精通Web Analytics 2.0 : 用户中心科学与在线统计艺术

What’s Inside the Book?

This book builds on the foundation laid by my first book, Web Analytics: An Hour a Day. I am not going to beat around the bush; Chapter 1 starts with a bang by introducing you to the Web Analytics 2.0 framework. That is followed immediately by a strong case for why the multiplicity mental model is mandatory for success with tools. We go from 0 to 60 in 13 pages!

Picking the right set of tools might be just as important as picking your friends: pick the wrong one, and it might take a long time to recover. With Chapter 2, I walk you through a process of self-reflection that will empower you to choose the right set of web analytics tools for your company. You’ll also learn questions you can ask tool vendors (why not stress them a bit?), the approach for choosing your vendor, and finally how to optimally negotiate your contract (stress them again!).

Chapters 3 and 4 cover the awesome world of traditional web analytics, clickstream analysis. In Chapter 3, using eight specific metrics, you’ll learn the intricate nuances that go into modern metrics: what you should look for, what you should avoid, and how to ensure that your company has chosen the right set of metrics. You’ll also learn my favorite technique for diagnosing the root cause behind poor performance.

Chapter 4 picks up the story and gently walks you through a primer on web analytics that will empower you to move very quickly from data to action on your website. I’ll then explore foundational analytical strategies followed by six specific analyses for your daily life. In every section you’ll learn how to kick things up a notch or two above average expectations. This chapter closes with a reality check on five key web analytics challenges (you are not going to want to miss this!).

Chapter 5 will be your best friend because it covers the single biggest reason for the existence of your websites: outcomes. That is, conversions, revenue, customer satisfaction, visitor loyalty, and more. You’ll learn the value of focusing on micro conversions (a must do!). At the end of the chapter, I offer two specific sets of recommendations on how to measure outcomes on non-ecommerce and B2B websites.

In Chapter 6, the Web Analytics 2.0 fun really starts because I cover the wonderful

world of customer centricity: listening to customers and doing so at scale. You’ll learn to leverage lab usability, surveys, and other user-centric design methodologies. Finally, I give an outline of exciting techniques on the horizon—techniques that will dramatically change how you think of leveraging voice of customer.

Chapter 7 covers experimentation and testing. If you have ever read my blog or heard me speak, you’ll know how absolutely liberating it is that the Web allows us to fail faster, frequently, and get smarter every single day. You’ll learn about A/B and multivariate testing, but I think you’ll remember this book the most for teaching you about the power of controlled experiments (finally you can answer the hardest questions you’ll ever face!).

Chapter 8 will help you come to grips with competitive intelligence analysis. Like the rest of this book, this chapter is not about teaching you how to use one tool or the other. No sirree, Bob! You’ll learn how to dig under the covers and understand how data is captured and why with competitive intelligence more than anywhere else the principle of garbage in, garbage out applies. By the time you finish this chapter, you’ll know how to analyze the website traffic of your competitors, use search data to measure brand and identify new opportunities, zero in on the audiences relevant for your campaign or business, and benchmark yourself against your competitors.

Chapter 9 will clarify how to measure the new and evolving fields of mobile analytics; you’ll see why measuring blogs is not like measuring websites and how to measure the success of your efforts on social channels such as Twitter. You’ll start by learning about the fundamental challenges that the social Web presents for measurement.

Chapter 10 starts the process of truly converting you to an analysis ninja. I cover the hidden rules of the game, issues to be careful about, tasks to do more, and why some approaches work and others don’t. You’ll want to read the end of this chapter to learn why revolutions in web data fail miserably and evolution works magnificently. Oh, and as you might expect, I offer a very specific recommended path to nirvana!

Chapter 11 is about analytical techniques—the key weapons that you’ll need in your arsenal as you head off to conquer the data world. You’ll get to know context, comparisons,“what’s changed,” latent conversions, the head and tail of search, and really, really advanced paid search analysis. Oh my.

Chapter 12 contains material that will be worth multiple times the price of this book. It tackles the hardest, baddest, meanest web data challenges on the planet today: multitouch campaign attribution analysis and multichannel analytics. There’s no dancing around here, just practical actionable solutions you can implement right now, today. Don’t do anything in web analytics until you have read this chapter.

Chapter 13 was one of the most fun chapters for me to write. Web Analytics 2.0 is about people (not surprising coming from the creator of the 10/90 rule for magnificent success). Regardless of your role in the data world, this chapter includes guidance on how to plan your career to ensure maximum success. I offer best practices for keeping your knowledge current, but I don’t stop there; I suggest ways to move to the bleeding edge. The chapter closes with advice for managers and directors about how to identify the right talent, nurture them, and set them up for success.

Chapter 14 collects all my experience and research in this nascent field and shares recommendations for tackling the one task that will make or break your success: creating a datadriven culture. I recommend approaches on how to present data, how to excite people, how to use metric definitions to influence behavioral change in your organization, and how to create a truly data-driven boss (yea!) and finally strategies for getting budget and support for your analytical program and people.

Does that sound exciting? Oh, it’s so much fun!