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Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
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Searching... | 30000003485194 | TK5105.875.I57 B86 2007 | Open Access Book | Book | Searching... |
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Summary
Summary
Knowing everything you can about each click to your Web site can help you make strategic decisions regarding your business. This book is about the why, not just the how, of web analytics and the rules for developing a "culture of analysis" inside your organization. Why you should collect various types of data. Why you need a strategy. Why it must remain flexible. Why your data must generate meaningful action. The authors answer these critical questions--and many more--using their decade of experience in Web analytics.
Author Notes
Jason Burby is Chief Analytics and Optimization Officer for ZAAZ, Inc., a web design and analytics consulting firm. His clients have included eTrade, Ford, Sony, PayPal/eBay, Washington Mutual, Reuters, T-Mobile, Levi Strauss, and Microsoft.
Shane Atchison , co-founder and CEO of ZAAZ, Inc., leads its long-term strategic vision of helping companies realize the potential of the Internet and its impact on their business. Among his client list have been Converse, Sony, Ford, Microsoft, and National Geographic .
Table of Contents
Foreword |
Introduction |
Part I The Changing Landscape of Marketing Online |
Chapter 1 The Big Picture |
New Marketing Trends |
The Consumer Revolution |
The Shift from Offline to Online Marketing |
Instant Brand Building (and Destruction) |
Rich Media and Infinite Variety |
The Analysis Mandate |
ROI Marketing |
Innovation |
Some Final Thoughts |
Chapter 2 Performance Marketing |
Data vs. Design |
Web Design Today |
The Web Award Fallacy |
When Visual Design Goes Wrong |
Where Data Goes Wrong |
Performance-Driven Design: Balancing Logic and Creativity |
Case Study: Dealing with Star Power |
Case Study: Forget Marketing at All |
Recap |
Part II Shifting to a Culture of Analysis |
Chapter 3 What "Culture of Analysis" Means |
What Is a Data-Driven Organization? |
Data-Driven Decision Making |
Dynamic Prioritization |
Perking Up Interest in Web Analytics |
Establishing a Web Analytics Steering Committee |
Starting Out Small with a Win |
Empowering Your Employees |
Managing Up |
Impact on Roles beyond the Analytics Team |
Cross-Channel Implications |
Questionnaire: Rating Your Level of Data Drive |
Recap |
Chapter 4 Avoiding Stumbling Points |
Do You Need an Analytics Intervention? |
Analytics Intervention Step 1: Admitting the Problem |
Analytics Intervention Step 2: Admit That You Are the Problem |
Analytics Intervention Step 3: Agree That This Is a Corporate Problem |
The Road to Recovery: Overcoming Real Gaps |
Issue #1 Lack of Established Processes and Methodology |
Issue #2 Failure to Establish Proper KPIs and Metrics |
Issue #3 Data Inaccuracy |
Issue #4 Data Overload |
Issue #5 Inability to Monetize the Impact of Changes |
Issue #6 Inability to Prioritize Opportunities |
Issue #7 Limited Access to Data |
Issue #8 Inadequate Data Integration |
Issue #9 Starting Too Big |
Issue #10 Failure to Tie Goals to KPIs |
Issue #11 No Plan for Acting on Insight |
Issue #12 Lack of Committed Individual and Executive Support |
Recap |
Part III Proven Formula for Success |
Chapter 5 Preparing to Be Data-Driven |
Web Analytics Methodology |
The Four Steps of Web Analytics |
Defining Business Metrics (KPIs) |
Reports |
Analysis |
Optimization and Action |
Results and Starting Again |
Recap |
Chapter 6 Defining Site Goals, KPIs, and Key Metrics |
Defining Overall Business Goals |
Defining Site Goals: The Conversion Funnel |
Awareness |
Interest |
Consideration |
Purchase |
Website Goals and the Marketing Funnel |
Understanding Key Performance Indicators (KPIs) |
Constructing KPIs |
Creating Targets for KPIs |
Common KPIs for Different Site Types |
E-Commerce |
Lead Generation |
Customer Service |
Content Sites |
Branding Sites |
Recap |
Chapter 7 Monetizing Site Behaviors |
The Monetization Challenge |
Case Study: Monetization and Motivation |
Web-Monetization Models |
Top 10 Ways Monetization Models Can Help Your Company |
How to Create Monetization Models |
Assembling a Monetization Model |
Monetization Models for Different Site Types and Behaviors |
E-Commerce Opportunity |
Lead Generation |
Customer Service |
Ad-Supported Content Sites |
Recap |
Chapter 8 Getting the Right Data |
Primary Data Types |
Warning: Avoid Data Smog |
Behavioral Data |
Attitudinal Data |
Balancing Behavioral and Attitudinal Data |
Competitive Data |
Secondary Data Types |
Customer Interaction and Data |
Third-Party Research |
Usability Benchmarking |