Web Analytics 2.0: A New Measurement Strategy For Marketing 2.0

In 2004, when I wrote my first book, Web Analytics Demystified: a Marketer’s Guide to Understanding How Your Web Site Affects Your Business, I started it with the following definition:

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.

This definition has withstood the test of time; now, more than ever, creating a robust view of visitor behavior online requires multiple sources of data, both quantitative and qualitative, allowing marketers to answer fundamental questions of who, what, where, when, why and how. When I originally developed that definition, the implication was that each of these data sources would be considered independently but used in concert to create a rich understanding of the relationships between intent and satisfaction, functionality and usability, performance and conversion.

The bar has clearly been raised. It is not enough for marketers to simply have the data at their disposal; they need a plan to integrate quantitative and qualitative data in a common environment, supporting deeper analysis of visitor activity and the creation of robust segments, based both on click-stream data and expressed visitor preferences.

In retrospect, my definition was very much limited to Web Analytics 1.0, appropriate for measuring visitors, visits and views. But new technology and increased investment in the online channel have created demand for a new measurement strategy, one able to accommodate more diverse visitor types, browser applications, activities and measurement points. Today’s marketers need a measurement strategy designed to handle the inherent challenges brought on by Web 2.0.

In response to this need, I propose the following definition:

Web Analytics 2.0 is the assessment of visitor interactions in the online channel, informed by the integration of a variety of data including event-based interactions, Web server performance and qualitative feedback, collected from multiple user and client types and able to measure diverse activities and events.

While this definition is slightly more verbose, I submit that it is also entirely more appropriate for measuring marketing 2.0 and the plethora of new technologies designed to create stickier, more engaging websites.

Historically speaking, Web Analytics 1.0 was powered largely by tools designed to parse log files and aggregate the output from script-based “tags” inserted into Web pages. These applications excel at processing quantitative data to produce any number of attractive reports designed to summarize visitor behavior, answering what, when and where questions.

But Web Analytics 2.0 requires additional inputs, largely qualitative in nature, designed to answer questions of who, why and how. Web Analytics 2.0 also creates a need for powerful technology designed to make data relevant to the business so marketers can actually use it. I refer to the collection of technologies powering Web Analytics 2.0 as the Website Optimization Ecosystem.

The Website Optimization Ecosystem

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.

Fortunately, there are two other classes of applications designed to provide a more qualitative view of online visitor behavior: those that report on the overall visitor/ customer experience (Customer Experience Management) and those that report direct feedback given by visitors and customers (Voice of the Customer).

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.

Web Analytics, Customer Experience Management and Voice of Customer systems together form a foundation that supports the online business’s ability to positively influence desired outcomes. These similar-yet-distinct systems each contribute to the site operator’s ability to recognize, react and respond to the ongoing challenges faced by every website owner. Fundamental to the optimization process is measurement – the data and information-gathering tools that can be transformed into recommendations for action. When properly used, these systems allow for convergent validation – combining different sets of data collected for the same audience to provide a richer and deeper understanding of audience behavior.

Questions Web Analytics 2.0 Is Designed to Answer

Web Analytics 1.0, while appropriate for the early days of the Internet, was primarily designed to help marketers answer relatively simple questions. Web Analytics 2.0 is more robust. The integration of qualitative and performance data allows marketers and site operators to answer a much wider array of questions. For example:

  • Click-stream data, satisfaction surveys and experience replay (the ability to review visitor sessions, much like watching a videotape) allow marketers to learn which site performance issues lead to low customer satisfaction;
  • Widget data, RSS feeds and click-stream data allow publishers to determine which content is most popular across their entire network, regardless of distribution point;
  • Event data, qualitative feedback and experience replay allow designers and programmers to learn where visitors struggle using rich Internet applications; and
  • Voice of Customer, subscription data and click-stream data allow marketers to learn where their most engaged visitors and customers are coming from.

By combining relevant data from these multiple systems into a single view of visitor behavior, marketers and analysts are able to create visitor segments that are far more informative than those based solely on click-stream behavior. Suddenly, questions about customer satisfaction, content distribution and visitor engagement can be answered in the context of the entire online business, not in individual silos powered by overlapping-but-distinct technology sets.

The Importance of Business Process to Web Analytics 2.0

One important idea that is often glossed over when talking about website measurement is that Web analytics is hard. A study conducted by my firm in March 2007 found that 57 percent of industry professionals described Web analytics as “difficult.”

More interestingly, depth of experience had no impact on this assessment. Survey respondents with more than five years of experience with these technologies were just as likely to rate Web analytics as “somewhat” to “extremely” difficult as were respondents new to the area.

Unfortunately, there is no easy solution to this problem. One reason why Web analytics is hard is that too few organizations have clearly established processes for taking advantage of the data they collect. In companies large and small, a lack of clear ownership over these systems often leads to great internal confusion over how the technology will be used. And more often than not, this confusion leads to a breakdown in the actual use of these systems – some companies get stuck in an endless implementation loop; others stop at the report-generation stage; and still others eventually forget they’ve made the investment in the first place.

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.

How to Get Started With Web Analytics 2.0

Assuming you’re with me so far on the need for process and a diverse set of inputs to inform your organization about online visitor behavior, the question you should be asking yourself now is, “How do we get started with Web Analytics 2.0?” There is no easy answer: You cannot get Web Analytics 2.0 from any single vendor, consulting group or services organization. This stuff is cutting edge and requires some careful planning to execute well.

The best advice I can give any company wanting to make the transition from Web Analytics 1.0 to Web Analytics 2.0 is this:

  1. Determine whether your Web analytics application allows you to effectively measure emerging Web 2.0 technologies. In October 2007, Google released true event-tracking for Google Analytics, specifically designed to track interaction with rich Internet applications built with AJAX, Adobe Flash, Adobe Flex and Microsoft Silverlight. At that time other vendors still required their customers to “hack” normal data collection and reporting mechanisms to track many of these new technologies. Ask your vendor about its commitment to helping you measure these emerging technologies.
  2. Determine whether you have Voice of Customer and Customer Experience Management applications already deployed. If not, start looking for ways to fill these gaps. Voice of Customer vendors like ForeSee Results and Opinion- Lab, and Customer Experience Management vendors like Coradiant and Tealeaf all have experience integrating with the top-tier Web analytics vendors. Talk to them and ask specifically how they contribute to the Website Optimization Ecosystem.
  3. Develop a strategic measurement road map to guide your Web Analytics 2.0 efforts. In my experience, too few companies have a truly strategic view of how Web analytics will help their organization compete in a marketing 2.0 world. A strategic measurement road map will help you clarify what your measurement needs truly are; what technologies and inputs are necessary to make those measurements; and how the results will help change and optimize your business. Start with a matrix detailing your current and planned technology deployments, overlaid with your measurement capabilities, and use this matrix to guide investment and process development.

As you clarify your data collection needs and fill gaps, you should be left with both the appropriate technologies and business processes required to successfully execute on Web Analytics 2.0 measurement projects. Properly done, your new capabilities will give you the potential to dramatically improve your understanding of visitor interaction; their response to your marketing 2.0 efforts; and ultimately, your ability to optimize the entire customer experience on your site.