At Fiverr, our Data Science Team is always looking for new methods to better understand our data, as well as create new protocols to ensure our web pages, products, and online campaigns are running effectively for our community.
We’re excited to share that we have developed our very own A/B testing guide to help benefit everyone from data scientists and analysts to product managers and marketing professionals. This A/B Testing Guide — which was developed based on internal feedback — includes a detailed structure, recommendations, and guidelines for planning, executing, and analyzing a test.
You may be wondering…what exactly is an A/B test and why should I consider using this for my online business performance? A/B Testing is an excellent way to test two variants within your business as it pertains to how something is performing online. This test compares two variants (A and B) of the same webpage to different groups of website visitors at the same time and creates a comparison to see which variant drives the most conversions. Whichever variant generates the highest conversion rate is, of course, the new preferred variant for your website’s performance!
While numerous articles, blog posts, and “how to” guides have been written on A/B testing, there are still a few things marketers and data experts seem to get wrong, and if not careful, these oversights can greatly impact results. As a cornerstone of product changes and system updates, these kinds of mistakes can lead teams down the wrong path and have significant business changes. You can find the full list of areas to watch out for in our handy guide.
Since we’ve implemented this version of testing internally, we saw an opportunity to help the many members of our community who manage various web pages and online campaigns. Our goal is to help them understand which methods they should continue working with and build higher conversion rates that will positively impact their business. Ultimately, we’re hoping that our new guide serves as a resource that helps greatly improve the way we test.
Have you used A/B testing for your business? Let us know in the comments below!