Slideshow transcript
Slide 1: Search To Social Search Danny Sullivan Editor-In-Chief Search Engine Land http://searchengineland.com
Slide 2: 1st Gen: “On The Page” Search engines “crawl” links to pages They make copies of pages they find and store in a book-like “index” They find pages using words you searched for The location and frequency of words influences which ranks tops
Slide 3: 1st Gen Spamming Want to be tops? “Stuff” a bunch of keywords into your web page
Slide 4: 1st Gen Spamming
Slide 5: 1st Gen Spamming
Slide 6: 1st Gen Spamming
Slide 7: 2nd Gen: “Off The Page” Use factors off the page that webmasters can’t manipulate (so easily) Clickthrough Links: “democratic nature of the web” AKA PageRank though PageRank is importance of links Other key factor is anchor text, actual words in the links
Slide 8: 2nd Gen Issues People begin overtly manipulating links – thinking about votes, campaigning for votes and even buying votes…
Slide 9: 3rd Gen ??? “Vertical” search Focus on a particular topic, such as news Personalized & Social Search Reshaping results based on… What you personally do or visit What others you know do or visit What people in aggregate do or visit
Slide 10: Google Personalized Search Results are reordered based on what’s deemed to be your personal preferences. Pages move up, down, in or out of top 10
Slide 11: Personalization Influencers Google Personalized Home Page content Google Bookmarks Search History (Clicks) Web History (Visits)…
Slide 12: Search & Web History
Slide 13: Social Search Eurekster experimented with friend clicks reshaping results in 2004 Yahoo My Web promised to let us tag and use a network to reshape results…
Slide 14: Yahoo My Web
Slide 15: Yahoo My Web
Slide 16: My Web & Old Search Features
Slide 17: Social Search Reality Neither really has succeeded The Promise & Reality Of Mixing The Social Graph With Search Engines http://searchengineland.com/070827-121805.php Eurekster says “swickis” much better Yahoo dropped many features quietly But what about Facebook?
Slide 18: Facebook & Search Social graph (ugh) / social network data is potentially useful Watch what others are searching on Monitor clicks in a more “trusted” environment Reshape results based on what you friends seem to like But who are your friends…
Slide 19: Future Facebook? http://www.dumpfolder.net/?p=193
Slide 20: Facebook & Search Do you have to filter to “true” friends? Do you then still need to consider what you’ll share? Does Facebook instead work on aggregate level? And what’s the underlying platform? They’ll likely remain dependent on someone else…
Slide 21: Facebook & Search Go vertical? People search? Plenty in the space, Spock among them… http://searchengineland.com/lands/people- search.php Or events search Upcoming rival Others? Or discovery…
Slide 22: Search Versus Discovery Search is an on-demand, have particular need to fulfill activity Discovery is related but less specific in what you want StumbleUpon, Digg iGoogle related magic tabs
Slide 23: Search Engine Land (http://searchengineland.com) Stories and news from me and others SearchCap (http://searchengineland.com/searchcap.php) Daily email recap of search news from SEL & across the web Daily SearchCast (http://dailysearchcast.com) Podcast where I recap the day’s search news Sphinn (http://sphinn.com) Social site for search marketers: share news stories, talk in forums, network and view upcoming events SMX: Search Marketing Expo (http://searchmarketingexpo.com) My conference series that focuses on search marketing topics, with shows ranging from advanced issues to local, along with country-specific and general events





Add a comment on Slide 1
If you have a SlideShare account, login to comment; else you can comment as a guest- Favorites & Groups
Showing 1-50 of 12 (more)