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Feature flagging
Feature flags for B2B with unlimited seats
Get started quickly with a simple implementation and company-level targeting rules.
Safe and gradual feature rollouts. Roll out feature flags to a subset of customers to safely launch features.
Instant roll backs. A release went wrong? Instantly roll back the latest changes from the Bucket UI.
Company-level targeting rules. Powerful targeting rules that let you target companies, not just users.
Feature flag-based segmentation. Segment companies by feature flag access with feature flag filters.
Give all team members access with unlimited seats on all plans
Client-side evaluation. Evaluate flags with our React SDK or Browser SDK with just a few lines of code.
Low latency evaluation times. Our global network keeps initial evaluation round-trip time low. Subsequent lookups are instant.
Server-side evaluation. Use our Node.js SDK or API to evaluate flags on the backend.
Environments. Bucket apps support unlimited environments.
With Bucket’s feature evaluation, everyone on the product team optimizes for customer impact, consistently.
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Andreas Klinger
CTO
2
Feature evaluation
Qualitative and quantitative leading indicators
Automatically collect feature engagement metrics and feedback, then evaluate with a standardized framework.
Quantitative
Track feature adoption and engagement with ease
STARS feature-level engagement metrics. STARS is a built-in framework that tracks feature adoption and satisfaction per company, right out of the box.
Qualitative
Talk to the right customers at the right time, automatically
Feature-level satisfaction scores and feedback. No-code in-app surveys ask users for feature feedback after a meaningful number of interactions.
The STARS framework
Features, not events. STARS states lets you easily set feature adoption and retention thresholds.
Feature satisfaction distribution. See satisfaction distribution and track evolution over time.
Iterate for customer satisfaction. Review goal progress and use the qualitative feedback and standardized metrics to decide if a feature needs another iteration or is good as is.
Powerful company filters. Create company-level segments based on STARS or feedback scores.
Export your data for custom analysis. Automatically export feature data to Amazon S3 to enrich internal business metrics.
Save 5 hours per release on evaluation
With Bucket’s feature evaluation, everyone on the product team optimizes for customer impact, consistently.
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Niels Tindbæk, Head of Product
3
Feature iteration
Continuous evaluation and iteration workflow
Set goals to start the automated evaluation and iteration workflow. Keep track of progress without ever leaving Slack.
Set feature goals. Define custom goals using STARS metrics or start with a template based on adoption and satisfaction.
Track feature goal progress in Slack. Customer feedback and release reporting automatically flows into Slack.
Group Analytics included with every plan
Getting the relevant feature data to chase you, and not the other way around, is changing how we evaluate features, effortlessly. This is where Bucket gets it right.
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Paul Dariye, Engineering Manager
Release your next feature with bucket
Get started in minutes.
Documentation
