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Web Analytics: An Hour a Day by Kaushik
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“Used book in good condition. Shows typical wear. Quick shipping. Satisfaction guaranteed!”
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Libro que se ha leído pero que está en buen estado. Daños mínimos en la tapa, incluidas rozaduras, pero sin roturas ni agujeros. Es posible que no incluya sobrecubierta para tapas duras. Tapa muy poco desgastada. La mayoría de las páginas están en buen estado con muy pocas arrugas o roturas. El texto subrayado a lápiz es prácticamente inexistente, no hay texto resaltado ni anotaciones en los márgenes. No faltan páginas. Consulta el anuncio del vendedor para obtener más información y la descripción de cualquier posible imperfección.
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Ubicado en: Multiple Locations, Estados Unidos
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Entrega prevista entre el mié. 23 jul. y el sáb. 26 jul. a 94104
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N.º de artículo de eBay:167617681666
Última actualización el 17 jul 2025 23:14:49 H.EspVer todas las actualizacionesVer todas las actualizaciones
Características del artículo
- Estado
- En buen estado
- Notas del vendedor
- “Used book in good condition. Shows typical wear. Quick shipping. Satisfaction guaranteed!”
- Book Title
- Web Analytics: An Hour a Day
- Topic
- Systems Analysis & Design
- Narrative Type
- Systems Analysis & Design
- Genre
- N/A
- Intended Audience
- N/A
- ISBN
- 9780470130650
Acerca de este producto
Product Identifiers
Publisher
Wiley & Sons, Incorporated, John
ISBN-10
0470130652
ISBN-13
9780470130650
eBay Product ID (ePID)
57220079
Product Key Features
Number of Pages
480 Pages
Language
English
Publication Name
Web Analytics : an Hour a Day
Publication Year
2007
Subject
Internet / General, Web / Design
Type
Textbook
Subject Area
Computers
Series
Serious Skills Ser.
Format
CD-ROM / Trade Paperback
Dimensions
Item Height
0.9 in
Item Weight
0 Oz
Item Length
9.2 in
Item Width
7.3 in
Additional Product Features
Intended Audience
Trade
LCCN
2008-272725
Dewey Edition
22
Illustrated
Yes
Dewey Decimal
025.04
Table Of Content
Foreword. Introduction. Chapter 1 Web Analytics-Present and Future. A Brief History of Web Analytics. Current Landscape and Challenges. Traditional Web Analytics Is Dead. What Web Analytics Should Be. Chapter 2 Data Collection-Importance and Options. Understanding the Data Landscape. Clickstream Data. Outcomes Data. Research Data. Competitive Data. Chapter 3 Overview of Qualitative Analysis. The Essence of Customer Centricity. Lab Usability Testing. Heuristic Evaluations. Site Visits (Follow-Me-Home Studies). Surveys (Questionnaires). Summary. Chapter 4 Critical Components of a Successful Web Analytics Strategy? Focus on Customer Centricity. Solve for Business Questions. Follow the 10/90 Rule. Hire Great Web Analysts. Identify Optimal Organizational Structure and Responsibilities. Chapter 5 Web Analytics Fundamentals. Capturing Data: Web Logs or JavaScript tags? Selecting Your Optimal Web Analytics Tool. Understanding Clickstream Data Quality. Implementing Best Practices. Apply the "Three Layers of So What" Test. Chapter 6 Month 1: Diving Deep into Core Web Analytics Concepts. Week 1: Preparing to Understand the Basics. Week 2: Revisiting Foundational Metrics. Week 3: Understanding Standard Reports. Week 4: Using Website Content Quality and Navigation Reports. Chapter 7 Month 2: Jump-Start Your Web Data Analysis. Prerequisites and Framing. Week 1: Creating Foundational Reports. E-commerce Website Jump-Start Guide. Support Website Jump-Start Guide. Blog Measurement Jump-Start Guide. Week 4: Reflections and Wrap-Up. Chapter 8 Month 3: Search Analytics-Internal Search, SEO, and PPC. Week 1: Performing Internal Site Search Analytics. Week 2: Beginning Search Engine Optimization. Week 3: Measuring SEO Efforts. Week 4: Analyzing Pay per Click Effectiveness. Chapter 9 Month 4: Measuring Email and Multichannel Marketing. Week 1: Email Marketing Fundamentals and a Bit More. Week 2: Email Marketing-Advanced Tracking. Weeks 3 and 4: Multichannel Marketing, Tracking, and Analysis. Chapter 10 Month 5:Website Experimentation and Testing-Shifting the Power to Customers and Achieving Significant Outcomes. Weeks 1 and 2: Why Test and What Are Your Options? Week 3: What to Test-Specific Options and Ideas. Week 4: Build a Great Experimentation and Testing Program. Chapter 11 Month 6: Three Secrets Behind Making Web Analytics Actionable. Week 1: Leveraging Benchmarks and Goals in Driving Action. Week 2: Creating High Impact Executive Dashboards. Week 3: Using Best Practices for Creating Effective Dashboard Programs. Week 4: Applying Six Sigma or Process Excellence to Web Analytics. Chapter 12 Month 7: Competitive Intelligence and Web 2.0 Analytics. Competitive Intelligence Analytics. Web 2.0 Analytics. Chapter 13 Month 8 and Beyond: Shattering the Myths of Web Analytics. Path Analysis: What Is It Good For? Absolutely Nothing. Conversion Rate: An Unworthy Obsession. Perfection: Perfection Is Dead, Long Live Perfection. Real-Time Data: It's Not Really Relevant, and It's Expensive to Boot. Standard KPIs: Less Relevant Than You Think. Chapter 14 Advanced Analytics Concepts-Turbocharge Your Web Analytics. Unlock the Power of Statistical Significance. Use the Amazing Power of Segmentation. Make Your Analysis and Reports "Connectable". Use Conversion Rate Best Practices. Elevate Your Search Engine Marketing/Pay Per C
Synopsis
Written by an in-the-trenches practitioner, this step-by-step guide shows you how to implement a successful Web analytics strategy. Web analytics expert Avinash Kaushik, in his thought-provoking style, debunks leading myths and leads you on a path to gaining actionable insights from your analytics efforts., Written by an in-the-trenches practitioner, this step-by-step guide shows you how to implement a successful Web analytics strategy. Web analytics expert Avinash Kaushik, in his thought-provoking style, debunks leading myths and leads you on a path to gaining actionable insights from your analytics efforts. Discover how to move beyond clickstream analysis, why qualitative data should be your focus, and more insights and techniques that will help you develop a customer-centric mindset without sacrificing your company's bottom line. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file., Develop a Successful Web Analytics Strategy A Step-by-Step Guide Learn web analytics the right way with this unique, thoroughly modern guide to today's web analytics challenges and opportunities. Written by an in-the-trenches practitioner, this book goes beyond concepts and definitions to challenge prevalent thinking about the field and provide a step-by-step guide to implementing a successful web analytics strategy. Web analytics expert Avinash Kaushik, in his thought-provoking style, debunks leading myths and leads you on a path to gaining actionable insights from your analytics efforts. Discover how to move beyond clickstream analysis, why qualitative data should be your focus, and more insights and techniques that will help you develop a customer-centric mindset without sacrificing your company's bottom line. Learn the pros and cons of data collection methodologies Find out how you can stop counting page views and still get a rich understanding of your customers Discover how to identify valuable metrics with the "three layers of so what" test Optimize your organizational structure and choose the right analytics tool Understand and apply advanced analytics concepts, including SEM/PPC analysis, the power of segmentation, conversion-rate best practices, and others Leverage quick-start solutions for blogs and e-commerce, support, and small business websites Learn the key ingredients of a great experimentation and testing platform Use competitive-intelligence analysis to glean insights and drive actions You'll also find: Ten steps to turbocharge your web analytics Seven steps for creating a data-driven culture in your organization Six ways to measure the success of a blog Three secrets behind making web analytics actionable Ten signs of a great web analyst Valuable CD Included The innovative CD includes more than three hours of insightful audio podcasts, a 45-minute video, PowerPoint presentations that mirror key topics in the book, and other useful analytics resources.
LC Classification Number
ZA4235.K38 2007
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