Facebook A/B split test is a new Facebook feature although it is an age-old digital marketing practice. What is AB Split Test? It’s a way for you to judge how well has your advertisement practice fared. Split testing is a way you judge the performance of your advertising campaigns by judging the performance of landing pages, ad copies, creatives, placement and optimization.
With Facebook A/B split test ads, you can judge the performance of two or more versions of a single variable. For example, you can show the same set of advertisements to two different audiences at the same point in time. Earlier, A/B split test with Facebook was complicated with Ad sets in place and the budgets were not rightly split between the ad sets. Sometimes, one of the ads would reach to people more and the rest wouldn’t, so we would judge the one getting the major traction as the best one.
The science behind it was, Facebook would quickly push the most performing ads or most performing audience in the front and then downplay the rest of the ads in the ad sets.
There are a few things about Facebook Ads A/B Split Test you need to learn:
- Currently, you can run A/B Split Test Ads with the following campaigns: Website traffic, Website conversion, Mobile App installation and Lead generation.
- Everyone can run Facebook A/B split test by logging on to www.facebook.com/ads.
- You need to run the campaign for a minimum of 3 to 14 days. You cannot test this feature for a day.
- You cannot immediately start the campaign, you will have to schedule the campaign at least 15 minutes from your campaign publishing time.
- When the test is over, you will receive an email. The winner of the campaign would be the variant that cost you least per lead.
- No audience overlap: Your potential reach will be randomised and split between advert sets to ensure an accurate test
- Single variable test: The advert sets will be identical except for the variable that you want to test
So what are those variables that you can test in this journey?
- Audience – Earlier it allowed to pick only saved audience, you can now create a new audience.
- Delivery Optimization – Between manual and optimized, leads vs. Link clicks
- Placement – Mobile, Desktop, Instagram, Instant article and all kinds of placements (whichever is applicable)
Step by Step Process to Run A/B Split Test Advertisements – My Trial.
I got my hands dirty on Facebook A/B Split Test Ads. I have learnt quite a few things in this process and I would like to share the same with you here.
Step 1: I picked up a Facebook Lead Generation campaign for my Free Digital Marketing Course. As you select the objective, you need to also tick the box to opt for a split test. Its shows as a new feature when you select Lead Generation, Website Traffic, Website Conversion or App Install as an objective.
Though Facebook ads dashboard shows saved audience, you can pick up an audience of your choice. You don’t have to necessarily make use of saved audience.
Option 2: Just for reference, when you pick up Delivery optimization as the variable, you can choose between Leads vs. Link Clicks to optimize your advert delivery. You can also choose between an automatic bid and a manual bid. Please note that delivery optimization variable options are different for website conversion advertisements.
Option 3: If you pick placements as a variable, you can choose between automatic placement and your choice of placement. If you are creating two ad sets on your choice of placement you can distinguish between mobile and desktop or facebook, Instagram and audience network. This is a brilliant way for you to learn which platform is delivering the most leads at a lesser cost.
Step 3: While you pick your ad budget, you can do an even split of the budget in between two advert sets or you can give weightage in the ratio of your choice. You need to run these ads for a minimum of 3 days. You can opt for an option to deliver you result as soon as the winning set is determined.
I spent about 20 dollars on Facebook Ads Split Test to test two different audiences for my Free Digital Marketing Course.
- SoravJain.com blog visitors and Lookalike audience of my blog visitors.
- People interested in Digital Marketing.
The first ad reached about 5,225 visitors and cost me about 10 cents per lead whereas the blog visitor and lookalike cost me about 20 cents. It is evident from the results that advert set 1, targeting digital marketing enthusiasts is a better option for further campaigns.
Lookalike audience and website visitors haven’t shown much interest in the advertisements compared to the Digital Marketing interested individuals.
- Cost Per Lead: 12.88 INR
- Reached: 3,489 people
- People Taking Action: 100 (Reaction, Comments, Shares, Clicks)
- Leads: 44
- CTR: 2.87%
- Total Amount: 563 INR
Though the first ad copy reached to almost 2000 people in both the case, the audience interested in Digital Marketing reacted more to the advertisements. Therefore, the leads are higher and cost per lead is cheaper when compared to Lookalike audience. Also, the creative that performed well with the first audience isn’t the same with the 2nd audience. This also defines what kind of creative both the audience would like to see with further advertisement sets targeting them.
- Cost Per Lead: 6.44 INR
- Reached: 5225 people
- People Taking Action: 188 (Reaction, Comments, Shares, Clicks)
- Leads: 85
- CTR: 3.60%
- Total Amount: 563 INR
Final Verdict for Facebook Ads A/B Split Test:
Is Facebook Ads Split Test worth a try?
Not at all. Here are few reasons:
- I have done the same analysis with generic advertisements without using split tests and I have got leads for Rs.2 for Digital Marketing enthusiasts and Rs.3 for lookalike audience.
- Facebook Ads Split test does no justice as the audience it reaches should be same. Since both blog lookalike and Digital Marketing interest audience had huge potential reach numbers, the audience reach should be the same.
- The cost per Lead here is very high, hence I would recommend you to really spend less on A/B split test or don’t spend at all. You would rather want to do a manual analysis by creating two different campaigns or two different advert sets in the same campaign.
- While the audience should be equally reached, the ad copies should also reach equally.
What are your thoughts? Please share your thoughts in the comment section below.