Branko Rihtman Linklove London 2012

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  • 1. Social Media and Links The Love Story (with numbers)Branko RihtmanLinklove London 2012@neyne
  • 2. How People See Scientists@neyne
  • 3. The Real Scientists The most exciting phrase to hear in science, the one that heralds the most discoveries, is not "Eureka!" (I found it!) but "Thats funny..." ~Isaac Asimov@neyne
  • 4. Scientific principles The official version The tl;dr version 1. Define the question 1. Don’t BS yourself (or the others) 2. Gather information and resources (observe) 3. Form hypothesis 4. Perform experiment and collect data 2. Truth above profit 5. Analyze data 6. Interpret data and draw conclusions that serve as a 3. Stay curious starting point for new hypothesis 7. Publish results 8. Retest (frequently done by other scientists) 4. Share@neyne
  • 5. SEO and Social Media What we’ve had so far@neyne
  • 6. What proof is missing? http://4.bp.blog spot.com/_clW9 Will it rank? 2NzmFvI/TFRRQ brsg6I/AAAAAAA AD8g/Gr91SYY7 D50/s1600/sea- kitten.jpg Links@neyne
  • 7. pinterest.com/ pinterest.com/nordstrom/ source/ikea.comRTs 0 379FB Shares 1 1FB Likes 0 27+1s 0 1Links 4 849Linking 2 134domains Not in top 1000Rank for [ikea] #2 [nordstrom] #3 for [ikea.com]@neyne
  • 8. Social Media in link buildingSome eyeballs = a link@neyne
  • 9. Brute force approach Lots of eyeballs = 2 links@neyne
  • 10. Let’s try and do it a bit smarter http://4.bp.blog @user1 spot.com/_clW9 @user2 2NzmFvI/TFRRQ @user3 brsg6I/AAAAAAA @user4 AD8g/Gr91SYY7 …. D50/s1600/sea- @user50000 kitten.jpg@neyne
  • 11. Let’s try and do it a bit smarter http://4.bp.blog @user1 spot.com/_clW9 @user2 2NzmFvI/TFRRQ @user3 brsg6I/AAAAAAA @user4 AD8g/Gr91SYY7 …. D50/s1600/sea- @user50000 kitten.jpgUsers that share more than onepiece of content = more important@neyne
  • 12. Let’s try and do it a bit smarter http://4.bp.blog @user1 spot.com/_clW9 @user2 2NzmFvI/TFRRQ @user3 brsg6I/AAAAAAA @user4 AD8g/Gr91SYY7 …. D50/s1600/sea- @user50000 kitten.jpgContent shared by more thanone user = more important@neyne
  • 13. The Minesweeper Effect@neyne
  • 14. How do we get all that information? APIs!!! APIs? That is CODING!!!!@neyne
  • 15. @neyne
  • 16. Ingredients APIs: Topsy FB graph Twitter API G+ API (more complicated) MajesticSEO API And Her Royal Majesty: EXCEL + His Royal Highness Neil Bosma’s SEOTools Excel Add-in@neyne
  • 17. Targets 2 Awesome articles http://www.distilled.net/excel-for-seo/ http://nielsbosma.se/projects/seotools/@neyne
  • 18. Scraping usernames of sharers =MID(DownloadString("http://otter.topsy.com/trackbacks.json?url="&$B$1&"&perpage=100"),FIND(" nick",DownloadString("http://otter.topsy.com/trackbacks.json?url="&$B$1&"&perpage=100"),1)+7,FI ND("""",DownloadString("http://otter.topsy.com/trackbacks.json?url="&$B$1&"&perpage=100"),FIN D("nick",DownloadString("http://otter.topsy.com/trackbacks.json?url="&$B$1&"&perpage=100"),1)+ 7)- (FIND("nick",DownloadString("http://otter.topsy.com/trackbacks.json?url="&$B$1&"&perpage=100"), 1)+7))@neyne
  • 19. Scraping shared URLs =IFERROR(MID(DownloadString("http://otter.topsy. com/linkposts.json?url=http://twitter.com/"&$A$2 &"&perpage=100"),B6+LEN($A$4)+2,C6- (B6+LEN($A$4)+2)),"N/A")@neyne
  • 20. Scraping social metrics@neyne
  • 21. Scraping backlink metrics@neyne
  • 22. Plotting links vs. tweets/likes/shares/+1s Y = aX + b a – slope of the graph, rate at which number of links increases as a function (???) of number of tweets@neyne
  • 23. Links as a function of RTs@neyne
  • 24. Links as a function of FB Likes@neyne
  • 25. Links as a function of FB Shares@neyne
  • 26. Links as a function of +1s@neyne
  • 27. Comparison of graph slopes@neyne
  • 28. Things to rememberFigures and relative values WILLvary from niche to niche (+1s may not be thebest link-producing social media strategy inevery industry)Actual numbers are not precise/important/proportional to number of achievable links.What matters is the feel for differences betweendifferent social media strategies@neyne
  • 29. Where did we start and where did we get to? 2 URLs 214 Twitter users ~ 12K URLs, 3.7K domains Minesweeper effect ?@neyne
  • 30. Where did we start and where did we get to? 2 URLs 214 Twitter users ~ 12K URLs, 3.7K domains1. Prune out the“selfish users” 2. Identify power users 3. Identify relevant users (search by keywords)@neyne
  • 31. Identifying the power users Users that have shared both articles@neyne
  • 32. Where did we start and where did we get to? 2 URLs 214 Twitter users ~ 12K URLs, 3.7K domains 4. Prune out the irrelevant URLs (logos of 4sq, paper.li, etc.) 5. Assign relevance to domains (Google site 6. Create a pool of 7. Grade domains according to: search + keywords) relevant domains for • Already linking to you future linking outreaches • Not yet linking to you (Google custom SE) • Linking to competitors • Not yet linking to competitors@neyne
  • 33. What these charts CAN do Hint towards trends in social media contribution towards links in a specific niche Content generation ideas Point out potential social media targets that may possibly perform above average in terms of linking potential Look pretty in reports/presentations What these charts CANNOT do Provide specific numbers and goals for link building campaigns Decide for you whether to prefer one kind of social engagement over another Do the actual link building work for you@neyne
  • 34. Thank you! Branko Rihtman branko@rankabove.com @neyne http://il.linkedin.com/in/brankorihtman http://www.seo-scientist.com@neyne