State of SearchWhere We Are, Where We’re Headed

and How to Win

Gillian MuessigPresident & Co-Founder, SEOmoz

http://www.seomoz.org/blog/director-of-bing-discusses-holistic-search-and-clickstream-data-whiteboard-friday

“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.nytimes.com/2011/02/11/business/media/11search.html

Matt Cutts, Head of Web Spam, Google

“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,”

http://www.nytimes.com/2011/02/11/business/media/11search.html

Rand Fishkin, the Wizard of Moz

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

Ranking Correlations Signals Today

Negative Correlations

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements

URL Length

.com TLD extension

Query Matching in Domain Name

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements

Contains All Query Terms in Domain Name

Exact MatchHyphenated Domain

Exact Match Domain

Exact Match Domains by TLD Extension

http:/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 .org

Exact Match .net

Exact Match .com

Exact Match

Keywords in Domain

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements

All Keywords inSubdomain

Exact Match .*

On Page Keyword Usage

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements

KWs in Body

KWs in Alt Attribute

KWs in H1 Tag

KWs in URL

KWs in Title

TLD Extensions

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements

.gov

.edu

.info

.net

.org

.com

Length of Domain, URL & Content

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements

Content Length(tokens in body)

URL Length(chars)

Domain NameLength (chars)

Website Home Pages

http:/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 Domain

Home Page of Site

Features w/Highest Correlation

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements

Number of Links

Domains Linkingw/Exact Match

Exact Match Domain

# of LinkingRoot Domains

Exact Match.com Domains

Link Attribute Correlations Today

Diversity of Domains + Linking C-Blocks

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/google-vs-bing-correlation-analysis-of-ranking-elements

# of Linking Root Domains to URL

# of Links to URL

Anchor Text

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.nytimes.com/2011/02/11/business/media/11search.html

# of Links w/ exact match anchor text

# of linking root domains w/ exact match anchor text

Features of Linking Pages

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlData via http://www.opensiteexplorer.org

Features of Linking Domains

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlData via http://www.opensiteexplorer.org

Topic Modeling

Topic Modeling

Topic models provide a simple way to analyze large volumes of unlabeled text.

A "topic" consists of a cluster of words that frequently occur together.

Topic Modeling

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

Why Engines Need Topic Modeling

Term Frequency & Inverse Document Frequency

Co-Occurence

Topic Modeling

Content-related signals require the ability to determine INTENT

Rock or baseball?Are you SURE?

If Your Response Is…

Simplistic Term Vector Model

Correlation Is Strong

Correlation Is Strong Standard 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 Labs

URL input box

It’s Relative

•Don'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 topics

Out of the SERPs!

Keyword spamming might improve your LDA score, …but not your rankings

Compare Your Friends

There’s Still Lots of Work to Do

• Correlations are good, but don’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 rankings

Link Building Signals of the Future

Social Signals

http:/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

Page A646 links from 36 root domains

2 tweets

Page B1 link from 1 root domain

522 tweets

Social Signals

http:/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

Page A646 links from 36 root domains

2 tweets

Page B1 link from 1 root domain

522 tweets

Page B – the tweeted version –

ranks #1!

Social Signals

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/tweets-effect-rankings-unexpected-case-study

Social Signals

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/tweets-effect-rankings-unexpected-case-study#jtc133590

Author Authority

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://searchengineland.com/what-social-signals-do-google-bing-really-count-55389

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?

Google: Yes we do compute and use author quality. We don’t know

who anyone is in real life :-)

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)

Brand Signals

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/the-next-generation-of-ranking-signals

Brands Generics

• 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

• Stay “under the radar”

• Search is often 90%+ of traffic

• Have little-no branded search demand

• Ignore the offline world

Domain Name / Brand Name “Mentions”

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/labs/blogscape

Depreciation/Filtering of Anchor Text

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/a-recommendation-for-googles-webspam-team

Some Future-Looking Link Building

Tactics I Love

Q+A Sites

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.readwriteweb.com/archives/question_and_answer_sites.php

Building Your Own Social Community

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://mashable.com/2010/11/15/biggest-facebook-brands/

Media Coverage

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.madetostick.com/excerpts/

Comment Marketing

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.seomoz.org/blog/recommendations-blog-commenting-marketing-strategy

Competitive Analysis of Top “Brands”

http:/googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.htmlhttp://www.opensiteexplorer.org

Where do these brands earn their links?

Facebook page

Blippr?

Crunchbase profile

App profile on Blackberry

Twitter account

BusinessWeek Profile

Chrome Extension

Mashable Article

Investigating Brand “Mention” Sources

Q+A

Gillian Muessig, President & Co-Founder, SEOmoz

• Twitter: @SEOmom

• Blog: www.seomoz.org/blog

• Email: gillian@seomoz.org

You can now try SEOmoz PRO Free!http://www.seomoz.org/freetrial