SearchLove London | Dave Sottimano, 'Using Data to Win Arguments'
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SearchLove London | Dave Sottimano, 'Using Data to Win Arguments'
•14 likes•6,294 views
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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.
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SearchLove London | Dave Sottimano, 'Using Data to Win Arguments'
- 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?
- 10. Data driven SEO Using data to win arguments David Sottimano Searchlove 2014
- 11. Do this. Because. {Insert Matt Cutts video link}
- 13. Meaningful, conclusive data is hard to come by.
- 14. Algorithms can be specific to queries.
- 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.
- 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
- 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