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Building a Website Testing and Optimization Program: Measurement (Part 3)

by Kim Ann King  |  
January 29, 2013
  |  1,986 views

Whether you have been testing for years or you are just getting started, building a successful website testing and optimization program depends on careful planning, implementation, and measurement. This is the third article in a three-part series that looks at the steps involved in creating a successful optimization program.

In this article, we'll look how to measure and communicate the results of your website optimization program.

Optimization Measurement—Integrating Analytics and Testing

Testing platforms and analytics applications are naturally related: One is fundamentally designed to drive improvements on your site, and the other is fundamentally designed to help quantify the value of those improvements. Although some testing applications do a good job of helping quantify success on their own, the integration of testing with analytics allows companies to develop a very broad view of the results of individual tests.

On the subject of measurement, one point is very important and frequently overlooked: The combination of measurement and testing should support both optimization and an incremental learning process about your visitors and customers.


Assuming you have a robust measurement program already in place, the integration of testing into those efforts is often a trivial effort and requires little more than patience. The upside from taking the time to integrate these systems correctly includes the ability to evaluate testing efforts over multiple criteria and the ability to evaluate test participant behavior over multiple sessions.

Seemingly dramatic design changes often have no significant impact when examined using simple measures such as click-through and conversion rate. An increasing number of companies have started applying more complex measures, such as "return visitation rate" and "lifetime customer value," and using more qualitative measurement systems to develop a more holistic view of test impact.

Although the specific measures you take will likely vary from test to test, depending on the systems you have in place, an important consideration is the ability to integrate those systems. The basic integration of testing and measurement systems involves exchanging data about test participation, either by after-the-fact bulk data loading or by real-time tag transformation. Done well, such integration allows the measurement team to create segments, build key performance indicators, and drill down into the activity of individual visitors based on test participation (via the use of data warehousing and customer experience management technologies).


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Kim Ann King is the CMO of Web and mobile optimization firm SiteSpect. A B2B software marketer for nearly three decades, she is the author of The Complete Guide to B2B Marketing: New Tactics, Tools, and Techniques to Compete in the Digital Economy (May 2015).

Twitter: @kimannking

LinkedIn: Kim Ann King

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