What do you think?
Rate this book
Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity
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!
475 pages, Paperback
First published October 1, 2009
298 people are currently reading
2,368 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 30 of 60 reviews
July 8, 2015
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 can honestly say that 95% of what I know now with regards to web analytics has come from this book. 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 anyone who is interested in web analytics.
With good writing, good visuals and easy-to-follow instructions, this is a must-read for anyone who is interested in web analytics.
August 12, 2016
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.
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.
February 28, 2013
Best Book on Web Analytics.. The most comprehensive and the most cited book on Web Analytics. I found this book to be a good companion for my Master Certification in Web Analytics at Market Motive with Avinash Kaushik. 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 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.
February 11, 2010
Avinash knows his stuff, that's for sure. While at times I found myself skimming sections (mainly in the e-commerce section, as I work on content sites) his insights were pretty solid. If you've dabbled in Analytics, especially his favorite from Google, then you probably already know a bit of what he's talking about in this book. Maybe even most of what he's saying. Despite that, Avinash does help focus one's lens on what is important for your business and your analytics. Insistence on core metrics, insights, and learning to take action even if the data is not perfect (it never will be!) were the most important pieces I pulled from this. I read his blog Occam's Razor, which I think is a solid replacement for this book if someone didn't want to dive into this.
August 17, 2018
After Reading This You'll Never Look At A Web Page in the Same Way Again!
This is the 2nd book on the topic of Analytics that I've read, the first being. 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.
This is the 2nd book on the topic of Analytics that I've read, the first being. 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.
August 30, 2016
Interesting read. Becoming somewhat dated but still holds its own. A bit repetitive and all over the place subject-wise, but got a solid intro to all things web analytics.
February 17, 2019
Incredible!
The most enlightening book on web analytics. Even though this book was written a few years ago, the approach still perfectly aligns with today’s marketing landscape
The most enlightening book on web analytics. Even though this book was written a few years ago, the approach still perfectly aligns with today’s marketing landscape
March 1, 2017
Avinash is brilliant. I read it, re-read it, and re-read it to absorb everything that the man has to say.
Implementing just bits of pieces of this book on various online assets worked wonders for me. Segmentation, and sticking to a "critical few" helped me set my priorities right.
Moreover, the book talks in length about things like data reconciliation, defining core matrices, and has wealth of other information that narrows down the focus.
I have highlighted about 100 different things in this book � and I shall keep it handy for reference. Most of the concepts outlined in this book are independent of new and evolving ways to collect data, which truly makes this book a timeless masterpiece.
Implementing just bits of pieces of this book on various online assets worked wonders for me. Segmentation, and sticking to a "critical few" helped me set my priorities right.
Moreover, the book talks in length about things like data reconciliation, defining core matrices, and has wealth of other information that narrows down the focus.
I have highlighted about 100 different things in this book � and I shall keep it handy for reference. Most of the concepts outlined in this book are independent of new and evolving ways to collect data, which truly makes this book a timeless masterpiece.
November 2, 2017
It took me than 1 month to read this book. Every page is filled with tons of knowledge. Though written on web analytics, it is the book which clears the basics of data analytics. After this book, you may experience the change in perspective to view the data & draw insights. I loved this book. You will too.
February 7, 2017
I've always wanted to learn more about web analytics.
But everything I read was either too simple or too advanced: this book was simply great because it explained the ideas behind the strategies, not only a step-by-step approach.
But everything I read was either too simple or too advanced: this book was simply great because it explained the ideas behind the strategies, not only a step-by-step approach.
June 20, 2017
Although published in 2010, this book remains highly relevant for crafting your analytics strategy. What to measure, why to measure it, and how to present it. Recommended for anyone doing web analytics.
November 25, 2017
Wartościowa książka i łatwo przyswajalna wiedza, której jedynym mankamentem jest to, że wraz z upływem lat stopniowo traci swój potencjał z racji przedawnienia się pewnych, zawartych w niej informacji.
August 13, 2017
La biblia de la analÃtica web.
Want to read
December 27, 2017Recommended by my MBA Digital Marketing Professor, Lil Mohan
March 28, 2018
This book will leave nothing out from the world of web analytics. Anyone doing any business that is connected to online (so everyone) should read this book.
January 4, 2019
One of my go-to authors for digital marketing and analytics. Forward thinking and practical.
January 30, 2020
A web analysts bible.. Simple
February 18, 2020
The first half is quite useful to help me understand the performance from data.
June 10, 2022
Some material is pretty dated now, but there still enough practical information to be useful. Generally dry as you would expect from a book like this.
February 21, 2023
If you want to understand web analytics and the important role they play in business, Avinash explains it clearly with examples and proof. His blog, Occam's Razor is a very good resource too.
April 17, 2012
Écrit par AvinashKaushik, l'un des gourous du Web Analytics, « Web Analytics 2.0 » est un excellent livre qui passe en revue les meilleures techniques et méthodes avancées de ce domaine du Web Analytics et de la mesure des performances des sites web.
Il ne s'agit pas d'un guide pour Google Analytics, ni d'un quelconque autre outil d'analyse de trafic, comme il ne s'agit pas non plus d'un guide pour ceux qui font leurs premiers pas avec la mesure et l'analyse des sites web, c'est un livre destiné aux experts du domaine.
Des sujets d'une importance capitale sont traités tout le long du livre. On y trouve des conseils sur le choix de l'outil du Web Analytics adéquat qui répond aux besoins de l'entreprise, les points à vérifier avant de signer avec un éditeur (dans le cas d'un outil payant) ou comment interpréter et prendre des décisions en se basant sur des indicateurs de performance qui varient selon la nature du site web en question.
On y apprend également comment analyser les performances des sites concurrents sans avoir accès à leurs données privées, ou comment analyser l'impact des réseaux sociaux, du mobile, ou de la vidéo sur l'ensemble des performances de l'entreprise. L'auteur explique également comment éviter les pièges cachés du Web Analytics, surtout quand il s'agit de la comparaison entre l'exactitude ou la précision des données collectées.
Le livre est accompagné d'un CD Rom qui contient plusieurs documents, poadcasts et vidéos sur le Web Analytics, ainsi qu'un coupon AdWords de 50 euros.
Il ne s'agit pas d'un guide pour Google Analytics, ni d'un quelconque autre outil d'analyse de trafic, comme il ne s'agit pas non plus d'un guide pour ceux qui font leurs premiers pas avec la mesure et l'analyse des sites web, c'est un livre destiné aux experts du domaine.
Des sujets d'une importance capitale sont traités tout le long du livre. On y trouve des conseils sur le choix de l'outil du Web Analytics adéquat qui répond aux besoins de l'entreprise, les points à vérifier avant de signer avec un éditeur (dans le cas d'un outil payant) ou comment interpréter et prendre des décisions en se basant sur des indicateurs de performance qui varient selon la nature du site web en question.
On y apprend également comment analyser les performances des sites concurrents sans avoir accès à leurs données privées, ou comment analyser l'impact des réseaux sociaux, du mobile, ou de la vidéo sur l'ensemble des performances de l'entreprise. L'auteur explique également comment éviter les pièges cachés du Web Analytics, surtout quand il s'agit de la comparaison entre l'exactitude ou la précision des données collectées.
Le livre est accompagné d'un CD Rom qui contient plusieurs documents, poadcasts et vidéos sur le Web Analytics, ainsi qu'un coupon AdWords de 50 euros.
May 4, 2014
A must-read for anyone in the digital marketing field! This book taught me a lot as I am new to the field so my review is based on being an amateur.
This book lays the foundation of understanding the prospect of customers and e-commerce not only on the web but also on mobile, social and offline. Avinash has an interesting way of making you understand what is analytics and what techniques and steps that you should take in order to become an analytics ninja. You don't need to be technically sound to understand the concepts in the book, but little knowledge of web2.0 helps.
The book helps people both on the technical and business side whether you run an e-commerce site or a blog. For technicals, the book discusses how several free and premium tools can be used to analyze data and customer behavior. For business, it offers the metrics and KPIs that companies can use to measure their performance assessing conversions and see real ROI. The book discusses strategic level approaches as well as operational steps and procedures to deal with data.
Highly-recommended.
This book lays the foundation of understanding the prospect of customers and e-commerce not only on the web but also on mobile, social and offline. Avinash has an interesting way of making you understand what is analytics and what techniques and steps that you should take in order to become an analytics ninja. You don't need to be technically sound to understand the concepts in the book, but little knowledge of web2.0 helps.
The book helps people both on the technical and business side whether you run an e-commerce site or a blog. For technicals, the book discusses how several free and premium tools can be used to analyze data and customer behavior. For business, it offers the metrics and KPIs that companies can use to measure their performance assessing conversions and see real ROI. The book discusses strategic level approaches as well as operational steps and procedures to deal with data.
Highly-recommended.
December 19, 2016
I like it.
September 9, 2011
Whether you're new to web analytics or you've been in the industry for some time but are looking to expand your horizons, you can't go wrong with this book. This book starts by educating people on how the old ways of assessing success on the web are inadequate and dives right in to how you can quickly obtain actionable insights with some web analysis. Later on, it touches on emerging concepts form which even some seasoned analysts will benefit, such as assessing your competition, attributing success to multi-touch campaigns, and accessing your social media success by tying it to more than just for number of followers.
May 5, 2014
A solid introductory text to website analytics. A good blend of theory with tactics over a wide range of example websites and scenarios. I already knew the basics of web analytics and still walked away with some good nuggets. My only major issue with the book was the mobile chapter was weak which may have been partially due to the lack of sophisticated tools at the time writing. Unfortunately the whole chapter seemed rushed and crammed in to seem relevant. That said, even mobile PMs can apply a fair amount of the theory to understand what to track as well as use the web tactics on their landing pages.
April 7, 2010
I can't say I ever would have expected (or believe possible) that I would read a book with a title like this and be glued to it. Nor would I expect to have found it to be one of the best books of the year.
But that is exactly what happened on both counts.
Now, it so happens that the agency I'm at is struggling to fill a measurement gap in our offering. So take my recommendation with a small grain of salt.
But I can say without question that you can hand this book to someone at just about any level (novice to analytics ninja) and they will find something of value in it.
But that is exactly what happened on both counts.
Now, it so happens that the agency I'm at is struggling to fill a measurement gap in our offering. So take my recommendation with a small grain of salt.
But I can say without question that you can hand this book to someone at just about any level (novice to analytics ninja) and they will find something of value in it.
February 27, 2014
To be up front, I didn't read this entire book. I was going to, but it was too technical. I had purchased it to learn Google Analytics on my own, but I ended up reading it as part of an analytics MOOC. The class coupled parts of this book with materials from Google's how-to guides on their website. I found the Google materials and other articles to be more helpful overall. I was coming to GA as a communications person looking for insights, not as a programmer / developer looking to implement the system on our website.
March 25, 2015
This book is an essential to any social media marketer's library. Not only will it help you discover which metrics matter to your executives (the HiPPOs), it will help you decide which ones may or may not work for your company. This is more of a textbook-style type of book, so it's better to refer to it as needed than consuming it from beginning to end as you would a novel. It's great for reference and to search topics as you go along in your career. It gives an excellent framework to apply to all web initiatives to accurately measure its value to the company.
March 1, 2021
I quit halfway, even though I was really looking forward to reading this. Such a shame. This may be good for a beginner, but for someone who is looking for in-depth analytics and exclusive experience insights, this is not it. The book (or as much as I've read) is filled with basic information you can easily find in Google documents, combined with a gigantic self-pat every now and then, topped with a bad attempt at being witty.
And someone get this guy laid, the word "sex" appears way too many times in a book about web analytics.
And someone get this guy laid, the word "sex" appears way too many times in a book about web analytics.
January 27, 2010
I read this for work and at over 400 pages it's not a page turner by any means, but was surprisingly engaging and easy to read considering it's a book about web analytics. I haven't read Kaushik's previous book so I have nothing to compare this to but I found Web Analytics 2.0 to provide a solid overview of analytics for the novice and was full of insights that I will come back to again.
Displaying 1 - 30 of 60 reviews
Can't find what you're looking for?
Get help and learn more about the design.