Will Critchlow - The Future of Search
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The document discusses the future of search and how search engines are moving from solely matching keywords to understanding user intent through both explicit and implicit signals. It provides tips for content marketers to succeed in this new search landscape, including building content optimized for mobile and testing content to ensure it provides value to users. Machine learning is increasingly powering search, and the document suggests testing content variations to understand what provides value to both users and search algorithms.
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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