Experimentation

At Split, we “dogfood” our own product in so many ways. Our engineering and product teams are using Split nearly every day. It’s how we make Split better.

A/B testing is a powerful tool for learning about your users, understanding your features’ impact, and making informed business decisions. To ensure you make the best decisions and are extracting the most insights from your experiments, some experimental design guidelines are essential. These guidelines can be cumbersome or confusing at…

We all know a good digital experience from a bad one. Great digital experiences make our lives easier, and negative experiences drive us, and our business, elsewhere. What many users don’t realize is how difficult it is for product and engineering teams to know that the features they’re building will…

Product experimentation is the most effective way to determine what works best for end-users. You can measure engagement with a feature and hypothesize ways to improve that engagement, which will ultimately impact one or more critical business metrics. If you’re setting up an experiment, it’s mission-critical to implement A/B testing…

Every tech company, should be using a robust feature flag system. A well-built system will provide a host of value-adds and efficiencies for your dev team

I’m thrilled to announce that Split has closed a $33 million Series C investment round, led by Comcast Ventures. With this round, we’ve been able to invite in additional new investors including Microsoft’s m12, 01 Advisors, Atlassian, and ServiceNow. Along with our previous investors, Accel, Lightspeed Venture Partners, and Harmony…

The same tools and practices that make modern software delivery sustainable and efficient are what our organizations need to achieve greater adaptability.

Split hits 1T feature flags served per month, and analyzes how COVID-19 has accelerated trends in digital transformation and feature experimentation.

Visitor behavior may differ based on the day of the week or the time of the year. Be sure to account for that when defining the duration of your experiment.