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State of SearchWhere We Are, Where We’re Headedand How to WinGillian MuessigPresident & Co-Founder, SEOmoz
“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 Searchhttp://www.seomoz.org/blog/director-of-bing-discusses-holistic-search-and-clickstream-data-whiteboard-friday
“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, Googlehttp://www.nytimes.com/2011/02/11/business/media/11search.html
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 Rand Fishkin, the Wizard of Mozhttp://www.nytimes.com/2011/02/11/business/media/11search.html
Ranking Correlations Signals Today
Negative CorrelationsURL Length.com TLD extensionhttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
Query Matching in Domain NameContains All Query Terms in Domain NameExact MatchHyphenated DomainExact Match Domainhttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
Exact Match Domains by TLD ExtensionExact Match .orgExact Match .netExact Match .comExact Match http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
Keywords in DomainAll Keywords inSubdomainExact Match .*http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
On Page Keyword UsageKWs in BodyKWs in Alt AttributeKWs in H1 TagKWs in URLKWs in Titlehttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
TLD Extensions.gov.edu.info.net.org.comhttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
Length of Domain, URL & ContentContent Length(tokens in body)URL Length(chars)Domain NameLength (chars)http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
Website Home PagesExact Match DomainHome Page of Sitehttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
Features w/Highest CorrelationNumber of LinksExact Match Domain# of LinkingRoot DomainsDomains Linkingw/Exact MatchExact Match.com Domainshttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
Link Attribute Correlations Today
Diversity of Domains + Linking C-Blocks# of Linking Root Domains to URL# of Links to URLhttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements
Anchor Text# of Links w/ exact match anchor text# of linking root domains w/ exact match anchor texthttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.nytimes.com/2011/02/11/business/media/11search.html
Features of Linking Pageshttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlData via http://www.opensiteexplorer.org
Features of Linking Domainshttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlData via http://www.opensiteexplorer.org
Topic Modeling
Topic ModelingTopic models provide a simple way to analyze large volumes of unlabeled text.
Topic ModelingA "topic" consists of a cluster of words that frequently occur together.http://neoformix.com/archive.html
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
Seo
Why Engines Need Topic Modeling
Term Frequency & Inverse Document Frequency
Co-Occurence
Topic Modeling
Content-related signals require the ability to determine INTENTRock or baseball?Are you SURE?
Seo
If Your Response Is…
Simplistic Term Vector Model
Correlation Is Strong
Correlation Is StrongStandard Deviation
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.
LDA Tool in the LabsURL input box
It’s RelativeDon't presume that getting a 15% or a 20% is a terrible result
Some queries simply won't produce results that fit remarkably well with given topicsOut of the SERPs!Keyword spamming might improve your LDA score, …but not your rankings
Compare Your Friends
There’s Still Lots of Work to DoCorrelations are good, butdon’t get carried away – we haven’t reversed the algo
We have built a tool to help grade & improve page content
YOUR in-field results will tell us whether it can really help improve rankingsLink Building Signals of the Future
Social SignalsPage A646 links from 36 root domains2 tweetsPage B1 link from 1 root domain522 tweetshttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/how-do-tweets-influence-search-rankings-an-experiment-for-a-cause
Social SignalsPage B – the tweeted version – ranks #1!Page A646 links from 36 root domains2 tweetsPage B1 link from 1 root domain522 tweetshttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/how-do-tweets-influence-search-rankings-an-experiment-for-a-cause
Social Signalshttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/tweets-effect-rankings-unexpected-case-study
Social Signalshttp:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/tweets-effect-rankings-unexpected-case-study#jtc133590
Author AuthorityDanny 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.htmlhttp://searchengineland.com/what-social-signals-do-google-bing-really-count-55389
Brand SignalsBrandsGenerics Have real people working at a physical address
 Have authentic, followed social accounts
 Display obvious, robust contact information
 Register with government/civic organizations
 Receive traffic from diverse sources
 Generate branded search query volume
 Run offline marketing/advertising campaigns
 Often exist only online
 Rarely have significant social accounts
 Frequently use email forms only

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Editor's Notes

  1. “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.”
  2. “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,”
  3. 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
  4. 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.
  5. 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
  6. 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)
  7. 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)
  8. 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.
  9. 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)
  10. 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.”
  11. 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
  12. 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)
  13. 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!
  14. 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
  15. The Page Authority, mozRank, mozTrust, total number of links, external citations, and PageRank are important factors in ranking well on Google.
  16. 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.
  17. 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.