Search Analytics: Diagnosing what ails your site Web Manager University September 27, 2006 Louis Rosenfeld www.louisrosenfeld.com
About me Information architecture (IA) consultant; formerly president Argus Associates Publisher and founder, Rosenfeld Media (www.rosenfeldmedia.com) Background in librarianship/information science; consult for Fortune 500s Co-author,  Information Architecture for the World Wide Web  (3rd edition out this fall) Co-founder,  Information Architecture Institute  (www.iainstitute.org) and  UXnet  (www.uxnet.org)
AOL Searcher #4417749 Interests 60 single men aameetings in georgia plastic surgeons in gwinnett county applying to west point bipolar panic disorders yerba mate shedless dogs movies for dogs new zealand real estate Thelma Arnold 62-year old widow Lilburn, GA resident NY Times , August 9, 2006:  “A Face Is Exposed for AOL Searcher No. 4417749”
Our Inadvertent Search Analytics Education, courtesy AOL  http://www.aolsearchdatabase.com 650,000 searchers 21,000,000 queries
Analyze This: Keywords: focis; 0; 11/26/04 12:57 PM; XXX.XXX.XXX.2 Keywords: focus; 167; 11/26/04 12:59 PM; XXX.XXX.XXX.2 Keywords: focus pricing; 12; 11/26/04 1:02 PM; XXX.XXX.XXX.2 Keywords: discounts for college students; 0; 11/26/04 3:35 PM; XXX.XXX.XXX.59 Keywords: student discounts; 3; 11/26/04 3:35 PM; XXX.XXX.XXX.59 Keywords: ford or mercury; 500; 11/26/04 3:35 PM; XXX.XXX.XXX.126 Keywords: (ford or mercury) and dealers; 73; 11/26/04 3:36 PM; XXX.XXX.XXX.126 Keywords: lorry; 0; 11/26/04 3:36 PM; XXX.XXX.XXX.36 Keywords: “safety ratings”; 3; 11/26/04 3:36 PM; XXX.XXX.XXX.55 Keywords: safety; 389; 11/26/04 3:36 PM; XXX.XXX.XXX.55 Keywords: seatbelts; 2; 11/26/04 3:37 PM; XXX.XXX.XXX.55 Keywords: seat belts; 33; 11/26/04 3:37 PM; XXX.XXX.XXX.55
The Head, the Long Tail, and the Interesting Stuff in Between Sorting queries by frequency results in a Zipf Distribution Can we improve performance for the most popular queries?
User Research: What do they want?… SA is a true expression of users’ information needs (often surprising:  e.g., SKU numbers at LL Bean; URLs at IBM) Provides context by displaying aspects of single search sessions
User Research: …who wants it?… What can you learn from knowing these things? What specific segments want; determined by: Security clearance IP address Job function Account information Which pages they initiate searches from
Users Research: …and when do they want it? Time-based variation (and clustered queries) By hour, by day, by season Helps determine “best bets” and “guide” develop- ment
Search Entry Interface Design: “The Box” or something else? SA identifies “dead end” points (e.g., 0 hits, 2000 hits) where assistance could be added (e.g., revise search, browsing alternative)  Syntax of queries informs selection of search features to expose (e.g., use of Boolean operators, fielded searching) … OR…
Search Results Interface Design: Which results where? #10 result is clicked through more often than #s 6, 7, 8, and 9 (ten results per page) From SLI Systems (www.sli-systems.com)
Search Results Interface Design: How to sort results? Financial Times  has found that users often include dates in their queries Obvious but effective improvement:  Allow users to sort by date
Navigation: Any improvements? Michigan State University builds A-Z index automatically based on frequent queries
Navigation: Where does it fail? Track and study pages (excluding main page) where search is initiated Are there obvious issues that would cause a “dead end”?  Are there user studies that could test/validate problems on these pages? Sandia Labs analyzes most requested documents to test content independent of site structure; results used to improve structure
Search System: What to change? Identify new functionality:  Financial Times  added spell checking Retrieval algorithm modifications: Deloitte, Barnes & Noble use SA to demonstrate that basic improvements (e.g., Best Bets) are insufficient Financial Times  weights company names higher
Metadata Development: How do users express their needs? SA provides a sense of  tone:  how users’ needs are expressed  Jargon (e.g., “cancer” vs. “oncology,” “lorry” vs. “truck,” acronyms) Length (e.g., number of terms/query) Syntax (e.g., Boolean, natural language, keyword)
Metadata Development: Which metadata values? SA helps in the creation of controlled vocabularies Terms are fodder for metadata values (e.g., “cell phone,” “JFK” vs. “John Kennedy,” “country music”), especially for determining preferred terms Works with tools that cluster synonyms (example from www.behaviortracking.com), enabling concept searching and thesaurus development
Metadata Development: Which metadata attributes? SA helps in the creation of vocabularies Simple cluster analysis can detect metadata attributes (e.g., “product,” “person,” “topic”) Look for variations between short head and long tail (Deloitte intranet:  “known-item”  queries are  common;  research topics  are infrequent) known-item queries research queries
Content Development: Do we have the right content? SA identifies content that can’t be found (0 results) Does the content exist?  If so, there are wording, metadata, or spidering problems If not, why not? www.behaviortracking.com
Content Development: Are we featuring the right stuff? Clickthrough tracking helps determine which results should rise to the top (example:  SLI Systems) Also suggests which “best bets” to develop to address common queries
Organizational Impact: Educational opportunities SA is a way to “reverse engineer” how your site performs in order to: Sensitize organization to analytics, specifically related to findability Sensitize content owners/authors to benefits of good practices around content titling, tagging, and navigational placement
Organizational Impact: Rethinking how you do things Financial Times  learns about breaking stories from their logs by monitoring spikes in company names and individuals’ names and comparing with their current coverage Discrepancy = possible breaking story; reporter is assigned to follow up Next step?  Assign reporters to “beats” that emerge from SA
The Ideal SLA report  1/2 (from Avi Rappoport) # searches for each week/month/quarter/year Top 1% of queries  (cluster by stem if possible) Top 10% of no-matches queries Top 10% of low-matches queries?  (one to 4 hits, or more depending on site size) # empty searches Changes in these over the last week/month/quarter/year Changes’ correlation to changes in the site, search engine,  company profile
The Ideal SLA report  2/2 (from Avi Rappoport) Queries showing significant increases Patterns in less-frequent queries -- names? places? web site addresses? Top pages retrieved in search results and the queries that retrieved them  Queries that retrieved the best/most important pages For search zones, create reports for each zone (will have significant impact on no-matches data)
SA as User Research Method:  Sleeper, but no panacea Benefits Non-intrusive Inexpensive and (usually) accessible Large volume of “real” data Represents actual usage patterns Drawbacks Provides an incomplete picture of usage:  was user satisfied at session’s end? Difficult to analyze:  where are the commercial tools? Ultimately an excellent  complement  to qualitative methods (e.g., task analysis, field studies)
SA headaches: What gets in the way? Lack of time Few useful tools for parsing logs, generating reports Tension between those who want to perform SA and those who “own” the data (chiefly IT) Ignorance of the method Hard work and/or boredom of doing analysis  From summer 2007 survey (134 responses)  www.rosenfeldmedia.com/books/searchanalytics/blog/search_analytics_survey_result/
Please Share Your SA Knowledge: Visit our “book in progress” site Site URL:  www.rosenfeldmedia.com/books/searchanalytics/ Feed URL:  feeds.rosenfeldmedia.com/searchanalytics/ Site contains: Reading list Survey results Perl script for  parsing logs Log samples … and more
Contact Information Louis Rosenfeld LLC 902 Miller Avenue Ann Arbor, Michigan  48103  USA [email_address] www.louisrosenfeld.com +1.734.302.3323 voice +1.734.661.1655 fax

More Related Content

PPT
tagging idea
PPT
Intro To Ia
PDF
Enterprise Information Architecture: Because users don't care about your org...
PDF
Searchland: Search quality for Beginners
PPT
Search Systems
PDF
Team of Rivals: UX, SEO, Content & Dev UXDC 2015
PPTX
Semtech bizsemanticsearchtutorial
PPT
Best practices for building usable & accessible Web content
tagging idea
Intro To Ia
Enterprise Information Architecture: Because users don't care about your org...
Searchland: Search quality for Beginners
Search Systems
Team of Rivals: UX, SEO, Content & Dev UXDC 2015
Semtech bizsemanticsearchtutorial
Best practices for building usable & accessible Web content

What's hot (19)

PPT
2008 web-managers-hwilfert-final
PPT
Hybrid Approaches to Taxonomy & Folksonmy
PPT
Dan Brown's Communicating Design Presentation to DOE
PDF
PPT
Search Analytics: Conversations with Your Customers
PPT
IA Summit 09 - User Interfaces with Metasearch Capabilities
PPTX
An Introduction to Entities in Semantic Search
PPTX
Understanding Information Architecture
PPT
Incentive Architecture 1224362486736986 8
PDF
Personalized search
PPT
Jensen Harris: Beyond Menus and Toolbars in Microsoft Office
PPTX
Introduction to Information Architecture & Design - 2/14/15
PPT
What is Information Architecture?
PDF
Introduction to Information Architecture
PPT
PowerPoint Only
PPTX
The Ultimate Website Development Roadmap
PDF
Information architecture and SharePoint
PPT
PR 313 - Public Relations & the World Wide Web
PDF
Google and their stance on Link Evolution
2008 web-managers-hwilfert-final
Hybrid Approaches to Taxonomy & Folksonmy
Dan Brown's Communicating Design Presentation to DOE
Search Analytics: Conversations with Your Customers
IA Summit 09 - User Interfaces with Metasearch Capabilities
An Introduction to Entities in Semantic Search
Understanding Information Architecture
Incentive Architecture 1224362486736986 8
Personalized search
Jensen Harris: Beyond Menus and Toolbars in Microsoft Office
Introduction to Information Architecture & Design - 2/14/15
What is Information Architecture?
Introduction to Information Architecture
PowerPoint Only
The Ultimate Website Development Roadmap
Information architecture and SharePoint
PR 313 - Public Relations & the World Wide Web
Google and their stance on Link Evolution
Ad

Viewers also liked (16)

PPS
Creative Photographs
PDF
Lisbeth amaro
PPTX
Presentación trabajo en equipo
PDF
Pre-Cal 20S September 16, 2008
PPTX
Sexsmith tv board
PPT
Financial Statements, Chapter 20
PDF
OS Bootcamp Workshop v1.4 - MR-5CN-GSAPICSOS
DOCX
Los ángeles
DOC
Prashant-MIS
PDF
Social information
PDF
PPTX
Cuidados de enfermeria durante el purperio
PDF
маркетинг лекція 1
PPT
Usability
PDF
Como elaborar-plan-estrategico
PPT
2010 12 Safety Audit
Creative Photographs
Lisbeth amaro
Presentación trabajo en equipo
Pre-Cal 20S September 16, 2008
Sexsmith tv board
Financial Statements, Chapter 20
OS Bootcamp Workshop v1.4 - MR-5CN-GSAPICSOS
Los ángeles
Prashant-MIS
Social information
Cuidados de enfermeria durante el purperio
маркетинг лекція 1
Usability
Como elaborar-plan-estrategico
2010 12 Safety Audit
Ad

Similar to Search Analytics: Diagnosing what ails your site (20)

PPT
Search Analytics: Powerful diagnostics for your site
PPT
Search Analytics: Diagnosing what ails your site
PPT
Search Analytics for Fun and Profit
PPT
Using Search Analytics to Diagnose What’s Ailing your Information Architecture
PPT
Site Search Analytics eMetrics Madrid 2009
PDF
Site search analytics workshop presentation
PPT
Search Analytics For Content Strategists @CSofNYC
PDF
Site Search Analytics in a Nutshell
PDF
Louis Rosenfeld: Nettstedssøk i et nøtteskall (Webdagene 2013)
KEY
Search Analytics for Content Strategists
PDF
How Just a Little Data Analysis Can Improve your Content
KEY
Improving Findability through Site Search Analytics
PPT
Tuning Up Site Search - IA Summit 2007
PDF
Configuring share point 2010 just do it
PDF
3 ways to improve searchability
PPTX
Keyword research tools for Search Engine Optimisation (SEO)
PPT
Search and Filter Interface Round Up - Userability Marathon 2009 - Amy Cueva
PDF
Information Architecture for SharePoint
PPTX
SharePoint 2013 search improvements
PDF
Search Analytics - Comperio
Search Analytics: Powerful diagnostics for your site
Search Analytics: Diagnosing what ails your site
Search Analytics for Fun and Profit
Using Search Analytics to Diagnose What’s Ailing your Information Architecture
Site Search Analytics eMetrics Madrid 2009
Site search analytics workshop presentation
Search Analytics For Content Strategists @CSofNYC
Site Search Analytics in a Nutshell
Louis Rosenfeld: Nettstedssøk i et nøtteskall (Webdagene 2013)
Search Analytics for Content Strategists
How Just a Little Data Analysis Can Improve your Content
Improving Findability through Site Search Analytics
Tuning Up Site Search - IA Summit 2007
Configuring share point 2010 just do it
3 ways to improve searchability
Keyword research tools for Search Engine Optimisation (SEO)
Search and Filter Interface Round Up - Userability Marathon 2009 - Amy Cueva
Information Architecture for SharePoint
SharePoint 2013 search improvements
Search Analytics - Comperio

More from Louis Rosenfeld (20)

PDF
Information Architecture for Truth
PDF
Falling in and out and in love with Information Architecture
PDF
What to do when you don't know what to do
PDF
Redesign Must Die (updated Feb 2014)
KEY
8 Information Architecture Better Practices
KEY
Closing the Findability Gap: 8 better practices from information architecture
KEY
Design to Refine: Developing a tunable information architecture
KEY
Redesign Must Die
KEY
Adaptable Information Workshop slides
PDF
Beyond User Research
KEY
Is there such a thing as a good business model for publishing these days?
PDF
User Experience + Publishing
KEY
Marrying Web Analytics and User Experience
PDF
Redesign Must Die
PDF
Site Search Analytics
PDF
Site Search Analytics: Conversations with your customers
PDF
PhillyCHI Site Search Analytics presentation (April 2, 2008)
KEY
Site Search Analytics Workshop Presentation
PPT
CanUX Keynote
PPT
Eating Our Own Dog Food: Using UX Methods to Build a UX Business
Information Architecture for Truth
Falling in and out and in love with Information Architecture
What to do when you don't know what to do
Redesign Must Die (updated Feb 2014)
8 Information Architecture Better Practices
Closing the Findability Gap: 8 better practices from information architecture
Design to Refine: Developing a tunable information architecture
Redesign Must Die
Adaptable Information Workshop slides
Beyond User Research
Is there such a thing as a good business model for publishing these days?
User Experience + Publishing
Marrying Web Analytics and User Experience
Redesign Must Die
Site Search Analytics
Site Search Analytics: Conversations with your customers
PhillyCHI Site Search Analytics presentation (April 2, 2008)
Site Search Analytics Workshop Presentation
CanUX Keynote
Eating Our Own Dog Food: Using UX Methods to Build a UX Business

Recently uploaded (20)

PDF
Five Habits of High-Impact Board Members
PPTX
Final SEM Unit 1 for mit wpu at pune .pptx
PPTX
Chapter 5: Probability Theory and Statistics
PDF
STKI Israel Market Study 2025 version august
PPTX
Microsoft Excel 365/2024 Beginner's training
PDF
Hindi spoken digit analysis for native and non-native speakers
PDF
TrustArc Webinar - Click, Consent, Trust: Winning the Privacy Game
DOCX
search engine optimization ppt fir known well about this
PDF
A comparative study of natural language inference in Swahili using monolingua...
PDF
Getting started with AI Agents and Multi-Agent Systems
PDF
CloudStack 4.21: First Look Webinar slides
PPTX
AI IN MARKETING- PRESENTED BY ANWAR KABIR 1st June 2025.pptx
PDF
Consumable AI The What, Why & How for Small Teams.pdf
PDF
UiPath Agentic Automation session 1: RPA to Agents
PDF
NewMind AI Weekly Chronicles – August ’25 Week III
PPTX
MicrosoftCybserSecurityReferenceArchitecture-April-2025.pptx
PDF
Two-dimensional Klein-Gordon and Sine-Gordon numerical solutions based on dee...
PDF
Zenith AI: Advanced Artificial Intelligence
PDF
A contest of sentiment analysis: k-nearest neighbor versus neural network
PDF
ENT215_Completing-a-large-scale-migration-and-modernization-with-AWS.pdf
Five Habits of High-Impact Board Members
Final SEM Unit 1 for mit wpu at pune .pptx
Chapter 5: Probability Theory and Statistics
STKI Israel Market Study 2025 version august
Microsoft Excel 365/2024 Beginner's training
Hindi spoken digit analysis for native and non-native speakers
TrustArc Webinar - Click, Consent, Trust: Winning the Privacy Game
search engine optimization ppt fir known well about this
A comparative study of natural language inference in Swahili using monolingua...
Getting started with AI Agents and Multi-Agent Systems
CloudStack 4.21: First Look Webinar slides
AI IN MARKETING- PRESENTED BY ANWAR KABIR 1st June 2025.pptx
Consumable AI The What, Why & How for Small Teams.pdf
UiPath Agentic Automation session 1: RPA to Agents
NewMind AI Weekly Chronicles – August ’25 Week III
MicrosoftCybserSecurityReferenceArchitecture-April-2025.pptx
Two-dimensional Klein-Gordon and Sine-Gordon numerical solutions based on dee...
Zenith AI: Advanced Artificial Intelligence
A contest of sentiment analysis: k-nearest neighbor versus neural network
ENT215_Completing-a-large-scale-migration-and-modernization-with-AWS.pdf

Search Analytics: Diagnosing what ails your site

  • 1. Search Analytics: Diagnosing what ails your site Web Manager University September 27, 2006 Louis Rosenfeld www.louisrosenfeld.com
  • 2. About me Information architecture (IA) consultant; formerly president Argus Associates Publisher and founder, Rosenfeld Media (www.rosenfeldmedia.com) Background in librarianship/information science; consult for Fortune 500s Co-author, Information Architecture for the World Wide Web (3rd edition out this fall) Co-founder, Information Architecture Institute (www.iainstitute.org) and UXnet (www.uxnet.org)
  • 3. AOL Searcher #4417749 Interests 60 single men aameetings in georgia plastic surgeons in gwinnett county applying to west point bipolar panic disorders yerba mate shedless dogs movies for dogs new zealand real estate Thelma Arnold 62-year old widow Lilburn, GA resident NY Times , August 9, 2006: “A Face Is Exposed for AOL Searcher No. 4417749”
  • 4. Our Inadvertent Search Analytics Education, courtesy AOL http://www.aolsearchdatabase.com 650,000 searchers 21,000,000 queries
  • 5. Analyze This: Keywords: focis; 0; 11/26/04 12:57 PM; XXX.XXX.XXX.2 Keywords: focus; 167; 11/26/04 12:59 PM; XXX.XXX.XXX.2 Keywords: focus pricing; 12; 11/26/04 1:02 PM; XXX.XXX.XXX.2 Keywords: discounts for college students; 0; 11/26/04 3:35 PM; XXX.XXX.XXX.59 Keywords: student discounts; 3; 11/26/04 3:35 PM; XXX.XXX.XXX.59 Keywords: ford or mercury; 500; 11/26/04 3:35 PM; XXX.XXX.XXX.126 Keywords: (ford or mercury) and dealers; 73; 11/26/04 3:36 PM; XXX.XXX.XXX.126 Keywords: lorry; 0; 11/26/04 3:36 PM; XXX.XXX.XXX.36 Keywords: “safety ratings”; 3; 11/26/04 3:36 PM; XXX.XXX.XXX.55 Keywords: safety; 389; 11/26/04 3:36 PM; XXX.XXX.XXX.55 Keywords: seatbelts; 2; 11/26/04 3:37 PM; XXX.XXX.XXX.55 Keywords: seat belts; 33; 11/26/04 3:37 PM; XXX.XXX.XXX.55
  • 6. The Head, the Long Tail, and the Interesting Stuff in Between Sorting queries by frequency results in a Zipf Distribution Can we improve performance for the most popular queries?
  • 7. User Research: What do they want?… SA is a true expression of users’ information needs (often surprising: e.g., SKU numbers at LL Bean; URLs at IBM) Provides context by displaying aspects of single search sessions
  • 8. User Research: …who wants it?… What can you learn from knowing these things? What specific segments want; determined by: Security clearance IP address Job function Account information Which pages they initiate searches from
  • 9. Users Research: …and when do they want it? Time-based variation (and clustered queries) By hour, by day, by season Helps determine “best bets” and “guide” develop- ment
  • 10. Search Entry Interface Design: “The Box” or something else? SA identifies “dead end” points (e.g., 0 hits, 2000 hits) where assistance could be added (e.g., revise search, browsing alternative) Syntax of queries informs selection of search features to expose (e.g., use of Boolean operators, fielded searching) … OR…
  • 11. Search Results Interface Design: Which results where? #10 result is clicked through more often than #s 6, 7, 8, and 9 (ten results per page) From SLI Systems (www.sli-systems.com)
  • 12. Search Results Interface Design: How to sort results? Financial Times has found that users often include dates in their queries Obvious but effective improvement: Allow users to sort by date
  • 13. Navigation: Any improvements? Michigan State University builds A-Z index automatically based on frequent queries
  • 14. Navigation: Where does it fail? Track and study pages (excluding main page) where search is initiated Are there obvious issues that would cause a “dead end”? Are there user studies that could test/validate problems on these pages? Sandia Labs analyzes most requested documents to test content independent of site structure; results used to improve structure
  • 15. Search System: What to change? Identify new functionality: Financial Times added spell checking Retrieval algorithm modifications: Deloitte, Barnes & Noble use SA to demonstrate that basic improvements (e.g., Best Bets) are insufficient Financial Times weights company names higher
  • 16. Metadata Development: How do users express their needs? SA provides a sense of tone: how users’ needs are expressed Jargon (e.g., “cancer” vs. “oncology,” “lorry” vs. “truck,” acronyms) Length (e.g., number of terms/query) Syntax (e.g., Boolean, natural language, keyword)
  • 17. Metadata Development: Which metadata values? SA helps in the creation of controlled vocabularies Terms are fodder for metadata values (e.g., “cell phone,” “JFK” vs. “John Kennedy,” “country music”), especially for determining preferred terms Works with tools that cluster synonyms (example from www.behaviortracking.com), enabling concept searching and thesaurus development
  • 18. Metadata Development: Which metadata attributes? SA helps in the creation of vocabularies Simple cluster analysis can detect metadata attributes (e.g., “product,” “person,” “topic”) Look for variations between short head and long tail (Deloitte intranet: “known-item” queries are common; research topics are infrequent) known-item queries research queries
  • 19. Content Development: Do we have the right content? SA identifies content that can’t be found (0 results) Does the content exist? If so, there are wording, metadata, or spidering problems If not, why not? www.behaviortracking.com
  • 20. Content Development: Are we featuring the right stuff? Clickthrough tracking helps determine which results should rise to the top (example: SLI Systems) Also suggests which “best bets” to develop to address common queries
  • 21. Organizational Impact: Educational opportunities SA is a way to “reverse engineer” how your site performs in order to: Sensitize organization to analytics, specifically related to findability Sensitize content owners/authors to benefits of good practices around content titling, tagging, and navigational placement
  • 22. Organizational Impact: Rethinking how you do things Financial Times learns about breaking stories from their logs by monitoring spikes in company names and individuals’ names and comparing with their current coverage Discrepancy = possible breaking story; reporter is assigned to follow up Next step? Assign reporters to “beats” that emerge from SA
  • 23. The Ideal SLA report 1/2 (from Avi Rappoport) # searches for each week/month/quarter/year Top 1% of queries (cluster by stem if possible) Top 10% of no-matches queries Top 10% of low-matches queries? (one to 4 hits, or more depending on site size) # empty searches Changes in these over the last week/month/quarter/year Changes’ correlation to changes in the site, search engine, company profile
  • 24. The Ideal SLA report 2/2 (from Avi Rappoport) Queries showing significant increases Patterns in less-frequent queries -- names? places? web site addresses? Top pages retrieved in search results and the queries that retrieved them Queries that retrieved the best/most important pages For search zones, create reports for each zone (will have significant impact on no-matches data)
  • 25. SA as User Research Method: Sleeper, but no panacea Benefits Non-intrusive Inexpensive and (usually) accessible Large volume of “real” data Represents actual usage patterns Drawbacks Provides an incomplete picture of usage: was user satisfied at session’s end? Difficult to analyze: where are the commercial tools? Ultimately an excellent complement to qualitative methods (e.g., task analysis, field studies)
  • 26. SA headaches: What gets in the way? Lack of time Few useful tools for parsing logs, generating reports Tension between those who want to perform SA and those who “own” the data (chiefly IT) Ignorance of the method Hard work and/or boredom of doing analysis From summer 2007 survey (134 responses) www.rosenfeldmedia.com/books/searchanalytics/blog/search_analytics_survey_result/
  • 27. Please Share Your SA Knowledge: Visit our “book in progress” site Site URL: www.rosenfeldmedia.com/books/searchanalytics/ Feed URL: feeds.rosenfeldmedia.com/searchanalytics/ Site contains: Reading list Survey results Perl script for parsing logs Log samples … and more
  • 28. Contact Information Louis Rosenfeld LLC 902 Miller Avenue Ann Arbor, Michigan 48103 USA [email_address] www.louisrosenfeld.com +1.734.302.3323 voice +1.734.661.1655 fax