What is A/B Testing?
A/B Testing is a simple concept of experimenting with two variations (or versions) of something to evaluate which one works better. Variation A and Variation B are tested against each other; one is assessed within a controlled environment and evaluated against variation B, which is set in an uncontrolled environment. This old and famous marketing experiment has a brilliant success rate with email marketing and conversion optimization.
It is also called ‘split testing’ – splitting the object into versions and testing them independently. Another version of this experiment is called ‘multi-variate testing’, which means testing more than two variations.
Where can we apply A/B Testing?
A/B Testing is a timeless technique that can be used in various stages of testing. You can apply it while developing a product, upgrading it, marketing a product, optimizing the landing page, sending out Facebook Ads, finalizing a headline for your content, and marketing your content through emails. A/B testing is such a simple yet robust process that every business must find a way to automate it, at least concerning data.
Why must you do an A/B Test?
A split test is a coherent way of evaluating ideas and performance that drives business metrics.
- Making the most of your traffic: Every visitor on your website is like a shopper in a physical store. Every session can teach you what and how the user interacts with the space you’ve created for them. This means every visitor is also an opportunity to make your space the best one. A/B testing can help you evaluate how your audience performs and enables you to fill the gap.
- Enhancing the experience: From product layouts to lean UI/UX, every element on the webpage contributes to a visitor’s experience. A split test can be performed to independently test all these small elements to achieve a seamless experience.
- Improving the RoI: From website developments to Facebook Ads, every minute spent understanding what makes the audiences click and act on the CTA is expensive. A/B testing before going live can help you justify the marketing expenses better.
- Small changes, significant improvements: From font sizes to background gradients, anything can be A/B tested. You can run these tests independently or together and provide the test version to your audiences.
When does A/B Testing make sense?
A/B Testing is a simple process; you’d think you could do it manually. However, there must be a set automated process to conduct these tests for statistically significant and solid results.
Here are a few things to take care of:
- Bias free: A/B Tests must be free of any discrimination. This must be conducted as a random experiment, and the control group must be picked at random.
- Traffic: It only makes sense to run this process when you get meaningful traffic. A smaller sample size may not yield statistically significant results for your business.
- Devoting the time: Owing to the scientific nature of the test, you must run the test for an appropriate amount of time. Jumping to conclusions and being impatient will be counter-intutive.
- Clarity of difference: Split tests are performed on two variations of a particular thing. This is why there must be clarity on the problem statements, the differences, and the reason behind having two variations of the same.
- High risk: A/B Tests are preferred when the stakes are relatively more significant. In low-risk situations, you can skip A/B tests and save yourself time.
Conclusion
A/B Testing is essential yet vigorous. For it to work, you must know what you are evaluating. Small changes can significantly impact business metrics, and A/B tests can help you make those decisions.
