Set SMART goals
In most cases, you’ll be measuring conversion rates on a web or landing page to determine which elements increase conversions. For email or advertisements, your SMART goals might be clicks, click-through rate (CTR), conversions, or email opens.
You should set SMART goals to ensure you have something to measure before your campaign begins.
What elements do you want to test? Identify the different variables up for debate that you think can be modified to improve conversion rates and help you reach your goals.
At this point, you should have a hypothesis. For example, if you’re testing the placement of your call to action button and a new headline, you may make the hypothesis that a new headline will improve conversion rates.
Create test variations
Once you’ve formed your hypothesis and set goals, you can create variations. You’ll need to use a multivariate testing tool like Google Optimize to create as many variations as you need.
Once your variations are published, you’ll need to continue driving traffic to your page. If your website receives significant traffic from search engine optimization (SEO), you may not have to invest in additional advertising.
However, if you want to ensure a larger sample size, you can invest in social media or Google ads to increase traffic to the page and ensure your results will be more accurate.
Once your campaign has finished, it’s time to analyze your test results. Compare the results with your original SMART goals to determine which elements performed best.
After analyzing your results, you’re armed with the data to help you redesign or modify your web page, email, or advertisement. For example, if you tested different email subjects, you now know which performs best and can use it in future campaigns to increase open rates, clicks, and conversions.
Multivariate testing vs. A/B testing
Multivariate testing is similar to A/B testing, but there are a few key differences, including the following:
- Number of variables: The most significant key difference between the two experimental methods is that A/B testing only has two variations, while an MVT test will have at least four. You can still test the same types of variables, but you’ll need to wait for one test to be completed before making any further changes.
- Ease of use: A/B testing is easier than running multivariate tests since there are only two variables possible combinations. With fewer different variations, you can better understand your data and its statistical significance to your campaign, allowing you to make more informed decisions with a smaller sample size.
- Required sample size: Since there’s less traffic required, A/B testing is best for small businesses that don’t receive significant traffic to a single page.
- Testing time: A/B testing gives you results faster than multivariate testing, especially if you don’t have significant website traffic. Instead of waiting for enough traffic to your site, you can use A/B testing on almost any page to make drastic changes that have a significant impact. How long you should run an A/B test depends on the amount of website traffic or the number of subscribers if you’re A/B testing an email campaign. However, the longer you let your tests run, the more accurate the results will be because you’ll have a larger sample size.
- Types of results: A/B testing can tell you which version or variable is best. Meanwhile, a multivariate test can determine which combination of elements works best, allowing you to create more effective campaigns with a single test.
- Expert level: A/B testing is easy for marketers of all levels. However, multivariate testing is more complex and better for individuals with experience running tests with multiple variables. In addition, too many combinations associated with MVT results can lead to confusion or inaccurate results due to a low sample size.
In most cases, A/B testing is ideal for campaigns where you want to make more drastic changes. Meanwhile, multivariate testing is best for websites with substantial website traffic that want to make small modifications to determine if they can increase conversion rates.
A/B testing is typically used to make informed decisions about redesigns, while multivariate testing is best for changing a few small elements that may not significantly impact results.
Optimize your campaigns
Multivariate testing can benefit marketing campaigns of all types to improve conversions and help you reach your goals. Compared to A/B testing, the multivariate testing method is more complicated to set up and requires higher traffic volumes. However, you can test multiple elements simultaneously if you have enough traffic on a single web page. Creating variations through either experimentation method can help increase conversions and improve your marketing campaigns.
Ready to start testing your email campaigns with multivariate or A/B testing? With Mailchimp, you can try both. Mailchimp’s multivariate testing allows you to determine which variables of your email to test to improve opens, clicks, and conversions. Optimize your campaigns today by A/B testing with Mailchimp or learn more about multivariate campaigns.