For years it has been clear that web analytics holds the promise to truly revolutionize how business is done on the Web. And why not? You can track every click of every person on your site. How can that not be actionable? Unfortunately, the revolution has not quite panned out. The root cause is that analysts and marketers have taken a very limited view of data on the Web and have restricted it just to clickstream data. In what follows, I make the case for why you need to drastically rethink what it means to use data on the Web. The Web Analytics 2.0 strategy adapts to the evolution of the Web and dramatically expands the types of data available to help you achieve your strategic business objectives.

Let’s start with a tale about the paradox of data. Professionally speaking, I grew up in the world of data warehousing and business intelligence (BI). I worked with massive amounts of enterprise data; multiterabytes; and sophisticated extract, transform, and load (ETL) middle layers—all fronted by complex business intelligence tools from companies such as MicroStrategy, Business Objects, and SAS. Although the whole operation was quite sophisticated and cool, the data set wasn’t really that complex. Sure, we stored customer names and addresses, products purchased, and calls made, along with company metadata and prices. But not much data was involved. As a result, we made lots of great decisions for the company as we valiantly went to battle for insights.

But the lack of breadth and depth of data meant that often, and I say this only partly in jest, we could blame incompetence on the lack of sufficient types of data. So, we always had a get-out-of-jail-free card, something like, “Gosh darn it. If I knew our customers’ underwear sizes, I could correlate that to their magazine subscriptions, and then we would know how to better sell them lightweight laptops.”

I know, it sounds preposterous. But it really isn’t.

With that context, you’ll appreciate why I was ecstatic about the world of web analytics. Data, glorious data all around! Depth and breadth and length. Consider this: Yahoo! Web Analytics is a 100 percent free tool. It has approximately 110 standard reports, each with anywhere from 3 to 6 metrics each. That number of 110 excludes the ability to create custom reports covering even more metrics than God really intended humanity to have.

But after a few weeks in this world, I was shocked that even with all this data I was no closer to identifying actionable insights about how to improve our website or connect with our customers.

That’s the paradox of data: a lack of it means you cannot make complete decisions, but even with a lot of data, you still get an infinitesimally small number of insights.

For the Web, the paradox of data is a lesson in humility: yes, there is a lot of data, but there are fundamental barriers to making intelligent decisions. The realization felt like such a letdown, especially for someone who had spent the prior seven years on the quest for more data.

But that’s what my book, Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity, is about: shedding old mental models and thinking differently about making decisions on the Web, realizing data is not the problem and that people might be, and focusing less on accuracy and more on precision. We will internalize the idea that the Web is an exquisitely unique animal, like nothing else out there at the moment, and it requires its own exquisitely unique approach to decision making.

That’s Web Analytics 2.0.

Before we go any further, let’s first reflect on where we are as an industry today.

As I reflect upon where we are today, I see a lot that has not changed from the very early days of web analytics—all of about 15 years ago. The landscape is dominated by tools that primarily use data collected by web logs or JavaScript tags. Most companies use tools from Google Analytics, Omniture Site Catalyst, Webtrends, Clicktracks, or Xiti to understand what’s happening on their websites.

However, one of the biggest changes in recent years was the introduction of a free robust web analytics tool, Google Analytics. Web analytics had been mostly the purview of the rich (translation: big companies that could afford to pay). Sure, a few free web log–based solutions existed, but they were hard to implement and needed a good deal of IT caring and feeding, presenting a high barrier to entry for most businesses.

Google Analytics’ biggest impact was to create a massive data democracy. Anyone could quickly add a few lines of JavaScript code to the footer file on their website and possess an easy-to-use reporting tool. The number of people focusing on web analytics in the world went from a few thousand to hundreds of thousands very quickly, and it’s still growing.

This process was only accelerated by Yahoo!’s acquisition of IndexTools in mid- 2008. Yahoo! took a commercial enterprise web analytics tool, cleverly rebranded it as Yahoo! Web Analytics, and released it into the wild for free (at this time only to Yahoo! customers).

A search on Google today for free web analytics tools results in 49 million results, a testament to the popularity of all these types of tools. All these free tools have put the squeeze on the commercial web analytics vendors, pushing them to become better and more differentiated. Some have struggled to keep up, a few have gone under, but those that remain today have become more sophisticated or offer a multitude of associative solutions.

Omniture is a good example of a competitive vendor. SiteCatalyst, its flagship web analytics tool, is now just one of its core offerings. Omniture now also provides Test&Target, which is a multivariate testing and behavior targeting solution, and the company entered the search bid management and optimization business with SearchCenter. It also offers website surveys, and it can now power ecommerce services through its acquisition of Mercado. Pretty soon Omniture will be able to wake you up with a gentle tap and help you into your work clothes! As a result of this competitive strategy, Omniture has done very well for itself and its shareholders thus far.

Beyond web analytics, I am personally gratified to see so many other tools that exploit the Trinity strategy of Experience, Behavior, and Outcomes, which I presented in my first book, Web Analytics: An Hour a Day (Sybex, 2007).

We can now move beyond the limits of measuring Outcomes from web analytics tools, or conversions, to measuring more robust Outcomes, say our social media efforts. Obvious examples of this are using FeedBurner to measure Outcomes from blogs and using the diverse ecosystem of tools for Twitter to measure the success of your happy tweeting existence. We are inching—OK, scraping—closer toward the Holy Grail of integrated online and offline Outcomes measurement.

The Behavior element of the strategy has not been neglected either. Inexpensive online tools allow you to do card sorts (an expensive option offline) to get rapid customer input into redesigns on your websites’ information architecture (IA). A huge number of free survey tools are now available; allow me to selfishly highlight 4Q, which is a free on-exit survey from iPerceptions that was based on one of my blog posts (“The Three Greatest Survey Questions Ever”.

Then there is the adorable world of competitive intelligence. It did not have an official place in the Trinity strategy (though it was covered in Web Analytics: An Hour A Day) because of the limited (and expensive) options in the market at that time. We have had a massive explosion in this area in the past two years with tools that can transform your business, such as Compete, Google’s Ad Planner and Insights for Search, Quantcast... and I am just scratching the surface.

Reflecting on the early days of web analytics, I am very excited about the progress the industry has made since the publication of my last book a couple years ago.

I am confident massive glory awaits the marketer, analyst, site owner, or CEO who can harness the power of these free or commercial tools to understand customer experience and competitive opportunities.