The A/B testing tool segment is exploding and this is a perfect time look closely at your A/B test strategy and share some learnings.
So what is A/B Testing ?
A/B testing or multivariate testing is experimenting with general variations in your design or user flow to establish what works for you what doesn’t. It works perfect if you dont want to rely on your ‘gut feeling’ and proceed purely by data-backed decisions. It is highly recommended to constantly optimize your app/site interface to improve performance – whether that means more sign ups, downloads or sales.
Here are some simple ways to make the most of A/B testing on mobile
1) Hypothesis Stage: A/B tests start with a hypothetical change that one conceives for your app interface. Your hypothesis should detail the following:
The critical metrics that you wish to optimize. Say you run a dating app, are you looking to improve registration rates by X% or retention rates by Y%. It is always better to register the optimum results you want to achieve as a part of the test.
The scope: Whats the premise that you would like to optimize? The homepage? The registration flow? The sales flow? Obviously the objective will need to be in sync with the scope.
2) Define the variations: Once you have the hypothesis you want to test, the next step is to set up variations in sync with your hypotheses. One tool that make it very easy to visually make the edits and instantly publish is the recently launched Appiterate.
Some things that can help at this stage are:
Choose a solution that doesnt need you to make app store updates for every variation. Some solutions Vessel
Ensure you are linked to your analytics platforms OR use an All in One package like LeanPlum.
If you are testing/deploying new feature, you could do it using an A/B testing tool that lets you target based on Geography, Carrier, Device, OS, Language etc.
3) Data Collection & Analysis: Going back to the critical metrics you defined in your first step – now is the time to lay it out in front of you and face the results. Again it helps to have an end-to-end solution like Swrve so your data analysis stage is seamless and is an extension of your A/B tests.
4) Deploy to the entire userbase: This is the easy part. Most A/B test help you activate the changes to the full user base in one single click.
It doesnt end here! The real success lies in carefully segmenting your optimized test base for maximising revenue, retention and life time value. Mobrulers will soon follow up with the best relationship management solutions in the market and some great tips.