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Search Analytics for Content Strategists
 

Search Analytics for Content Strategists

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Given at Confab 2012, Minneapolis, USA; May 16, 2012, NYC Content Strategy Meetup, September 27, 2012. Slides highly subject to change.

Given at Confab 2012, Minneapolis, USA; May 16, 2012, NYC Content Strategy Meetup, September 27, 2012. Slides highly subject to change.

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  • \n
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  • We get two major things out of this data: SESSIONS and FREQUENT QUERIES\n
  • Your brain on data: what will it do?\n
  • Your brain on data: what will it do?\n
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  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
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  • Personas: http://www.uie.com/images/blog/YahooExamplePersona.gif\nTable: From Jarrett, Quesenbery, Stirling, and Allen’s report “Search Behaviour at OU;” April 6, 2007.\n
  • Personas: http://www.uie.com/images/blog/YahooExamplePersona.gif\nTable: From Jarrett, Quesenbery, Stirling, and Allen’s report “Search Behaviour at OU;” April 6, 2007.\n
  • Personas: http://www.uie.com/images/blog/YahooExamplePersona.gif\nTable: From Jarrett, Quesenbery, Stirling, and Allen’s report “Search Behaviour at OU;” April 6, 2007.\n
  • Personas: http://www.uie.com/images/blog/YahooExamplePersona.gif\nTable: From Jarrett, Quesenbery, Stirling, and Allen’s report “Search Behaviour at OU;” April 6, 2007.\n
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  • More great illustrations by Eva-Lotta Lamm\n
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Search Analytics for Content Strategists Search Analytics for Content Strategists Presentation Transcript

  • Search Analytics forContent StrategistsLouis Rosenfeld • Rosenfeld Medialou@louisrosenfeld.com • @louisrosenfeldNYC Content Strategy Meetup • September 27, 2012
  • Hello, my name is Lou www.louisrosenfeld.com | www.rosenfeldmedia.com
  • Let’s look at the data
  • No, let’s really look at the dataCritical elements in bold: IP address, time/date stamp, query, and # of results:XXX.XXX.X.104 - - [10/Jul/2006:10:25:46 -0800] "GET /search?access=p&entqr=0 &output=xml_no_dtd&sort=date%3AD%3AL %3Ad1&ud=1&site=AllSites&ie=UTF-8 &client=www&oe=UTF-8&proxystylesheet=www& q=lincense+plate&ip=XXX.XXX.X.104 HTTP/1.1" 200 971 0 0.02XXX.XXX.X.104 - - [10/Jul/2006:10:25:48 -0800] "GET /searchaccess=p&entqr=0 &output=xml_no_dtd&sort=date%3AD%3AL %3Ad1&ie=UTF-8&client=www& q=license+plate&ud=1&site=AllSites &spell=1&oe=UTF-8&proxystylesheet=www& ip=XXX.XXX.X.104 HTTP/1.1" 200 8283 146 0.16
  • No, let’s really look at the dataCritical elements in bold: IP address, time/date stamp, query, and # of results: What are usersXXX.XXX.X.104 - - [10/Jul/2006:10:25:46 -0800] "GET /search?access=p&entqr=0 searching? &output=xml_no_dtd&sort=date%3AD%3AL %3Ad1&ud=1&site=AllSites&ie=UTF-8 &client=www&oe=UTF-8&proxystylesheet=www& q=lincense+plate&ip=XXX.XXX.X.104 HTTP/1.1" 200 971 0 0.02XXX.XXX.X.104 - - [10/Jul/2006:10:25:48 -0800] "GET /searchaccess=p&entqr=0 &output=xml_no_dtd&sort=date%3AD%3AL %3Ad1&ie=UTF-8&client=www& q=license+plate&ud=1&site=AllSites &spell=1&oe=UTF-8&proxystylesheet=www& ip=XXX.XXX.X.104 HTTP/1.1" 200 8283 146 0.16
  • No, let’s really look at the dataCritical elements in bold: IP address, time/date stamp, query, and # of results: What are usersXXX.XXX.X.104 - - [10/Jul/2006:10:25:46 -0800] "GET /search?access=p&entqr=0 searching? &output=xml_no_dtd&sort=date%3AD%3AL %3Ad1&ud=1&site=AllSites&ie=UTF-8 &client=www&oe=UTF-8&proxystylesheet=www& q=lincense+plate&ip=XXX.XXX.X.104 HTTP/1.1" 200 971 0 0.02XXX.XXX.X.104 - - [10/Jul/2006:10:25:48 -0800] "GET /searchaccess=p&entqr=0 &output=xml_no_dtd&sort=date%3AD%3AL How often are %3Ad1&ie=UTF-8&client=www& users failing? q=license+plate&ud=1&site=AllSites &spell=1&oe=UTF-8&proxystylesheet=www& ip=XXX.XXX.X.104 HTTP/1.1" 200 8283 146 0.16
  • SSA is semantically rich data, and...
  • SSA is semantically rich data, and... Queries sorted by frequency
  • ...what users want in their own words
  • A handful of queries/tasks/ways to navigate/features/ documents A little goes a long waymeet the needs of your most important audiences
  • A handful of queries/tasks/ways to navigate/features/ documents A little goes a long waymeet the needs of your most important audiences Not all queries are distributed equally
  • A handful of queries/tasks/ways to navigate/features/ documents A little goes a long waymeet the needs of your most important audiences
  • A handful of queries/tasks/ways to navigate/features/ documents A little goes a long waymeet the needs of your most important audiences Nor do they diminish gradually
  • A handful of queries/tasks/ways to navigate/features/ documents A little goes a long waymeet the needs of your most important audiences
  • A handful of queries/tasks/ways to navigate/features/ documents A little goes a long waymeet the needs of your most important audiences 80/20 rule isn’t quite accurate
  • (and the tail is quite long)
  • (and the tail is quite long)
  • (and the tail is quite long)
  • (and the tail is quite long)
  • (and the tail is quite long)
  • The Zipf Curve, textually
  • Hey content strategists:ever heard this one?
  • Hey content strategists:ever heard this one? unverified rumor alert
  • Hey content strategists:ever heard this one? unverified rumor alert 90% of Microsoft.com content
  • Hey content strategists:ever heard this one? unverified rumor alert 90% of Microsoft.com content has never been accessed...
  • Hey content strategists:ever heard this one? unverified rumor alert 90% of Microsoft.com content has never been accessed... not even once
  • Hey content strategists:ever heard this one? unverified rumor alert 90% of Microsoft.com content has never been accessed... not even once
  • 7 ways SSA helps content strategists 1.Determine logical content types 2.Develop contextual navigation 3.Detect failed content 4.Reduce jargon 5.Learn how audiences differ 6.Develop a publishing schedule 7.Predict the future
  • #1Determine logical content types
  • Start with basic SSA data:queries and query frequency Percent: volume of search activity for a unique query during a particular time period Cumulative Percent: running sum of percentages
  • “What types of content areusers seeking?”
  • Logical content types out ofsite search analytics Take an hour to... • Cluster and analyze top 50 queries (20% of all search activity) • Ask and iterate: “what types of content would users be looking for when searching these queries?” • Add cumulative percentages Result: prioritized list of potential content types #1) application: 11.77% #2) reference: 10.5% #3) instructions: 8.6% #4) main/navigation pages: 5.91% #5) contact info: 5.79% #6) news/announcements: 4.27%
  • #2Develop contextual navigation
  • 1.Choose acontent type (e.g.,events) 
2.Ask: “Whereshould users gofrom here?” 
3.Analyze thefrequent queriesfrom this contenttype from aiga.org 

  • 
 
 
 
 
 
Analyze frequent queries generated from each content sample
  • Hello, desire lines...
  • Content types + contextual navigation= content models album pages artist descriptions TV listingsalbum reviews discography artist bios
  • Content models also improvesearch performance
  • Content models also improvesearch performance
  • Content models also improvesearch performance Content objects related to products
  • Content models also improvesearch performance Content objects related to products Raw, crappy search results
  • (Pssst. User studies are anotherway to get at content models)
  • #3Detect failed content
  • Unexpected searchingmay indicate failed content Look for critical pages (beyond main page) that generate lots of search traffic What’s going on?
  • Where navigation is failing (“Professional Resources” page)Do users andAIGA meandifferentthings by“ProfessionalResources”?
  • Comparing what users findand what they want
  • Comparing what users findand what they want
  • #4Reduce jargon
  • Saving the brand by killing jargonat a community collegeJargon related to online education: FlexEd, COD, College on DemandMarketing’s solution: expensive campaign to educate public (via posters, brochures)The Numbers query rank query (from SSA): #22 online* #101 COD #259 College on Demand #389 FlexTrack * “online” part of 213 queriesResult: content relabeled, money saved
  • #5Learn how audiences differ
  • Who cares about what? (AIGA.org)
  • Who cares about what? (AIGA.org)
  • Who cares about what?
  • Who cares about what?
  • Who cares about what?
  • Who cares about what?
  • Why analyze queries by audience?Fortify your personas with dataLearn about differences--including tone and voice--between audiences • Open University “Enquirers”: 16 of 25 queries are for subjects not taught at OU • Open University Students: search for course codes, topics dealing with completing programDetermine what’s commonly important to all audiences (these queries better work well)
  • #6Develop a publishing schedule
  • Interest in the football team: going...
  • Interest in the football team: going... ...going...
  • Interest in the football team: going... ...going... gone
  • Time toInterest in the study! football team: going... ...going... gone
  • BeforeTax Day
  • AfterTax Day
  • #7Predict the future
  • Shaping theFinancial Times’ editorial agendaFT compares these • Spiking queries for proper nouns (i.e., people and companies) • Recent editorial coverage of people and companiesDiscrepancy? • Breaking story?! • Let the editors know!
  • Again: 7 ways SSA helps you guys1.Determine logical content types2.Develop contextual navigation3.Detect failed content4.Reduce jargon5.Learn how audiences differ6.Develop a publishing schedule7.Predict the future
  • Some things you can do right away
  • Some things you can do right away1.Set up SSA in Google Analytics
  • Some things you can do right away1.Set up SSA in Google Analytics2.Query your queries
  • Some things you can do right away1.Set up SSA in Google Analytics2.Query your queries3.Start developing a site report card
  • Turn on SSA in Google AnalyticsSet up GA for your site if you haven’t alreadyThen teach it to parse and capture your search engine’s queries (not set by default)References • http://is.gd/cR0qr • http://is.gd/cR0qP
  • Seed your analysis byquerying your queriesStarter questions 1. What are the most frequent unique queries? 2. Are frequent queries retrieving quality results? 3. Click-through rates per frequent query? 4. Most frequently clicked result per query? 5. Which frequent queries retrieve zero results? 6. What are the referrer pages for frequent queries? 7. Which queries retrieve popular documents? 8. What interesting patterns emerge in general?
  • Use SSA to start workon a site report card
  • Use SSA to start work SSA helps determine commonon a site report card information needs
  • Read this Search Analytics for Your Site: Conversations with Your Customers by Louis Rosenfeld (Rosenfeld Media, 2011) www.rosenfeldmedia.com Use code FOLBR2020 for 20% off all Rosenfeld Media products
  • Say helloLouis Rosenfeldlou@louisrosenfeld.comwww.louisrosenfeld.comwww.rosenfeldmedia.com@louisrosenfeld@rosenfeldmedia