Personalization allows you to serve different versions of your site customized to the different interests of your audience. With this we can segment audiences, serve content for each segment and report on an audience’s engagement with specific content.
Steps to create a Personalization Experiment
Click on the “New” button. Provide the Experiment name and URL for which you want to run the experiment. You can create a Personalization experience by two ways.
1) Using Freshmarketer's Visual editor
2) Using Personalize by Redirection
Using Freshmarketer's Visual editor:
The page lands up in the variation page by default for making the changes as shown below. You can have a glimpse at this link to learn about the different editor options.
Using Personalize by Redirection:
If you are creating Personalization by Redirection, you will be taken to the page shown below where you can provide your variation experience URL. You can add any number of experiences and match audience segments for each one of them.
On click of next you will be landed on the Goals page. Setting up goals for an experiment is essential as it tracks the data which then would help us in analyzing our test. You can get more insights about goals by going through this article.
On click of “next” you will be landed on audience targeting page. You can choose among the different audience segments we have to match with the experiences that you create.
For example, if you set your variation 1 to the mobile traffic, the users who access your site from mobile will be seeing the new experience.
On click of next you will be taken to the preflight where you can preview the configurations of your experiment. On click of launch campaign, your experiment will be created.
NOTE: In Personalization you will not be able to set traffic like A/B Testing. Because, here the audience segment is different for each experiences. While in A/B we have the same set of audience divided into groups based on traffic we set to validate our experience. Simply put, we use Personalization for optimizing audience experience while A/B testing is a verification tool for content effectiveness.
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