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-- President of Western Union, 1876
(to Alexander Graham Bell)
This ‘telephone’ has too many
shortcomings to be seriously
...
-- New York Times, 1936
A rocket will never be able to
leave the Earth’s atmosphere
-- Microsoft CEO, Steve Balmer, 2007
There’s no chance that the
iPhone is going to get any
significant market share.
-- Nobel Prize-winning physicist Niels Bohr
It's hard to make predictions,
especially about the future
In 2013
I talked about:
This query really shouldn’t work
But it does
In 2014
I talked about:
VISION: STRONG AI
REALITY: WEAK AI
2015:
what we need to change in
our campaigns
brought to you by...
WHAT DOES GOOGLE
WANT?
WILL CRITCHLOW, FODM 2015
Results are heavily
personalised and contextual
(best shown via voice search - see this blog post)
1
Different
“algorithms” for
different queries
See Dr. Pete’s presentation
2
Even Google engineers
don’t know why one page
ranks above another
(Complex systems)
3
The more techniques mimic human thought, the less explainable they are
Image source: The Analytics Store
Tricks
Rules (set
by Google)
Best
practices
ML /
Panda
Tricks
Rules (set
by Google)
Best
practices
ML /
Panda
Towards AI
We are
here
See Kelvin’s excellent presentation for more on this
All this means you need to
be TESTING
So. Two kinds of testing
Google is aiming for
satisfied users
We can test against the users, or
against Google
GOOGLEBOT
For users: “CRO”
1
There are some pitfalls
BUT: Google’s proxies for “quality” aren’t perfect
e.g. duplicated content can be a great user experience
It’s hard to measure user “happiness”
Satisfied
Delighted
Worn down
For googlebot: “SEO testing”
2
Say with me:
Correlation does not imply
…?
...causation. Wait. What?
Further reading for those interested:
● Predicting the present with Bayesian
structural time ser...
Consider typical traffic data
Read Ben Este’s blog post for more
We can extract:
Read Ben Estes' blog post for more
Seasonality...
We can extract:
Read Ben Este’s blog post for more
...and trend
We can extract:
Then we can make forecasts
(Dotted line = forecast, blue area = confidence interval)
We can detect anomalies
We use this on our client-only ops platform to spot unexpected changes
Forecast is
correct Beats the
forecast
It’s not all roses
It’s hard to make these kinds of changes:
Check out this post from Pinterest’s
engineering blog
Haven’t worked out how to test
internal linking
Where the effect propagates throughout the site
But it is powerful
Optimise for actual Google
preferences
(rather than guessing how Google will interpret user preferences)
1
Avoid wide scale losses
from unsuccessful tests
2
In short:
THANK YOU
@willcritchlow
One more thing...
One more thing...
We have an early private beta of a product
to do SEO split testing. Come see me
afterwards if you are in...
Speaker
photo
goes
here
WILL CRITCHLOW
CEO and Co-Founder, Distilled
will.critchlow@distilled.net
@willcritchlow
What does Google want? Future of Digital Marketing 2015
What does Google want? Future of Digital Marketing 2015
What does Google want? Future of Digital Marketing 2015
What does Google want? Future of Digital Marketing 2015
What does Google want? Future of Digital Marketing 2015
What does Google want? Future of Digital Marketing 2015
What does Google want? Future of Digital Marketing 2015
What does Google want? Future of Digital Marketing 2015
What does Google want? Future of Digital Marketing 2015
What does Google want? Future of Digital Marketing 2015
What does Google want? Future of Digital Marketing 2015
What does Google want? Future of Digital Marketing 2015
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After focusing in previous years on the future of search technologies, this presentation focuses instead on the future of marketing for search.

What do we need to change about our marketing to continue to appeal to a changing Google?

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What does Google want? Future of Digital Marketing 2015

  1. 1. -- President of Western Union, 1876 (to Alexander Graham Bell) This ‘telephone’ has too many shortcomings to be seriously considered as a means of communication
  2. 2. -- New York Times, 1936 A rocket will never be able to leave the Earth’s atmosphere
  3. 3. -- Microsoft CEO, Steve Balmer, 2007 There’s no chance that the iPhone is going to get any significant market share.
  4. 4. -- Nobel Prize-winning physicist Niels Bohr It's hard to make predictions, especially about the future
  5. 5. In 2013 I talked about:
  6. 6. This query really shouldn’t work
  7. 7. But it does
  8. 8. In 2014 I talked about:
  9. 9. VISION: STRONG AI
  10. 10. REALITY: WEAK AI
  11. 11. 2015: what we need to change in our campaigns
  12. 12. brought to you by... WHAT DOES GOOGLE WANT? WILL CRITCHLOW, FODM 2015
  13. 13. Results are heavily personalised and contextual (best shown via voice search - see this blog post) 1
  14. 14. Different “algorithms” for different queries See Dr. Pete’s presentation 2
  15. 15. Even Google engineers don’t know why one page ranks above another (Complex systems) 3
  16. 16. The more techniques mimic human thought, the less explainable they are Image source: The Analytics Store
  17. 17. Tricks Rules (set by Google) Best practices ML / Panda
  18. 18. Tricks Rules (set by Google) Best practices ML / Panda Towards AI We are here
  19. 19. See Kelvin’s excellent presentation for more on this
  20. 20. All this means you need to be TESTING
  21. 21. So. Two kinds of testing Google is aiming for satisfied users
  22. 22. We can test against the users, or against Google GOOGLEBOT
  23. 23. For users: “CRO” 1
  24. 24. There are some pitfalls
  25. 25. BUT: Google’s proxies for “quality” aren’t perfect e.g. duplicated content can be a great user experience
  26. 26. It’s hard to measure user “happiness” Satisfied Delighted Worn down
  27. 27. For googlebot: “SEO testing” 2
  28. 28. Say with me: Correlation does not imply …?
  29. 29. ...causation. Wait. What? Further reading for those interested: ● Predicting the present with Bayesian structural time series [PDF] ● Inferring causal impact using Bayesian structural time series [PDF] ● CausalImpact R package ● Finding the ROI of title tag changes
  30. 30. Consider typical traffic data
  31. 31. Read Ben Este’s blog post for more We can extract:
  32. 32. Read Ben Estes' blog post for more Seasonality... We can extract:
  33. 33. Read Ben Este’s blog post for more ...and trend We can extract:
  34. 34. Then we can make forecasts (Dotted line = forecast, blue area = confidence interval)
  35. 35. We can detect anomalies We use this on our client-only ops platform to spot unexpected changes
  36. 36. Forecast is correct Beats the forecast
  37. 37. It’s not all roses
  38. 38. It’s hard to make these kinds of changes:
  39. 39. Check out this post from Pinterest’s engineering blog
  40. 40. Haven’t worked out how to test internal linking Where the effect propagates throughout the site
  41. 41. But it is powerful
  42. 42. Optimise for actual Google preferences (rather than guessing how Google will interpret user preferences) 1
  43. 43. Avoid wide scale losses from unsuccessful tests 2
  44. 44. In short:
  45. 45. THANK YOU @willcritchlow
  46. 46. One more thing...
  47. 47. One more thing... We have an early private beta of a product to do SEO split testing. Come see me afterwards if you are interested
  48. 48. Speaker photo goes here WILL CRITCHLOW CEO and Co-Founder, Distilled will.critchlow@distilled.net @willcritchlow
  • JAKenny

    Jun. 16, 2015
  • danielsy82

    Jun. 14, 2015
  • aJoutsi

    Jun. 12, 2015

After focusing in previous years on the future of search technologies, this presentation focuses instead on the future of marketing for search. What do we need to change about our marketing to continue to appeal to a changing Google?

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