A/B Testing vs Multivariate Testing - What Should You Use?

As marketers, we understand that A/B testing is a cornerstone of effective marketing campaigns.

But should we test as many variations as possible, or stick to A and B variations when testing?

And how often should we perform such tests?

I'd like to share some insights on the benefits of increasing the number of variations in your A/B tests, and why conducting frequent tests is pivotal.

👉 Better Confidence in Results:
More data equals higher statistical confidence. By conducting multiple tests with various variations, we can more accurately pin down the variables that truly impact outcomes. More tests, more data, more precision.

👉 Unearthing the Best Version:
By testing a wider array of variations, we boost our chances of uncovering the most effective version. Neglecting this could mean missing out on a potential winning strategy. This holds true for various aspects of marketing, be it email marketing or webpage design.

👉 Reducing Risk: 
Conducting more tests with a broad spectrum of variations mitigates the risk of having no alternative if a strategy flops. It's like having a safety net of knowledge, ensuring that we always have a solid backup plan.

👉 Surprises in Results: 
More tests increase the probability of stumbling upon unexpected results. Ever thought a simple wording tweak in your call-to-action could bolster your click-through rates? Or a particular color scheme could be more appealing than initially thought? Testing unveils such surprising revelations.

👉 Never-Ending Improvement: 
Regular testing equates to constant learning, fostering improvement. Remember, what worked a year ago might not be effective today. Continuous testing keeps our strategies current and on the pulse of consumer behavior.

👉 Mastering Personalization: 
More variations mean deeper insights into customer preferences. This intelligence enables us to craft more personalized, and thus, potent marketing strategies.

That being said, while there are manifold benefits to running more tests and variations, we must balance this with resources and considerations for statistical significance.

Each additional test requires more design, implementation, and analysis efforts. Also, we must be wary of the possibility of false positives cropping up with more tests.

It's crucial to utilize statistical adjustments, like the Bonferroni correction (a simple, effective way to manage the risks associated with multiple comparisons) to maintain the integrity of our results.

More variations and more frequent A/B tests can turbocharge our marketing efforts.

However, remember to approach testing with a clear hypothesis and beware of over-testing.