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Machine learning. Artificial intelligence's influence on marketing.

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Machine learning. Artificial intelligence's influence on marketing.

This presentation shows how machine learning influence marketing. The algorithm selecting content on mobile devices based on their relevance answering needs. The url internet as we know is less and less visited. The Alpha Apps are taking over. All big players are working on their own personal assistants trying to predict what we want, directly acting on our needs. So what is marketing role in future and how can you marketing when an self-learning algorithm is your audience?

This presentation shows how machine learning influence marketing. The algorithm selecting content on mobile devices based on their relevance answering needs. The url internet as we know is less and less visited. The Alpha Apps are taking over. All big players are working on their own personal assistants trying to predict what we want, directly acting on our needs. So what is marketing role in future and how can you marketing when an self-learning algorithm is your audience?

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Machine learning. Artificial intelligence's influence on marketing.

  1. 1. 1 Machine Learning Artificial intelligence’s influence on marketing Alina Hückelkamp – Razorfish
  2. 2. 2 Alina Hückelkamp Chief Strategy and Innovation Officer/ Razorfish Germany @psyxonaut
  3. 3. 3
  4. 4. 4
  5. 5. 5
  6. 6. 6
  7. 7. 7
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  9. 9. 9
  10. 10. 10
  11. 11. 11
  12. 12. Here for Tomorrow. “Everything that can be digital will be digital” – Jeff Dachis (1999), Founder Razorfish is an agency purpose-built for the digital world.
  13. 13. 13
  14. 14. 14
  15. 15. 15
  16. 16. 16 IBM Watson
  17. 17. 17
  18. 18. 18 But... How does it work?
  19. 19. 19 Machine Learning Any application where you use data (past experiences) to tune / fine-tune an algorithm for completing a task.
  20. 20. 20
  21. 21. 21
  22. 22. 22
  23. 23. 23
  24. 24. 24 Machine Learning Today
  25. 25. 25 Before Searchs and select
  26. 26. 26 Today Understand and answer
  27. 27. More Google searches take place on mobile devices than on computers. In 10 countries including the US and Japan. Source: Google
  28. 28. The Google App gets 30x as many action queries by voice as by typing. Asking your virtual assistant. Source: Google
  29. 29. 29 What do they do on their phones? www.bild.de www.nyt.com www.buzzfeed.de www.techcrunch.de www.cnn.com www.spiegel.de
  30. 30. 30 The reality: Social Apps are killing the url web Apps = 90% of time spent on device Social/IM=112 min Web=28 min Other apps=9 min
  31. 31. 31 Less frequent, long interactions. High text input. Frequent short to medium Interactions. Moderate text input Very short, very frequent interactions. Low to no text input. Why? Devices are getting smaller. Learning algorithm help to curate.
  32. 32. 32 Today: Learning algorithms place information where we go to see our friends
  33. 33. 33 More features are being inserted into these apps, to eat even more of our time.
  34. 34. 34
  35. 35. 35 And they are getting better in fulfilling my needs because they observe and learn.
  36. 36. 36 GAFA is focusing on customer needs only. A one stop destination for all consumer needs.
  37. 37. 37 GAFA are Gatekeeper. The Layer beteween you and your customer. Company Consumers
  38. 38. 38 Where is machine learning taking us next?
  39. 39. 39 You can add a little something here
  40. 40. 40 All major companies are working on a digital assistant
  41. 41. 42 Platforms Cortana Google Now Siri Alexa Devices
  42. 42. 43 Different companies, same functionality. For now.
  43. 43. 44
  44. 44. 45 ... But Facebook M stands out
  45. 45. 46 It doesn‘t only tell us the weather – it accomplish tasks – like purchasing items, or booking tables
  46. 46. 47 It‘s powered by artificial intelligence, with people backing it up to solve problems the AI can‘t.
  47. 47. 48 Digital Assistants will be center to peoples life and learn more and more about its users Cortana Google Now Siri Alexa M
  48. 48. 49 Machine learning will become so advanced and trusted, users will allow it to complete increasingly complex tasks for their owners
  49. 49. 50 So what can marketers do?
  50. 50. 51 #1 While the Internet is more and more an Social App Web, don‘t forget to be where your customers are and understand the algorithm. Social 112 min/day Web 28 min/day
  51. 51. 52 #2 Should I still build Apps? Well there is still room for new apps, as long as you find a niché – but it‘s getting crowded. News Communication Image Sharing ShoppingNavigation Industry App? ?
  52. 52. 53 #3 – Are Alpha Apps cutting the line between me and my customer? They are getting more and more between you and them, but they have smart tools and invest a lot. Collaborate. Create benefit. Facebook messenger lets businesses communicate with consumers
  53. 53. MyLincoln integrated in Google Now. MyLincoln Native AppGoogle Now launched Open API
  54. 54. 55 #4 – Machines can‘t predict taste or recommend emotional products? Machines are getting better. Start trusting them. Provides playlists curated by humans Provides personalized playlists curated by an algorithm
  55. 55. 56 „ It felt like an intimate gift from someone who knew my tastes inside and out, and wasn’t afraid to throw me a curveball. But the mix didn’t come from a friend — it came from an algorithm.“ – The Verge on Spotify Discover Weekly
  56. 56. 57 „Algorithms alone can’t do that emotional task. You need a human touch.“ - Jimmy Iovine of Apple Beats Music on music curation
  57. 57. 58
  58. 58. Man-Machine Collaboration Tapping into expert knowledge to derive personalization treatments Data Scientist Data Scientist let the machine find all art related content. Using other existing algorithm to preselect relevant and contemporary art. Program the algorithm to learn from the art expert on how to select, segment and judge. Learn taste. Art Experts Look at the Articles and decide of relevant or not. Segment and add meta-information. Check Machine Output, correct and and re-train if necessary. Help to segment target groups and curate on taste
  59. 59. 60 #5 – How can I give my information to the Gatekeeper? Don‘t hide it, optimize for it.
  60. 60. 61
  61. 61. 62
  62. 62. 63 Who is our Audience?
  63. 63. 64 Your audience is already a machine.
  64. 64. 65
  65. 65. 66 We are here
  66. 66. 67 So what could the future look like?
  67. 67. 68
  68. 68. 69 Dankeschön. @psyxonaut

Notas do Editor

  • Chess... For hundreds of years, the game of chess has been the mark of human intelligence.

    Up untill 1997, where one of the the most famous games ever took place. Not between two men, but between man and computer.
  • “Razorfish is built to handle the kinds of challenges you’re facing”

    Wording to be finalized. Meant to convey in simple terms what we are and why we’re different.
  • Chess... For hundreds of years, the game of chess has been the mark of human intelligence.
    Up untill 1997, where one of the the most famous games ever took place. Not between two men, but between man and computer.
  • In 1997, IBM and Garry Kasparov, amongst the best chess players of all time, met in a legendary game.
  • While the legendary game that was played between Kasparov and Deep Blue is the one remembered, there was actually a game which took place one year earlier, a game which Deep Blue lost. Kasparov said that while the machine was playing mathematically correct, it was predictable. For the follow up game, IBM had the machine scan past games of chess between grand master, and had it practive against other champions of chess.
  • In 2011, IBM had created a new computer called watson which was not made to play chess, but to be able to answer questions asked in natural language.

    And like chess before it, IBM now wanted to crack what is considered to be one of the most complex applications of questions asked in natural language – Jeopardy!

  • This is how they did it.
  • So what is machine learning?

    IBM used machine learning to have Watson analyze thousands of games, and practiced against real people to learn how to be better at chess.
  • https://www.youtube.com/watch?v=lL16AQItG1g
    That‘s why cars soon can drive by themselve (there are still in the trainingscamp)
  • https://www.youtube.com/watch?v=lL16AQItG1g
  • But a chess playing machine, or a machine who can win Jeopardy isn’t useful to most. Let’s have a look at how machine learning exists in our lives today.
  • Up until recently, computer searches have only spit out a list of 10 blue links, leaving it to the user to find the answer amongst these links.

  • But Google has used machine learning to help people not only find 10 blue links, but the answer directly.
    So you don‘t have to click anymore. Just read the answer through Google.

  • http://adwords.blogspot.de/2015/05/building-for-next-moment.html
  • http://think.storage.googleapis.com/docs/top-3-tech-trends-marketers-should-watch-in-2015_infographics.pdf
  • Are they using the web?

    No they‘re not.
  • The reality is, 90% of all mobile time is spent in apps. The web only has 10% of a users time.

    http://www.marketingcharts.com/online/90-of-us-mobile-internet-time-said-spent-in-apps-58693/
  • Why? Smaller screens are more difficult to navigate, so users rely on learning algorithms to deliver them information without having to go through page after page or app after app on the hunt for info.
  • Facebooks algorithm learns your behaviours and habits, and delivers you content right into your newsfeed.
  • These social apps are gaining more and more features
  • This means we are using other apps less and less.
  • These social apps are becoming so called „Alpha Apps“ a one stop destination that becomes like an operating system existing independently of platform – no matter if it‘s iOS or Android.
  • You might think GAFA only builds alpha apps for user convenience. But they don‘t. Gafa are all fighting over internet user‘s digital time and money from which they make their profits - – to lock us into their system.

  • Digital Assistants are not a fluke. Every major company is working on them.
  • Although these assistants are made by different companies, their functionality is very similar.

    ---------
    Extra:

    Key for future of each assistant lies in each companies mission statement:

    Microsoft: „To empower every person and every organization on the planet to achieve more“
    – Microsoft‘s Cortana is likely to focus on becoming an assistant which will help you throughout your workday. Windows has a tradition with being strong in work environment – corporate PCs are most often windows, and Microsoft office will help people get through their work day in most countries.

    Google: „Organizing the world‘s information“
    Google‘s personal assistant is aiming to organize your private data and give it to you at the right moment. If you think about it, serving you airline tickets or showing you how long the drive home from work is – it‘s all organizing and serving your information.

    Apple: „Make great products“
    Apple‘s mission statement is perhaps the vaguest one, but they are trying to create a digital assistant which is not only smart, but excudes a distinct personality in every interaction – a qualitative product.

    Amazon: „To be earth‘s most customer centric company, where customer can find and discover anything on Amazon.„
    Amazon‘s assistant is based around „Customer“. Amazons end goal, and we‘re seeing that today, is for their assistant to be the perfect home butler, which makes anything possible within the home, no matter if it‘s playing music or ordering home washing detergent.
  • Facebook M moves beyond setting a calendar appointment, or telling the weather. It can actually complete tasks.
  • It‘s powered by artificial intelligence, but backed up by humans – if the AI fails to complete a task, it‘s send to a human helper. But what‘s really interesting is that the computer learns how to solve the task by analyzing the human. This means that M can improve over time, through machine learning.
  • While digital assitants functionality today are limited, they will improve over time.
  • In the future, the digital assistants will know their humans so well, their „owners“ will trust them to do decisions for them.
  • There is only so much room on the home screen – if you don‘t think you can create something truly useful, which will end up on the home screen, work within the other apps.
  • http://www.bloomberg.com/news/articles/2015-10-07/facebook-plunges-into-home-repair-matchmaking-service
  • http://www.autoconnectedcar.com/2015/02/mylincoln-mobile-app-now-has-google-now-suggestions/
  • http://www.theverge.com/2015/9/30/9416579/spotify-discover-weekly-online-music-curation-interview
  • http://www.theverge.com/2015/9/30/9416579/spotify-discover-weekly-online-music-curation-interview
  • How getting product information in the future might work, on websites or via Google Now/Siri


    https://www.bmwi3.co.za/
  • How a car brand focused on safety might work with your digital assistant.


    https://www.bmwi3.co.za/
  • And soon, machines decide or influence our purchasing decisions.

    Is your business ready to negotiate with a machine?
  • And soon, machines decide or influence our purchasing decisions.

    Is your business ready to negotiate with a machine?
  • We are here right now, and with the help of machine learning, the speed ot innovation is accelerating so that we can achieve things we did not think were possible before.
  • As apps are getting more functionliaty,

    Samantha fullfilling a task - Knows it better etc...

    One chart speaking with a robot! They are negotiating what you will buy in the future. -algorithm fight in the middle.

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