Jason Burby,
Shane Atchison
Actionable Web Analytics: Using Data to Make Smart Business Decisions
Paperback Engels 2007 1e druk 9780470124741Levertijd ± 8 werkdagen
Gratis verzonden
Samenvatting
Right now someone is clicking on your website, and knowing everything you can about those clicks and the people that make them is a business imperative. That is the first of a set of compelling business lessons the expert authors of this guide have distilled from a decade of experience with the world's most powerful online brands. These lessons help executives, marketers, web managers, designers, and developers take action based on the actual behavior of site visitors.
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. Read on, and learn to demonstrate real ROI from your Web site.
Powerful lessons in this book include:
- Learning to use Web analytics data to help make strategic decisions and set corporate goals
- Asking the right questions when planning your Web site
- Recognizing how your data reflects the perceptions of your customers, information on your competitors, and your marketing costs
- Developing criteria for choosing an agency to help you interpret your data
- Discovering how successful your marketing efforts have been
- Overcoming common barriers that keep most companies from leveraging analytics data successfully
- Creating a culture of analysis within your organization
Specificaties
ISBN13:9780470124741
Taal:Engels
Bindwijze:paperback
Aantal pagina's:256
Uitgever:Sybex
Druk:1
Hoofdrubriek:IT-management / ICT
Lezersrecensies
Wees de eerste die een lezersrecensie schrijft!
Inhoudsopgave
Foreword.
Introduction.
Part 1: The Changing Landscape of Marketing Online.
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.
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 2: Shifting to a Culture of Analysis.
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.
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.
Introduction.
Part 1: The Changing Landscape of Marketing Online.
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.
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 2: Shifting to a Culture of Analysis.
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.
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 3: Proven Formula for Success.
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.
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.
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.
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.
-Heuristic Evaluation and Expert Reviews.
-Community Sourced Data.
-Leveraging These Data Types.
-Comparing Performance with Others.
-What Is a Relative Index?
-Examples of Relative Indices.
-Customer Engagement.
-Methodology: Leveraging Indices across Your Organization.
-Case Study: Leveraging Different Data Types to Improve Site Performance.
-Recap.
9. Analyzing Site Performance.
-Analysis vs. Reporting.
-Don't Blame Your Tools.
-Examples of Analysis.
-Analyzing Purchasing Processes to Find Opportunities.
-Analyzing Lead Processes to Find Opportunities.
-Understanding What Onsite Search Is Telling You.6
-Evaluating the Effectiveness of Your Home Page.
-Evaluating the Effectiveness of Branding Content: Branding Metrics.
-Evaluating the Effectiveness of Campaign Landing Pages.
-Segmenting Traffic to Identify Behavioral Differences.
-Segmenting Your Audience.
-Case Study: Segmenting for a Financial Services Provider.
-Analyzing Drivers to Offline Conversion.
-Tracking Online Partner Handoffs and Brick-And-Mortar Referrals.
-Tracking Offline Handoffs to Sales Reps.
-Tracking Visitors to a Call Center.
-Delayed Conversion.
-Tracking Delayed Conversion.
-Reporting in a Timely Manner.
-Recap.
10. Prioritizing.
-How We Prioritize.
-The Principles of Dynamic Prioritization.
-Traditional Resource Prioritization.
-Dynamic Prioritization.
-Dynamic Prioritization Scorecard.
-Dynamic Prioritization in Action.
-Forecasting Potential Impact.
-Comparing Opportunities.
-Moving Your Company Toward Dynamic Prioritization.
-Overcoming Common Excuses.
-Conclusion.
-Recap.
11. Moving from Analysis to Site Optimization.
-Testing Methodologies and Tools.
-A/B Testing.
-A/B/n Testing.
-Multivariate Tests.
-How to Choose a Test Type.
-Testing Tools.
-What to Test.
-Prioritizing Tests.
-Creating a Successful Test.
-Understanding Post-Test Analysis.
-Optimizing Segment Performance.
-Example One: Behavior-Based Testing.
-Example Two: Day-of-the-Week Testing.
-Planning for Optimization.
-Budgeting for Optimization.
-Skills Needed for a Successful Optimization Team.
-Overcoming IT Doubts.
-IT Doesn't Understand the Process.
-Testing Prioritization.
-Lack of Executive Support.
-Learning from Your Successes and Mistakes.
-Learning from the Good and the Bad.
-A Quick Way Up the Learning Curve.
-Spreading the Word.
-Test Examples.
-Price.
-Promotional.
-Message.
-Page Layout.
-New Site Launches or New Functionality.
-Site Navigation and Taxonomy.
-Recap.
12. Agencies.
-Why Use an Agency at All?
-Finding an Agency.
-Creating an RFP.
-Introduction and Company Background.
-Scope of Work and Business Goals.
-Timelines.
-Financials.
-The Rest of the RFP: Asking the Right Questions.
-Mutual Objective: Success.
-Doing the Work.
-The Secret Agency Sauce.
-Recap.
13. The Creative Brief.
-What Is a Creative Brief?
-The Brief.
-Components of a Data-Driven Brief.
-Creative Brief Metrics.
-Analytics and Creativity.
-The Iterative Design Cycle.
-A Sample Creative Brief.
-Creative Brief: Robotwear.Com.
-Recap.
14. Staffing and Tuning Your Web Team.
-Skills That Make a Great Web Analyst.
-Technical vs. Interpretive Expertise.
-Key Web Analyst Skills.
-The Roles of the Web Analyst.
-Building Your Web-Analytics Team: Internal and External Teams.
-Estimating Your Cost.
-Key Analytics Positions.
-Expanding the Circle of Influence.
-Internal vs. External Teams.
-Education and Training for Web Analysts.
-Web Analytics Association.
-Conferences.
-University of British Columbia Courses.
-Message Boards.
-ClickZ and Other Online Media.
-Blogs.
-Web Analytics Wednesdays.
-Vendor Training.
-Agency Partners.
-Hands-on Experience.
-Recap.
15. Partners.
-When to Choose an Analytics Tool Vendor.
-Methodology for Selecting a Tool.
-Selecting a Review Committee.
-Establishing a Timeline.
-Criteria to Review and Select Vendors.
-10 Questions to Ask Web Analytics Vendors.
-Comparing to Free Tools.
-ASP or Software Version.
-Data Capture.
-Total Cost of Ownership.
-Support.
-Data Segmentation.
-Data Export and Options.
-Data Integration.
-The Future.
-References.
-Recap.
-Conclusion.
Appendix: Web Analytics "Big Three" Definitions.
-How We Define Terms.
-Definition Framework Overview.
-Term: Unique Visitors.
-Term: Visits/Sessions.
-Term: Page Views.
Index.
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.
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.
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.
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.
-Heuristic Evaluation and Expert Reviews.
-Community Sourced Data.
-Leveraging These Data Types.
-Comparing Performance with Others.
-What Is a Relative Index?
-Examples of Relative Indices.
-Customer Engagement.
-Methodology: Leveraging Indices across Your Organization.
-Case Study: Leveraging Different Data Types to Improve Site Performance.
-Recap.
9. Analyzing Site Performance.
-Analysis vs. Reporting.
-Don't Blame Your Tools.
-Examples of Analysis.
-Analyzing Purchasing Processes to Find Opportunities.
-Analyzing Lead Processes to Find Opportunities.
-Understanding What Onsite Search Is Telling You.6
-Evaluating the Effectiveness of Your Home Page.
-Evaluating the Effectiveness of Branding Content: Branding Metrics.
-Evaluating the Effectiveness of Campaign Landing Pages.
-Segmenting Traffic to Identify Behavioral Differences.
-Segmenting Your Audience.
-Case Study: Segmenting for a Financial Services Provider.
-Analyzing Drivers to Offline Conversion.
-Tracking Online Partner Handoffs and Brick-And-Mortar Referrals.
-Tracking Offline Handoffs to Sales Reps.
-Tracking Visitors to a Call Center.
-Delayed Conversion.
-Tracking Delayed Conversion.
-Reporting in a Timely Manner.
-Recap.
10. Prioritizing.
-How We Prioritize.
-The Principles of Dynamic Prioritization.
-Traditional Resource Prioritization.
-Dynamic Prioritization.
-Dynamic Prioritization Scorecard.
-Dynamic Prioritization in Action.
-Forecasting Potential Impact.
-Comparing Opportunities.
-Moving Your Company Toward Dynamic Prioritization.
-Overcoming Common Excuses.
-Conclusion.
-Recap.
11. Moving from Analysis to Site Optimization.
-Testing Methodologies and Tools.
-A/B Testing.
-A/B/n Testing.
-Multivariate Tests.
-How to Choose a Test Type.
-Testing Tools.
-What to Test.
-Prioritizing Tests.
-Creating a Successful Test.
-Understanding Post-Test Analysis.
-Optimizing Segment Performance.
-Example One: Behavior-Based Testing.
-Example Two: Day-of-the-Week Testing.
-Planning for Optimization.
-Budgeting for Optimization.
-Skills Needed for a Successful Optimization Team.
-Overcoming IT Doubts.
-IT Doesn't Understand the Process.
-Testing Prioritization.
-Lack of Executive Support.
-Learning from Your Successes and Mistakes.
-Learning from the Good and the Bad.
-A Quick Way Up the Learning Curve.
-Spreading the Word.
-Test Examples.
-Price.
-Promotional.
-Message.
-Page Layout.
-New Site Launches or New Functionality.
-Site Navigation and Taxonomy.
-Recap.
12. Agencies.
-Why Use an Agency at All?
-Finding an Agency.
-Creating an RFP.
-Introduction and Company Background.
-Scope of Work and Business Goals.
-Timelines.
-Financials.
-The Rest of the RFP: Asking the Right Questions.
-Mutual Objective: Success.
-Doing the Work.
-The Secret Agency Sauce.
-Recap.
13. The Creative Brief.
-What Is a Creative Brief?
-The Brief.
-Components of a Data-Driven Brief.
-Creative Brief Metrics.
-Analytics and Creativity.
-The Iterative Design Cycle.
-A Sample Creative Brief.
-Creative Brief: Robotwear.Com.
-Recap.
14. Staffing and Tuning Your Web Team.
-Skills That Make a Great Web Analyst.
-Technical vs. Interpretive Expertise.
-Key Web Analyst Skills.
-The Roles of the Web Analyst.
-Building Your Web-Analytics Team: Internal and External Teams.
-Estimating Your Cost.
-Key Analytics Positions.
-Expanding the Circle of Influence.
-Internal vs. External Teams.
-Education and Training for Web Analysts.
-Web Analytics Association.
-Conferences.
-University of British Columbia Courses.
-Message Boards.
-ClickZ and Other Online Media.
-Blogs.
-Web Analytics Wednesdays.
-Vendor Training.
-Agency Partners.
-Hands-on Experience.
-Recap.
15. Partners.
-When to Choose an Analytics Tool Vendor.
-Methodology for Selecting a Tool.
-Selecting a Review Committee.
-Establishing a Timeline.
-Criteria to Review and Select Vendors.
-10 Questions to Ask Web Analytics Vendors.
-Comparing to Free Tools.
-ASP or Software Version.
-Data Capture.
-Total Cost of Ownership.
-Support.
-Data Segmentation.
-Data Export and Options.
-Data Integration.
-The Future.
-References.
-Recap.
-Conclusion.
Appendix: Web Analytics "Big Three" Definitions.
-How We Define Terms.
-Definition Framework Overview.
-Term: Unique Visitors.
-Term: Visits/Sessions.
-Term: Page Views.
Index.
Afgekapt op 60 regels
Rubrieken
- advisering
- algemeen management
- coaching en trainen
- communicatie en media
- economie
- financieel management
- inkoop en logistiek
- internet en social media
- it-management / ict
- juridisch
- leiderschap
- marketing
- mens en maatschappij
- non-profit
- ondernemen
- organisatiekunde
- personal finance
- personeelsmanagement
- persoonlijke effectiviteit
- projectmanagement
- psychologie
- reclame en verkoop
- strategisch management
- verandermanagement
- werk en loopbaan