What is an A/B Test?
An A/B test is a method used to compare two versions of a website, direct marketing message, or another marketing campaign to determine which variant performs better. The campaign is split into two versions, and website visitors are randomly assigned to one of the two versions. In the case of recipient groups, they are divided into two test groups. The results of the two versions are then compared to see, based on traffic or orders, which version delivers better performance.
A/B tests create clear facts – vague assumptions come to an end. You can measure which page or advertising material works better and, for example, achieves a higher conversion rate. This can help you optimize your website or marketing campaigns and improve your results.
Goal of the A/B Test
The goal is to improve the performance of a website or campaign. Two versions of an element are compared to see which one performs better. In an A/B test, only one variable should be changed at a time. This ensures that it is indeed this single factor that, for instance, led to more purchases. If multiple variables are changed simultaneously, it becomes difficult to determine which change was responsible for the improvement.
The goals can vary, such as:
- Acquiring new customers
- Increasing sales
- Generating newsletter sign-ups
- Boosting traffic
What to Consider During an A/B Test
An A/B test should ideally run over a longer period to account for different audience groups and ensure that results are not distorted, for instance, by seasonal fluctuations. In general, the larger the sample size, the shorter the test duration. You should also ensure that only one test is running at a time and not multiple A/B tests in parallel. Before starting an A/B test, the campaign goal must be defined to clarify which performance metrics will be compared.
What Can You Test? Possible A/B Test Variables for Performance Measurement:
- Images
- Subject Line
- Offer
- Sender Address
- Links
- Call-to-Action Text
Example of an A/B Test:
For an online shop, a standalone campaign is designed to acquire new customers. The goal of the campaign is to gain 500 new customers. Assuming that email lists in the target group segment achieve about a 5% open rate and 0.5% response rate, 2 million standalone emails would need to be sent to reach the projected goal. Before rolling out the campaign, the company wants to determine which template promises more new customers.
Through two A/B tests, the subject line and the offer are compared in terms of performance. In the first step, two different subject lines are sent to a small test group (10,000 recipients per variant). The test groups receive the emails on the same day. It becomes evident that subject line variant A achieves a significantly higher open rate.
In the second step, another small test group receives a template, this time with different offers but with subject line variant A. The subsequent A/B test shows that offer variant B performs better and generates more new customers.
Now it is clear that the standalone campaign using subject line variant A and offer variant B promises the best results. The campaign for 2 million recipients can now begin. The sending is spread over several days, allowing for optimization if needed.
Your Contact for A/B Tests:
A/B tests help improve the performance of your campaigns. If you need assistance with conducting an A/B test, contact Tanja Hensler (hensler@trebbau.com Tel.: 0221/37646 – 330). We are happy to assist you.