Web Analytics: An Hour a Day / Edition 1

Web Analytics: An Hour a Day / Edition 1

by Avinash Kaushik
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Web Analytics: An Hour a Day / Edition 1

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.

Product Details

ISBN-13: 9780470130650
Publisher: Wiley
Publication date: 06/05/2007
Series: Serious Skills Series
Pages: 480
Product dimensions: 9.14(w) x 7.42(h) x 1.02(d)

About the Author

Avinash Kaushik is the author of the highly rated web analytics blog Occam's Razor (www.kaushik.net/avinash). He is an independent consultant and currently the Analytics Evangelist for Google. Prior to that he was the Director of Web Research & Analytics for Intuit, where he was responsible for the business, technical, and strategic elements of the analytics platform that supported more than 70 Intuit websites. Avinash is a frequent speaker at such conferences as Emetrics Summits and Ad-Tech, and he is often quoted in the media as a web metrics expert.
Avinash is donating all proceeds from this book to two charities, The Smile Train and Doctors Without Borders.

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Table of Contents



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).


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 Click Analysis.

Measure the Adorable Site Abandonment Rate Metric.

Measure Days and Visits to Purchase.

Leverage Statistical Control Limits.

Measure the Real Size of Your Convertible “Opportunity Pie”.

Chapter 15 Creating a Data-Driven Culture—Practical Steps and Best Practices.

Key Skills to Look for in a Web Analytics Manager/Leader.

When and How to Hire Consultants or In-House Experts.

Seven Steps to Creating a Data-Driven Decision-Making Culture.


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Web Analytics: An Hour a Day 5 out of 5 based on 0 ratings. 4 reviews.
Guest More than 1 year ago
Web Analytics is a must read because it learns you how to view analytics the right way. One of the hardest part when first diving into analytics is figuring out how to focus on the right data - the data that tells you what is happening with your site. One of the first questions Avinash gets you to focus on is: 'What's the purpose of your web site?' Your analytics strategy should be very much aligned with the answer to this question. With this attitude towards the data, we can 'infer the intent' of the user - ultimately, inferring is the best you can do with this type of data. Inferences are important, as they will inform strategy. If the strategy is then met with improved performance of the site, your confidence in the data and its interpretation grows. If not, you should re-analyze and re-strategize. Early in the book, Avinash identifies this as your top priority in analytics. In fact, he says, 'Is it a bit extreme to dump clickstream in favor of measuring outcomes first? Yes. Necessary? You bet.' The challenge is that the quality of the information available from your traditional web analytics tools is too poor for you to analyze outcome. In order to make sense of the data, we need broader research and analysis, so that we can find relationships between the different types of data, and infer meaning from them. To achieve this, Avinash enriches the data with Focus group analysis, continuous surveys, multivariate testing, etc. Avinash also integrates competitive intelligence in his interpretation of the data. Services such as comScore and Hitwise can provide direct information about what your customers are doing. It is a great book that teaches you all this from the ground up, and goes into amazing detail. I recommend it wholeheartedly.
Anonymous More than 1 year ago
robw3712 More than 1 year ago
Avinash Kaushik's book is simply amazing! It truly goes far beyond web analytics, offering up profound and easily digestible advise for all site strategists and owners.
Anonymous More than 1 year ago