My talk from brightonSEO on two big trends around keywords and a couple of practical ways to respond to them.

1. Kelvin Newman
Founder - BrightonSEO
Scary SERPs (and keyword creep)
@kelvinnewman
http://www.slideshare.net/kelvinnewman

2. @kelvinnewman
So, who is this guy?
@kelvinnewman

3. Founder of BrightonSEO
@kelvinnewman
kelvin@brightonseo.com
http://www.slideshare.net/kelvinnewman
Kelvin Newman

4. @kelvinnewman
Shhhhh, but I don’t live in
Brighton
@kelvinnewman

5. @kelvinnewman
Actually; I live in Worthing

6. @kelvinnewman
Which is famous for one thing…
@kelvinnewman
Birdman Competition where people see how far
they can jump of the pier

7. @kelvinnewman
So what is this presentation
about?
@kelvinnewman

8. @kelvinnewman
Well, this presentation isn’t
about…
@kelvinnewman

9. @kelvinnewman
So, if you use the Google
Keyword Planner you can find
some excellent keywords
“
“

10. @kelvinnewman
It’s more about getting you to
think differently about the future
of keywords.

11. @kelvinnewman
One True Answer
Part 1

12. @kelvinnewman
Start with a story

13. @kelvinnewman
Peter A. Shulman
Historian of sci, tech, and American
politics. Author of Coal & Empire.
Associate Professor of History

14. Lecturing on the
reemergence of the Ku Klux
Klan in the 1920s when a
student asked an odd
question:
@kelvinnewman

15. Was President Warren Harding a
member of the KKK?
@kelvinnewman

16. @kelvinnewman
He wasn’t

17. @kelvinnewman

18. @kelvinnewman

19. @kelvinnewman
This isn’t an isolated occurrence

20. https://theoutline.com/post/1192/google-s-featured-snippets-are-worse-than-fake-news
@kelvinnewman

21. https://theoutline.com/post/1192/google-s-featured-snippets-are-worse-than-fake-news
@kelvinnewman

22. http://searchengineland.com/googles-one-true-answer-problem-featured-snippets-270549
@kelvinnewman

23. @kelvinnewman
Bad on desktop, terrible on voice

24. https://theoutline.com/post/1192/google-s-featured-snippets-are-worse-than-fake-news

25. @kelvinnewman
Easy to mock but what can we
learn from this

26. Preference for “one
true answer”
http://searchengineland.com/googles-one-true-answer-problem-featured-snippets-270549
@kelvinnewman

27. Risk for Google but
opportunity for us
@kelvinnewman

28. @kelvinnewman
End of Keyword Precision
Part 2

29. @kelvinnewman
Not-Bloody-Provided

30. @kelvinnewman
Keyword Bloody Planner
Estimates

31. @kelvinnewman
Close-Bloody-Variants

32. @kelvinnewman
Query Re-writing

33. @kelvinnewman
It would seem Machine Learning
is involved in Query Re-writing
@kelvinnewman

34. @kelvinnewman

35. @kelvinnewman

36. @kelvinnewman
Machine learning
is sexy
And Artificial Intelligence, Deep Learning and other
sort of related things along those lines.
@kelvinnewman

37. @kelvinnewman
I studied media studies at Uni not
computer science or anything like it…
Now feels like a good time to share
@kelvinnewman

38. @kelvinnewman
Machine Learning
Machine Learning at its most basic is the practice of using algorithms to
parse data, learn from it, and then make a determination or prediction
about something in the world.
So rather than hand-coding software routines with a specific set of
instructions to accomplish a particular task, the machine is “trained” using
large amounts of data and algorithms that give it the ability to learn how to
perform the task.

39. @kelvinnewman
Deep Learning
A branch of machine learning based on a set of algorithms that attempt to
model high level abstractions in data by using a deep graph with multiple
processing layers, composed of multiple linear and non-linear
transformations.

40. Seeing the
connections
below the
surface
@kelvinnewman

41. @kelvinnewman

42. @kelvinnewman
So what are the actions?
@kelvinnewman

43. @kelvinnewman
Use some
off the shelf
options
@kelvinnewman

44. https://algorithmia.com/
algorithms/nlp/Word2Vec
@kelvinnewman

45. @kelvinnewman
Tutorials on use Machine
Learning on over 1M hotel
reviews finds interesting insights
https://blog.monkeylearn.com/machine-learning-1m-hotel-reviews-finds-interesting-insights

46. Or wait for SEO tool suites to
start doing this properly
@kelvinnewman

47. Easiest solution is to know
the space and know your
customers
@kelvinnewman

48. But just writing for users is a lazy
suggestion.
We can better understand our users
needs if we can better understand how
other websites are writing about a topic

49. @kelvinnewman
To optimise a page now you need
more than add keyphrases.

50. @kelvinnewman
You need to have all the phrases
and words they’d expect

51. Is the search query on the page and
does deserve to rank?
Old Model
@kelvinnewman

52. Does it contain the search query and
phrases used be other pages that rank
for the term and does deserve to rank?
New Model
@kelvinnewman

53. @kelvinnewman
Two hacky & clunky way of
seeing those you’d need
include.
Method 1

54. @kelvinnewman
Take the top ten results for your
query and extract the text using
something like textise.net
Method 1

55. @kelvinnewman
Bung the copy from all the
pages into a Word Cloud
Tool
I like jasondavies.com/
wordcloud/

57. @kelvinnewman
Treat the most common words
like bingo

58. @kelvinnewman
Take the top 3 results for your
query and extract the text using
something like textise.net
Method 2

59. @kelvinnewman
Create a list of all the single
words used on the page
using something like
writewords.org.uk/
word_count.asp

60. @kelvinnewman
Create a Venn Diagram of the
overlap
Method 2

61. @kelvinnewman

62. @kelvinnewman
kelvin@brightonseo.com
http://www.slideshare.net/kelvinnewman
Thanks