Multivariate Testing: What It is & How to Conduct It
Multivariate testing (or A/B/n testing) allows you to compare the effectiveness of several content variations in email newsletters and other mailings. It is possible to test templates as a whole or their individual elements. The goal is to understand which version works better and brings more conversions.
- the amount of text in emails;
- the text, design, size or placement of CTA buttons;
- the subject line or preheader of an email newsletter;
- the title or icon of a push notification;
- product prices;
- product descriptions and headings within the description;
- product illustrations.
What Makes A/B/n Testing Helpful
- Reducing the risk of financial loss. The easier it is for a customer to find the right product and place an order, the more likely they are to make a purchase. Inconspicuous buttons and confusing navigation lead to loss of customers and potential revenue.
- Increasing conversion. The test helps identify the most clickable options that will lead your customers to purchase faster.
- Testing ideas. If disputes arise during the development stage, split testing allows you to check whose idea or hypothesis turned out to be more effective.
- Saving time. The test allows you to identify effective options faster than sequentially testing several content versions one by one.
- New ideas for future campaigns. User reactions to different content options can serve as a source of new insights (sometimes unexpected).
How to Conduct A/B/n Testing
In Altcraft Platform, both simple split tests (A/B) and more complex A/B/n testing are available. As an example, we will conduct a simple A/B test: compare two variations of a single message.
Step 1. Identify the Problem and Formulate a Hypothesis
Suppose you notice that a welcome email newsletter has a high Open Rate but a low CTR. This means the subject line and preheader are good, and the problem most likely lies with the content: irrelevant text, weak visuals, or an ineffective call to action.
Step 2. Create Template Variations for the Test
Next, you need to create several template options. You can test up to 8 templates simultaneously.
Important: the more message variants you have, the larger the test audience must be. Results will be meaningful only with sufficient traffic for each template option. Also, to obtain reliable results, it is recommended to test only one template element at a time.
We will test two email templates for a promotional newsletter. The goal is to check which one will prove more effective.
Step 3. Create the Mailing
Basic settings of an MVT newsletter
Sending channel
Step 4. Determine the Sample Size
- Baseline Conversion Rate — the average expected conversion rate (taking into account experience from previous mailings).
- Minimum Detectable Effect — the difference between A and B that will be noticeable to you.
- Statistical Significance — the confidence level. It characterises the probability that the sample will be significant for the selected results.
Optimizely calculator
Next, you need to select what percentage of this audience will participate in the experiment. In our example, we will select 20%: one half of them will receive the first template variant, and the other half the second. After the most effective option is determined, the winning template will be automatically sent to the remaining subscribers.
Step 5. Add Templates
Step 6. Select the Method for Determining the Winner Template
The most effective template can be determined by:
- the number of opened messages (the platform will automatically select the template that was opened more often);
- the number of message link clicks (the platform will automatically select the template in which test subscribers clicked on links more often);
- user decision (you select the template manually, based on analytical data).
After the open or click statistics have been collected, the most effective message template (according to the selected metric) will be sent to the rest of the audience by the specified schedule.
The winning template can also be selected in the newsletter list by clicking the corresponding button in the context menu.
In the window that shows with statistics for each template, the following will be displayed:
- Send — the number of messages sent.
- Delivery rate — the number of messages delivered.
- Content CTR — the percentage of clicks in the message, calculated using the formula: (Number of clicks / Number of delivered messages) × 100%.
- Content OR — the percentage of message opens, calculated using the formula: (Number of opens / Number of delivered messages) × 100%.
Step 7. Launch the Test
Step 8. Make a Decision
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