Feature Flags and
Split Testing for
While using feature flags, continuous delivery and constant innovation involve several teams working together across an organization. Built for engineers, product managers, data scientists, and software architects, Split is the hub that gives each team in your organization what it needs to help you meet your product KPIs.
- Make the production launch a “non-event.”
- Minimize time spent on rollbacks or emergency fixes that will eat into my next sprint's work.
- Deliver products faster.
- Focus on building products rather than infrastructure that is not a core competency.
- A single platform for engineers to collaborate with product managers (PMs) and other stakeholders.
- A visual control panel with rich targeting capabilities.
- Packaged with the critical tools required by engineers to run a production system: permissioning, tagging, and audit logging.
- Out-of-the-box SDKs and open APIs.
- Impact company product metrics through feature development.
- Iterate faster, increase feature adoption, and accelerate revenue growth.
- Use feature flags for successful and safe product launches.
- A feature experimentation platform that shows the impact of every feature release on company metrics.
- A visual control panel for rich feature flag targeting capabilities without requiring engineering assistance.
- Unlock the power of data to derive deeper insights with advanced analytics.
- Influence the building of better products through data science.
- A visual control panel for rich targeting capabilities.
- An experimentation dashboard that shows the impact of every feature release on company metrics.
- A statistics engine that establishes causality between feature releases and company metrics.
- An ability to experiment with non-visual data products.
- Select the best tools and platforms for the organization to standardize on.
- Resolve complex technical challenges that span multiple dev teams.
- Keep the architecture up to speed with developing trends that impact speed, risk, and quality of technical decision making (e.g. evaluating serverless, migrating toward containers or introducing IoT with a consistent experience across devices and channels).
- Robust data and insight into the impact of granular components of the codebase.
- Rich set of APIs to tailor the feature release process and experimentation to fit a unique environment.
- Flexibility for developers to experiment with serverless functions and phase in the exposure of these new services to users.
- Enable the use of new microservices using containers, while limiting the risk of disrupting the main application.
- Ensure the same features execute for a given user, regardless of the client, while experimenting with new features.