You are previewing Web Analytics: An Hour a Day.

Web Analytics: An Hour a Day

Cover of Web Analytics: An Hour a Day by Avinash Kaushik Published by Sybex
  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?
  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
  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
      2. 2.2.2. Web Beacons
      3. 2.2.3. JavaScript Tags
      4. 2.2.4. Packet Sniffing
    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
      2. 2.5.2. ISP-Based Measurement
      3. 2.5.3. Search Engine Data
  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
      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
      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
      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
    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
      7. 5.4.7. Be Aware of 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
      2. 6.1.2. Wednesday: URL Parameters
      3. 6.1.3. Thursday and Friday: Cookies
    2. 6.2. Week 2: Revisiting Foundational Metrics
      1. 6.2.1. Monday: Visits and Visitors
      2. 6.2.2. Tuesday and Wednesday: Time on Site
      3. 6.2.3. Thursday and Friday: Page Views
    3. 6.3. Week 3: Understanding Standard Reports
      1. 6.3.1. Monday and Tuesday: Bounce Rate
      2. 6.3.2. Wednesday through Friday: Referrers—Sources and Search Key Phrases
    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
      2. 6.4.2. Wednesday: Top Destinations (Exit Links)
      3. 6.4.3. Thursday and Friday: Site Overlay (Click Density Analysis)
  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
      2. 7.2.2. Tuesday: Site Content Popularity and Home Page Visits
      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
      2. 7.3.2. Week 3: Indexing Performance and Measuring Merchandizing Effectiveness and 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
      2. 7.4.2. Week 3: Measuring Success by Using VOC or Customer Ratings (at a Site and Page Level)
    5. 7.5. Blog Measurement Jump-Start Guide
      1. 7.5.1. Week 2: Overcoming Complexity to Measure the Fundamentals (by Using New Metrics)
      2. 7.5.2. Week 3: Competitive Benchmarking and Measuring Cost and ROI
    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
      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
      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
      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
      2. 9.3.2. Week 4: Tracking and Analyzing Multichannel Marketing
  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
      2. 10.1.2. Week 2: Moving Beyond A/B Testing
    2. 10.2. Week 3: What to Test—Specific Options and Ideas
      1. 10.2.1. Monday: Test Important Pages and 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
      2. 10.3.2. Tuesday: Test and Validate for Multiple Goals
      3. 10.3.3. Wednesday: Start Simple and Then Scale and Have Fun
      4. 10.3.4. Thursday: Focus on Evangelism and Expertise
      5. 10.3.5. Friday: Implement the Two Key Ingredients for Every Testing Program
  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
      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
      2. 11.3.2. Tuesday: Create Relevant Dashboards
      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
      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
      2. 12.1.2. Week 2: Search Engine Reports
    2. 12.2. Web 2.0 Analytics
      1. 12.2.1. Week 3: Measuring the Success of Rich Interactive Applications (RIAs)
      2. 12.2.2. Week 4: Measuring the Success of RSS
  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
      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
      2. 15.2.2. Stage 2: Toddler to Early Teens
      3. 15.2.3. Stage 3: The Wild Youth
      4. 15.2.4. Stage 4: Maturity—You Are 30+
    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?
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Chapter 5. Web Analytics Fundamentals

After you have put the right strategy in place for people and the organization, your web analytics program will address data capture, tool selection, data quality (sadly, you can't escape this one), implementation, and metrics selection. Often many of these choices are all rolled into one. You pick a tool, for example, and the rest go with that (how you collect data, where it is stored, how good it is, what metrics you can report on, and so forth).

There is a ton of inherent complexity on the Web. This complexity results in challenges in collecting data and having confidence in its ability to provide insights. Customer use complexity relates to what data to use and where and how to use it. Organizational complexity ...

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