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Seo
- 1. State of SearchWhere We Are, Where We’re Headedand How to Win Gillian MuessigPresident & Co-Founder, SEOmoz
- 2. “Essentially, we've been doing the same kind of search now for over a decade, right? It's basically anchor text and PageRank and inbound links, and that's how we've kind of decided what page is best for a particular term… But there are signals beyond this.” Stefan Weitz, Director for Bing Search http://www.seomoz.org/blog/director-of-bing-discusses-holistic-search-and-clickstream-data-whiteboard-friday
- 3. “One piece of advice I give to SEO masters is, don’t chase after Google’s algorithm, chase after your best interpretation of what users want, because that’s what Google’s chasing after,” Matt Cutts, Head of Web Spam, Google http://www.nytimes.com/2011/02/11/business/media/11search.html
- 4. Every 3-4 years, there's a big shift or addition to the key metrics Google (and, to a lesser extent MSN/Bing and Yahoo!) uses to order competitive search results. 1996-1999: On-page keyword usage + meta data 1999 - 2002: PageRank + On-page 2002 - 2005: Anchor text + Domain name + PageRank + On-Page 2005 - 2009: Domain authority + Diversity of linking domains + Topic modeling + Anchor text + Domain name + PageRank + On-Page Rand Fishkin, the Wizard of Moz http://www.nytimes.com/2011/02/11/business/media/11search.html
- 5. Ranking Correlations Signals Today
- 6. Negative Correlations URL Length .com TLD extension http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
- 7. Query Matching in Domain Name Contains All Query Terms in Domain Name Exact MatchHyphenated Domain Exact Match Domain http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
- 8. Exact Match Domains by TLD Extension Exact Match .org Exact Match .net Exact Match .com Exact Match http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
- 9. Keywords in Domain All Keywords inSubdomain Exact Match .* http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
- 10. On Page Keyword Usage KWs in Body KWs in Alt Attribute KWs in H1 Tag KWs in URL KWs in Title http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
- 11. TLD Extensions .gov .edu .info .net .org .com http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
- 12. Length of Domain, URL & Content Content Length(tokens in body) URL Length(chars) Domain NameLength (chars) http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
- 13. Website Home Pages Exact Match Domain Home Page of Site http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
- 14. Features w/Highest Correlation Number of Links Exact Match Domain # of LinkingRoot Domains Domains Linkingw/Exact Match Exact Match.com Domains http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
- 15. Link Attribute Correlations Today
- 16. Diversity of Domains + Linking C-Blocks # of Linking Root Domains to URL # of Links to URL http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
- 17. Anchor Text # of Links w/ exact match anchor text # of linking root domains w/ exact match anchor text http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.nytimes.com/2011/02/11/business/media/11search.html
- 18. Features of Linking Pages http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html Data via http://www.opensiteexplorer.org
- 19. Features of Linking Domains http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html Data via http://www.opensiteexplorer.org
- 20. Topic Modeling
- 21. Topic Modeling Topic models provide a simple way to analyze large volumes of unlabeled text.
- 22. Topic Modeling A "topic" consists of a cluster of words that frequently occur together. http://neoformix.com/archive.html
- 23. Using contextual clues, topic models can connect words with similar meanings and distinguish between uses of words with multiple meanings. http://www.stanford.edu/~kaisa/research.html
- 25. Why Engines Need Topic Modeling
- 26. Term Frequency & Inverse Document Frequency
- 27. Co-Occurence
- 28. Topic Modeling
- 29. Content-related signals require the ability to determine INTENT Rock or baseball? Are you SURE?
- 31. If Your Response Is…
- 32. Simplistic Term Vector Model
- 34. Correlation Is Strong Standard Deviation
- 35. Causation? Not So Fast! Perhaps, good links are more likely to point to pages that are more "relevant" via a topic model or some other aspect of Google's algorithm that we don't yet understand naturally biases towards these.
- 36. LDA Tool in the Labs URL input box
- 41. We have built a tool to help grade & improve page content
- 43. Social Signals Page A 646 links from 36 root domains 2 tweets Page B 1 link from 1 root domain 522 tweets http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/how-do-tweets-influence-search-rankings-an-experiment-for-a-cause
- 44. Social Signals Page B – the tweeted version – ranks #1! Page A 646 links from 36 root domains 2 tweets Page B 1 link from 1 root domain 522 tweets http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/how-do-tweets-influence-search-rankings-an-experiment-for-a-cause
- 45. Social Signals http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/tweets-effect-rankings-unexpected-case-study
- 46. Social Signals http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/tweets-effect-rankings-unexpected-case-study#jtc133590
- 47. Author Authority Danny Sullivan: Do you try to calculate the authority of someone who tweets that might be assigned to their Twitter page. Do you try to “know,” if you will, who they are? Bing: Yes. We do calculate the authority of someone who tweets. For known public figures or publishers, we do associate them with who they are. (For example, query for Danny Sullivan) Google: Yes we do compute and use author quality. We don’t know who anyone is in real life :-) http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://searchengineland.com/what-social-signals-do-google-bing-really-count-55389
- 49. Have authentic, followed social accounts
- 50. Display obvious, robust contact information
- 51. Register with government/civic organizations
- 52. Receive traffic from diverse sources
- 53. Generate branded search query volume
- 54. Run offline marketing/advertising campaigns
- 55. Often exist only online
- 56. Rarely have significant social accounts
- 57. Frequently use email forms only
- 58. Stay “under the radar”
- 59. Search is often 90%+ of traffic
- 60. Have little-no branded search demand
- 61. Ignore the offline worldhttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/the-next-generation-of-ranking-signals
- 62. Domain Name / Brand Name “Mentions” http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/labs/blogscape
- 63. Depreciation/Filtering of Anchor Text http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/a-recommendation-for-googles-webspam-team
- 64. Some Future-Looking Link Building Tactics I Love
- 65. Q+A Sites http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.readwriteweb.com/archives/question_and_answer_sites.php
- 66. Building Your Own Social Community http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://mashable.com/2010/11/15/biggest-facebook-brands/
- 67. Media Coverage http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.madetostick.com/excerpts/
- 68. Comment Marketing http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.seomoz.org/blog/recommendations-blog-commenting-marketing-strategy
- 69. Competitive Analysis of Top “Brands” Where do these brands earn their links? http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html http://www.opensiteexplorer.org
- 70. Investigating Brand “Mention” Sources Facebook page Blippr? Crunchbase profile App profile on Blackberry Twitter account BusinessWeek Profile Chrome Extension Mashable Article
- 73. Email: gillian@seomoz.orgYou can now try SEOmoz PRO Free! http://www.seomoz.org/freetrial
Hinweis der Redaktion
- “Essentially, we've been doing the same kind of search now for over a decade, right? It's basically anchor text and PageRank and inbound links, and that's how we've kind of decided what page is best for a particular term… But there are signals beyond this.”
- “One piece of advice I give to SEO masters is, don’t chase after Google’s algorithm, chase after your best interpretation of what users want, because that’s what Google’s chasing after,”
- Every 3-4 years, there's a big shift or addition to the key metrics Google (and, to a lesser extent MSN/Bing and Yahoo!) uses to order competitive search results.1996-1999: On-page keyword usage + meta data1999 - 2002: PageRank + On-page2002 - 2005: Anchor text + Domain name + PageRank + On-Page2005 - 2009: Domain authority + Diversity of linking domains + Topic modeling + Anchor text + Domain name + PageRank + On-Page
- This chart shows data points where the correlation is negative. Ie: longer urls tend to have lower placement in the results. No surprise. More surprising, .com’s didn’t do as well as other TLDs in the dataset we reviewed. This doesn’t mean that using a .com will lower your rankings, only that ALL OTHER THINGS BEING EQUAL, .com’s didn’t rank as well as other TLDs.
- Exact match domains appear to continue powerful level of influence in both search enginesSurprise: Google has a higher correlation with ranking exact match domains higher (when they appear on page 1 of the results) than Bing.Hyphenated exact matches appear to be less influential, though they're more frequent (Google: 271 results contained hyphenated exact matches vs. Bing: 890)Just including keywords in the domain name has substantive positive correlationie: to rank for "dog," the domain mydog.com would fit with this correlation point
- For exact match, .com extensions are the way to go. Others aren't nearly as well correlated.Bing seems to rank non-dot-com exact matches better than Google, but it’s a small difference. (especially in the case of .org)
- Keywords in subdomains aren't nearly as powerful as they are in root domain namesBing may be rewarding subdomain keyword usage less than they have historically, but these results numbers suggest they do show up on page 1 much more frequently (Google: 673 vs. Bing: 1,394)
- The alt attribute of images is interesting - our research last year found this as a peculiarity and it would appear to still be potentially useful in both engines (definitely worth some testing)Placing keywords in your URL string has some correlation with rankings on GoogleNote the placement of the "0" axis – some of these are negatively correlated, though not massively. All of the correlations are in a fairly narrow zone here.Everyone seems to be optimizing their title tags these days (appeared in Google: 11,115 vs. Bing: 11,143). Differentiating here is hard.Overall, simplistic on-page optimization doesn't appear to be a huge factor.
- This data gives us more reason to believe Google's webspam chief, Matt Cutts, when he says .gov, .info, and .edu don't receive special bonuses or penalties to rankingsThe .org TLD extension is surprising - do these sites earn more links? Do they have less spam? Perhaps they tend to be less commercial and have an easier time garnering references? In any case, we're happy to be SEOmoz.org!Don't forget about the exact match data from above - .com is still probably a very good thing (at least own it if you're using a different extension)
- Shorter URLs are probably a good best practice (especially on Bing)Long domains may not be ideal, but don't seem to be awfulRaw content length seems marginal in correlation, which fits with Matt Cutts' advice from the Google I/O panel - "Don’t overfill your page with text for the sake of search engines. They don’t need a dissertation to decide to rank it highly; they want what the users want – for your site to be useful and informative.”
- Bing has the stereotype of ranking homepages much more than GoogleThis appears to hold true in the correlation results – Bing shows about double Google's propensity/preference for higher rankings on website homepages Note that we included site.com/, site.com/index.*, site.com/default.* and site.com/home.* in these numbers
- Link attributes as a whole have much higher correlation with rankings than on-page or domain related elementsExact match is still a powerful influencerGoogle and Bing are remarkably similar - building two different sites/pages to separately target the two engines would appear to be a waste of energyBing seems to be moving much closer to Google over time; although we didn't measure all of these results precisely last year, the similarity of the two has dramatically increased (of course, it's also possible that Google is getting more Bing-like, though this doesn't fit with our personal experiences)
- Links are still likely a major part of the algorithms. These numbers are among the highest we observe with any single metric.Bing may be slightly more naive in their usage of link data than Google, but appear to have improved since last year.Diversity of link sources remains more important than raw link quantity.Correlation numbers this high says good things about Linkscape's Index - way to go engineering team!
- Bing has the stereotype of ranking homepages much more than GoogleThis appears to hold true in the correlation results – Bing shows about double Google's propensity/preference for higher rankings on website homepages Note that we included site.com/, site.com/index.*, site.com/default.* and site.com/home.* in these numbers
- The Page Authority, mozRank, mozTrust, total number of links, external citations, and PageRank are important factors in ranking well on Google.
- I’ve tried this with a site with ZERO inbound links. I arranged for 10 twitter accounts to tweet 10 times each with a link to the page; no duplicate or spammy tweets. No impact observed. Perhaps more tweets are necessary, more authoritative tweeters are required, or better relevancy of the tweets were required. It bears investigating.
- One of the reasons Google took so long to penalize JCPenney (it was first spam reported to me in late 2009) is that their human raters and user data likely suggested it was actually quite a good result for searches like "dresses" and "bedding." The brand name meant that people felt good about the listing and Google, up until the bad press, felt no need to take punitive action, if the methodology was manipulative (I'm pretty sure they knew about the manipulation for a long time, but wanted to solve it algorithmically).For millions of retail, transactional-focused searches, Google's results are, to be honest, easily and often-gamed. We could find hundreds of examples in just a few hours, but the one below serves the purpose pretty well.