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Osip Aksenov
Osip Aksenov

Web Analytics 2.0



The presentation covered the back story about my book, Web Analytics: An Hour A Day, the back story about why traditional web analytics finds itself in a pickle and presented my vision, definition and outline of Web Analytics 2.0.




Web Analytics 2.0


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Each circle representing a key component of what your web analytics strategy should be, regardless of what your size is. Each circle also approximately represents the amount of data that you'll have access to as you try to find insights / correlations.


There are lots of web analytics and online marketing blogs and your's truly falls into the "crazy ones, misfits, troubles makers, round pegs in square holes and no respect for status quo" bucket. I have been reading your blog for a long time now, this is by far my favourite post.


Hi, Definitely there is a need for the analysts to think differently and focus on the core derivatives of the analytics. Every analyst should have a vision on how to leverage the best insights to be kept in to practice. Also I feel that there is going to be a lot of change in the way the world is viewing analytics today.


If nothing else then "up-versioning" is my attempt put to rest the mindset that web analytics has taken on since its inception and move us forward to think differently (and based on your comment it is moving everyone back to what it was supposed to be in the first place! :)).


I like your approach, as you know Logan Tod & Co have been using a similar approach for a number of years, but this is all about people. I don't need to convince you of this though. This post should be the 'Why Web Analytics should be put to sleep" or something similar. What you are defining so eloquently is Digital Customer Insight 1.0, a new more rounded methodology. Yes, web analytics forms part of the process but this is so big it deserves a rebrand. I have ribbed Jim Sterne in the past that the WAA should have had a different name!


I have to admit I had visions of torching the name web analytics (for reasons you mention and others that I have thought of as well). But in the end after battling with my own demons my decision was to keep the term web analytics but to expand the definition.


It took me a few days to grab the hour to listen to this, but it was an hour well spent. I love your enthusiasm (especially about a subject as frequently dry as people make analytics), and I absolutely agree about taking an outcomes-based approach.


Too many times (and you get into this at the end a bit), I've seen marketing people and executives use analytics and mine data, creating an ever growing mountain of numbers, and hoping that the answers will magically pop to the top of that mountain. It just doesn't happen. You have to ask the right questions and then build the architecture to answer those questions.


I am working as SEO-SEM proj manager ans I have watched your video which has impressed me a lot. I would like to know more about your book web analytics 2.0. Could you please let me know from where I can get this book.


This is not saying that you did it badly or didn't add value, you did it quite well. It was just that it was nothing substantially new to me, other than the website orientation. It made me think about web analytics in a different way. :-)


Fortunately, the majority of us stopped relying on the web analytics 1.0 framework a long time ago and have started computing the impact of our marketing campaigns like SEO and PPC on our sales, leads, and other business goals.


What do companies practicing next-generation Web analytics, a mere 5 percent of enterprise-size organizations, have in common? Some top traits of our most successful clients in terms of understanding their customers and prospects:


Web analytics is the assessment of a variety of data, including Web traffic, Web-based transactions, Web server performance, usability studies, user submitted information and related sources to help create a generalized understanding of the visitor experience online.


Many software vendors would have you believe that the Website Optimization Ecosystem and Web analytics applications are one and the same. These same vendors would have you believe that all that can be known about Web visitors can be gleaned through their data collection strategy and reporting interface. While Web analytics tools are certainly very powerful, understanding visitor behavior is as much a function of qualitatively determining interests and intent as it is quantifying clicks from page to page.


Yet Customer Experience Management and Voice of Customer applications on their own are no more likely to provide a complete view of visitor behavior than Web analytics applications. Each application plays a valuable role in the Website Optimization Ecosystem, and smart business owners have already learned how to take advantage of each in an ongoing effort to optimize the online channel and maximize profits while simultaneously minimizing costs. The real challenge facing online business is not recognizing that each of these systems exists; the challenge is understanding the true capabilities each system provides and where the three systems converge to create a more accurate view of visitor and customer behavior.


Especially when working to create convergent validity using the multiple systems described in this article, the need for solid process becomes critical. Given the complexity associated with integrating Web analytics, Customer Experience Management and Voice of Customer data, leveraging the combined data effectively often requires careful analysis supported by robust processes for data gathering and validation. And given the depth of analysis required to fully benefit from ecosystem technologies used in tandem, it is critical that organizations have clear processes to take advantage of analysis output.


Avinash Kaushik is the author of the leading research & analytics blog Occam's Razor. He is also the Analytics Evangelist for Google and the Chief Education Officer at Market Motive, Inc. He is a bestselling author and a frequent speaker at key industry conferences around the globe and at leading American universities. He was the recipient of the 2009 Statistical Advocate of the Year award from the American Statistical Association. The author donates all proceeds from his books to two charities, The Smile Train and The Ekal Vidyalaya Foundation. Permissions Request permission to reuse content from this site


MarketShare CEO Wes Nichols explains how many big companies are now deploying analytics 2.0, a set of capabilities that can chew through terabytes of data and hundreds of variables in real time to accurately reveal how advertising touch points interact dynamically. The results: 10% to 30% improvements in marketing performance.


The company ultimately decided to retool its marketing analytics by applying the attribution, optimization, and allocation framework to its entire game portfolio. EA had been measuring advertising performance using traditional methods such as customer surveys and media-mix models, and it had been attributing year-to-year and title-to-title variations in sales to creativity in advertising and game quality.


Marketers are also using analytics 2.0 to run what-if scenarios for advertising new-product launches, ad buys in markets where data are limited, and the potential effects of surprise moves by competitors. For instance, as a global consumer electronics company client of ours was preparing to launch a game-changing product in an emerging market where historical sales-marketing data were scarce, it used advanced analytics to review advertising behavior by competitors and accurately predict their spending for upcoming releases. Using those predictions and optimization scenarios, the company successfully entered the market with a much clearer understanding of the strategic landscape and adjusted its plans quickly to address new competitive dynamics.


Analytics, once a back-of-the-house research function, is becoming entwined in daily strategy development and operations. Executives who were pioneering early digital marketing teams 10 years ago are advancing to the CMO office. Already wired for measurement, they are often amazed at the analytics immaturity of the broader advertising industry. These new CMOs are taking more responsibility for technology budgets and are creating a culture of fact-based decision making within advertising. Technology consultancy Gartner estimates that within five years, most CMOs will have a bigger technology budget than chief technology officers do.


Second, assign an analytics-minded director or manager to become the point person for the effort. It should be someone with strong analytical skills and a reputation for objectivity. This person can report to the CMO or sit on a cross-functional team between marketing and finance. As the project expands, he or she can help guide business planning and resource allocation across units.


Third, armed with a prioritized list of questions you seek to answer, conduct an inventory of data throughout the organization. Intelligence that is essential to successful analytics 2.0 efforts is often buried in many functions beyond marketing, from finance to customer service. Identify and consolidate those disparate data sets and create systems for ongoing collection. Treat the data as you would intellectual property, given its asset value.


You can load a buffered version of analytics.js that requires you call load explicitly to before analytics.js initiates any network activity. This is useful if you want to, for example, wait for user consent before you fetch tracking destinations or send buffered events to Segment.


When you develop against Analytics 2.0, the plugins you write can augment functionality, enrich data, and control the flow and delivery of events. From modifying event payloads to changing analytics functionality, plugins help to speed up the process of getting things done.


The snippet asynchronously requests and loads a customized JavaScript bundle (analytics.min.js), which contains the code and settings needed to load your device-mode destinations. The size of this file changes depending on the number of and which destinations you enable. 041b061a72


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