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Web Analytics 2.0 is a very classic entry-level book for learning web statistics. It tells a lot of summary of experience based on current industry, makes a painstaking investigation and analysis on the Internet data, and puts forward the more specific, simpler and more advanced methods. For readers who want to become a web analytics expert or are interested in online marketing and web statistics, Web Analytics 2.0 will be the best choice for you.
After Avinash Kaushik‘s first best-selling book Web Analytics: An Hour a Day, in Web Analytics 2.0, he further explained how to measure and analyze the current new technology and applications on the Internet, and make rapid actions on this basis. These new techniques and applications include: social media, online video, mobile Internet, as well as designs focusing on users, etc.
In brief, through the framework proposed by Avinash Kaushik in his Web Analytics 2.0 for the next generation of websites analysis, we will be able to greatly improve the initiative of our organization and the response speed to the web market, thus to turn to the data-driven decisions and make full use of the websites data to gain competitive advantage.
// Table Of Contents //
- Chapter 1 The Bold New World of Web Analytics 2.0
- Chapter 2 The Optimal Strategy for Choosing Your Web Analytics Soul Mate
- Chapter 3 The Awesome World of Clickstream Analysis: Metrics
- Chapter 4 The Awesome World of Clickstream Analysis: Practical Solutions
- Chapter 5 The Key to Glory: Measuring Success
- Chapter 6 Solving the “Why” Puzzle: Leveraging Qualitative Data
- Chapter 7 Failing Faster: Unleashing the Power of Testing and Experimentation
- Chapter 8 Competitive Intelligence Analysis
- Chapter 9 Emerging Analytics: Social, Mobile, and Video
- Chapter 10 Optimal Solutions for Hidden Web Analytics Traps
- Chapter 11 Guiding Principles for Becoming an Analysis Ninja
- Chapter 12 Advanced Principles for Becoming an Analysis Ninja
- Chapter 13 The Web Analytics Career
- Chapter 14 HiPPOs, Ninjas, and the Masses: Creating a Data-Driven Culture
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