When you start using Datatrics, we feel it’s very important to be able to show you how well we are performing. For this reason we use an A/B Test.
While using this test we divide your website’s visitors into 2 groups and show different content to both groups. Group A will see the Datatrics content while group B will not.
Starting out both groups will be set to 50% of the total visitor amount. When the Datatrics group is shown to have a better performance, you can move the percentage slider up to display the Datatrics content to more visitors.
You can choose to shift it up as far as you like. We however do not recommend going any higher than 90% Datatrics. The reason for this is that we always want to keep checking whether the Datatrics group is indeed performing better.
One very important thing to note is that once a visitor has been assigned to a group, that visitor stays assigned to the same group for his entire lifespan. This is especially important when moving the percentage slider. New visitors will be divided using the new ratio. The visitors already assigned to a group prior to the change will remain in the group they were initially assigned to.
The funnel for A/B Testing looks like this:
What does ignored mean and who is in it?
As you can see we have profiles that are targeted by Datatrics and Ignored visitors. Our platform filters your visitors to make sure only the ones who have any chance of achieving a conversion will be used for your control and hide group. The ignored group generally consists of bots, spiders, people who leave the website within a couple of seconds of entering and people that don't match the targeting of your journeys and campaigns.
How does it measure performance?
As you can see below, this example has both groups at 50%. It also shows that there is a conversion increase of 10% so far. The next step here would be changing the ratio of A to B by increasing the amount of people who see Datatrics. Always keep an eye on the conversion rate to make sure everything is working according to plan.
If you set up a campaign to be displayed to 100% of visitors (100% A, 0% B) there will be no label assigned to the visitors in that campaign. This campaign will also ignore any previously assigned label (the label will still remain for other content). This means that even though you may have a group of people who never see your other Datatrics content, you can still show them campaigns. This can be especially useful when setting up marketing campaigns for special events or holidays.
Reporting in Datatrics VS Google Analytics
It is very important to understand that Datatrics reports results on a user level as opposed to Google Analytic's session based reporting. Keep in mind that this can end up showing different results because of that. We recommend using both metrics simultaneously to know what's going on within the two platforms.
Help, my Google Analytics ratio shows 90% while my journey is set to 50/50!
The first touchpoint a visitor encounters determines the group he/she is placed in. Let's say you have a campaign set up that is being shown to all new visitors. You set this campaign up to use a 90/10 ratio. Because it is being shown to all new visitors, all of them will be divided using this ratio. As mentioned before, once a visitor has been assigned a group, he/she will stay in that group. In short: In this example the campaign determines the ratio and the customer journey has no impact because the ratio has been set before they ever get to the journey.
My Google Analytics environment won't let me use custom dimensions.
Chances are you are running a legacy library of Google Analytics. Unfortunately custom dimensions are not supported here. You can read more about this here.
Google says: “…you should strongly consider upgrading your tracking code to get all the benefits of Universal Analytics.”
If you want to upgrade, check out this link.
Note: We simply allow you to send over custom fields. Any questions regarding your Google Analytics environment and the upgrading process should be discussed with the Google Analytics support staff.