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Will Critchlow - The Future of Search
- 1. INBOUND15 The Future of Search And what you should be doing about it right now Will Critchlow CEO, Distilled
- 2. INBOUND15 1 What’s going on with search?
- 3. INBOUND15 Keywords become intents Everything used to be about matching the words you use to search with words on a web page
- 5. INBOUND15 This query really shouldn’t work
- 7. INBOUND15 See reddit thread for more
- 8. INBOUND15 When someone searches for “best” • From Google Trends
- 9. INBOUND15 They probably don’t mean a page that says “best”
- 10. INBOUND15 Watch this presentation for more
- 11. INBOUND15 “london tube stations” query Old Query Model
- 12. INBOUND15 explicit query implicit query iPhone user, on street in London “london tube stations” New Query Model
- 19. INBOUND15 User signals and personalization The unexpected power of machine learning at Google
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- 28. INBOUND15 Different “algorithms” for different queries See Dr. Pete’s presentation
- 29. INBOUND15 COMPLEX SYSTEMS Even Google engineers don’t know why one page ranks above another
- 30. INBOUND15 The growth of mobile You’ve heard all this before
- 31. INBOUND15 The iPod revolutionized an industry Source: Business Insider
- 32. INBOUND15 The iPhone makes it look slow Source: Business Insider
- 33. INBOUND15 Then came the iPad Source: Business Insider
- 34. INBOUND15 Wow. Android. Source: Business Insider
- 35. INBOUND15 And it keeps going Source: Business Insider
- 36. INBOUND15 Source: Benedict Evans The point is social is mobile
- 37. INBOUND15 So content marketing is mobile Source: Recent B2B Distilled campaign
- 38. INBOUND15 Let’s look at a viral loop
- 40. INBOUND15 Bunch of people see it.
- 41. INBOUND15 At least some think it’s cool.
- 42. INBOUND15 If on average more than 1 new share happens each time it is shared, then it is “viral” (k > 1)
- 43. INBOUND15 What if it sucks on mobile?
- 44. INBOUND15 It sucks for more than half
- 45. INBOUND15 Half as many share it
- 46. INBOUND15 k has to be twice as big to achieve virality
- 47. INBOUND15 This isn’t about disappointing 10% …or even 50% of mobile visitors
- 48. INBOUND15 It’s the difference between… …getting a couple thousand visitors and getting millions
- 49. INBOUND15 2 Practical tips and tactics to succeed
- 50. INBOUND15 Don’t build things differently. Build different things. What does content marketing look like “mobile first”?
- 51. INBOUND15 This is a creative piece we made
- 52. INBOUND15 This view is probably more important
- 53. INBOUND15 Quick tip: Right-click → inspect element. Click on mobile icon.
- 54. INBOUND15 Mobile emulation You can choose a device and speed filters, try out touch responses and more
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- 57. INBOUND15 It was made in 2012 so this isn’t so bad
- 58. INBOUND15 The answer is not a responsive animation
- 59. INBOUND15 No. Probably still not the answer
- 60. INBOUND15 • Simple • Unexpected • Concrete • Credible • Emotional • Stories
- 61. INBOUND15 • Simple • Unexpected • Concrete • Credible • Emotional • Suitable - for your medium • Stories
- 62. INBOUND15 • Simple • Unexpected • Concrete • Credible • Emotional • Suitable - for mobile • Stories
- 63. INBOUND15 And how do we attack machine learning? Let’s make the users happy in order to make the algorithms happy
- 64. INBOUND15 a) Tips from conversion rate optimization Let’s make the users happy in order to make the algorithms happy
- 65. INBOUND15 Optimize for what would happen if you did rank Do I click? Do I like what I see? Do I get what I want?
- 66. INBOUND15 #1 #2 #3 #4 #5 #1 #2 Your site #4 #5 A B It’s possible Google is testing user happiness directly
- 67. INBOUND15 Even if Google isn’t testing this directly These are the signals that Google is optimizing for
- 68. INBOUND15 ‘Traditional’ CRO A/B testing is user oriented
- 70. INBOUND15 Discovery Finding out what people like and dislike is often the most important part, and doesn’t have to be aimed at “conversions”
- 71. INBOUND15 Test against each of these stages Do I click? Do I like what I see? Do I get what I want?
- 72. INBOUND15 Note: what makes users happy may not please Google
- 73. INBOUND15 b) A/B testing for Google Without breaching their guidelines
- 74. INBOUND15 Check out this post from Pinterest’s engineering blog
- 75. INBOUND15 SEO A/B testing page oriented
- 76. INBOUND15 Consider typical traffic data
- 77. INBOUND15 Read Ben Estes’ blog post for more We can extract:
- 79. INBOUND15 ...and trend We can extract:
- 80. INBOUND15 Then we can make forecasts (Dotted line = forecast, blue area = confidence interval)
- 81. INBOUND15 We can detect anomalies We use this on our client-only ops platform to spot unexpected changes
- 83. INBOUND15 It’s hard to make these kinds of changes:
- 84. INBOUND15 But there are real benefits
- 85. INBOUND15 1 Optimise for actual Google preferences (rather than guessing how Google will interpret user preferences)
- 86. INBOUND15 2 Avoid wide scale losses from unsuccessful tests
- 88. INBOUND15 One more thing… We have an early private beta of a product to do SEO split testing. Contact me if you’re interested