“Web analytics is a mystery, not a puzzle,” declares Avinash Kaushik, Google Analytics evangelist, in his book Web Analytics 2.0. “A puzzle has a factual answer waiting to be found. Mysteries rarely do.”
With his latest guide on web analytics measurement, Avinash (he goes by Avinash in all his presentations, reflecting his approachable nature) makes the mystery less intimidating. He encourages the reader to be comfortable playing detective with web data.
What is Web Analytics?
A recap for those who do not know what web analytics is (and its significance): Web analytics is the measurement of website visitor behavior. It measures such things as number of visitors, time on site, and bounce rate (the percentage of visitors who leave a site in 3 seconds or less — equivalent to entering a store, realizing you don’t want to be there, and leaving immediately). Web analytics data is used to help improve a website for users.
Since a website can be used for registering for a cause or selling a product, the benefits of evaluating web analytics data are endless. Given the recent announcements of real-time search, coupled with the growth of social media tools, website owners who conduct retail online or rely on websites to engage customers can ill afford to not understand online behavior that contributes to business results.
But web analytics is still in its infancy. Many firms are still struggling with how to incorporate the data into actionable decisions. Even the mindset regarding online presence has not caught up in some industries outside of media, where some senior managers equate the web to television in terms of behavior (contrary to various reports).
Web Analytics 2.0 Takes Web Analytics to the Next Level
Enter Web Analytics 2.0, Avinash’s second book. The previous release, Web Analytics: An Hour A Day, became a bible among online marketers and web analysts alike. Web Analytics 2.0 goes to the next step, linking analytic metrics and measurement techniques to business value and decisions.
Avinash thoroughly covers the essentials, such as selection criteria for choosing a web analytics solution vendor and steps for analysts to become analytics “ninjas” in evaluating data and reporting to management.
The key to successfully drawing conclusions from web analytics data is to select relevant metrics — what do you want to measure? Is it related to the website’s purpose? How does the online measurement fit into your business decisions? Many of the steps and processes recommended revolve around these three questions and how to take action.
For example, Avinash explains the difference between precision and accuracy. He says a business can “focus obsessively on accuracy. It’s good to want accuracy, but it is more important to balance costs and benefits.” Avinash encourages analysts and managers alike to keep using the data to learn and seek outcomes quickly, even with minor mistakes. ”An educated mistake”, says Avinash, “is better than no action at all.” These statements are not meant to justify any major business errors, but to explain how to use information to make solid and timely decisions.
The book reinforces its points through well-organized examples and covers virtually all the current online tools available. Avinash also gives a good overview that shows how to incorporate social media tools into a coherent measurement that identifies value.
Fun and Fresh Writing Style
He is enthusiastic and has a fresh communication style, using interesting metaphors such as “I have compared web analytics to Angelina Jolie; that comparison should suggest how sexy it is, how powerful it is, and what a force of good it can be.” Or he tells readers to “get jiggy with it” in regards to unique visitor data. Yes, Will Smith has long moved on from the catch-phrase, but it is refreshing that someone realizes that information can be fun with the right mindset.
The only downside to Web Analytics 2.0 is that despite its efforts, more examples that link standard business metrics would potentially hit home with the fence sitters, i.e., the managers who really can benefit but do not feel fully “jiggy” with data. Suggesting that you use simple metrics instead of complex metrics is nice. But managers are probably comfortable with math enough to understand what is essentially an equation.
Who This Book is For
Avinash’s 10-90% rule says that an analytic budget should spend 10% on the tool, 90 % on the analysis. With 2.0, Avinash has successfully extended this rule, laying out how the 90% is supposed to work.
Business managers with a working knowledge of web analytics will enjoy this book. It also will pique the interest of those new to the subject. Newbies, though, are really better served by a more basic introduction, provided in Avinash’s Web Analytics: An Hour A Day and other books, like Eric Peterson’s Web Analytics Demystified.
One nice point: Like the first book, Avinash donates his book proceeds to charity. You can do good while learning about a business subject growing in importance with every website visit (and these days, with every tweet).