SEO and IA: The Beginning of a Beautiful Friendship

Slide 1: PREPARED FOR 2007 IA Summit: Las Vegas SEO and IA: The Makings of a Beautiful Friendship ASCENTIUM 225 108th Ave NE, Ste 225 Bellevue, WA 98004 t 425.519.7700 f 425.519.7758 ascentium.com

Slide 2: Introduction Me: Information architect/Search specialist   IA since 1998  Search since 2004 Topic: Search engine optimization and IA   Shift in user locus of attention  From navigation to search box  Shift in our locus of attention  From macro-structure to micro-wayfinding What I want   IA to become a partner in developing search technology that works with the user  IA community to “think” about how users find their websites when they design them  Key takeaways [fingers crossed at my end] ascentium.com  Search optimization and IA can and should co-exist  One should not exist at the expense of the other

Slide 3: Search Usability Web analytics show preference for search box over any site navigation of any  kind  Search enables users to develop a need-specific/use-specific information path Search engine users visit more pages than those using navigation   Pogo effect  Ask.com now offers preview service so user does not have to click through  How much of the navigation will they see in a thumbnail? Out of the top 20 results and you are out of sight and out of mind for a majority of  users ascentium.com

Slide 4: Blame it all on Google PageRank is a pre-query valuation   Based on number of links to the page  1 link=1 vote  Most votes wins top placement  Has no relationship to the subject of the query Googlearchy : dominant Web sites become more firmly entrenched in search results  by nature of size  Link rich get richer Failings soon uncovered   Link farms  Googlehacks ascentium.com

Slide 5: Search 2.0 Web 2.0 give us Search 2.0   Harnessing the collective intelligence  Online bookmarking  Architecture of participation  Open source Search  Peer-to-peer Search  Index of nodes in system  Query passed to find appropriate node  Remixable data sources and data transformation  Local search  Any of the “maps” applications  Kayak.com and other travel sites  Software above the level of a single device  Mobile search Compensation for the commercialization of organic search   Paid ads do not have to map semantically to the results they accompany  Wales and Searchipedia  Program not tied to a revenue model ascentium.com

Slide 6: Now It is All About Meaning As Moore’s Law brings about  cheaper, faster, stronger hardware, the quest changes from indexing everything to the presentation of results Search challenge to determine  relevance without understanding meaning Transition from strict computation  to computational techniques to determine meaning  Hilltop Algorithm  Topic-sensitive PageRank ascentium.com

Slide 7: Hilltop Algorithm Segmentation of corpus into broad topics   Subset that is then extrapolated to Web as a whole  Created by Jon Kleinberg at Cornell in late 1990s  Consultant to Google Selection of authority sources within these topic areas   Authorities have lots of non-related pages on the same subject pointing to them  Quality of links more important than quantity of links Determination of HUBS   Pages that point to many authority sources Pre query calculations applied at query time  Likely part of Google’s Florida update in 2004  ascentium.com

Slide 8: Topic-Sensitive PageRank Consolidation of Hypertext Induced Topic Selection [HITS] and PageRank  Pre-query calculation of factors based on subset of corpus  Context of term use in document  Context of term use in history of queries  Context of term use by user submitting query  Creator now a Senior Engineer at Google  ascentium.com

Slide 9: Search Further Down the Road Semantic search technology patents  Search tool with preset categories and keywords  4-part database of information   Index, categories, keywords, document-specific data Categories define topics through human-mediation  Keywords extracted from document text  User can iterate search results through related keywords presented from database  Search manager  Brokering application that facilitates selection of best search engine for the user’s query  Similarity estimation  Creates “sketch” or compact representation  Compares sketches based on determined similarity threshold  Deleted duplicate entries  Personalized search  Microsoft: Compares snippets of Web search engine results with data collected from user  behavior and client  Demonstrated in NYT article March 7, 2007 Google: user bookmarks [online and client] used to construct “personalized search object” that  is used to filter Web search result Predictive search  Bayesian model  Compares user choices to predict more appropriate result from same vector space  ascentium.com

Slide 10: SEO and IA: Choices Capitulate   No action  Search technology continue on parallel path Cooperate   Work with current search technology  Develop best practices that build on developments in search technology Initiate   Influence development of search technology  Become a partner in developing user-centric search technology Action Items  Influence the technology to work for not against user  Site Navigation Strategy  Site Organization Strategy  Link Strategy  Page Code Strategy  Content Strategy  Metadata Strategy  ascentium.com

Slide 11: Initiate: Site Navigation Strategy Locus of attention has changed from navigation to search   Hard-coded navigation structures are losing ground to pogo strikes Navigation Blindness  Navigation Fatigue  Page Paradigm  Transitional Volatility  Users need inducement to move further into the site  Search technology rewards relationship navigation   Berrypicking Information Model System approach to navigation development   Systems have specific behaviors and outcomes ascentium.com

Slide 12: Initiate: Site Organization Strategy Distance makes a difference  Hierarchy reflects relevance  MOSS 2007 and use of structural factors  URL depth: the further from the homepage, the less important it must be   Click distance: the further from an authority page, the less important it must be Architecture extends from the site to the page  ascentium.com

Slide 13: Initiate: Linking Strategy Links are human-mediated relationships   Blast services are no longer worthwhile Related sites, niche directories, online bookmarking sites, provide starting points  Create link-based relationship model of relevance   Create or find authority  Hook up to HUBs  Think beyond the site ascentium.com

Slide 14: Cooperate: Page Code Strategy Reveal the site to the search technology   Sitemap.xml Provide on the page navigation   Don’t rely on dynamic navigation that spider cannot read Craft structures that cue technology on importance  Illuminate the non-textual functionality   Optimize JScript and Flash ascentium.com

Slide 15: Initiate: Content Strategy Dense, subject-specific content is what is indexed  People will scroll  If they don't scroll, they will print it out  Content to code ratio of 25%  Promote a keyword-to-content ratio 10–15%  Design on-the-page structure to move important information to the top  Design relational content models   Next steps as well as more information Develop authority sections on site  Topic-based, not type-based  ascentium.com

Slide 16: Cooperate: Metadata Strategy Many forms of description   In the code  Page title [in the browser window]  Description  Keywords?  In the content  Display title  Content headings Most effective if unique to the content on the page   Say goodbye to cut and paste Description rivals structure for importance for user context   Ask.com thumbnails Humans determine the “meaning” of the document and inform the machine  ascentium.com

Slide 17: SEO and IA: Threats and Opportunities Threats Opportunities Users seeking human-mediated guides  Search technology advances without  to find information user representation Current search rewards a more flexible  Search engines have become  and intuitive IA dominant navigation tool through information spaces Replaced by a new structural paradigm   Bountiful based on relationship and context  Relevant?  Hub and authorities  Quality over quantity Traditional IA methodology  increasingly less useful  Birds of a feather subject-wise  Hierarchy: pages further from the home page deemed less important  Hard-coded navigation: not visible to search engines  Not Authority-based ascentium.com

Slide 18: Marianne Sweeny marianne.sweeny@ascentium.com ascentium.com