Marketers need to know exactly how effective their actions are and how they affect their bottom line. When they try to evaluate their actions, they tend to attribute success or lack of success to various exogenous variables, such as increased revenue around Black Friday.
Multi-Campaign A/B Test brings a simple yet very effective way to test your messages along multiple variables at the same time and find the highest-converting message.
1. What are Multi-Campaign A/B Tests?
Simply put, you can now run controlled experiments to find out
What message types work best,
If your campaigns perform better than no campaigns at all,
What segments have the highest conversion rates,
What combination of messages bring the best results.
Multi-Campaign A/B Tests can be run, including any existing campaign - both active and inactive on the same domain. You can pick any campaign to test against each other.
2. Inspiration for what you may want to test
1. A/B test message variants
If you want to test different design variants, CTAs, colors, copy, or images in your messages, you can do that with Variant A/B testing within a campaign without running a full Multi-Campaign A/B Test.
However, if you want to test different templates or message types against each other, you're at the right place. Multi-Campaign A/B Tests allow you to test
gamification templates against the standard list builders,
lead magnet list builders against discount offers,
teaser vs. no teaser campaigns
and much more!
2. A/B testing segments & audiences
test different geolocations against each other, e.g., UK vs US
test different Klaviyo segments & lists, e.g., new subscribers vs. potential purchasers
test audience from different traffic sources, e.g., organic vs. paid traffic
test segments with different cart values, e.g., low vs. high cart value
3. A/B testing the overall effectiveness of messages
Test messages against a control group to find out whether your campaigns have an impact on your revenue at all.
4. A/B testing complete sets/groups of campaigns
Test entire experiences to find the best combination of messages.
Discount Code vs.(Discount Code + Discount Code Reminder)
Discount Code vs. (Discount Code + Post-Purchase Feedback Popup)
Discount Code vs. (Discount Code + Free Shipping)
Free Shipping Bar vs. (Free Shipping Bar + Discount Code)
Welcome Back Recommender vs. (Welcome Back Recommender + Discount Code)
3. How to run Multi-Campaign A/B Tests
Step 1: Log in to your OptiMonk account
First, log in to your OptiMonk account at https://app.optimonk.com/login/en
If you previously created Multi-campaign A/B tests, you will find a lab icon in the left toolbar. Your tests will be available here.
If you have not created a Multi-campaign A/B test before, you'll need to follow these steps:
Step 2: Select "New Campaign"
Select "New Campaign" in the top right corner:
Step 3: Choose "Optimize a Website"
Step 4: Click on "Multi-campaign A/B test"
Step 5: Launch a new test from the A/B Test Center
Here, you'll see all your previously created Multi-Campaign A/B Tests — if you have any — listed by their names and domains. If you haven't run experiments before, don't be surprised to find this page empty. To launch your (first) experiment, click on New A/B Test in the top right corner.
Step 6: Select your domain
First, select which domain you'd like to run the test on.
⚠️ Keep in mind that Multi-Campaign A/B Tests can only run a single domain, a.k.a. you cannot test two campaigns running on two different domains within the same Multi-Campaign A/B Test.
Step 7: Name your test
Name your Multi-Campaign A/B Test to help you identify it later.
💡 Here's a hint: include the domain and the subject of your A/B test in the name for easy identification. For example: US vs. UK segment | List builder | Sissora.com
Step 8: Add campaigns
Add campaigns to display to different visitor segments by clicking on Add campaign and browsing your existing campaigns.
⚠️ If you add an active campaign to a Multi-Campaign A/B Test, you'll receive a small notification that this campaign will be inactivated and activated again once you start the Multi-Campaign A/B Test. The reason for this is that a campaign cannot run independently from a Multi-Campaign A/B Test.
⚠️ You can create up to 5 visitor groups.
Step 9: Determine traffic share
Once you've selected which campaigns you'd like to test against each other, determine the traffic share between the campaigns. You may want to display both campaigns in the same ratio to your visitors, but you may want to show Campaign A to most of them and only test Campaign B with a small traffic share. This option allows you to run tests with a lower risk.
Step 10: Launch your test
To launch your Multi-Campaign A/B Test, click Start. Once you launch a Multi-Campaign A/B Test, if you wish to end it, you'll have to do it manually.
Step 11: End your test
You can end your Multi-Campaign A/B Test any time by clicking on End.
Step 12: View results
Once your Multi-Campaign A/B Test has been completed, you can view its results on the Multi-Campaign A/B Tests page.
⚠️ Keep in mind that the stats here only reflect the results achieved within the timeframe of the Multi-Campaign A/B Test. Further data can be measured in Google Analytics.
4. How to run Multi-Campaign A/B Tests With and Without an OptiMonk Campaign
In some cases, we would like to measure and see the additional revenue we can achieve with the help of the OptiMonk Campaigns.
Step 1: Log in to your OptiMonk account
First, log in to your OptiMonk account at https://app.optimonk.com/login/en
Step 2: Select the Multi-Campaign A/B Tests icon
Select the Multi-Campaign A/B Tests icon from the left navigation bar.
Step 3: Launch a new A/B Test
To launch your Multi-Campaign A/B Test, click on New A/B Test in the top right corner.
Step 4: Select your domain
First, select which domain you'd like to run the Multi-Campaign A/B Test on.
Step 5: Name your test
Name your Multi-Campaign A/B Test to help you identify it later.
Step 6: Add a campaign to the Control Group
Add a campaign to the Control Group by clicking on Add campaign and browsing your existing campaigns.
⚠️ If you add an active campaign to a Multi-Campaign A/B Test, you'll receive a small notification that this campaign will be inactivated and activated again once you start the Multi-Campaign A/B Test. The reason for this is that a campaign cannot run independently from a Multi-Campaign A/B Test.
Step 7: Leave the other group empty
Leave the other group empty by not adding any campaigns to it.
Step 8: Launch your test
To launch your Multi-Campaign A/B Test, click Start. Once you launch a Multi-Campaign A/B Test, if you wish to end it, you'll have to do it manually.
Step 9: End your test
You can end your Multi-Campaign A/B Test at any time by clicking on End.
Step 10: Track in Google Analytics
You can track the monetary performance of your Campaigns in Google Analytics by following the steps below.
5. How to track the monetary performance of your Multi-Campaign A/B Test in Google Analytics 4
You can track the performance of the groups of your Multi-Campaign A/B Test in terms of profit with the help of Google Analytics 4. To do that, please follow steps 7 and 8 in this article.
6. Things to keep in mind regarding Multi-Campaign A/B Test
If a campaign is part of a Multi-Campaign A/B Test, it will be indicated with a small icon on the campaign list page.
Once a campaign is added to a Multi-Campaign A/B Test, you cannot inactivate it from the campaign list.
Multi-Campaign A/B Tests can be run only once and cannot be restarted.
A given campaign can only be part of one Multi-Campaign A/B Test at once. Once that Multi-the Campaign A/B Test has been completed, it can be added to a new Multi-Campaign A/B Test freely.
Users can only add campaigns to the Multi-Campaign A/B Test that run on the same domain, a.k.a. the domain of campaigns, and the domain the Multi-Campaign A/B Test must match.
Results of each Multi-Campaign A/B Test are displayed on the test's page. The statistics shown here refer only to the results achieved during the time window of the Multi-Campaign A/B Test. All-time performance of campaigns is displayed under Campaigns or Campaign Analytics.
Detailed data on Multi-Campaign A/B Test, such as average order value, number of orders placed, and revenue attributed to a campaign, can be tracked in Google Analytics. OptiMonk shows data on impressions, conversions, and conversion rates exclusively.
Need help?
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