Raise your hand if you've had this happen to you, run a bunch of ads across several channels you collect your data but in the end, you're not exactly sure what worked what didn't.
Then why well understanding some of the science behind digital marketing can help in this article we will focus on two great ways to measure campaign success and how advertisers know if they're getting the most out of every marketing dollar.
Split test and lift test don't worry there's no gymnastics or weight lifting involved. When you understand the benefits of and difference between split test and lift test and when to use them.
You'll have the confidence to make better strategic decisions with your campaign budget and ad placement of an ad campaign but they go about it a little differently.
Facebook Split Test
A split test is what test measures correlation quickly assessing how one variable performs against another within the same campaign that can include variables like the size or focus of the image in the ad for variations in the background color.
For example, let's say you have two ads for a bike-sharing service, one ad shows just the bike the other ad shows people riding the bikes.
In a split test, one group will see the ad with the bikes only from another group see only the Ad people riding their bikes, if one performs better than the other you'll know which one to use.
To get the best possible campaign results to keep in mind split tests don't use a control group so there might be other variables that play here too, also see what tests don't tell us if the campaign is effective as a whole.
Lift Test Facebook
That's when lift test comes in handy lift test measure incrementality in the ad world this usually means how many more conversion to get because of your ad campaign. The lift has let us know if the incremental results you're seeing are a causal impact of your campaign or if it's just pure luck. Lift test is particularly useful when you want to look at the effect of larger strategic changes in your campaign.
A lift test establishes a control group a subset of the audience who won't see any of your ad the test then compared to the control group response against in the audience who has seen your ad.
A quick example in organic produce delivery service in Buenos Aires that wants to find out if an ad campaign causes an increase in subscription.
A test group of people in Buenos Aires see the digital ads at the same time they ensure that a control group of audience members in Buenos don't see the ads
After the campaign, they compare the number of new subscriptions among those who saw the ads and those who didn't.
The difference between the test and control groups is the lift caused by the campaign, the only difference between the two groups is if they saw the campaign or not so now we know exposure to the campaign causes audience members to subscribe.
so think about how you currently measure your campaign success how do you think you might benefit from using a split test versus a lift test as always for more digital marketing tips and tricks keep reading our blog articles.