Robin Johnston: Author, Keynote Speaker, Sales & Marketing Consultant - Asheboro, NC, USA

 

   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
   
   
   
   
   
   
   
   
   
   
   
   
     
 

The ABC's of A-B testing

At some point, every aspect of business comes down to effective decision-making. Marketing communications are no different. Few marketing activities are laden with more opportunities for decision-making. After all, there is so much to accomplish, and only so much money to go around.

One tool in the marketer's arsenal that can help you make better communication-related decisions is A-B Testing. This age-old technique is a systematic approach to testing alternatives that can yield terrific improvements in promotional effectiveness. Tests can be done for a wide range of features, including ad format, colors, headlines, body copy, calls to action, and response devices (i.e. toll-free number vs. e-mail address vs. internet site landing page, etc.). Tests can also be done for sales promotions, marketing literature and telemarketing scripts.

A simple A-B Test works like this:

  • Split your audience into 2 groups: an 'A' group which represents your control group, and a 'B' group which represents your test group
  • Develop 2 versions of whatever it is you are trying to test, and present one version to each of the two groups
  • Measure the results seen from each group
  • Isolate the test with the stronger results, and adopt the format of that tested feature in future campaigns

It is now possible to conduct A-B Testing on individual elements of Internet web sites. Drugstore.com, for example, uses A-B Testing routinely to test various elements of their web site, and determine what should be changed in order to increase orders and raise profits. Two visitors to the Drugstore.com site might very well see different layouts, colors, text or offers, even though they visit within seconds of each other. As in any A-B Test, the stronger combination prevails, and is rolled out to all visitors as soon as the alternatives have been presented to a statistically-valid sample size, and conclusive performance data has been accumulated.  

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