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A/B Testing
Allows you to test one variant vs. another to see which performs the best.
This can be anything from a banner, landing page, offer and even different price points.
Usually, A/B testings consist of sending 50% of your visitors to one variant a and sending the other 50% to variant b.
ABTest
Pros:
By using A/B testing, you’re able to more quickly identify which of the two variants perform the best.
Since your traffic is only split 50/50, you will be able to reach statistical significants fairly quickly.
Usually, I only use A/B testing once I have a campaign that is already running profitably.
I use A/B testing always to improve the campaign by always trying to beat the current winner.
Cons:
Though it’s quicker to identify a winner, you have less of a chance to identify a variant that is out performing the rest of the group.
Multi-Variant Testing
Similar to A/B testing, multi-variant testing allows you to test more variants at a time.
Instead of sending 50/50 to A and B, multi-variant allows you to test as many variants as you want.
In the example below we’re testing four different variants: variant a, b, c & d each of which get’s 25% of our traffic distributed evenly.
Multi-Variant
Pros:
Multi-variant testing is best when you are first starting a campaign. It allows you to test drastically different marketing angle and styles.
This will allow you to identify which angle or style your audience responds to the best by comparing them all at once.
When I am first testing out a particular offer, landing page or banner I usually will use multi-variant testing.
Then once I identify a clear winner I will then revert to A/B testing to try and beat the current best performer.
Cons:
Since you’re splicing up your traffic so much with multi-variant testing. It’s going to take a lot longer to get statistical significance.
Optimization Through Testing
Though there is no perfect way for you to optimize your campaign, there is one thing that does matter.
Consistency
If you just launch a campaign at random with no rhyme or reason and then make changes to that same campaign a few hours later….
…The data you did collect is useless.
No matter how bad a test appears to be performing, if you want to have accurate data you need to allow yourself to gather enough data.
This means that when you’re preparing to test something…
No matter if it’s a new banner, landing page, offer, etc
You need to setup the test and then leave it alone.
Start researching your next campaign launch and stop refreshing the stats like a maniac.
If nothing else takes a step away from the
