Whilst improving Mojito's PRNG & devising an ITP2.X workaround last year we introduced a modular splitting tool in Mojito that lets users split traffic with hash functions. We're amazed by the features that hash function
Running A/B tests or experiments on the web requires injecting lots of JS and CSS into your web app to change the look and feel of the page. Reckless deployments of this code can (and sometimes does) break web applicatio
The Mojito split testing framework's docs are built upon Facebook's Docosaurus. It's been a couple of months since we announced that we'd open sourced Mojito... and at long last you can now find all the documentation for
Experiments built entirely within SaaS platforms’ web interfaces often take longer and require unnecessary busy work. This article explores the reasons we would rather build experiments in an IDE and how Mojito supports
There's a reason tag managers are now the de facto for tag deployment. Before tag managers, you'd embed tags directly into your application. It could take weeks or months to deploy them inside large, monolithic apps... M
Update: We have just launched our documentation site for Mojito here . We're excited to open source Mojito the experimentation stack we've used to run well over 500 experiments for Mint Metrics' clients. It's a fully sou
We typically find that relying just on Optimizely, VWO or Convert.com's A/B test tracking has hidden costs: Restrictive analytics capabilities Worse site performance Increases your compliance obligations & compromises yo
Remember the good old days of JS errors? (Image credit) Building large, complex experiments introduces new logic, new code and sometimes new bugs. But most A/B testing tools don't perform error tracking or handling for y
Client side A/B testing tools get criticised for loading huge chunks of JS synchronously in the head (rightfully so). Despite the speed impact, these tools deliver far more value through the experiments they deliver. And
