Actionable Web Analytics Using Data to Make

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.

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.

Foreword
Introduction
The Changing Landscape of Marketing Online
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
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
Shifting to a Culture of Analysis
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
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
Lack of Established Processes and Methodology
Failure to Establish Proper KPIs and Metrics
Data Inaccuracy
Data Overload
Inability to Monetize the Impact of Changes
Inability to Prioritize Opportunities
Limited Access to Data
Inadequate Data Integration
Starting Too Big
Failure to Tie Goals to KPIs
No Plan for Acting on Insight
Lack of Committed Individual and Executive Support
Recap
Proven Formula for Success
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
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
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
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
Table of Contents provided by Publisher. All Rights Reserved.

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Actionable Web Analytics Using Data to Make Smart Business Decisions

Summary

Author Biography

Table of Contents

Supplemental Materials