Split: Feature Management and Experimentation

Split Software

Split: Feature Management and Experimentation

Split Software

Speed up development cycles, reduce release risk, and measure the impact of every feature

Today, software applications are broken down into thousands of features, and those features have become the new unit of measurement and control. Every feature released represents an opportunity to learn about your customers’ experiences and preferences, allowing you to stay ahead of the competition, and actually move the needle for the business.

Unfortunately, for most engineering teams, gaining feature-level context is elusive due to:
  • Delivery delays: feature code sits in “merge hell” for weeks or months
  • Unreliable releases: 23% of releases fail, breaking the user experience
  • Misguided features: 80% of features have negative or no business impact

Why choose Split?

Split provides a unified Feature Data Platform to address these issues, helping development teams manage feature flags, monitor release performance, experiment and surface data to make ongoing, data-driven decisions. Split’s Azure DevOps integration increases agility and safety by weaving robust feature flagging capabilities into the development lifecycle. Once configured, users can associate Split feature flags with work items to track features in Azure Boards and leverage Split’s granular targeting capabilities to define custom rollouts to run in Azure Pipelines. In addition, customers can also power their Azure App Configuration with Split’s experimentation capabilities to truly understand what features are or aren’t resonating with your audiences.

As a result, engineering teams achieve greater momentum by deploying frequently, increasing the reliability of each release, and creating dynamic customer feedback loops.

Deploy frequently

Unblock teams by separating deploy from release. Merge code quickly and test in production.

Increase reliability of each release

Use progressive rollouts to monitor for impact. Get immediate feedback on errors and performance degradation and use the instant kill switch to address the source of the issue.

Create dynamic customer feedback loops

Ingest data, map features to guardrail and business metrics, and export to your preferred BI tools. Quickly and accurately attribute features to outcomes to drive data-driven decision-making.

Common use cases:

  • Continuous Integration/Continuous Delivery
  • Targeted rollouts
  • Dark launches
  • Canary releases
  • A/B testing
  • Ongoing experimentation
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