Lifecycle Control Groups
On this page, we will explain what it means to use Control Groups for your Lifecycles, why you should consider using them, and how to set them up.
A control group can be added to any lifecycle version. Adding a control group to your lifecycle version will make sure that randomly selected players, who enter the lifecycle, won't receive any player engagement from within the lifecycle.
To specify, the players who are a part of the control group will only enter and exit according to the set conditions, they won't have any events/activities/actions triggered for them.
By using a control group for your lifecycle versions you are able to evaluate just how successful your lifecycle engagements are. It's the only true way to measure success!
With the insights, you can get from running a control group, you also give yourself the possibility to make educated decisions, such as, if and where your lifecycle version needs improvements.
The insights, that we're referring to, are the collected conversion data that you can analyse after running with your lifecycle version and control group for some time. Read more about Analysing the Results further down on this page for more information about this stage.
You have to enable the control group and set the percentage of how many players you wish to be part of it. Players entering the lifecycle version will be picked at random to be included in the control group - all according to the percentage you've set.
Please note; Due to the random factor, there will never be a "perfect split" according to the percentage setup. However, the more players that enter the Lifecycle the split will even out more and more, and become more accurate according to the numbers that you've set.
In the development stage, when you build your lifecycle version, you can easily enable the control group. Next, you need to decide how many players you wish to be a part of the control group, in percentage. By default, it will be set to 10%, which we believe to be the ideal number, but you can change the percentage to your liking.
After you've run with your A/B testing for some time, and enough players have passed through the lifecycle for us to have sufficient data, it is time to analyse the results.
This is where you will get valuable information, about how your lifecycle version has performed in comparison to the control group and therefore also draw the conclusion if it was successful.
You can easily access the conversion data, inside of your Lifecycle Projects, when hovering over the Lifecycle project that you wish to analyse;
Here you will be presented with the conversion analytics for your lifecycle version(s) and control group(s) that are included in your lifecycle project. If needed, adjust the filtering options at the top;
We recommend that you pay extra attention to the Lifecycle Entry Date settings, to make sure that you're looking at all relevant data.
Beneath the filtering options, you can see the Lifecycle Version Summary, followed by a number of graphs and other interesting data;
Please note that slightly different data will be displayed in the conversion analytics for your lifecycle depending on what lifecycle template you have used. We've simply adjusted the conversion analytics to show the most relevant information for the chosen template.
Understanding the numbers
Going back to the Lifecycle Version Summary, this is where you can get the most valuable information, as you can quickly get a good understanding of the performance of your lifecycle version in comparison to the control group performance;
The information found here is pretty straightforward and self-explanatory.
Looking at the conversion data from Version 1 and Version 1 - Control Group, in the above example, we can see that Version 1 (the players that did receive the lifecycle player engagements) overall performed much better;
Version 1 had a higher conversion rate (= more players that entered this lifecycle version have made their first deposit)
The players belonging to Version 1 had a higher first deposit average (= their first deposit was a higher amount on average in comparison to the deposits of the players belonging to the control group)
The players that received player engagements, belonging to Version 1, converted quicker (= the players were quicker to make their first deposit)
We also have the 'Significance' comparison in the three fields furthest to the right, which are directly correlated to the categories displayed to the left. This comparison will quickly give you an understanding if the player engagements resulted in a better performance or not, in comparison to the control group, in the different areas.
Hint: For some of the table headers, you get a more detailed explanation if you hover over them;
If you would like to remove a control group from a lifecycle version, you simply clone your current lifecycle version (containing the control group you wish to remove);
and push the new and cloned version all the way to the READY stage (without implementing a control group in the first stage).
Once at the READY stage you > Edit > Modify Entry Conditions > De-select the old version you want to stop running with > Select the new version > Update Configuration
This way you now have the new lifecycle version live without a control group and without disrupting the flow of your players entering the lifecycle at any point.
As a best practice, we would recommend that you combine the use of Control Groups and for your lifecycles.
Read about the best practice .
If you haven't already, we recommend that you also read up on Lifecycle A/B Testing; what it is, what the perks are, and how to set it up. Read it all .