1. Reverse Engineering Competitors Rankings 8/31/2010 @wilreynolds

2. 2 3 steps Step 1 - Background on REAL client example Step 2 - How a losing SERP changed our process Step 3 - Turn data analysis into SERP improvement

3. 3 “Let’s get Busy”

4. Client who has links from

5. 5 Client profile 10+ years online .edu links from research 4 million searches / month Newspaper / magazine links Some SERPS are adult category CEO is sought after by media outlets

6. 6 Competitive SERP Only 1 result in the top 10 of Google had a link from 1-2 of these quality magazine / newspaper sites

7. Tee-Ball right? 7

8. This guy is gonna love me 8

9. 9 What did those big media drops do? Let me show you…

10. 10

11. 11 Nothing Like Getting your Butt Kicked

12. 12 To make you change the way you do things

13. What I needed… Needed to bring in a vast amount of data on the top 10 sites for target keyword. Include big brands and exact match domains even though you won’t learn a ton from them More KWs = uncover trends Needed to be way more deep than PR & link tallies SEOQuake was not going to do it (poor mans) 13

14. 14 Time to get some data

15. Manual Aggregation 80 factors About ½ come from OSE or are calculated by multiple OSE metrics Others come from Twitter* Delicious Alexa Majestic YSE Google webmaster tools 15

16. Manual Aggregation Factors # of links (excel limits at 10,000 – impacts %’s) Compare OSE, YSE, Majestic (conditional formats) Linking domains relative to # of links (sitewides) Linking domains w/o anchor Linking domains w/ domain name as anchor % of links with targeted anchor text % links from edus – ex: competitor 16

17. Factors to review Factors Domain age mR & mT Major 301 event (trigger by outliers) Steady growth (.edus/ high mT) % keywords in domain # of linking domains over 25/50 domain auth % of linking domains over 25/50 domain auth % of links over 25/50 domain auth 17

18. Manual Aggregation – Excel First 18

19. 19 The output of this data aggregation looks like this…

20. 20 API’s and scripts make mistakes

22. When # of OSE links > Majestic links

24. Visual Trends 23

25. Link analysis visuals Go from this 24

26. % Anchor text vs Brand Links

27. Link analysis To this… 26

28. Importance of Visuals 27

29. So what did we learn from this experience? 28

30. Gameplan FIRST 29

31. Use analysis to uncover Un-Natural link building profiles Yourself & Your competitors 30

32. Un-Natural Works but is risky 31

33. 32 Client who is at 20% the average of the top 10 is 2.5% - time to diversify

34. Homepage link juice / domain authority on large sites does not really flow to article pages Authority links don’t add instant value Big sites paginate like crap and bury stories 33

35. What happens when you get exact match anchor texton a page 1 link from the homepage of one the most popular women’s magazines in the world… 34

36. What happens when you get exact match anchor texton a page 1 link from the homepage of one the most popular women’s magazines in the world… Nada 35

37. Refuse to take a butt kickin’ lying down 36

38. Here’s what we did about it… 37

39. Getting the links we NEEDED Sought out pages that don’t cycle content that have been around for a LONG time: Sponsors In Kind Donations Testimonials Supporters 38

40. You must socially promote the page where your link lives. Twitter Facebook Delicious 39

41. You must socially promote the page where your link lives. Queries in Twitter Queries in Forums [keyword phrase] + powered by vbulletin / phpbb Subscribe to search results in yahoo Yahoo Answers 40

42. Good homepage / evergreen page links Badges / Awards Watch the anchor text Wordcamp / other “camps” Edu discounts 41

43. Bad homepage / evergreen page links Bought homepage links in blogrolls with exact match anchor text Watched bought links on homepages of “cigarette sites” work like a charm phpdircetory link swaps working like it was 2004 42

44. What you learn from spammers Reverse engineering rankings lets you see how long spam and aggressive tactics last (actually watch the serps) 43

45. I see a site with only reciprocals + 2 kws in domain winning 44

46. 45

47. I see localcleaning up spam with one of our clients who has the weakest link profile in the top 10 (not in the 7 pack) 46

48. Double D’s of SEO 47 D iversification efendability

49. Manual Aggregation 48 Download the exact / phrase match counter - http://bit.ly/boiFGz

50. Create your game plan 49

52. Build data on the top 10 and trend it (25 data points)

53. Sign up for Majestic SEO, Raven, other tools with API’s

55. Create conditional formats to trigger un-natural patterns for you and your competitors

56. Use conditional formats & trends to learn how long spam works