Conversion Rate Optimization

When you set up your first Content Experiment, you might face a cookie domain name consistency error. This error is caused by using different domain name settings for Google Analytics and Content Experiments code. 

Before you decide and pick the testing tool, consensus should be reached on the goal(s) that you are trying to achieve. Preferably, have one major goal.

How do you set a goal?

The first thing after optimizing a page for design is to think about persuasion. It might sound easy to change the call to action and test out the variation but to convert those visits to valuable leads or sale; you have to think about the visitor.

The number one rule in persuasion optimization is Empathy.

We have often heard Conversion Rate Optimization experts professing about the need for statistical significance. Most Businesses look at this advice with marked skepticism. There are valid reasons for this.

1) Low Page Views

On August 9th 2012, Google released the guidelines for conducting A/B and multivariate tests. The guidelines were released in response to the commonly asked question – “How will testing impact search ranking?” Google has warned marketers from running the experiments for too long.

After you have developed a testable hypothesis, it is to time to create the variations of your control page. Follow these recommendations before creating the variations:

1) Brainstorm

Before you jump into creating variations of your control page, formulate a hypothesis. Hypothesis is an assumption about the occurrence of an event. For example, if you believe that changing your checkout button color from blue to green will improve conversion, then your hypothesis would be something like:

On 1st June 2012, Google announced that it would retire Google website optimizer (GWO) on Aug 1st 2012. GWO was a free website optimization tool that allowed webmasters to improve conversion rate and user experience. 

We have been running a few tests to find out what makes the visitors click links, inside and below an article. When you have tools to measure user engagement at page level, make use of them. You will be surprised to learn that lot of your assumptions are wrong. It hurts but this is going to be one of the best learning experiences.