1 Reply Latest reply on Oct 15, 2015 7:29 PM by Shekhar_Dhiman

    Measuring click throughs on homepage

    anne-marie_garcia

      Hi All,

      Apologies if this is a basic question! I'm still in the learning phase and haven't been using these tools for long.

      I have set up an A/B campaign on our company homepage. There are two scenarios, both display the same banner but one goes to a landing page and one goes to the product page. I would like to measure how each of these scenarios impact conversion.

      I am trying to measure just the clickthroughs (the amount of people who click on this banner) as the 'visitor' number but I am not able to get this data. The numbers that are coming through  for visitors are far too high and suggest to me that it is recording everyone who lands on the homepage which I don't want to measure.

      In the conversion/other metrics section I have set up a value of 'clicks' with a location of 'clicks from [mbox value]' but I don't know how to use this data in the report to get the measurements that I want. I have also put an mbox on the basket page, but again not sure how I can use this to measure click throughs/people that add this specific product to basket.

      Can anyone offer any instruction/advice? I have successfully measured the total amount of conversions on the confirmation page, really what I'm after is a way to measure how many people click through to the next pages in each scenario.

      • 0. Re: Measuring click throughs on homepage
        Shekhar_Dhiman Adobe Employee

        Hi Ann,

        Thanks for reaching out to Adobe Community.

        I see that you have two different experiences/landing landing pages for the same banner but how exactly you are classifying your experience. What I am trying to say here is what is your audience and what sort of targeting %age you have? When there is no targeting on your experiences, each experience is randomly shown an equal number of times over time. Initially, however, the distribution of traffic is slightly uneven. For example, in an A/B test with four experiences, each experience is shown to 25% of visitors. Note too that you may override the random equalization by adding targeting to each experience.

        Thanks!