You’ve got a great idea for a new online marketing campaign – but is it better than your standard offers? Online advertising networks like Google Ads give you all the tools you need to find out – and often for free!
Split Testing or A/B Testing – What is it and why do I need it?
Split testing divides your target audience into two or more groups, usually called groups A and B, which is where the name A/B testing comes from. Each group is shown a different version of your ad, website, shopping cart, blog or whatever you want to test.
Historically, this had to be done in live focus groups, but online marketing has immediate, responsive analytic tools that let you test out an idea live.
What can Split Testing Tell Me?
A/B testing lets you compare how a new ad campaign or product fares against the old one, so you know whether your hunch was correct. The two campaigns are run simultaneously, so you know the data is directly comparable. As an example, if you’re comparing this year’s Christmas campaign with last year’s a boom, a bust, a new competitor and other factors can muddy the waters, but if you run both side-by-side, you can easily find which is better.
How do I use Google Ads to do A/B Testing?
Google Ads and other ad networks let you target your online marketing and run multiple campaigns or ad variations simultaneously. To run your own A/B test, set up a campaign showcasing your new idea. Set up a campaign that features a previous ad or another new idea, but is otherwise identical. Run the two simultaneously, and you’ll see which is more effective.
There will be a cost for running additional ads. You can split your budget 50/50, but if you’re confident one will work better, you may want to go with a less even split, like 90/10. However, it definitely helps to have enough views and clicks to get a good data set. Ideally, you’d want at least a few thousand views and a few hundred clicks in the smaller sample.
Understanding the Results
Testing is only useful if you measure the results. Compare your two campaigns and look for useful data such as:
– Which campaign had a higher click-per-view rate?
– Which campaign got more sales?
– Which campaigns got the best return on investment?
– Were different campaigns drawing responses from different demographics? Or at different times of day?
Making a Better Product
Once you’ve assessed the data, use it to build a better product. If one ad was obviously more successful, hypothesise why and build a new, better ad to test against the previous winner.
You can also use Google Ad A/B testing to decide on new product names, slogans or even product types. Simply run campaigns with the different options and see which is most popular with users.