Most popular A/B testing tools in 2019
There are plenty of articles on the Top 17 A/B Testing Platforms (number 8 will blow your mind!) … but which ones do people actually use?
I checked BuiltWith.com to find out.
Who’s got the most users?
Google Optimize! Followed closely by Optimizely. VWO’s in the running.
Out of the 9 platforms listed, the top 2 tools are installed on 80% of total websites. The top three tools account for 91% of total installs.
What’s missing here?
Not all tools are represented!
I could’ve included another ten platforms with lower usage than Maxymiser, but left them out to simplify the graph.
I also left out one app that BuiltWith classifies as an A/B testing tool: Mixpanel.
While it’s got A/B testing functionality built in, I’ve only ever encountered teams who used it for passive analytics. (If you’re using Mixpanel for A/B testing, please send me an angry email.)
Speaking of “not using the functionality” …
Not all of these sites are actually using the tool they’ve installed
This is a big one. It’s especially important to consider with Google Optimize, which is free.
But even with paid tools, it’s distressingly common to buy it, install it, maybe run a couple tests, and never touch it again.
So Optimizely might be installed on > 150,000 sites, but how many are currently running a campaign?
These tools serve different markets
Optimizely and Adobe Target are enterprise products. AB Tasty has a lot of customers in Europe.
I know little to nothing about the other tools. Dynamic Yield is installed on fewer than 5,000 sites. But for all I know, 8 of the 10 largest media sites in the world could be using it.
Why does this matter?
If you’re selecting an A/B testing tool, it’s worth considering the size of the user base.
More users mean it’s easier to hire people who know the tool. More users also mean more helpful blog posts, or answers in forums, or instructional videos on YouTube. (Fewer users might mean a better deal, more customized service, or hipster points if you pick a tool that’s growing in popularity.)
If you’re just getting into A/B testing, you should learn at least one of the top three tools. If you already know one, you should learn another.
If you’re learning one of the tools in the long tail, have fun! But be aware that it’s likely your next company will be using something different.
Don’t spend too much time with the minutiae of one platform’s custom settings or taxonomy. (“We create Experience Nodes which Visiting Cookie Holders can Trigger via Technographic Criterial Markers™!”)
Just learn what you need to get experiments and campaigns live. Happy testing!