Web Site Measurement Hacks. Tips & Tools to Help Optimize Your Online Business

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• Web Site Measurement Hacks
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  • Copyright
  • Foreword
  • Credits
    • About the Author
    • Contributors
    • Acknowledgments
  • Preface
    • Why Web Site Measurement Hacks?
    • How This Book Is Organized
    • About the Use of Screenshots and Vendor Information in This Book
    • Conventions Used in This Book
    • Using Code Examples
    • How to Contact Us
    • Safari Enabled
    • Got a Hack?
  • 1. Web Measurement Basics
    • 1.1. Hacks 113: Introduction
      • 1.1.1. Why Measure Your Site?
      • 1.1.2. A Brief History of Web Site Measurement
      • 1.1.3. What Web Measurement Is Not
      • 1.1.4. Why Not "Web Analytics?"
      • 1.1.5. About the "Build Your Own" Hacks
        • 1.1.5.1. Requirements
    • Hack #1. Talk the Talk
      • 1.2.1. Hits
      • 1.2.2. Page Views
      • 1.2.3. Visits
      • 1.2.4. Unique Visitors
      • 1.2.5. Referrers
      • 1.2.6. Tying It All Together
    • Hack #2. Best Practices for Web Measurement
      • 1.3.1. Identify Your Objectives Before You Begin
      • 1.3.2. Make Sure You Have Executive Buy-In
      • 1.3.3. Build the Right Team
      • 1.3.4. Measure and Improve: The Continuous Improvement Process
    • Hack #3. Select the Right Vendor
      • 1.4.1. Software
      • 1.4.2. Hosted Services
      • 1.4.3. Popular Vendors Providing Software and Services
      • 1.4.4. Tying It All Together
    • Hack #4. Staff for Web Measurement Success
      • 1.5.1. Staff for Measurement Success
      • 1.5.2. Skills for a Web Data Analyst
      • 1.5.3. Finding a Web Data Analyst
        • 1.5.3.1. Put the word out that youre looking for some serious talent.
        • 1.5.3.2. Be prepared to hire someone senior enough to be truly effective.
        • 1.5.3.3. Provide additional financial incentive based on successful attainment of goals.
    • Hack #5. Get to Know Your Visitors
      • 1.6.1. Totally Anonymous Visitors
      • 1.6.2. Mostly Anonymous Visitors
      • 1.6.3. Known Visitors
    • Hack #6. Understand Common Data Sources
      • 1.7.1. Problems with Web Server Logfiles
      • 1.7.2. Enter the Packet Sniffers
      • 1.7.3. JavaScript Page Tags Are Born
      • 1.7.4. Evaluating Data Sources
    • Hack #7. Understand Visitor Intent
      • 1.8.1. Determining Intent Explicitly
      • 1.8.2. Determining Intent Implicitly
      • 1.8.3. Once You've Determined Intent, Then What?
    • Hack #8. Know When to Use Packet Sniffing
      • 1.9.1. The Ugly, Ugly Details
      • 1.9.2. How to Use a Network Collector in a Switched Environment
      • 1.9.3. Using a Network Collector with Encrypted (SSL) Traffic
    • Hack #9. Write a Useful Web Measurement Request for Proposal (RFP)
      • 1.10.1. Focus on Your Current Needs
      • 1.10.2. Ask Only Well-Qualified People for Input
      • 1.10.3. Send Your RFP to as Few Vendors as Possible
      • 1.10.4. Remember, Less Is More
    • Hack #10. Find a Free or Cheap Web Measurement Solution
      • 1.11.1. Free Web Measurement Solutions
      • 1.11.2. Inexpensive Web Measurement Solutions
    • Hack #11. Use Analog to Process Logfiles
      • 1.12.1. Analog: Where to Get It!
      • 1.12.2. How to Install Analog
      • 1.12.3. Telling Analog Where Your Logfiles Are
      • 1.12.4. Creating Basic Reports in Analog
      • 1.12.5. Running the Hack
    • Hack #12. Build Your Own Web Measurement Application: An Overview and Data Collection
      • 1.13.1. Collecting the Data
      • 1.13.2. Returning the Image and Logging the Page View
      • 1.13.3. The Code
      • 1.13.4. Running the Code
    • Hack #13. Build Your Own RSS Tracking Application: An Overview and Data Collection
      • 1.14.1. The Data Collection Code
        • 1.14.1.1. Tracking code to be placed into the feed or article you want to track.
        • 1.14.1.2. Tracking code to be referenced externally (the track_rss.js file).
        • 1.14.1.3. Code to parse the JavaScript into an RSS logfile (write_rss_tag.cgi).
      • 1.14.2. Running the Code
      • 1.14.3. The Results
  • 2. Implementation and Setup
    • 2.1. Hacks 1436: Introduction
      • 2.1.1. Once You've Selected a Vendor
      • 2.1.2. Relax, and Don't Forget to Breathe
    • Hack #14. Optimize the Implementation Process
      • 2.2.1. Know What to Collect in Advance
      • 2.2.2. Work Closely with Your Vendor
      • 2.2.3. Get the Five Most Important Reports Right Away
      • 2.2.4. Get Training, but Have the Right Expectations
      • 2.2.5. Know Who to Call
    • Hack #15. Improve Data Accuracy with Cookies
      • 2.3.1. Session Cookies for Short-Term Accuracy
      • 2.3.2. Persistent Cookies for Long-Term Measurement
        • 2.3.2.1. First-party cookies.
        • 2.3.2.2. Third-party cookies.
        • 2.3.2.3. When a first-party cookie is a third-party cookie.
      • 2.3.3. Improve Accuracy with Persistent Cookies
        • 2.3.3.1. Use true first-party cookies whenever possible.
        • 2.3.3.2. Use DNS to make it look like you're using first-party cookies.
        • 2.3.3.3. Make sure your privacy and P3P policies accurately reflect what you're doing.
    • Hack #16. Know When to Use First-Party Cookies
      • 2.4.1. The Advantage of First-Party Cookies
      • 2.4.2. Third-Party Cookies Have Their Place
      • 2.4.3. How Can I Tell If I'm Using a First- or Third-Party Cookie?
    • Hack #17. Alternatives to Cookies
      • 2.5.1. Reasonable (If Not Great) Alternatives to Cookies
        • 2.5.1.1. Using the IP address.
        • 2.5.1.2. Using IP address and user agent strings.
        • 2.5.1.3. Using the authenticated username (when available).
        • 2.5.1.4. Using a session identifier (when available).
      • 2.5.2. Alternatives to Cookies for Identifying Repeat Visitors
      • 2.5.3. Tying It All Together
    • Hack #18. Use Macromedia Flash Local Shared Objects Instead of Cookies
      • 2.6.1. The JavaScript Code
      • 2.6.2. The Flash ActionScript Code
      • 2.6.3. Running the Hack
      • 2.6.4. A Note About Whether This Is a Good Idea
    • Hack #19. Fine-Tune Your Data Collection
      • 2.7.1. Web Server Logfiles
      • 2.7.2. JavaScript Page Tags
      • 2.7.3. Why Not Just Collect Everything?
        • 2.7.3.1. It takes time to reprocess data.
        • 2.7.3.2. There are costs associated with collection and storage.
    • Hack #20. Define Useful Page Names and Content Groups
      • 2.8.1. Good Names, Bad Names, I Know You've Had Your Share
      • 2.8.2. Rules for Naming Pages and Content Groups
    • Hack #21. Understand Where Data Gets Lost
      • 2.9.1. Data Collection Issues Common to Page Tags
        • 2.9.1.1. A page tag did not get placed in the page.
        • 2.9.1.2. The page tag doesn't work as intended.
        • 2.9.1.3. Page tagging is your only data collection method.
        • 2.9.1.4. The visitor's browser has JavaScript turned off.
        • 2.9.1.5. The request was blocked by security software.
        • 2.9.1.6. The information is never received by the data collector.
      • 2.9.2. Data Collection Issues Common to Web Server Logfiles
        • 2.9.2.1. The browser serves the request from the local cache.
        • 2.9.2.2. The content is served from a content distribution network (CDN).
      • 2.9.3. Knowing All This, What Should You Do?
    • Hack #22. Deconstruct Web Server Logfiles
      • 2.10.1. Anatomy of a Web Server Logfile
      • 2.10.2. Types of Web Server Logfiles
      • 2.10.3. The (Occasional) Need for Translation
    • Hack #23. Exclude Robots and Spiders from Your Analysis
      • 2.11.1. Strategies for Limiting the Impact of Robots and Spiders
        • 2.11.1.1. Identify known robots and spiders.
        • 2.11.1.2. Be on the lookout for new robots and spiders.
        • 2.11.1.3. Build and deploy a robots.txt file.
      • 2.11.2. Remember That Some Spiders Are Good!
    • Hack #24. Bust the Cache for Accuracy
      • 2.12.1. Bust the Cache Using Document Headers
      • 2.12.2. How Cache Busting Affects the Visitor Experience
      • 2.12.3. "Unbusting" the Cache for Images and Scripts
        • 2.12.3.1. Deploy an "images never expire" policy.
        • 2.12.3.2. Use caching defaults for occasionally changing content.
        • 2.12.3.3. Consider a content distribution network (CDN) for images and code.
      • 2.12.4. The Obvious Alternative to Cache Busting
    • Hack #25. Use Query Strings Effectively
      • 2.13.1. Some Common Uses for the Query String in Web Measurement
        • 2.13.1.1. Properly identifying dynamically generated pages.
        • 2.13.1.2. Identifying marketing campaign response.
        • 2.13.1.3. Collecting HTML form data for analysis.
      • 2.13.2. Putting the Query String to Work
    • Hack #26. Web Measurement and Visitor Privacy
      • 2.14.1. It's Not About the Technology, It's About the Practices
        • 2.14.1.1. Notice.
        • 2.14.1.2. Choice.
        • 2.14.1.3. Access.
        • 2.14.1.4. Security.
      • 2.14.2. How to Assemble a Good Privacy Policy
        • 2.14.2.1. Know where you're collecting personably identifiable information.
        • 2.14.2.2. Explain clearly and truthfully what you're going to do with the data.
        • 2.14.2.3. Consider third-party privacy certification.
        • 2.14.2.4. Beware of the spookiness factor.
      • 2.14.3. P3P Technology
      • 2.14.4. For More Information
    • Hack #27. Establish a P3P Privacy Policy
      • 2.16.1. Sounds Great, How Do I Set One Up?
        • 2.16.1.1. Step one: Create a written privacy policy.
        • 2.16.1.2. Step two: Determine which policies apply to which pages.
        • 2.16.1.3. Step three: Select a P3P policy generator.
        • 2.16.1.4. Step four: Enter the information.
        • 2.16.1.5. Step five: Create a policy reference file.
        • 2.16.1.6. Step six: Validate your policy.
      • 2.16.2. Wait, How Do I Deliver the Compact Policy?
        • 2.16.2.1. Apache Web Server.
      • 2.16.3. Consequences of Omitting a Privacy Policy
        • 2.16.3.1. The "red eye".
        • 2.16.3.2. Visitors will wonder why you don't care about their privacy.
        • 2.16.3.3. Eventually, the press will wonder why you don't care.
    • Hack #28. Deconstruct JavaScript Page Tags
      • 2.17.1. How Do Web Measurement Tools Use JavaScript?
      • 2.17.2. How a JavaScript Page Tag Works
        • 2.17.2.1. Step one: JavaScript in web pages is executed.
        • 2.17.2.2. Step two: JavaScript source file is requested and returned to the browser.
        • 2.17.2.3. Step three:The page tag collects data and reports back.
        • 2.17.2.4. Step four: A cookie and P3P privacy policy are returned.
      • 2.17.3. Deconstructing an Archetypical JavaScript Page Tag
    • Hack #29. Understand Web Bugs
      • 2.18.1. Really, What Is a "Web Bug"
      • 2.18.2. The Consumer Mindset About Web Bugs
      • 2.18.3. Be Explicit About Your Use of Web Bugs and Beacons
        • 2.18.3.1. Ensure that your privacy policy reflects your use of page tags.
        • 2.18.3.2. Ensure that your P3P policy reflects your use of page tags.
        • 2.18.3.3. Have a good explanation ready if people complain.
    • Hack #30. Hack the JavaScript Document Object Model
      • 2.19.1. Placing the Beacon
      • 2.19.2. Returning Document Information
      • 2.19.3. Finding the Browser Width
      • 2.19.4. Track Form Entry Errors
      • 2.19.5. Form AnalysisManna from the DOM
    • Hack #31. Use Custom Variables Wisely
      • 2.20.1. Uses for Custom Variables
      • 2.20.2. One-to-One Direct Marketing and Custom Variables
      • 2.20.3. Custom Variables in Action: An Example
    • Hack #32. Best Practices for Data Integration
      • 2.21.1. Examples of Common Data Integrations
        • 2.21.1.1. Integrate cost data to calculate gross margin contribution.
        • 2.21.1.2. Integrate marketing cost data to determine real campaign ROI.
        • 2.21.1.3. Integrate customer registration data to drill into demographics.
        • 2.21.1.4. Integrate customer satisfaction data.
        • 2.21.1.5. Integrate data from targeted email campaigns.
      • 2.21.2. Taking Action to Integrate Non-Web Data
        • 2.21.2.1. Identify the problem you'd like to solve.
        • 2.21.2.2. Identify the sources of web and non-web data that will be required.
        • 2.21.2.3. Determine how you're going to tie the data sources together.
        • 2.21.2.4. Integrate the data.
        • 2.21.2.5. Generate reports and take action.
    • Hack #33. Measure Your Intranet or Extranet
      • 2.22.1. Justifying Return on Investment
      • 2.22.2. Measuring Content and Application Adoption
      • 2.22.3. Examining Internal Searches
      • 2.22.4. Named User Analysis
      • 2.22.5. Tying It All Together
    • Hack #34. Measure Your Mistakes
      • 2.23.1. Types of Mistakes
        • 2.23.1.1. Web site is slow or fails to respond.
        • 2.23.1.2. Broken hyperlinks.
        • 2.23.1.3. Aborted page views and downloads.
        • 2.23.1.4. Client-side script errors.
      • 2.23.2. How to Measure Your Mistakes
        • 2.23.2.1. Using logfiles as a data source.
        • 2.23.2.2. Using page tags as a data source.
        • 2.23.2.3. Measuring client-side JavaScript errors.
      • 2.23.3. Investigating Your Mistakes
        • 2.23.3.1. Investigate errors in relation to traffic loads.
        • 2.23.3.2. Investigate errors in relation to web browsers.
        • 2.23.3.3. Investigate errors in relation to your servers.
        • 2.23.3.4. Investigate errors in relation to dynamic URLs.
    • Hack #35. Build Your Own Web Measurement Application: The Core Code
      • 2.24.1. Parsing the Data into Sessions
      • 2.24.2. The Code
      • 2.24.3. Next Steps
    • Hack #36. Build Your Own RSS Tracking Application: The Core Code and Reporting
      • 2.25.1.
        • 2.25.1.1. RSS_Article.pm.
        • 2.25.1.2. RSS_Articles.pm.
        • 2.25.1.3. RSS_Data.pm.
        • 2.25.1.4. RSS_Event.pm.
        • 2.25.1.5. RSS_Request.pm.
        • 2.25.1.6. Bringing the packages together with rss_report.pl.
      • 2.25.2. Running the Code
      • 2.25.3. The Results
      • 2.25.4. Hacking the Hack
  • 3. Online Marketing Measurement
    • 3.1. Hacks 3753: Introduction
      • 3.1.1. It's Only Data
      • 3.1.2. ROI
    • Hack #37. Understand Marketing Terminology
      • 3.2.1. Reach and Acquisition
        • 3.2.1.1. Click-though rate (CTR).
        • 3.2.1.2. Cost-per-click (CPC).
        • 3.2.1.3. Response rate.
        • 3.2.1.4. Cost-per-acquisition (CPA).
      • 3.2.2. Conversion
        • 3.2.2.1. Conversion rate.
        • 3.2.2.2. Cost-per-conversion (CPC).
        • 3.2.2.3. Revenue per visit or visitor.
        • 3.2.2.4. Order and buyer conversion rates.
        • 3.2.2.5. Return on investment (ROI).
      • 3.2.3. Retention
        • 3.2.3.1. Visitor retention rate.
        • 3.2.3.2. Lifetime value of a campaign.
    • Hack #38. Identify Your Business Objectives
      • 3.3.1. Every Site Has Business Objectives
      • 3.3.2. Translate Business Objectives into Measurable Activities
    • Hack #39. Define Conversion Events
      • 3.4.1. Identify Your Conversion Events
        • 3.4.1.1. Be open-minded.
        • 3.4.1.2. Don't limit your definition to a single session.
        • 3.4.1.3. If you're not sure how to set conversion events, consult your vendor.
        • 3.4.1.4. Make an attempt to assign a dollar value to non-revenue conversion events.
      • 3.4.2. Measure Conversion
        • 3.4.2.1. Overall conversion.
        • 3.4.2.2. Scenario conversion.
      • 3.4.3. Bringing It All Together
    • Hack #40. Measure Banner Advertising
      • 3.5.1. Impressions
      • 3.5.2. Response
      • 3.5.3. Conversion
      • 3.5.4. The Measurements You Need to Make
        • 3.5.4.1. Click-through rate (CTR).
        • 3.5.4.2. Click-to-conversion rate (CTC).
        • 3.5.4.3. Cost per acquisition (CPA).
      • 3.5.5. Measuring Banner Advertising: A Checklist
    • Hack #41. Measure Email Marketing
      • 3.6.1. Things That Can Be Measured
        • 3.6.1.1. Hard bounces.
        • 3.6.1.2. Tracked opens.
        • 3.6.1.3. Tracked click-through.
        • 3.6.1.4. Unsubscribes.
      • 3.6.2. The Fundamental Email Response Metrics
        • 3.6.2.1. Response rate and basic response metrics.
        • 3.6.2.2. Click-through rate.
        • 3.6.2.3. Landing page "stickiness".
        • 3.6.2.4. Conversion events and rates.
        • 3.6.2.5. Value metrics.
      • 3.6.3. Things That Should Be Tested
        • 3.6.3.1. Format and layout.
        • 3.6.3.2. Length and tone.
        • 3.6.3.3. Date and time of delivery.
        • 3.6.3.4. Return email address.
        • 3.6.3.5. The subject line.
        • 3.6.3.6. The call to action.
      • 3.6.4. How to Put This Data to Work!
    • Hack #42. Measure Paid Search Engine Marketing
      • 3.7.1. How to Identify Paid Search Traffic
        • 3.7.1.1. Low data gathering strategy.
        • 3.7.1.2. Medium data gathering strategy.
        • 3.7.1.3. Large data gathering strategy.
      • 3.7.2. Which Data Should You Be Collecting
        • 3.7.2.1. Response rate (click-through rate).
        • 3.7.2.2. Cost-per-click (CPC).
        • 3.7.2.3. Conversion rate by search engine and keyword.
        • 3.7.2.4. Revenue (or loss) by search engine and keyword.
        • 3.7.2.5. Lifetime value of visitors from paid search marketing.
      • 3.7.3. What Do You Do with the Data?
        • 3.7.3.1. Low data gathering strategy.
        • 3.7.3.2. Medium data gathering strategy.
        • 3.7.3.3. Large data gathering strategy.
    • Hack #43. Measure Organic Search
      • 3.8.1. The Nature of the Problem
      • 3.8.2. The Solution
      • 3.8.3. Welcome to the World of Tracking URLs
      • 3.8.4. Tell Your Web Measurement Software to Ignore the Paid Search Traffic
      • 3.8.5. Now That I Can Tell Them Apart, What Do I Do?
        • 3.8.5.1. Cost-per-click.
        • 3.8.5.2. Conversion rate by engine and keyword.
        • 3.8.5.3. Revenue (or loss) by search engine and keyword.
        • 3.8.5.4. Lifetime value of visitors from organic search.
    • Hack #44. Contrast Paid Keywords Versus Actual Search Queries
      • 3.9.1. Paid Search Visits Versus Organic Search Visits
      • 3.9.2. Paid Search Keywords Versus Actual Search Queries
      • 3.9.3. Exact Matching Versus Broad Matching
      • 3.9.4. How Can I Capture the Necessary Information and Create This Report?
    • Hack #45. Measure Affiliate Marketing
      • 3.10.1. Pay for Clicks, Leads, or Revenue: Which Is Better?
      • 3.10.2. Use Web Measurement to Identify Affiliate Successes
        • 3.10.2.1. Paying for clicks? Determine your per-affiliate click-through rate.
        • 3.10.2.2. Paying for leads? Measure lead generation rates.
        • 3.10.2.3. Paying for performance? Paying commissions based on sales.
        • 3.10.2.4. Other useful metrics used to measure affiliate marketing.
      • 3.10.3. Tying It All Together
    • Hack #46. Use Unique Landing Pages
      • 3.11.1. Unique Landing Pages Are Focused
      • 3.11.2. Unique Landing Pages Are Not Always Unique
      • 3.11.3. Hacking Unique Landings Pages: The Mini-Site Model
      • 3.11.4. Measuring Unique Landing Page Activity
    • Hack #47. Measure Content Syndicated via RSS
      • 3.12.1. Easy Things You Can Do to Measure RSS Readership
      • 3.12.2. Hacking Your Web Measurement Tool to Track RSS
        • 3.12.2.1. Simple RSS tracking using web server logfiles.
        • 3.12.2.2. Simple RSS Tracking Using JavaScript Page Tags.
      • 3.12.3. Treat RSS Like Email or Banner Advertising
    • Hack #48. Segment Visitors to Understand Specific Group Activity
      • 3.13.1. Examples of Visitor Segments
      • 3.13.2. General Requirements for Segmentation
      • 3.13.3. Defining Good Visitor Segments
      • 3.13.4. Tying It All Together
    • Hack #49. Measure Conversion Through Multiple Goals
      • 3.14.1. How to Measure Conversion Through Multiple Goals
        • 3.14.1.1. Understand the capabilities of your web measurement application.
        • 3.14.1.2. Clearly identify your value events.
        • 3.14.1.3. Clearly delineate multiple value events.
        • 3.14.1.4. Decide what information is to be captured at each value event.
      • 3.14.2. Types of Calculations for Visit Conversion
        • 3.14.2.1. Calculation of conversion to one value event.
        • 3.14.2.2. Calculation of conversion to one or more value events.
        • 3.14.2.3. Calculation of conversion through more than one value event.
    • Hack #50. Leverage Referring Domains and URLs
      • 3.15.1. How Referring URLs Are Typically Reported
      • 3.15.2. Common Problems with Referrers
      • 3.15.3. Using Referrers to Your Advantage
    • Hack #51. Calculate Click-to-Visit Drop-off
      • 3.16.1. Make Sure Your Measurement Strategy Is Working
      • 3.16.2. The System Is Working, So Where Did the Clicks Go?
        • 3.16.2.1. Is your landing page a bandwidth hog?
        • 3.16.2.2. Is your tracking code in the optimal location (for tag-based solutions)?
        • 3.16.2.3. Is your tracking code still deployed properly (tag-based solutions)?
        • 3.16.2.4. Are you tracking page views, visits, or visitors?
    • Hack #52. Create Visitor Loyalty Segments
      • 3.17.1. Use Visitor Segmentation to Measure Visitor Loyalty
      • 3.17.2. Profitable Loyalty Segmentation Strategies
        • 3.17.2.1. By media source of the visitor.
        • 3.17.2.2. By the "offer" you make to the visitor.
        • 3.17.2.3. By the advertising copy you use.
        • 3.17.2.4. By content area.
        • 3.17.2.5. By category or item of purchase.
    • Hack #53. Build Your Own Web Measurement Application: Marketing Data
      • 3.18.1. The Code
      • 3.18.2. Running the Code
  • 4. Measuring Web Site Usability
    • 4.1. Hacks 5467: Introduction
    • Hack #54. Measure the Value of Pages and Clicks
      • 4.2.1. Measuring the Value of Clicks
        • 4.2.1.1. Link tracking.
        • 4.2.1.2. Browser overlays.
      • 4.2.2. Measuring the Value of Pages
        • 4.2.2.1. Page allocation.
        • 4.2.2.2. Page participation.
      • 4.2.3. Tying It All Together
    • Hack #55. Measuring Clicks the Old-Fashioned Way
      • 4.3.1. The Code
    • Hack #56. Use Language to Drive Action
      • 4.4.1. Know Your Visitors Motivations and Create Scent Trails
      • 4.4.2. Use Two Types of Hyperlinks
      • 4.4.3. Put More Effort into Copy
        • 4.4.3.1. What Matters to People Matters to Search Engines.
    • Hack #57. Deconstruct Time Spent on Site
      • 4.5.1. The Basic Terms and Concepts
        • 4.5.1.1. Time spent per page.
        • 4.5.1.2. Time spent on site.
        • 4.5.1.3. Visit expiration.
      • 4.5.2. Sources of Inaccuracy When Calculating Time Spent on Site
        • 4.5.2.1. Delays due to download and rendering time.
        • 4.5.2.2. Variability in treatment of the final page in a visit.
        • 4.5.2.3. The randomness of human behavior.
      • 4.5.3. Hacking Time Spent on Site
      • 4.5.4. Assessing Page View Times
        • 4.5.4.1. Think about your pages in context.
        • 4.5.4.2. Compare page times to ideal ranges.
        • 4.5.4.3. Identify why problems occur.
    • Hack #58. Use the Entry, Exit, and Single-Access Page Report
      • 4.6.1. Entry Pages
        • 4.6.1.1. Page caching.
        • 4.6.1.2. Missing page tracking tags.
        • 4.6.1.3. Expiration of visit session.
      • 4.6.2. Exit Pages
      • 4.6.3. Single-Access Pages
      • 4.6.4. Using All Three Reports Together
        • 4.6.4.1. Page "stickiness."
        • 4.6.4.2. Ratio of page entries to exits.
    • Hack #59. Measure Multi-Step Processes
      • 4.7.1. Identify the Leaks
      • 4.7.2. Analyzing Multi-Step Processes
      • 4.7.3. The Payoff
    • Hack #60. Measure Usability in the Checkout Process
      • 4.8.1. Stylized Checkout Process
        • 4.8.1.1. Step one: Adding a product to the shopping cart.
        • 4.8.1.2. Step two: Logging in.
        • 4.8.1.3. Step three: Billing and shipping.
        • 4.8.1.4. Step four: Payment and confirmation.
    • Hack #61. Measure "Internal Campaigns"
    • Hack #62. Use Browser Overlays
      • 4.10.1. Optimize Site Design
      • 4.10.2. Identify and Minimize Page Abandonment
      • 4.10.3. Optimize Multi-Step and Transactional Processes
      • 4.10.4. Engage the Previously Unengaged
    • Hack #63. Run Your Own Split-Path Tests
      • 4.11.1. The Code
      • 4.11.2. Check for Test Participation: Pages and People
      • 4.11.3. Assign to a Test or Control Group
      • 4.11.4. Tag the Visitor
      • 4.11.5. Redirect Test Subjects to the Appropriate Page
      • 4.11.6. Monitor for Completion of Goals
      • 4.11.7. Running the Hack
      • 4.11.8. Hacking the Hack
    • Hack #64. Measure Internal Searches
      • 4.12.1. Understanding How Visitors Search Your Site
        • 4.12.1.1. Percentage of visits using search.
        • 4.12.1.2. Searches per search visit.
        • 4.12.1.3. Percentage of exits from the search return page.
        • 4.12.1.4. Conversion of search visits to sales, leads, or other desired conversion.
        • 4.12.1.5. Average items per order for search visits versus non-search visits.
        • 4.12.1.6. Percentage of searches with no results ("zero results" searches).
        • 4.12.1.7. Percentage of searches that generate no clicked links ("zero yield" searches).
        • 4.12.1.8. Top search terms.
    • Hack #65. Take Advantage of "Zero Results" Internal Search Results
      • 4.13.1. Measuring "Zero Results" Searches
        • 4.12.1.9. How to track "zero results" searches.
      • 4.13.2. Decreasing Search Failure
        • 4.13.2.1. Point your search index to the "right" information.
        • 4.13.2.2. Improve site navigation.
        • 4.13.2.3. Loosen spelling requirements.
        • 4.13.2.4. Make sure new pages are indexed correctly.
        • 4.13.2.5. Take Advantage of "Zero Results" Searches
    • Hack #66. Effectively Measure the "Known" Visitor
      • 4.14.1. Identify Known Visitors
      • 4.14.2. Types of Known Visitors
      • 4.14.3. Reports That Help Build Relationships with Known Visitors
        • 4.14.3.1. Application usage/activity reports.
        • 4.14.3.2. Content consumption reports.
        • 4.14.3.3. Customer support reports.
        • 4.14.3.4. Sales analysis reports.
      • 4.14.4. Hacking Known Visitor Reporting Using Content Groups
      • 4.14.5. Tying It All Together
    • Hack #67. Build Your Own Web Measurement Application: Usability Data
      • 4.15.1. The Code
      • 4.15.2. Running the Code
  • 5. Technographics and "Demographics"
    • 5.1. Hacks 6880: Introduction
      • 5.1.1. Why the "Quotes" on Demographics?
    • Hack #68. Measure Site Performance
      • 5.2.1. Web Performance Measurement: The Basics
      • 5.2.2. Integrating Performance and Visitor Data Meaningfully
        • 5.2.2.1. Basic aggregate performance and availability integration.
        • 5.2.2.2. Detailed performance and availability integration.
        • 5.2.2.3. Geographically correlated performance and availability integration.
    • Hack #69. Measure Connection Type
      • 5.3.1. The Code
      • 5.3.2. Running the Code
      • 5.3.3. The Results
    • Hack #70. Know How to Use Screen Resolution Data
      • 5.4.1. Use Your Screen Resolutions Report
      • 5.4.2. So When Do We Switch Over?
      • 5.4.3. The Code
      • 5.4.4. Running the Code
    • Hack #71. Know How to Use Browser Version Information
      • 5.5.1. Build for Your Top Five Browsers
      • 5.5.2. Pay Attention to Emerging Trends
      • 5.5.3. Monitor Internet Averages
    • Hack #72. Know if People Are Bookmarking Your Site
      • 5.6.1. How to Measure Bookmarking with favicon.ico
      • 5.6.2. Hacking the Hack: Differentiate IE from Firefox Requests
    • Hack #73. Measure Browser Plug-ins
      • 5.7.1. Ask the Browser
      • 5.7.2. The Code
      • 5.7.3. Hacking the Hack
    • Hack #74. Know Which Technographic Data to Ignore
      • 5.8.1. Technographic Data to Use
      • 5.8.2. Technographic Data to Ignore
      • 5.8.3. Technographic Data that Depends on Your Specific Needs
    • Hack #75. Know How to Use Visitor Language Reports
      • 5.9.1. Visitor Language Reporting
      • 5.9.2. How to Use Language Information
      • 5.9.3. Knowing When and How Much to Translate
    • Hack #76. Hacking into Page-Level Details for Language
      • 5.10.1. The Code
      • 5.10.2. Running the Code
      • 5.10.3. The Results
      • 5.10.4. An Alternative to Hacking for Page-Level Details
    • Hack #77. Track Demographic Data Using Custom Variables and Visitor Segmentation
      • 5.11.1. How to Pass Demographic Data to Your Measurement Application
        • 5.11.1.1. Pass demographic data to a server log analyzer.
        • 5.11.1.2. Pass demographic data to a client-side page tag.
      • 5.11.2. What to Do with Demographic Data Once You Get It
      • 5.11.3. Things to Keep in Mind
        • 5.11.3.1. It is usually not easy to do.
        • 5.11.3.2. It requires tremendous planning to pull off properly.
        • 5.11.3.3. Most often your sample size will not be significant.
        • 5.11.3.4. Some consumers are liars when filling out forms.
        • 5.11.3.5. Not every report is always available for every segment.
        • 5.11.3.6. Occasionally the payback is hardly worth the effort.
      • 5.11.4. Simple Demographic Segmentation
    • Hack #78. Track Your Geographic Visitor Distribution
      • 5.12.1. Geographic Distribution Reports
      • 5.12.2. How Do They Do That?
      • 5.12.3. How to Really Use Geographic Distribution Data
    • Hack #79. Accurately Measure Downloads
      • 5.13.1. Multiple Levels of Measurement Can Be Used to Track Downloads
        • 5.13.1.1. Mine basic HTTP requests.
        • 5.13.1.2. Mine basic HTTP requests for download completion.
        • 5.13.1.3. Compensate for download managers.
    • Hack #80. Build Your Own Web Measurement Application: Technographic Data
      • 5.14.1. Installing IP::Country and Geography::Countries
      • 5.14.2. The Code
      • 5.14.3. Running the Code
  • 6. Web Measurement and the Online Retail Model
    • 6.1. Hacks 8190: Introduction
    • Hack #81. Know How to Use Retail Analytics
      • 6.2.1. Optimize Your Marketing Spend
      • 6.2.2. Analyze Product Placement and Look to Book
      • 6.2.3. Streamline the Checkout Funnel
    • Hack #82. Measure the Shopping Cart
      • 6.3.1. Measuring Products Being Added to the Cart
      • 6.3.2. Measuring Products Being Abandoned in the Cart
      • 6.3.3. Measuring Maximum Shopping Cart Value
      • 6.3.4. Measuring What Matters in Shopping Carts
      • 6.3.5. When Is a Shopping Cart Not a Shopping Cart?
        • 6.3.5.1. The cart as a shopping list.
        • 6.3.5.2. Persistent shopping carts.
    • Hack #83. Measure the Checkout Process
      • 6.4.1. Step One: Establish a Baseline
      • 6.4.2. Step Two: Diagnose Problems
      • 6.4.3. Bringing It All Together
    • Hack #84. Understand Frequency and Lifetime Value
      • 6.5.1. The Limits of the "Percent Returning Visitors" Metric
      • 6.5.2. Use Frequency and Lifetime Value to Better Understand Your Visitors and Customers
        • 6.5.2.1. Frequency.
        • 6.5.2.2. Lifetime value.
      • 6.5.3. Use Frequency and Lifetime Value to Segment Your Customers
      • 6.5.4. Use Lifetime Value per Visit to Drive Action
    • Hack #85. Measure Potential Customer Value Using Recency and Latency
      • 6.6.1. Recency
      • 6.6.2. Use Recency to Drive Revenue
      • 6.6.3. Latency
      • 6.6.4. Use Latency to Drive Revenue
    • Hack #86. Manage Lifetime Value Using the Visitor Segment Value Matrix
      • 6.7.1. Use the Matrix to Drive Content Decisions
      • 6.7.2. Hacking the Hack
    • Hack #87. Use Cross-Sell Data to Sell More Products
      • 6.8.1. Quantify the Value of Product Recommendations
        • 6.8.1.1. Step one: Track cross-sell links separately.
        • 6.8.1.2. Step two: Measure cross-sell performance.
        • 6.8.1.3. Step three: Take action.
      • 6.8.2. Data-Driven Analysis: Find the Low-Hanging Fruit
        • 6.8.2.1. Tracking cart overlap.
        • 6.8.2.2. Tracking common buyers.
      • 6.8.3. Leverage Cross-Sell Data
    • Hack #88. Use Geographic Segmentation to Measure Offline Marketing
      • 6.9.1. Key Measurements
      • 6.9.2. An Example
    • Hack #89. Measure New and Returning Customers
      • 6.10.1. Serve Your Own First-Party Cookie
      • 6.10.2. Have Your Application Provider Serve a First-Party Cookie for You
      • 6.10.3. Using the Information
    • Hack #90. Build Your Own Web Measurement Application: Commerce Data
      • 6.11.1. The Code: Page Tag and Tag Processor
      • 6.11.2. The Code: readlog.pl
      • 6.11.3. Running the Code
  • 7. Reporting Strategies and Key Performance Indicators
    • 7.1. Hacks 91100: Introduction
      • 7.1.1. Sometimes It's How You Say It
      • 7.1.2. Patience, Patience, Patience
      • 7.1.3. Microsoft Excel: the World's Most Popular Analytics Application
    • Hack #91. Distribute Reports Wisely
      • 7.2.1. Give the People What They Want, or Better Yet, What They Need
      • 7.2.2. Use the Same Language Your Audience Uses Whenever Possible
      • 7.2.3. A Picture Says a Thousand Words
      • 7.2.4. Ratios Are Better than Counts
      • 7.2.5. Distribute Reports Regularly
    • Hack #92. Know If the News Is Good
      • 7.3.1. Comparing Your Site to Industry Standards and Competitors
    • Hack #93. (Don't) Benchmark Your Site
      • 7.4.1. The Foolproof Benchmarking Hack for Anyone
      • 7.4.2. The Only Way to Benchmark Against External Data
        • 7.4.2.1. Fireclick Index ().
        • 7.4.2.2. Coremetrics LIVEmark ().
    • Hack #94. Use Key Performance Indicators
      • 7.5.1. Best Practices for Defining Key Performance Indicators
        • 7.5.1.1. Use KPIs to drive action.
        • 7.5.1.2. Present KPIs visually whenever possible.
      • 7.5.2. Use the language of the business to increase familiarity.
        • 7.5.2.1. Explain the how and why of KPIs.
    • Hack #95. Know the Difference Between a KPI and a Measurement
    • Hack #96. Key Performance Indicators for Online Retailers
      • 7.7.1. Basic Key Performance Indicators for Online Retailers
        • 7.7.1.1. Sales per visitor.
        • 7.7.1.2. Average order value (AOV).
        • 7.7.1.3. Percent new and returning visitors.
        • 7.7.1.4. Ratio of new to returning visitors.
        • 7.7.1.5. Customer retention rate.
      • 7.7.2. Advanced Key Performance Indicators for Online Retailers
        • 7.7.2.1. Order conversion rate.
        • 7.7.2.2. Buyer conversion rate.
        • 7.7.2.3. Cart add to purchase conversion rate.
        • 7.7.2.4. Checkout-to-purchase conversion rate.
        • 7.7.2.5. Search to purchase conversion rate.
        • 7.7.2.6. New and returning visitor conversion rates.
        • 7.7.2.7. Percent of visits less than 90 seconds.
      • 7.7.3. Other Important Measurements
    • Hack #97. Key Performance Indicators for Advertising and Content Sites
      • 7.8.1. Basic Key Performance Indicators for Content Sites
        • 7.8.1.1. Average pages viewed per visit.
        • 7.8.1.2. Average visits per visitor.
        • 7.8.1.3. Percent new and returning visitors.
        • 7.8.1.4. Ratio of new to returning visitors.
        • 7.8.1.5. Average time spent on site.
      • 7.8.2. Advanced Key Performance Indicators for Content Sites
        • 7.8.2.1. Percent of visits less than 90 seconds.
        • 7.8.2.2. Percent committed visits.
        • 7.8.2.3. "Stickiness" for key pages.
      • 7.8.3. Other Important Measurements
    • Hack #98. Key Performance Indicators for Customer Support Sites
      • 7.9.1. Basic Key Performance Indicators for Customer Support Sites
        • 7.9.1.1. Average pages viewed per visit.
        • 7.9.1.2. Percent new and returning visitors.
        • 7.9.1.3. Average time spent on site.
      • 7.9.2. Advanced Key Performance Indicators for Customer Support Sites
        • 7.9.2.1. Percent "zero results" searches.
        • 7.9.2.2. Support satisfaction rate.
        • 7.9.2.3. Percent "zero yield" search results.
        • 7.9.2.4. Percent of visits less than 90 seconds.
        • 7.9.2.5. "Stickiness" for key pages.
        • 7.9.2.6. "Information find" conversion rate.
      • 7.9.3. Other Important Measurements
    • Hack #99. Key Performance Indicators for Business Sites (Lead Generation)
      • 7.10.1. Basic Key Performance Indicators for Business Sites
        • 7.10.1.1. Lead generation conversion rate.
        • 7.10.1.2. Average visits per visitor.
        • 7.10.1.3. Percent new and returning visitors.
        • 7.10.1.4. Ratio of new to returning visitors.
        • 7.10.1.5. Average time spent on site.
      • 7.10.2. Advanced Key Performance Indicators for Business Sites
        • 7.10.2.1. Average hours to response (online inquiry).
        • 7.10.2.2. Percent of visits less than 90 seconds.
        • 7.10.2.3. Percent interested visits.
        • 7.10.2.4. Percent committed visits.
        • 7.10.2.5. "Stickiness" for key pages.
      • 7.10.3. Other Important Measurements
    • Hack #100. Build Your Own Web Measurement Application: Reporting
      • 7.11.1. Running the Application
      • 7.11.2. Extending This Application
        • 7.11.2.1. Add simple visitor segmentation.
        • 7.11.2.2. Clean up duplicate page names.
        • 7.11.2.3. Improve the reporting.
        • 7.11.2.4. Add user configuration.
        • 7.11.2.5. Improve program efficiency.
        • 7.11.2.6. Add error checking.
        • 7.11.2.7. Track exits from the site.
        • 7.11.2.8. Add multi-session tracking functionality.
        • 7.11.2.9. You could get the logfile from a remote location via FTP.
  • About the Author
  • Colophon
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