Customer Reviews: Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity
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on October 15, 2009
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.
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on August 19, 2010
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!
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on May 6, 2011
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.
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on September 21, 2010
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 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 views a camera and then the store locator. It is very possible that the customer viewing the camera at may also go to 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
Very Satisfied= .5
Extremely Satisfied= 1

With these weights the scale is also -100 to 100.
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on October 30, 2009
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.
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on April 16, 2010
Web Analytics 2.0 is not a sequel to Kaushik's first book Web Analytics: An Hour a Day.
The latter was a hard core offering that covered all aspects of the subject.
2.0 is a more general book that covers a wide range of topics related to and around Web Analytics.
The coverage of Social Media and Mobile analytics is sparse and that's my only gripe. Considering that both topics are quite hot and that Social Media has gained maturity it would have been helpful to have both these covered in depth. That said the book is pretty robust in its coverage of a wide mix of topics. The list of tools mentioned is also quite exhaustive.

Key Takeaways
· Paid Web Analytics providers are better than the free ones if you need advanced reporting. The other reason is that the paid tools integrate well with other allied offerings/tools. (A project that I'm working on validates both these points)
· Data needs to be actionable. No point collecting old data if the business cannot use it
· Keep an eye on the competition using Google Insights For Search(contains search keyword data on[...] only), Google Trends (contains broad web usage data), Compete, Hitwise. Also check Google Ad Planner and Quantacast since both use self reported data. Most analytics tools now allow you to benchmark against specific verticals.
· Use tools like page level/site level surveys to gather user feedback(kampyle, uservoice, opinionlab). The Voice of the Consumer is necessary to fill in the gaps
Now if only we could get key sales and marketing folks to read this book and understand how much data is there for them to use

Web Analytics: Omniture, WebTrends, CoreMetrics, Google Analytics
Mobile Analytics: Bango Analytics, [...], [...]
Experimentation and Testing: Google Optmizer, Omniture Test and Target, Optimost, Sitespect
Voice of the Customer: 4Q, iPerceptions, ForeseeResults, Ethnio
Competitive Intelligence: Google Insights For Search, Google Trends, Compete, Hitwise, Technorati, Google Ad Planner, Quantacast
Analytics Tags Audit: SiteAudit(ObservePoint)
SEO gaps, Web Application Performance Management, more : Maxamine, Coradiant
Page level/site level surveys to gather user feedback: Kampyle, Uservoice, Opinionlab
Usability: Ethnio, Usertesting
Analyze Actual Online Experiences: Tealeaf, Clicktale
Information Architecture: OptimalSort, [...]
Visual heat maps:, Crazyegg
Keyword Analysis: Google Adwords Tool, Wordtracker, KeywordSpy
Onsite Behavior Targeting Platforms: Audience Science, kefta, Netmining, BTBuckets(free)
Paid Search Tools: Marinsoftware, Kenshoo, ClickEquations

For this and other Web Marketing articles, my blog: [...]
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on August 18, 2011
This is the 2nd book on the topic of Analytics that I've read, the first being Sams Teach Yourself Google Analytics in 10 Minutes. 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.

What you don't measure you can't improve and what you choose to measure and what you do about it defines what you and your organization are about. Metrics should be simple, relevant, focussed and timely. A very useful tool for segmenting your users is the creative use of "tagging" - that is giving a user a cookie that identifies either what group(s) she belongs to, or key pages that she has been to.

Kaushik summarizes the strengths and weakness of a number of third party tools such as ClickStream, Mazamine and CoRadiant and what they can measure. Its also useful to know what can't be tracked, at least not yet, but the book only hints here. Rich media such as Flash can be internally instrumented, but not retroactively if you don't have the source code. Chapter 9 gives some hypothetical tracking information for video - if YouTube were to retrofit playing information such as it would be a goldmine for users to get feed back on start, and stop, replayed sections and dropout points.

Another important aspect of the book is it's discussion of Competitive Intelligence. Services such as google trends and google insight can show you where your traffice is coming from in the world, and can drill down the numbers of people visitting your site and that of your competitors. This can be segmented by geographic regions and trended over time. You can use this not only to see who your competitors are, but where their traffic is coming from, thus giving you a picture of who else competes with your competition and where their strengths are.

The book concludes with a disucssion of how to target oneself for a Web Analytics career.

Highly recommended for business and technical professionals and those who rely on the web to push their message and is interested in improving the effectiveness of their reach. I found the book informative yet also frightening. Kaushik complains that Analytics generates a lot of data and most of it is not very good. The notion of a user session and a page view varies greatly and there is no way to tell without the inconvenience of a login whether a user looking at your web site from home, his mobile and then their office. There is no way to tell if this is 1 user or 3. In the author's view being able to identify the user rather than just the session would result in improved analytics. With services such as Facebook and Google+ it becomes possible to assign each user a unique identity and track their digital footprint, no matter how they access your site. There are huge implications here for the preservation of privacy and anonymity and its extremely likely that there will be strong social pressures to deny services to prevent people from opt out. Kaushik doesn't engage in that discussion - it would have been interesting if he had.
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on December 7, 2015
What a fun to read author! This is one book I actually looked forward to reading, not only for how absolutely informative it was, but for the author's fun sense of humor. Kaushik is a foremost authority on all things "web metrics" and has a great blog as well as being a great author. I can't imagine anyone being disappointed with this book as far as wanting to learn the basics (or remembering what is important, for those already experienced). For beginners, Kaushik covers the most important things to focus on early, so you don't get overwhelmed. He then provides the extras that are good to incorporate once you get comfortable with the beginning stuff. For experienced users, Kaushik reminds you of how going back to the basics and getting out of the weeds will improve your results, and again, provides the advanced concepts as well. This book was easy to understand for me, as a beginner and had lots of great examples.
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on November 10, 2009
This book is like dark chocolate covered pretzels on top of walnut ice cream- blissful & enlightening... Whether you're a seasoned analytics practitioner or a newbie, you'll find Web Analytics 2.0 engaging and informative. Avinash breaks down hard-to-grasp concepts into digestible nuggets by pulling in relevant examples and using real analytics tools to illustrate each point. If you're in the process of vendor selection, chapter two will be your guiding light. If you're re-visiting your initial implementation, or are still trying to figure out how to use the tool you implemented, look no further. This book will help you figure out what you're looking at, isolate actionable metrics, and tell a story with the data that will drive your online and offline strategies. It doesn't hurt that Avinash is hilarious and paints a colorful picture with every insightful anecdote. Who knew web analytics could be this simple?
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on October 28, 2010
I have to say that what I liked least in the book is Avinash's humour ;)
Besides being a great analist and blogger, avinash is a great marketer. He has built a powerful marketing platform rotating around his blog, twitter account, books and his start up company: a masterpiece.
If you are looking for good advice, understandable concepts, tricks and best practices, in depth analysis just as quick glances at new evolutions, innovative metrics and curiosities, he is the best.
If you are looking for good jokes then look somewhere else :)
I have rarely been so impressed by a book, or blog, although editing and proof reading are a little scarce.
I just don't like the "reporting squirrel" analogy, or the "analist ninja", which sound to me as flattering or engaging -marketing?- devices to us, the audience.
Sometimes the author likes himself too much, and being a European with some inborn sense of guilt, I tend to perceive it as a defect.
However, his work is outstanding. Simply outstanding.
If you read him you will improve your skills and productivity, no doubts.
I want also to thank him because he shares his knowledge with the "reporting squirrels" for free through his blog (why did Avinash have to coin that metaphor? I really can't take it of looking myelf in the mirror and thinking of myself as a squirrel!). Given the value of what he shares, you could not take it for granted. He is doing a service to all of us!
Not all marketers are evil, I'll try and learn the example.
Thanks for the book, it has taught me more about Web 2.0 than I would ever expect!
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