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Figaro Search Seminar, December 15

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Martin Dinham and Anthony Tuite from Barracuda discussing Google Rankbrain and its impact on SEO and marketers

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Figaro Search Seminar, December 15

  1. 1. Figaro Digital, December 2015 “From PageRank to RankBrain”, an evolution of Googles algorithm
  2. 2. Who are Barracuda?  Dedicated search marketing agency (SEO and PPC)  Recognised by our peers for expertise and innovation within SEO  Blend of best in class and proprietary technology, including our own Panguin SEO algorithm analysis tool  Collaborative working model  20 strong agency  Wide range of clients 2
  3. 3. Some of our Clients… 3
  4. 4. Why Barracuda? 4
  6. 6. It’s the next evolution of the algorithm… 6
  7. 7. Let’s go back a step or two, and grab some context; what is Google trying to achieve with its search engine? 7
  8. 8. the “perfect search engine” is something that “understands exactly what you mean and gives you back exactly what you want.” 8 User Perspective
  9. 9. If your website has something users want then Google wants to return it… "Even if you do brain-dead stupid things and shoot yourself in the foot, but have good content, we still want to return it,“ Matt Cutts, Former Head of Search Quality, Google 9 Your Perspective
  10. 10. Even if you do everything right, it’s complicated! And who’s doing it right all the time?! That’s a tall task when programming an effective search engine. 10
  11. 11. To achieve the ‘perfect search engine’ scenario, we need it to behave more like a human, that is to say, behave with human-like intelligence, particularly in the area of decision making. 11
  12. 12. …because explicitly programming all eventualities in search is a fools errand and not scalable. 12
  13. 13. So how have Google done it up to now and where’s it going? 13
  14. 14.
  15. 15. Page Rank… We assume page A has pages T1...Tn which point to it (i.e., are citations). The parameter d is a damping factor which can be set between 0 and 1. We usually set d to 0.85. There are more details about d in the next section. Also C(A) is defined as the number of links going out of page A. The PageRank of a page A is given as follows: PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn)) Note that the PageRanks form a probability distribution over web pages, so the sum of all web pages' PageRanks will be one. PageRank or PR(A) can be calculated using a simple iterative algorithm, and corresponds to the principal eigenvector of the normalized link matrix of the web
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  18. 18. So, what is Rank Brain? 18
  19. 19. 19
  20. 20. 20 3rd most important ranking signal!
  21. 21. 21 RankBrain is the first system within Google’s search algorithm to employ machine learning to process huge volumes of search queries submitted to Google, including voice search. It attempts to understand what those queries mean and use that understanding to provide better answers.
  22. 22. 22 For example, the system helps with interpreting the meaning of ambiguous or new search strings. Google states that approximately 15% of search terms have never been used before.
  23. 23. What is machine learning? 23
  24. 24. 24
  25. 25. What is artificial intelligence? 25
  26. 26. 26
  27. 27. 27 Disambiguate: • STOP explicitly programming every eventuality. • SPOT patterns and deal with new eventualities based on what has been learnt. • ASSESS decisions that have been made with user feedback (click-through, bounce, dwell time etc) • AMEND results for next time.
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  29. 29. It’s the next evolution of the algorithm… 29
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  31. 31. RankBrain is an application of machine learning that is resulting in Google behaving in a more ‘human’/intelligent way (making decisions for itself based on what it has learnt from patterns), when serving search results to user queries. 31
  33. 33. On-page keyword targeting & content PageRank (External Links) RankBrain Top 3 ranking factors (probably)
  34. 34. RankBrain is there to amplify the good work being done in the areas of keyword targeting, content and links. It is not a factor that can be ‘directly’ influenced in the same way we can the other two. 34
  35. 35. 35 Technical (Speed, Architecture, Mark-up) Off-Page (Link Profile) On-Page (Keyword Targeting) SEO fundamentals
  36. 36. 36 ResonanceRelevance What you want to say What they’re interested in M A G I C Adds value, is different
  37. 37. 24 Rules of Content 4 Rules of Content Relevant / brand Resonant Different Adds value 37
  38. 38. Musement film map 38
  39. 39. An example - Musement film map 39
  40. 40. An example - Musement film map 40
  41. 41. So, what are the lessons here ? RankBrain changes nothing about the direction of travel The underlying principles still apply Underpin strategy with a strong technical foundation And then move to content (E A T) And ensure that its focused on users, not search engines 41
  42. 42. In summary, the advent of RankBrain in 2015 is symptomatic of Google’s push to make its search products more ‘intelligent’. This is a good thing for marketers who are already engaging in best practice on-site SEO and content marketing, because we’re already doing what we need to do. 42
  43. 43. The rest need to get with the program! 43
  44. 44. Thankyou ! 0207 593 1848
  45. 45. 45 RankBrain’s learning mechanisms are not in continuous operation – rather, it employs ‘assisted learning’ where new data sets and processing models are periodically input by Google engineers, who then assess the output and deploy the changes to the live running system if they show improved results.