing remains largely human powered, with a bit of automation mixed in.
  26. 26. The future may be closer than you think.
  28. 28. @paulroetzer 60% of all trades are executed by computers with little or no real-time oversight from humans. Source: Christopher Steiner, Automate This
  29. 29. @paulroetzer avg 120 stops/day
  30. 30. what is the possible number of alternatives for ordering those stops? @PaulRoetzer
  31. 31. 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
  32. 32. “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 combinations.” Jack Levis Senior director of process management, UPS Source: Wall Street Journal
  33. 33. NETFLIX uses algorithms to suggest content and manufacture shows based on subscriber viewing habits and preferences. Source: Ne*lix Tech Blog
  34. 34. 75% of what people watch on Netflix is from some sort of algorithm-generated recommendation Source: Ne*lix Tech Blog@PaulRoetzer
  35. 35. Epagogix algorithms analyze movie scripts to predict how much money they will make at the box office and offer recommendations on how to make them more marketable and profitable, including through changes to plot lines, settings, character roles and actors.
  36. 36. Source: Tesla
  37. 37. @PaulRoetzer
  39. 39. 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 . . . @PaulRoetzer
  40. 40. Source: Social Media Frontiers h?ps:// “We’re committed to advancing the field of machine intelligence and developing technologies that give people better ways to communicate. In the long term, we seek to understand intelligence and make intelligent machines.” @PaulRoetzer
  41. 41. search, voice recogni*on, language transla+on, robots, driverless cars . . . @PaulRoetzer
  42. 42. “Alphabet Inc.’s Google named the head of its artificial-intelligence research to run its search engine, demonstrating the importance of the rapidly evolving technology to the company’s main profit engine.” Source: The Wall Street Journal @PaulRoetzer
  43. 43. Source: Campaign In October, lingerie retailer Cosabella replaced its digital agency with an AI platform named 'Albert'. Since then it has more than tripled its ROI and increased its customer base by 30 percent. @PaulRoetzer
  44. 44. Source: Popular Science “IBM used machine learning and experimental Watson APIs, parsing out the trailers of 100 horror movies. It did visual, audio, and composition 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.” @PaulRoetzer
  45. 45. Source: The Drum “Content creation is something that we have been doing for a very long time . . . what I want to start experimenting with is automated narratives.” This experimentation will explore how AI can be applied to everything from choosing music, updating social media and even writing scripts . . . (Mariano Bosaz, Coca-Cola’s global senior digital director, interview with AdWeek) @PaulRoetzer
  46. 46. Source: The Guardian “A machine will win a Pulitzer one day,” predicts Kris Hammond from Narrative Science, a company that specialises in natural language generation. “We can tell the stories hidden in data.”
  47. 47. "Cognitive technology is there to extend and amplify human expertise, not replace it.” — Rob High, Chief Technology Officer, IBM Watson @PaulRoetzer
  48. 48. 3 THINGS TO KNOW
  49. 49. #1 It is still very early. Many of the rising AI tech companies have significant venture capital funding, but limited market success to prove the products work and that the models are scalable.
  50. 50. #2 Artificial intelligence requires massive amounts of data (structured and unstructured) and customized solutions, so large enterprises are more likely to see short-term benefits from AI investments.
  51. 51. #3 There is a push to make AI technology more affordable and accessible. The challenge will be finding technical talent capable of building and executing AI solutions.
  53. 53. #1 Evaluate repetitive, manual marketing tasks that could be intelligently automated.
  54. 54. Source: Timothy Neesom There are dozens of AI-powered marketing tools that you can use to plan, create, optimize, personalize, promote, measure and analyze content.
  55. 55. #2 Assess opportunities to get more out of your data— discover insights, predict outcomes, devise strategies, personalize content and tell stories at scale.
  56. 56. @PaulRoetzer
  57. 57. @PaulRoetzer
  58. 58. #3 Consider the AI capabilities of your existing marketing technology, and explore the potential of emerging AI solutions.
  60. 60. dra$ing social media updates discovering keywords planning blog post topics wri4ng content op4mizing content cura4ng content personalizing content automa4ng content building email workflows crea3ng ad copy managing digital ad campaigns tes3ng headlines, ads scheduling social shares predic3ng conversions reviewing analy4cs wri3ng performance reports recommending strategies
  61. 61. and imagine if that was only the beginning . . .
  62. 62.
  63. 63. Paul Roetzer Founder & CEO | PR 20/20 Creator | Marketing AI Institute