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| | Description | Adeptly address today’s business challenges with this powerful new book from web analytics thought leader Avinash Kaushik. Web Analytics 2.0 presents a new framework that will permanently change how you think about analytics. It provides specific recommendations for creating an actionable strategy, applying analytical techniques correctly, solving challenges such as measuring social media and multichannel campaigns, achieving optimal success by leveraging experimentation, and employing tactics for truly listening to your customers. The book will help your organization become more data driven while you become a super analysis ninja!Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file. | |
| | Product Details | | Author: | Avinash Kaushik | | Paperback: | 475 pages | | Publisher: | Sybex | | Publication Date: | October 26, 2009 | | Language: | English | | ISBN: | 0470529393 | | Product Length: | 9.22 inches | | Product Width: | 7.32 inches | | Product Height: | 1.13 inches | | Product Weight: | 1.66 pounds | | Package Length: | 9.0 inches | | Package Width: | 7.3 inches | | Package Height: | 1.3 inches | | Package Weight: | 1.65 pounds | | Average Customer Rating: |  based on 72 reviews |
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| | Customer Reviews | Average Customer Review: ( 72 customer reviews )
Write an online review and share your thoughts with other customers.
Most Helpful Customer Reviews
36 of 37 found the following review helpful:
Must buy for anyone looking to grow and succeed in the Internet Oct 15, 2009
By Daniel Waisberg
As with most books, I started by taking a look at a few sample pages of the book before getting deep into it. My first data point was page 248: where Avinash describes elegantly a case study on measuring offline applications using Google Analytics. Exquisite. Than, on page 279 he shows how to analyze video influence on revenues. Amazing.
After leafing through the book for a while I went back to the beginning and I really enjoyed the way Avinahs Kaushik links the content; bringing basic and important concepts and very advanced techniques side by side. The book has a friendly tone, i.e., it feels like walking down the street and talking to a friend. Avinash knows when to soothe the reader and let him know that this might be frustrating or difficult, he does not pretend to give all the answers.
A central theme on Avinash philosophy also in his previous book (Web Analytics: An Hour a Day) is that people will bring change, not tools. So, even though he proposes several techniques for choosing vendors, he puts in in its place: if you don't have people, you better look for them, no tool will help you. For every $100 you have, you should invest $90 on people and $10 on tools.
This book describes a holistic approach of the Web Analytics field which he defines as "the analysis of qualitative and quantitative data from your website and the competition, to drive a continual improvement of the online experience that your customers, and potential customers have, which translates into your desired outcomes (online and offline)."
The book treats all the aspects that need to be understood in order to have a successful web strategy: clickstream data, testing, Voice of Customer, social, mobile, video, you name it. In addition, you will learn about planning and growing a web analytics career, so if you are serious about your career, this book is for you.
Concluding, 'Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity' is a landmark on the Web Analytics field and a must buy for anyone looking to grow and succeed in the Internet.
14 of 14 found the following review helpful:
Fantastic book for leveraging the power of analytics Oct 30, 2009
By Christopher Smith
If you manage a website, run your own online business, or handle the Internet marketing for your business, you really need this book. You might be spending oodles of money on pay per click ads or hiring firms to redesign a site or manage your campaigns - but you'll want Web Analytics 2.0 to provide you with the foundation you need to make intelligent decisions, to ask the right questions, and make sure you're taking advantage of every ounce of data you can collect about your site visitors. As the book tells you early on, you'll want to align your site to increase your revenue, reduce your costs, or improve customer loyalty and satisfaction.
One of the best things of this book is that it helps to clarify the heaps of data and reporting you can get from the many available analytics tools. What data should you look at? What are actionable outcomes you want to measure? What are some ways to measure success of your site?
I'd go so far as to say that every site designer should read this book - not just analytics or marketing pros. This is because it has some great sections about how you should be testing the impact of site designs and changes. The book also includes a CD and one of the items is a usability checklist that every designer should have. And if you're interested in a career in analytics, there's even a chapter at the end dedicated to this - I'm happy in my job, so I didn't read this section, but he closes out with some ideas and advice on how to find the right people for analytics jobs you may need to fill.
It's difficult to make a book about data interesting - but Avinash Kaushik has definitely done so with this book. I've already given a copy of this book to a colleague knowing that he'll find it valuable.
12 of 12 found the following review helpful:
Beware - the Kindle version has no link to content on the CD Aug 19, 2010
By Allison Hartsoe
"a8llison"
I own both the Kindle version and the paperback version of this book. I originally bought the Kindle copy thinking there would be some referece to the CD in the back of the book - a handy place where Kindle readers could download or otherwise access the content on the CD. Not so! The publishers decided not to make this available so the ONLY way to get CD content is by purchasing the book.
That said, a web analytics book like this is really a reference book. I personally find it a lot easier to flip the pages and find what I'm looking for. And while the author does do a good job of starting at the novice or "reporting squirrel" level and leading the reader up to the expert or "ninja" level, this is not a work of fiction. You really don't need to read it start to finish in order.
The content, as others have said, is engaging and highly readable. Even if you have been practicing in this space for awhile, you will still learn much from this book. If you are new to the space, then this book is a requirement!
14 of 16 found the following review helpful:
 Some Problems... Sep 21, 2010
By eugenebinx
"eugenebinx"
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 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. You have to know how much was spent, and you have to know how much incremental revenue came in from SEO/PPC efforts. It is not an easy task. Test and control or some other method should have been addressed. In calculating ROI for PPC in chapter 11, he assumes that all visits from PPC are ones you would not have without the ad. Not necessarily true.
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: turning it off in some regions and have it on in others? This method would allow you to compare the on and off markets and find incremental sales.
In the marginal attribution model from page 368, 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 375 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 377, the Author says: "The analyst at Walmart.com can use the previous URL to track how many people use the website and then visit the store." A view the store locator on the web does NOT equal a visit to your store. In his example, a user on walmart.com views a camera and then the store locator. It is very possible that the customer viewing the camera at walmart.com may also go to target.com and find the same camera at a similar price and find that the target store was much more convenient to visit. 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 419, the author says this method is preferred because it has a scale of 0 to 100. It actually has a scale of -100 to 100.
If 5 responders all gave a Not Satisfied or a Not At All Satisfied, the score would be [(0+))-(5):]/5*100=-100. The other method, weighted means can also give a scale of -100 to 100 if the right weights are used.
Not Satisfied At all:=-1
Not Satisfied =-.5
Satisfied=0
Very Satisfied= .5
Extremely Satisfied= 1
With these weights the scale is also -100 to 100.
13 of 16 found the following review helpful:
 Introduces analytical techniques ... missing from Web Analytics: An Hour a Day May 06, 2011
By Tim Dire
"Chelsea Shedboy"
To Kaushik's credit he ventures into true analysis that was missing in `Web Analytics: An Hour a Day'. Early in chapter 3 he writes that "when people say "web analytics", they really mean web metrics". Kaushik was aware of the need, and has done a solid job of addressing the earlier analytical shortcomings. Some of the methodologies may not be mega-profound, but enough is done to whet the reader's whistle as to the possibilities.
On the downside Kaushik's writing is irritating. He is very repetitive. For example, he overly evangelizes the need for context. While I fully concur with him on this need, how many times does he have to tell me?!?! In general his writing style is higgledy-piggledy. If he had an editor, his editor let him down. The book is a good 100 pages longer than it need have been. I saw the same not-getting-to-the-point in the one video presentation of his I watched.
I was somewhat perplexed by Kaushik's Analytic Ninja. The analogy is inappropriate. I have always pictured ninjas as working surreptitiously, while the need is for the web analyst to become a visible and integral part of strategy development.
See all 72 customer reviews on Amazon.com
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