Web Analytics The Art of Online Accountability and Science of Customer Centricity. Avinash Kaushik. ISBN: Oct pages.
Table of contents
- Description
- Web Analytics 2.0: The Art of Online Accountability & Science of Customer Centricity [With CDROM]
- Web Analytics : Avinash Kaushik :
Metrics 35 Standard Metrics Revisited: What, Why, and How Much? Remote and Online Outsourced Surveys: Step Up Your Analytics Game!
Description
Challenges Path to Nirvana: Chapter Page Details Date Print Run Short urls in the 1st printing no longer redirect to the correct web pages The author used a website called sn. That site is now defunct and so those urls do not redirect properly as printed in the book. The short urls are now being handled through another domain, called "zqi. To go to any of the webpages, you need to replace the domain in the url, "sn.
The shortcut portion of the short urls remains unchanged. It will provide a holistic view of what it takes to make good decisions and exactly how to go about doing that. Web analytics practitioners continue to have a tremendous interest only increased by the current economic condition in being more data-driven. At the same time, the web continues to evolve in significant ways video, blogs, flash, social media, etc.
Furthermore it will be agnostic in terms of tools, which will make it a must-read for online marketers of all hues, web analysts, web designers and architects, and online executives at all levels of the organization interested in successfully collecting, analyzing, and acting upon web analytics data. In true Web 2. Why did the last two clients you lost cancel their contracts? Leveraging Industry Benchmarks and Competitive Data.
Measuring Latent Conversions and Visitor Behavior. The book will help your organization become more data driven while you become a super analysis ninja Note: Paperback , pages. To see what your friends thought of this book, please sign up. To ask other readers questions about Web Analytics 2. Hi, it looks like there are a few editions of the 2. Is the 2nd edition any different than the 1st edition ?
Before reading this book is previous book by the author, Web Analytics: An Hour a Day advised? Are the topics covered in both books are different? See 2 questions about Web Analytics 2. Lists with This Book. Mar 30, Alvaro Berrios rated it it was amazing. This book essentially taught me that everything I thought I knew about web analytics was either wrong, incomplete or skewed and really shed new light on me on how to analyze web data. I love Avniash's focus on actionable insights and he explains everything in a way that makes it easy for you to implement. With good writing, good visuals and easy-to-follow instructions, this is a must-read for an This book essentially taught me that everything I thought I knew about web analytics was either wrong, incomplete or skewed and really shed new light on me on how to analyze web data.
With good writing, good visuals and easy-to-follow instructions, this is a must-read for anyone who is interested in web analytics.
Jul 15, Liz rated it really liked it Shelves: Lots of good information, but there are no descriptions for any software or how to get the reports seen in the book. I am trying to recreate these reports using Google Analytics, Coremetrics and Omniture. It seems that most of the reports are the standard reports out of Google Analytics, but I am having a difficult time recreating some of these with other software.
I think this was a great book, but I have a few things I disagree with: Page 85, he says if he could only have one report, it would be Lots of good information, but there are no descriptions for any software or how to get the reports seen in the book. Page 85, he says if he could only have one report, it would be Outcomes by All Traffic Sources. This report shows Goal Conversion Rates, but he does not describe what these are.
In Google Analytics, these are custom, so this could be anything. I am disappointed, he does say it is important to measure ROI, but does not talk about how to do this. The author says that you can do this by comparing the data from Google to your campaign data.
It is not that easy. It is not an easy task. Test and control or some other method should have been addressed. In Chapter 7, testing is finally addressed. I disagree with his method of testing the impact of PPC by turning it off and on completely; this does not take into account any seasonality that may occur naturally in web traffic.
This is also a problem if there is a lot of variation in web visits and sales over time. Why not try test and control markets: This method would allow you to compare the on and off markets and find incremental sales. In the marginal attribution model from page , you change the spending for one type of online marketing, then attribute any sales higher than last month sales to the additional marketing. In my experience, web sales tend to have a large variation in sales from month to month making it difficult to say what the cause of any increase is without any kind of confidence bounds.
The "controlled experiment" on page is a really bad example. The ad is run at the same time in all markets and then compared to pre and post ad time periods. What if at the same time as the ad, some celebrity tweeted that they loved your product or some news program aired a warning about your product. There are too many uncontrollable situations to compare pre and post ad sales. You should have test and control markets to compare sales in the same time period.
On page , the Author says: In his example, a user on walmart. It is very possible that the customer viewing the camera at walmart.
Web Analytics 2.0: The Art of Online Accountability & Science of Customer Centricity [With CDROM]
There is no way in this case to tie a store locator and product page view to an offline purchase. Using a discount code or unique offer would provide a better method of tracking online to offline behavior. In Chapter 14, the BMI is introduced. But on page , the author says this method is preferred because it has a scale of 0 to It actually has a scale of to The other method, weighted means can also give a scale of to if the right weights are used.
Not Satisfied At all: Feb 28, Brijesh Bolar rated it really liked it Shelves: Best Book on Web Analytics..
Web Analytics : Avinash Kaushik :
The most comprehensive and the most cited book on Web Analytics. This book has everything that is there in his blog Occam's Razor but the book is more organized and structured for anyone new to Web Analytics to get a feel of the responsibility involved.
What is not covered in the book is Avinash's framework on measuring the performance of your Best Book on Web Analytics.. What is not covered in the book is Avinash's framework on measuring the performance of your analytics efforts on a website. You would learn about this framework and get the most out of this book when you attend his online course on web analytic at Market Motive. Aug 17, Phoenix rated it it was amazing Shelves: The first gave me a technical understanding of how web site information was collected and an overview of the kinds of reports that can be generated.
Kaushik's book complemented this by looking at a much broader range of tools and by performing and in depth discussion of which metrics are important and which are not. The most useful aspect of the book consists of the strategies Kaushik recommends for promoting Analytics into different styles of organizations including individual bloggers, non-profits, market driven corporations from small to large and organizations where web site success is measured information.
If you're a seasoned business analyst this is simple good old fashioned change management. If not, it's simply good advice. Kaushik is exhuberantly evangelical about his subject and its easy to get caught up in his enthusiasms. Realize that that adopting new technology is an evolving process - buying into overly sophisticated tools too early may lead to a failed implementation. And free tools are not actually free if you factor in the total cost of ownership which should include the cost of your own time and that of your colleagues. One of the interesting exercises that Kaushik goes through using Analytics is one which justifies the time spent on his own blog to his wife in terms of income generated.
Know your organization and be realistic about its ability to absorb and implement change. Media guru Marshal McLuhan once observed that the "content of media is the audience" which is delivered to the advertisers. To be cynical the Analytics vendors are in the business of selling you information that you and your clients voluntarily give them, but repackaged.
Kaushik gives 4 basic kinds of advice. The first is to segment the audience into smaller tiers in order to obtain an insight into their behaviour. The second is to limit one's metrics to those that will most likely be useful. Thirdly, create actionables based on these metrics, not just be happy or sad with a bunch of pretty pictures.
An actionable might be a redesign of web pages resulting improvement in goal completion or market penetration on your site, or it may be better utilization of information gathered. And the 4th piece of advice is to follow up any change with validation to confirm that the changes actually worked.