Organizations of all sizes have always been able to test their market using traditional mediums, making various tweaks to improve returns. Whether this is the encyclopedia salesperson testing a sales strategy or a hotel chain adjusting uniforms, given proper testing, results can be measured and acted upon.
For an online business, these same practices have often been just as applicable for the web. However, due to the technical nature of the work, implementing online market testing has been out of reach for the average small business owner.
We experienced this first hand many years ago with one of our first commercial projects. This business specialized in traditional marketing and sales, and the owners were very involved in making and testing adjustments in short order. For us, the project was ongoing and involved gathering and presenting detailed analysis based on media coverage, various conversion hooks we had placed, and server traffic logs for the website. Although we were able to present a fairly accurate picture, the amount of effort involved was tremendous.
Over time, website analytics have continued to evolve and with today's tools, you can get a pretty clear idea of who your visitors are for virtually no cost. The really interesting aspect is when technologies begin to converge, in this case, with the advancement of easy-to-use content management systems. A small business owner can now have access to a website where just about every aspect of a page can be managed and the results observed without outside technical assistance.
Of course, making changes this way is going to give you varying results unless you know and can control the traffic visiting your site as you make adjustments. A traditional analogy would be to the business owner who prepares a flyer to advertise a special deal. Through various adjustments, a means to track the results (i.e. bring this flyer in for instant savings!), and randomizing the distribution, they are able to gauge the effectiveness of a variety of tests based on differences in the flyers (i.e. does the yellow header sell better than the blue header?). A website has the same characteristics in that although you may have a rough idea of who your visitors are, attempting a controlled test needs to be done by randomizing the distribution and measuring the differences. There are a number of terms and definitions here, but basically, A/B Testing (Split Testing) is referring to a single change, whereas Multivariate testing consists of a number of controlled A/B tests in the same run, and uses an algorithm to assist in compiling the results.
From a web developer perspective, this type of test involves cloning several pages, making adjustments to the different pages, and configuring a tool to alternate and track the distribution. Not a huge effort for a developer but for the average business owner, the cost and hassle involved is a deterrent.
Open Source and the New Age
As open source content management systems continue to mature, new capabilities are constantly being made available at a breakneck pace. The key with these systems is that when set up properly, they are designed to be manageable by people with limited time and resources in order to quickly and efficiently add content to their website. For example, when using Drupal with the inclusion of the Multivariate module, the content manager can now manage their website market testing in-house and without the help of a website technician. Content maintainers can now clone an existing page and relocate various page elements, change verbiage and/or images, then specify the pages along with the conversion goal page to the module and Drupal will provide measures on the results of this testing.
I truly hope many small business owners take this to heart and begin to experiment with improving their website conversions. I feel strongly that although there is a moral issue to market research and how far it has gone, for the majority of small business websites, it is more an issue of website usability which will quickly become highlighted as a key factor in improving the conversion rates.
- Google website optimizer module for Drupal