One of the best ways to increase your profitability? A/B split testing. Google Ads has a feature called the Experiments where you can create custom experiments for your campaigns and compare how your test group performs against your original campaigns (control group) over time. Only problem is, this is only available for Search and Display campaigns. Not for Shopping.
- The cluster analysis method
With a cluster analysis you’ll divide based on historical performance (e.g., dividing your products into equal groups based on metrics like clicks, revenue, costs, and conversion value). You can do this via spreadsheet for smaller datasets or in R (or other programming languages) for larger datasets.
- The random split method
A random split can be done based on the ID of your product. For example, if you use numeric values as product IDs, you can assign group A to all even numbers and B to all uneven numbers. The most important thing while splitting your products is to make sure that all groups of your experiment have an equal number of products and that your key metrics are also very close. Once you’ve made the split, make the changes to the product IDs in your test group. Make sure you’re able to report on all of your product IDs and corresponding groups. This way you can analyze them and find winners.
- The Customer Match split method
With Customer Match, you can target first-party audiences in Google Ads. It works by uploading a list of email addresses from your existing database that you want to target, and Google will match those email addresses to Google accounts.
- The geo split test method
Geo splits are often used to find incremental uplifts in campaigns. This could answer questions like: Is there incremental value in advertising on branded keywords? In a geo test, a market is divided into smaller geographical regions called geos. Each geo gets assigned either a control or a test group. Users in the test geos are exposed to the changed campaigns while users in the control geos are served the control campaigns. The split can be done on country or region, as long as both regional groups are highly correlated. You’ll need to use the cluster anaysis to determine your groups.
- The campaign split method
In a campaign split, you simply divide your campaigns or accounts into two highly correlated groups. Both groups need to have an equal number of key metrics like clicks, conversions, and costs. In one group of campaigns (test group), you make the changes while in the control group your current best practices will serve. If you label and track the different groups of campaigns, you can tell something about the differences in performance.
