SEO Master Class Webit 2010

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All 166 slides on advanced SEO and social media master class from Rand Fishkin, CEO of SEOmoz, at Webit 2010 in Sofia, Bulgaria.

Transcript of SEO Master Class Webit 2010

Positioning and Messages May 5, 2010

SEO Masterclass

Rand Fishkin, CEO & Co-founder, SEOmozWebit, Sofia October 2010

Topics for the Masterclass Correlation analysis of search results Changes from Google Instant Information architecture & navigation structure Overcoming Twitters cannibalization of the link graph Making Analytics Actionable New Research: Topic Modeling in the Search Results

Use Statistical Analysis to Answer Important SEO Questions

Correlation Causation

The more I wear suits, the more I speak on panels.Therefore: wearing suits causes me to speak on panels.Understanding Correlation Significance

No CorrelationExact Match DomainPerfect CorrelationMost of our data for search rankings falls in this region(which wed expect given algorithms w/ 200+ ranking factors)

Question #1:How to Best Optimize a Site for Search Engine Rankings


11,351 SERPs via Google AdWords Suggest 1st Page Only (usually ~10 results per page) Correlations are w/ Higher Position on Page 1 Controlled for SERPs Where All (or None) of the Results Matched the MetricMethodology

Looking for elements that higher ranking pages have that lower ones do notNOT looking at raw counts of how many pages featured a given element

Contains All Query Terms in Domain NameExact Match Hyphenated DomainExact Match DomainHighest Stderr = 0.0241804

Our Interpretation

Exact match domains remain powerful in both engines (anchor text could be a factor, too) Hyphenated versions are less powerful, though more frequent in Bing (G: 271 vs. B: 890) Just having keywords in the domain name has substantial positive correlation

Highest Stderr = 0.00350211KWs in BodyKWs in Alt AttributeKWs in H1 TagKWs in URLKWs in Title

Our Interpretation

The Alt attribute of images is interesting Putting KWs in URLs is likely a best practice Everyone optimizes titles (G: 11,115 vs. B: 11,143). Differentiating here is hard. (Simplistic) on-page optimization isnt a huge factor

Highest Stderr =

Our Interpretation

More reasons to believe Google when they say .gov, .info and .edu are not special cased The .org TLD extension is surprising do they earn more links? Less spam? More non-commercial? Dont forget about branding/user behavior - .com is still probably a very good thing (at least own it)

Highest Stderr = 0.0033353Content Length (tokes in body)URL Length(chars.)Domain Name Length (chars.)

Our Interpretation

Shorter URLs are likely a good best practice (especially on Bing) Long domains may not be ideal, but arent awful Raw content length seems marginal in correlation

Question #2:What Kind of Links Matter & How Should We Evaluate Links?

Highest Stderr = 0.00335677# of Linking Root Domains to URL# of Links to URL

Our Interpretation

Links are likely still a major part of the algorithms Bing may be slightly more nave in their usage of link data than Google, but better than before Diversity of link sources remains more important than raw link quantity

Highest Stderr = 0.00415058# of Links w/ exact match anchor text# of linking root domains w/ exact match anchor text

Our Interpretation

Many anchor text links from the same domain likely dont add much value Anchor text links from diverse domains, however, appears highly correlated Bing and Google are relatively similar in evaluating these metrics

Correlation of Page-Level Link Valuation Metrics

Our Interpretation

PageRank (and similar algorithms) are not particularly representative of rankings (but are somewhat correlated) Linking domains are likely a better metric than raw links Page Authority is reasonably good, but has a way to go

Correlation of Domain-Level Link Valuation Metrics

Our Interpretation

No single domain valuation metric is especially well correlated with rankings Rankings of individual pages may be more disparate we typical think re: domain authority Overall, were still very nave when it comes to understanding how links influence search rankings

Question #3:How Does Google Instant Change Keyword Demand / SEO?

Are Most Users Seeing/Using Google Instant?

Methodology: Keyword Referral Search Data

Look at keyword sending traffic via analytics Distribute into groups by word-length Analyze shifts in demand by keywords that brought visits to the site Compare from period prior to Google Instant and directly after MEC Manchester (UK)5 Sites, 4 Verticals, 10K+ Keywords

Via Distilled Consulting (UK)11 Sites, Various Sizes (3.5K 75K weekly visits), 75K+ Keywords

Via ConductorMultiple sites, 880K visits, 10Ks of keywords Takeaways

Google Instant seems not to have shifted keyword demand by much (if at all) Google suggest has been out for a long time already; users are likely accustomed to this feature The long tail may get longer/shorter over time, but Instant seems less responsible than other factors

Goals of Successful Information Architecture

Semantically Logical Structure

Minimize Click-Depth

Maximize Usability of Navigation

Tips for Semantically Useful Navigation

Initially Design without Keyword Research

Add in Keyword Research Based Modifications

Validate Architecture/Path with Non-SEOs

Tips for Minimal Click-Depth

Imitate the Ideal Nav Pyramid

Broad Linking at Top Levels

Editorial Categorization > User-Defined

Editorial Categorization > User-Defined

HACK: Multi-Level HTML Sitemap

Tips for Usable Navigation

Obvious Navigation Elements

Naming Conventions that Match Intent

User & Usability Testing

Avoiding Common Big Site Problems

Duplicate Content Issues

Rel Canonical Tags

Google Webmaster Tools

SEOmoz Web App

Scraping & Re-Publishing

Employ Absolute URLs

Absolute: anchor

Relative: anchor C&D vs. Large, Credible Orgs that Scrape

Dont Go Overboard w/ Bot Blocking

Incomplete Indexation

Track Referrals, not Site: Commands

Check Page Types that Dont Receive Traffic

XML Sitemaps

Content Syndication

RSS Feeds

Twitter for Indexation

Search Results in the SERPs

Create Category Landing Pages

Remove Obvious Traces of Search on Landing Pages

Thin Content Issues

Bolster w/ UGC

Employ Scalable Content Production

Keep Thin Pages Out of the SERPs

Faceted Navigation

Rel Canonical Can Help

Use AJAX to Reload Pages

Watch Out for Google Crawling Javascript

Offer Facets Only to Logged-In / Cookied Users

Logged-In = 345 / Googlebot = 141

Overcoming Twitters Cannibalization of the Link Graph

Way Back in 2007Interesting content, blog posts & linkbait earned LOTS of links

Fast Forward to 2010Not so many links (in comparison)

Fast Forward to 2010But tons of social sharing (and tweets)

Are Pages Linking Out Less?Via Linkscapes web index

How Do We Earn Traditional Web Links (the kind search engines love)?

Tactic #1:Embeddable Content

Infographics,085 links from 356 root domains


Value-Add Widgets

Tactic #2:Reference Material

Research & Data,8599,2014332,00.html

Awards + Rankings

Citation-Worthy Explanations

Tactic #3:Syndicated Content

Niches where content is low-supply/high-demand

ID sites that already syndicate from someone else

Tactic #4:Stick to Niches w/o Twitter Adoption

Find sectors where traditional blogs/forums dominate conversation

Many of these old-school sites have followed external links (but dont abuse these)

Note the nofollow highlighting

Some Web 2.0 Ones, Too Impressive domain and page level metrics

Tactic #5:Friends, Partners, Customers & Vendors

Friends + Family




Tactic #6:Twitter May Take Your Tweets, But Theyll Never Take Your Content!

Turn Your Tweets Into Content

Turn Tweets from industry leaders into content, too (this entices them to share)

Tactic #7:Cant Beat em? Join em!

Twitter is (almost certainly) influencing (at least some) rankings

Lots of tweets, virtually no links, but remarkable rankings

Twitter can send lots of direct traffic

You need to target the right Tweeters

The Ones Who Send Rea