From past experiences with data, Dave knows relying on your gut can be a mistake. Instead, we need to take comfort in the validation of solid data to ensure we’re making profitable decisions. Sharing real client examples, Dave will run through the essential steps: how to decide on a hypothesis, create conditions, and gather data.

1. Data driven SEO
David Sottimano
Searchlove 2014

2. Can a post rank solely by having keywords in the URL?

3. Yep.

4. What does meta NOINDEX do?

5. Removes a page from the index..

6. But it can lower Googlebot crawl rate too.

7. Are meta keywords actually useful?

9. Don’t be silly.

10. Data driven SEO Using data to win arguments
David Sottimano
Searchlove 2014

11. Do this.
Because.
{Insert Matt Cutts video link}

12. Caveat, caveat, caveat….

13. Meaningful, conclusive data is hard to come by.

14. Algorithms can be specific to queries.

15. http://searchengineland.com/google-pay-day-loan-algorithm-google-search-algorithm-update-to-target-spammy-queries-162941

16. Data we need is out of reach.

17. Actual click through rates?
Actual bounces back to search results?

18. Our “good” isn’t Google’s “good”

20. Clues are scarce, and often vague.

21. Source: http://insidesearch.blogspot.com.es/2012/04/search-quality-highlights-50-changes.html

22. Would you trust the information presented in this article?
http://googlewebmastercentral.blogspot.co.uk/2011/05/more-guidance-on-building-high-quality.html

23. Presence of author
Presence of author information
Presence of author image

24. Presence of logo
Presence of contact information
Presence of social proof

25. This is why we need a data driven approach.

26. Because “best practice” isn’t a good enough answer.

27. Throwing stuff against the wall doesn’t make us any wiser!

28. Be curious!
Question everything!

29. More input, less valuable output

30. Sometimes, simple is best.

31. How’s this idea guys?

32. It’s pretty shit.
*not actually what they said

33. How I completely failed* to win arguments before.
*pretty much all the time

35. This could have been avoided.

36. If I had done this…
Keyword
If you move off page 1
Money you will lose
Keyword 1
-3,000 visits
-$10,000
Keyword 2
-2,000 visits
-$7,500
-5,000 visits per month
-$17,500 per month

37. My first time.

38. “We’re going International, what do we do with hreflang?”

39. Get the right people to the right pages in search &
Don’t screw up rankings / traffic
Hreflang, canonical or both?

41. Okay, test it.

42. > 2
Analytics
WMT
Rank tracking
Logs
Testing configuration

43. Did you know Distilled had an Australian office?

44. Think about all the variants you want to test first

45. Ask for testing methodology feedback.

46. Wait.
How will I know if it worked or not?

47. 1)Rankings
2)Organic traffic
3) The right pages display in the right countries

48. Custom reports

49. Fancy shmancy segmentation

50. mmm custom dashboards

51. Share it with clients to follow along.

52. Set it and move on. Remind yourself!

53. So, what happened with the hreflang project?

54. No conclusive ranking improvements Display issues completely corrected

55. A few tips.

56. Scenario1: I forgot to track the data.

57. Historical search results
http://www.semrush.com/info/gmail+download+all+attachments+(source)?domain=davidsottimano.com&position=4&ts=1413494980

58. Historical screenshots
http://www.screenshots.com/
https://archive.org/web/

59. Historical rankings (specific keywords)
http://www.spyfu.com/Ranking

60. Scenario 2: How do I find examples around the web?

61. Brilliant source code search, by Nerdydata.com
http://nerdydata.com/

62. Peek by Linkrisk. Search by SEO metrics.
http://linkrisk.com/peek/

63. Scenario 3: I can’t open the entire CSV in Excel.
No, I don’t know how to code.

64. No problemo.

65. Use one of these.
http://delimitware.com/
*windows 7 >
http://recsveditor.sourceforge.net/csv02.htm *independent

66. Scenario 4: I need to gather data from webpages.
I don’t know how to code.

67. Scraping is fun, really fun.
https://import.io/
http://scrapinghub.com/scrapy-cloud

68. The (highly experimental) future

69. Search is becoming too complex.

70. Why are we trying to analyse vast amounts of machine data?
Why not fight fire with fire?

71. I had goals…
Reverse engineer why Distilled blog posts do well in search.
And predict how successful new blog posts would be (organic traffic)

72. I foolishly expected...
and failed.

74. URL Majestic Status
URL Majestic CitationFlow
URL Majestic TrustFlow
URL Majestic Ext Back Links
URL Majestic Ref Domains
URL Mozscape Domain Authority
URL Mozscape Page Authority
URL Mozscape External Equity Links
URL Mozscape MozRank
URL Mozscape MozTrust
URL Mozscape Subdomain External Links
URL Mozscape RootDomain External Links
URL Mozscape Juice Passing Links
URL Mozscape Subdomains Linking
URL Mozscape Root Domains Linking
URL Mozscape Links
URL Mozscape Subdomain Subdomains Linking
URL Mozscape Root Domain Root Domains Linking
URL Mozscape Subdomain MozRank
URL Mozscape RootDomain MozRank
URL Mozscape Subdomain MozTrust
URL Mozscape Root Domain MozTrust
URL Mozscape External MozRank
URL Mozscape Subdomain External Domain Linking Juice
URL Mozscape Root Domain External Domain Juice
Reading Time
Sentiment
Sentiment Score
Dale-Chall Score
Flesch Kincaid Grade Level
Flesch Kincaid Reading Ease Score
Flesch Kincaid Reading Ease
Gunning Fog Score
Smog Index
Images
Images with Alt
Images without Alt
Videos
External Link Count
Internal Link Count
Total Link Count
Author
Author URL
Robots File Allowed
Robots Meta
Robots HTTP Header
Canonical HTTP Header
Canonical Head
Date published
Year published
Alchemy Sentiment score
Alchemy top concept
Alchemy top keywords
HTTP Status
Redirected
Original HTTP Status Code
Original HTTP Status
Content Type
Content Length
URL Google Indexed
Hash
HTML Length
Text Length
Text to HTML Ratio
Title
Title Length
Description
Description Length
Word Count
Sentence Count
Header Count
Paragraph Count
Last cached date
# likes
# shares
# tweets
# retweets
# g+
Theme (custom)
Type (custom)
Alchemy entity
Sessions
Bounce rate

75. I used organic sessions as my objective field, to classify what was good/bad.

76. Mean
Good
Bad
0
~16,000
~110

77. < 20%
90% >
80
70
60
50
40
30
Not so interesting

80. So, longer posts = profit?

85. I fed garbage in, and got garbage out.
Tip! Don’t use metrics that are well correlated with rankings.

86. There’s so much opportunity here.
So what can you do about it?

87. Get better at defining “great content”.

88. If it gets links, shares, converts, we usually class it as “good”.
But what made it “good” ?

89. Tutorial
Technical > contains code
Controversial
Breaking news
Funny
Serious
Off topic
Controversial
List post > top 5,10, checklist
Tool review

90. Try it. A free version is available.
http://goo.gl/NKtXOl

91. Two little things I want you to remember.

92. Build a better practice by binning best practice

93. Prove it.
Data or it didn’t happen

94. Thanks 
@dsottimano