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Web Analytics: An Hour a Day

Book Description

Written by an in-the-trenches practitioner, this step-by-step guide shows you how to implement a successful Web analytics strategy. Web analytics expert Avinash Kaushik, in his thought-provoking style, debunks leading myths and leads you on a path to gaining actionable insights from your analytics efforts. Discover how to move beyond clickstream analysis, why qualitative data should be your focus, and more insights and techniques that will help you develop a customer-centric mindset without sacrificing your company’s bottom line.

Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Table of Contents

  1. Copyright
  2. Dear Reader,
  3. Acknowledgments
  4. About the Author
  5. Foreword
  6. Introduction
      1. Why Focus on Web Analytics?
      2. Who Can Use This book?
      3. What's Inside?
        1. Part I: The Foundation of Web Analytics
        2. Part II: The Trinity Approach
        3. Part III: Implementing your Web Analytics Plan
        4. Part IV: Advanced Web Analytics and "Data in your DNA"
        5. This Book's Companion Websites
        6. Request for Feedback
        7. Next Stop: Wonderland
  7. 1. Web Analytics—Present and Future
    1. 1.1. A Brief History of Web Analytics
    2. 1.2. Current Landscape and Challenges
    3. 1.3. Traditional Web Analytics Is Dead
    4. 1.4. What Web Analytics Should Be
      1. 1.4.1. Measuring Both the What and the Why
      2. 1.4.2. Trinity: A Mindset and a Strategic Approach
        1. 1.4.2.1. Behavior Analysis
        2. 1.4.2.2. Outcomes Analysis
        3. 1.4.2.3. Experience Analysis
        4. 1.4.2.4. Solving for Companies and Customers: Win-Win
        5. 1.4.2.5. Building an Integrated Trinity Platform
  8. 2. Data Collection—Importance and Options
    1. 2.1. Understanding the Data Landscape
    2. 2.2. Clickstream Data
      1. 2.2.1. Web Logs
        1. 2.2.1.1. Benefits of Using Web Logs as Your Data Collection Mechanism
        2. 2.2.1.2. Concerns about Using Web Logs as Your Data Collection Mechanism
        3. 2.2.1.3. Recommendation
      2. 2.2.2. Web Beacons
        1. 2.2.2.1. Benefits of Using Web Beacons as Your Data Collection Mechanism
        2. 2.2.2.2. Concerns about Using Web Beacons as Your Data Collection Mechanism
        3. 2.2.2.3. Recommendation
      3. 2.2.3. JavaScript Tags
        1. 2.2.3.1. Benefits of Using JavaScript Tagging as Your Data Collection Mechanism
        2. 2.2.3.2. Concerns about Using JavaScript Tagging as Your Primary Data Collection Mechanism
        3. 2.2.3.3. Recommendation
      4. 2.2.4. Packet Sniffing
        1. 2.2.4.1. Benefits of Using Packet Sniffers as Your Data Collection Mechanism
        2. 2.2.4.2. Concerns about Using Packet Sniffers as Your Data Collection Mechanism
        3. 2.2.4.3. Recommendation
    3. 2.3. Outcomes Data
      1. 2.3.1. E-commerce
      2. 2.3.2. Lead Generation
      3. 2.3.3. Brand/Advocacy and Support
    4. 2.4. Research Data
      1. 2.4.1. Mindset
      2. 2.4.2. Organizational Structure
      3. 2.4.3. Timing
    5. 2.5. Competitive Data
      1. 2.5.1. Panel-Based Measurement
        1. 2.5.1.1. Benefits of Using comScore (Panel-Based Measurement)
        2. 2.5.1.2. Concerns about Using comScore (Panel-Based) Data
        3. 2.5.1.3. Recommendation
      2. 2.5.2. ISP-Based Measurement
        1. 2.5.2.1. Benefits of Using Hitwise (ISP-Based Measurement)
        2. 2.5.2.2. Concerns about Using Hitwise (ISP-Based Measurement)
        3. 2.5.2.3. Recommendation
      3. 2.5.3. Search Engine Data
        1. 2.5.3.1. Benefits of Using Search Engine Data
        2. 2.5.3.2. Concerns about Using Search Engine Data
        3. 2.5.3.3. Recommendation
  9. 3. Overview of Qualitative Analysis
    1. 3.1. The Essence of Customer Centricity
    2. 3.2. Lab Usability Testing
      1. 3.2.1. Conducting a Test
        1. 3.2.1.1. Preparing the Test
        2. 3.2.1.2. Conducting the Test
        3. 3.2.1.3. Analyzing the Data
        4. 3.2.1.4. Following Up
      2. 3.2.2. Benefits of Lab Usability Tests
      3. 3.2.3. Things to Watch For
    3. 3.3. Heuristic Evaluations
      1. 3.3.1. Conducting a Heuristic Evaluation
      2. 3.3.2. Benefits of Heuristic Evaluations
      3. 3.3.3. Things to Watch For
    4. 3.4. Site Visits (Follow-Me-Home Studies)
      1. 3.4.1. Conducting a Site Visit
        1. 3.4.1.1. Preparing the Site Visit
        2. 3.4.1.2. Conducting the Site Visit
        3. 3.4.1.3. Analyzing the Data
      2. 3.4.2. Benefits of Site Visits
      3. 3.4.3. Things to Watch For
    5. 3.5. Surveys (Questionnaires)
      1. 3.5.1. Website Surveys
      2. 3.5.2. Post-Visit Surveys
      3. 3.5.3. Creating and Running a Survey
        1. 3.5.3.1. Preparing the Survey
        2. 3.5.3.2. Conducting the Survey
        3. 3.5.3.3. Analyzing the Data
        4. 3.5.3.4. Following Up
      4. 3.5.4. Benefits of Surveys
      5. 3.5.5. Things to Watch For
    6. 3.6. Summary
  10. 4. Critical Components of a Successful Web Analytics Strategy?
    1. 4.1. Focus on Customer Centricity
    2. 4.2. Solve for Business Questions
    3. 4.3. Follow the 10/90 Rule
    4. 4.4. Hire Great Web Analysts
    5. 4.5. Identify Optimal Organizational Structure and Responsibilities
      1. 4.5.1. Centralization
      2. 4.5.2. Decentralization
      3. 4.5.3. Centralized Decentralization
  11. 5. Web Analytics Fundamentals
    1. 5.1. Capturing Data: Web Logs or JavaScript tags?
      1. 5.1.1. Separating Data Serving and Data Capture
      2. 5.1.2. Type and Size of Data
      3. 5.1.3. Innovation
      4. 5.1.4. Integration
    2. 5.2. Selecting Your Optimal Web Analytics Tool
      1. 5.2.1. The Old Way
      2. 5.2.2. The New Way
        1. 5.2.2.1. Benefits of the New Way
    3. 5.3. Understanding Clickstream Data Quality
    4. 5.4. Implementing Best Practices
      1. 5.4.1. Tag All Your Pages
      2. 5.4.2. Make Sure Tags Go Last (Customers Come First!)
      3. 5.4.3. Tags Should Be Inline
      4. 5.4.4. Identify Your Unique Page Definition
      5. 5.4.5. Use Cookies Intelligently
      6. 5.4.6. Consider Link-Coding Issues
        1. 5.4.6.1. JavaScript Wrappers
        2. 5.4.6.2. Anchors
        3. 5.4.6.3. Multiple Source Links on a Page to the Same Target
      7. 5.4.7. Be Aware of Redirects
        1. 5.4.7.1. Internal Redirects
        2. 5.4.7.2. External Redirects
      8. 5.4.8. Validate That Data Is Being Captured Correctly
      9. 5.4.9. Correctly Encode Your Your Website Rich Media
    5. 5.5. Apply the "Three Layers of So What" Test
      1. 5.5.1. Key Performance Indicator: Percent of Repeat Visitors
      2. 5.5.2. Key Performance Indicator: Top Exit Pages on the Website
      3. 5.5.3. Key Performance Indicator: Conversion Rate for Top Search Keywords
  12. 6. Month 1: Diving Deep into Core Web Analytics Concepts
    1. 6.1. Week 1: Preparing to Understand the Basics
      1. 6.1.1. Monday and Tuesday: URLs
        1. 6.1.1.1. Why Should You Care?
        2. 6.1.1.2. What Should You Care About?
      2. 6.1.2. Wednesday: URL Parameters
        1. 6.1.2.1. Why Should You Care?
        2. 6.1.2.2. What Should You Care About?
      3. 6.1.3. Thursday and Friday: Cookies
        1. 6.1.3.1. Why Should You Care?
        2. 6.1.3.2. What Should You Care About?
    2. 6.2. Week 2: Revisiting Foundational Metrics
      1. 6.2.1. Monday: Visits and Visitors
        1. 6.2.1.1. Visits
        2. 6.2.1.2. Unique Visitors
        3. 6.2.1.3. Why Should You Care?
        4. 6.2.1.4. What Should You Care About?
      2. 6.2.2. Tuesday and Wednesday: Time on Site
        1. 6.2.2.1. Why Should You Care?
        2. 6.2.2.2. What Should You Care About?
      3. 6.2.3. Thursday and Friday: Page Views
        1. 6.2.3.1. Why Should You Care?
        2. 6.2.3.2. What Should You Care About?
    3. 6.3. Week 3: Understanding Standard Reports
      1. 6.3.1. Monday and Tuesday: Bounce Rate
        1. 6.3.1.1. Why Should You Care?
        2. 6.3.1.2. What Should You Care About?
      2. 6.3.2. Wednesday through Friday: Referrers—Sources and Search Key Phrases
        1. 6.3.2.1. Why Should You Care?
        2. 6.3.2.2. What Should You Care About?
    4. 6.4. Week 4: Using Website Content Quality and Navigation Reports
      1. 6.4.1. Monday and Tuesday: Top Pages—Most Viewed, Top Entry, Top Exit
        1. 6.4.1.1. Most Viewed Pages
          1. 6.4.1.1.1. Why Should You Care?
          2. 6.4.1.1.2. What Should You Care About?
        2. 6.4.1.2. Top Entry Pages
          1. 6.4.1.2.1. Why Should You Care?
          2. 6.4.1.2.2. What Should You Care About?
        3. 6.4.1.3. Top Exit Pages
          1. 6.4.1.3.1. Why Should You Care?
          2. 6.4.1.3.2. What Should You Care About?
      2. 6.4.2. Wednesday: Top Destinations (Exit Links)
        1. 6.4.2.1. Why Should You Care?
        2. 6.4.2.2. What Should You Care About?
      3. 6.4.3. Thursday and Friday: Site Overlay (Click Density Analysis)
        1. 6.4.3.1. Why Should You Care?
        2. 6.4.3.2. What Should You Care About?
  13. 7. Month 2: Jump-Start Your Web Data Analysis
    1. 7.1. Prerequisites and Framing
    2. 7.2. Week 1: Creating Foundational Reports
      1. 7.2.1. Monday: Top Referring URLs and Top Key Phrases
        1. 7.2.1.1. Top Referring URLs
        2. 7.2.1.2. Top Key Phrases from Search Engines
      2. 7.2.2. Tuesday: Site Content Popularity and Home Page Visits
        1. 7.2.2.1. Site Content Popularity
        2. 7.2.2.2. Percentage of Visitors Who Visit the Home Page
      3. 7.2.3. Wednesday and Thursday: Click Density, or Site Overlay
      4. 7.2.4. Friday: Site Bounce Rate
    3. 7.3. E-commerce Website Jump-Start Guide
      1. 7.3.1. Week 2: Measuring Business Outcomes
        1. 7.3.1.1. Monday through Wednesday: Measure Outcomes
        2. 7.3.1.2. Thursday and Friday: Measure Conversion Rate
      2. 7.3.2. Week 3: Indexing Performance and Measuring Merchandizing Effectiveness and Customer Satisfaction
        1. 7.3.2.1. Monday: Index Performance to Goals
        2. 7.3.2.2. Tuesday and Wednesday: Measure Effectiveness of Onsite Efforts
        3. 7.3.2.3. Thursday and Friday: Measure Customer Satisfaction
    4. 7.4. Support Website Jump-Start Guide
      1. 7.4.1. Week 2: Walking in the Customer's Shoes and Measuring Offline Impact
        1. 7.4.1.1. Monday and Tuesday: Identify Top Methods of Finding Information
        2. 7.4.1.2. Wednesday and Thursday: Perform Click Density Analysis of Top FAQs
        3. 7.4.1.3. Friday: Determine What Percent of Site Visitors Call the Support Phone Number
      2. 7.4.2. Week 3: Measuring Success by Using VOC or Customer Ratings (at a Site and Page Level)
        1. 7.4.2.1. Monday through Wednesday: Measure Problem Resolution, Timeliness, and Likelihood to Recommend
        2. 7.4.2.2. Thursday and Friday: Conduct Page-Level Surveys
    5. 7.5. Blog Measurement Jump-Start Guide
      1. 7.5.1. Week 2: Overcoming Complexity to Measure the Fundamentals (by Using New Metrics)
        1. 7.5.1.1. Monday: Understand Blog Measurement Complexity and Challenges
        2. 7.5.1.2. Tuesday: Measure Frequency and Raw Author Contribution
        3. 7.5.1.3. Wednesday and Thursday: Measure Unique Blog Readership
        4. 7.5.1.4. A Recap of Readership Definitions
        5. 7.5.1.5. Friday: Assess Conversation Rate
      2. 7.5.2. Week 3: Competitive Benchmarking and Measuring Cost and ROI
        1. 7.5.2.1. Monday: Use External Benchmarking—Technorati Rank
        2. 7.5.2.2. Tuesday and Wednesday: Measure the Cost of Blog Ownership
        3. 7.5.2.3. Thursday and Friday: Measure Return on Investment
    6. 7.6. Week 4: Reflections and Wrap-Up
  14. 8. Month 3: Search Analytics—Internal Search, SEO, and PPC
    1. 8.1. Week 1: Performing Internal Site Search Analytics
      1. 8.1.1. Monday: Understand the Value of the Internal Search
      2. 8.1.2. Tuesday: Spot Internal Search Trends
        1. 8.1.2.1. Measure Internal Site Search Usage Metrics
        2. 8.1.2.2. Report on the Top Internal Site Search Key Phrases
      3. 8.1.3. Wednesday: Analyze Click Density by Using the Site Overlay Report
      4. 8.1.4. Thursday: Measure Effectiveness of Actual Search Results
        1. 8.1.4.1. Measure the Exit Rate from the Search Results Page
        2. 8.1.4.2. Measure Effectiveness of Synonyms, or Best Bets
      5. 8.1.5. Friday: Measure Outcome Metrics for Internal Searches
    2. 8.2. Week 2: Beginning Search Engine Optimization
      1. 8.2.1. Monday: Understand the Impact of, and Optimize, Links
      2. 8.2.2. Tuesday: Link to Press Releases and Social Sites
      3. 8.2.3. Wednesday and Thursday: Optimize Web Page Tags and Content
      4. 8.2.4. Friday: Provide Guidance for Search Robots
    3. 8.3. Week 3: Measuring SEO Efforts
      1. 8.3.1. Monday: Check How Well Your Site Is Indexed
      2. 8.3.2. Tuesday: Track Inbound Links and Top Keywords
        1. 8.3.2.1. Track Inbound Links
        2. 8.3.2.2. Track Your Ranking for Your Top Keywords
      3. 8.3.3. Wednesday: Split Organic Referrals from PPC
      4. 8.3.4. Thursday: Measure the Value of Organic Referrals
      5. 8.3.5. Friday: Measure Optimization for Top Pages
    4. 8.4. Week 4: Analyzing Pay per Click Effectiveness
      1. 8.4.1. Monday: Understand PPC Basics
      2. 8.4.2. Tuesday: Measure Search Engine Bid-Related Metrics
      3. 8.4.3. Wednesday: Define Critical Bottom-Line-Impacting Metrics
      4. 8.4.4. Thursday: Measure Unique Visitors
      5. 8.4.5. Friday: Learn PPC Reporting Best Practices
  15. 9. Month 4: Measuring Email and Multichannel Marketing
    1. 9.1. Week 1: Email Marketing Fundamentals and a Bit More
      1. 9.1.1. Monday: Understand Email Marketing Fundamentals
      2. 9.1.2. Tuesday and Wednesday: Measure Basic Response Metrics
      3. 9.1.3. Thursday and Friday: Measure Outcome Metrics
    2. 9.2. Week 2: Email Marketing—Advanced Tracking
      1. 9.2.1. Monday and Tuesday: Measure Website Effectiveness
      2. 9.2.2. Wednesday: Avoid Email Analytics Pitfalls
      3. 9.2.3. Thursday and Friday: Integrate Your Email Campaign with Your Web Analytics Tools
    3. 9.3. Weeks 3 and 4: Multichannel Marketing, Tracking, and Analysis
      1. 9.3.1. Week 3: Understanding Multichannel Marketing, and Tracking Offline-to-Online Campaigns
        1. 9.3.1.1. Monday and Tuesday: Ponder Offline, Online, and Nonline Marketing
        2. 9.3.1.2. Wednesday through Friday: Track Offline-to-Online Behavior and Campaigns
      2. 9.3.2. Week 4: Tracking and Analyzing Multichannel Marketing
        1. 9.3.2.1. Monday and Tuesday: Track Online to Offline Behavior and Campaigns
        2. 9.3.2.2. Wednesday: Track Online-to-Online Behavior and Campaigns
        3. 9.3.2.3. Thursday and Friday: Track Online-for-Multichannel Behavior and Campaigns
  16. 10. Month 5: Website Experimentation and Testing—Shifting the Power to Customers and Achieving Significant Outcomes
    1. 10.1. Weeks 1 and 2: Why Test and What Are Your Options?
      1. 10.1.1. Week 1: Preparations and A/B Testing
        1. 10.1.1.1. Monday: Understand the Case for Testing
        2. 10.1.1.2. Tuesday: Learn to Be Wrong
        3. 10.1.1.3. Wednesday: Gain an Overview of the Methodologies
        4. 10.1.1.4. Thursday and Friday: Understand A/B Testing
          1. 10.1.1.4.1. Pros of Doing A/B Testing
          2. 10.1.1.4.2. Cons of Doing A/B Testing
          3. 10.1.1.4.3. Bottom Line on A/B testing
      2. 10.1.2. Week 2: Moving Beyond A/B Testing
        1. 10.1.2.1. Monday: Obtain an Overview of Multivariate Testing
        2. 10.1.2.2. Tuesday: Consider the Pros and Cons of Multivariate Testing
          1. 10.1.2.2.1. Pros of Doing Multivariate Testing
          2. 10.1.2.2.2. Cons of Doing Multivariate Testing
          3. 10.1.2.2.3. Bottom Line on Multivariate Testing
        3. 10.1.2.3. Wednesday: Obtain an Overview of Experience Testing
        4. 10.1.2.4. Thursday: Consider the Pros and Cons of Experience Testing
          1. 10.1.2.4.1. Pros of Doing Experience Testing
          2. 10.1.2.4.2. Cons of Doing Experience Testing
          3. 10.1.2.4.3. Bottom Line on Experience Testing
        5. 10.1.2.5. Friday: Reflect
    2. 10.2. Week 3: What to Test—Specific Options and Ideas
      1. 10.2.1. Monday: Test Important Pages and Calls to Action
        1. 10.2.1.1. Test Important Website Pages
        2. 10.2.1.2. Consider Calls to Action
      2. 10.2.2. Tuesday: Focus on Search Traffic
      3. 10.2.3. Wednesday: Test Content and Creatives
      4. 10.2.4. Thursday: Test Price and Promotions
      5. 10.2.5. Friday: Test Direct Marketing Campaigns
    3. 10.3. Week 4: Build a Great Experimentation and Testing Program
      1. 10.3.1. Monday: Hypothesize and Set Goals
        1. 10.3.1.1. Get Over Your Own Opinions
        2. 10.3.1.2. State a Hypothesis, Not a Test Scenario
        3. 10.3.1.3. Set Goals and Metrics Beforehand
      2. 10.3.2. Tuesday: Test and Validate for Multiple Goals
      3. 10.3.3. Wednesday: Start Simple and Then Scale and Have Fun
        1. 10.3.3.1. Accept Simple or "Silly" Initial Tests
        2. 10.3.3.2. Create a Fun Environment
      4. 10.3.4. Thursday: Focus on Evangelism and Expertise
      5. 10.3.5. Friday: Implement the Two Key Ingredients for Every Testing Program
        1. 10.3.5.1. Process
        2. 10.3.5.2. Requirements Gathering
  17. 11. Month 6: Three Secrets Behind Making Web Analytics Actionable
    1. 11.1. Week 1: Leveraging Benchmarks and Goals in Driving Action
      1. 11.1.1. Monday and Tuesday: Understand the Importance of Benchmarks and Setting Goals
      2. 11.1.2. Wednesday: Leverage External Benchmarking
      3. 11.1.3. Thursday: Leverage Internal Benchmarking
      4. 11.1.4. Friday: Encourage and Create Goals
    2. 11.2. Week 2: Creating High Impact Executive Dashboards
      1. 11.2.1. Monday: Provide Context—Benchmark, Segment, and Trend
        1. 11.2.1.1. Use Benchmarks
        2. 11.2.1.2. Always Segment
        3. 11.2.1.3. Trending Rocks
      2. 11.2.2. Tuesday: Isolate Your Critical Few Metrics
      3. 11.2.3. Wednesday: Don't Stop at Metrics—Include Insights
      4. 11.2.4. Thursday: Limit Your Dashboard to a Single Page
      5. 11.2.5. Friday: Know That Appearance Matters
    3. 11.3. Week 3: Using Best Practices for Creating Effective Dashboard Programs
      1. 11.3.1. Monday: Create Trinity Metrics That Have a Clear Line of Sight
        1. 11.3.1.1. Apply the Trinity Approach
        2. 11.3.1.2. Maintain a Clear Line of Sight
      2. 11.3.2. Tuesday: Create Relevant Dashboards
        1. 11.3.2.1. Short Lag Time
        2. 11.3.2.2. Churn
      3. 11.3.3. Wednesday: One Metric, One Owner
      4. 11.3.4. Thursday: Walk the Talk
      5. 11.3.5. Friday: Measure the Effectiveness of Your Dashboards
    4. 11.4. Week 4: Applying Six Sigma or Process Excellence to Web Analytics
      1. 11.4.1. Monday: Everything's a Process
      2. 11.4.2. Tuesday through Thursday: Apply the DMAIC Process
        1. 11.4.2.1. Define
        2. 11.4.2.2. Measure
        3. 11.4.2.3. Analyze
        4. 11.4.2.4. Improve
        5. 11.4.2.5. Control
      3. 11.4.3. Friday: Reflect on What You've Learned
  18. 12. Month 7: Competitive Intelligence and Web 2.0 Analytics
    1. 12.1. Competitive Intelligence Analytics
      1. 12.1.1. Week 1: Competitive Traffic Reports
        1. 12.1.1.1. Monday: Share of Visits by Industry Segment
        2. 12.1.1.2. Tuesday: Upstream and Downstream Traffic against Competition
        3. 12.1.1.3. Wednesday and Thursday: Competitor Traffic by Media Mix
        4. 12.1.1.4. Friday: Alexa Daily Reach Reports
      2. 12.1.2. Week 2: Search Engine Reports
        1. 12.1.2.1. Monday: Share of Search and Search Keywords
          1. 12.1.2.1.1. Share of Search Report
          2. 12.1.2.1.2. Share of Brand and Category Keywords
        2. 12.1.2.2. Tuesday: Search Keyword Funnels and Keyword Forecasts
          1. 12.1.2.2.1. Search Funnel Report
          2. 12.1.2.2.2. Keyword or Key Phrase Forecast
        3. 12.1.2.3. Wednesday: Keyword Expansion Tool
        4. 12.1.2.4. Thursday and Friday: Demographic and Psychographic Reports
          1. 12.1.2.4.1. Demographic Prediction
          2. 12.1.2.4.2. Psychographic Reporting
    2. 12.2. Web 2.0 Analytics
      1. 12.2.1. Week 3: Measuring the Success of Rich Interactive Applications (RIAs)
        1. 12.2.1.1. Monday: Understand the Reality of RIAs
        2. 12.2.1.2. Tuesday and Wednesday: Learn about Emerging "Standards" for RIA Tracking
        3. 12.2.1.3. Thursday and Friday: Learn the Steps for Successful RIA Tracking
      2. 12.2.2. Week 4: Measuring the Success of RSS
        1. 12.2.2.1. Monday: Understand the Reality of RSS
        2. 12.2.2.2. Tuesday: Learn about Emerging "Standards" for RSS Tracking
        3. 12.2.2.3. Wednesday: Track Subscribers and Reach
          1. 12.2.2.3.1. Subscribers
          2. 12.2.2.3.2. Reach
        4. 12.2.2.4. Thursday: Measure Reads and Clicks to Website (Referrals)
          1. 12.2.2.4.1. Reads (Views)
          2. 12.2.2.4.2. Clicks to Website
        5. 12.2.2.5. Friday: Analyze Subscriber Location and Feed Reader Type
          1. 12.2.2.5.1. Location
          2. 12.2.2.5.2. Feed Reader Type
  19. 13. Month 8 and Beyond: Shattering the Myths of Web Analytics
    1. 13.1. Path Analysis: What Is It Good For? Absolutely Nothing
      1. 13.1.1. Challenges with Path Analysis
      2. 13.1.2. An Alternative: The Funnel Report
    2. 13.2. Conversion Rate: An Unworthy Obsession
      1. 13.2.1. Problems with Conversion Rate
      2. 13.2.2. An Alternative: Task Completion Rate by Primary Purpose
    3. 13.3. Perfection: Perfection Is Dead, Long Live Perfection
      1. 13.3.1. Perfect Data
      2. 13.3.2. Web at the Speed of Web
      3. 13.3.3. Fractured Multisource Data
    4. 13.4. Real-Time Data: It's Not Really Relevant, and It's Expensive to Boot
      1. 13.4.1. Results of Getting Real-Time Data
      2. 13.4.2. A Checklist for Real-Time Data Readiness
    5. 13.5. Standard KPIs: Less Relevant Than You Think
  20. 14. Advanced Analytics Concepts—Turbocharge Your Web Analytics
    1. 14.1. Unlock the Power of Statistical Significance
    2. 14.2. Use the Amazing Power of Segmentation
      1. 14.2.1. Segmenting by Bounce
      2. 14.2.2. Segmenting by Search
      3. 14.2.3. Combining Search and Bounce
      4. 14.2.4. Trending Segmented Data
    3. 14.3. Make Your Analysis and Reports "Connectable"
      1. 14.3.1. Using Pretty Pictures
      2. 14.3.2. Using Connectable Language
    4. 14.4. Use Conversion Rate Best Practices
      1. 14.4.1. Forget about Overall Site Conversion Rate
      2. 14.4.2. Trend over Time and Don't Forget Seasonality
      3. 14.4.3. Understand Your Website's/Company's Acquisition Strategy
      4. 14.4.4. Measure Conversion Rate by the Top Five Referring URLs
      5. 14.4.5. Don't Measure Conversion Rate by Page or Link
      6. 14.4.6. Segment like Crazy
      7. 14.4.7. Always Show Revenue Next to Conversion Rate
      8. 14.4.8. Measure Conversion Rate with a Goal in Mind
    5. 14.5. Elevate Your Search Engine Marketing/Pay Per Click Analysis
      1. 14.5.1. Measure Your Bounce Rate (in Aggregate and by Top Key Phrases)
      2. 14.5.2. Audit Your Vendors/Agencies
      3. 14.5.3. Measure PPC Campaigns Cannibalization Rate (vs. Organic)
      4. 14.5.4. Aggressively Push for Testing and Experimentation
      5. 14.5.5. Strive for Multigoal Understanding of Visitors
    6. 14.6. Measure the Adorable Site Abandonment Rate Metric
      1. 14.6.1. Using Segmentation with Abandonment Rate
        1. 14.6.1.1. Cart Abandonment Rate
        2. 14.6.1.2. Checkout Abandonment Rate
      2. 14.6.2. Finding Actionable Insights and Taking Action
    7. 14.7. Measure Days and Visits to Purchase
      1. 14.7.1. How to Measure the KPIs
      2. 14.7.2. Finding Actionable Insights and Taking Action
    8. 14.8. Leverage Statistical Control Limits
      1. 14.8.1. Calculating Control Limits
      2. 14.8.2. A Practical Example of Using Control Limits
    9. 14.9. Measure the Real Size of Your Convertible "Opportunity Pie"
      1. 14.9.1. Use Bounce Rate
      2. 14.9.2. Filter Out Search Bots, Image Requests, 404 Errors, Website-Monitoring Software "Visits"
      3. 14.9.3. Use Customer Intent
      4. 14.9.4. Take Action
  21. 15. Creating a Data-Driven Culture—Practical Steps and Best Practices
    1. 15.1. Key Skills to Look for in a Web Analytics Manager/Leader
      1. 15.1.1. Deep Passion for the Job
      2. 15.1.2. Loves Change, Owns Change
      3. 15.1.3. Questions Data to the Point of Being Rude
      4. 15.1.4. CDI Baby, CDI (Customer-Driven Innovation)
      5. 15.1.5. Not Really Good "Numbers Gods"
      6. 15.1.6. Raw Business Savvy and Acumen
      7. 15.1.7. Impressive People Skills
    2. 15.2. When and How to Hire Consultants or In-House Experts
      1. 15.2.1. Stage 1: Birth
        1. 15.2.1.1. What Do You Need?
        2. 15.2.1.2. What Is Your Role?
        3. 15.2.1.3. What Is the Consultant's Expected Role?
        4. 15.2.1.4. What Should You Be Careful About?
        5. 15.2.1.5. What Do You Pay Consultants?
      2. 15.2.2. Stage 2: Toddler to Early Teens
        1. 15.2.2.1. What Do You Need?
        2. 15.2.2.2. What Is Your Role?
        3. 15.2.2.3. What Is the Consultant's Expected Role?
        4. 15.2.2.4. What Should You Be Careful About?
        5. 15.2.2.5. What Do You Pay Consultants?
      3. 15.2.3. Stage 3: The Wild Youth
        1. 15.2.3.1. What Do You Need?
        2. 15.2.3.2. What Is Your Role?
        3. 15.2.3.3. What Is the Consultant's Expected Role?
        4. 15.2.3.4. What Should You Be Careful About?
        5. 15.2.3.5. What Do You Pay Consultants?
      4. 15.2.4. Stage 4: Maturity—You Are 30+
        1. 15.2.4.1. What Do You Need?
        2. 15.2.4.2. What Is Your Role?
        3. 15.2.4.3. What Is the Consultant's Expected Role?
        4. 15.2.4.4. What Should You Be Careful About?
        5. 15.2.4.5. What Do You Pay Consultants?
    3. 15.3. Seven Steps to Creating a Data-Driven Decision-Making Culture
      1. 15.3.1. Go for the Bottom Line First (Outcomes)
      2. 15.3.2. Remember That Reporting Is Not Analysis, and Encourage the Latter
      3. 15.3.3. Depersonalize Decision Making
      4. 15.3.4. Be Proactive Rather Than Reactive
      5. 15.3.5. Empower Your Analysts
      6. 15.3.6. Solve for the Trinity
      7. 15.3.7. Got Process?