Definition
A phased rollout is the practice of releasing a new feature or product change to progressively larger groups of users over days or weeks, rather than all at once. Each phase has specific monitoring criteria, and the release only advances to the next phase when the current one proves healthy.
Facebook (now Meta) popularized phased rollouts at scale. When Facebook redesigns a major surface like News Feed, it typically follows a pattern: employees first, then a small percentage of users in one geographic region, then 10% globally, then 50%, then 100%. Each phase runs for days or weeks while the team monitors engagement, performance, and support contacts. Instagram used this approach when rolling out Reels, initially testing in Brazil before expanding globally over 18 months. This allowed the team to iterate on the product based on real user behavior before committing to a worldwide launch.
Why It Matters for Product Managers
Phased rollouts give PMs something rare in product development: the ability to observe real user behavior at a safe scale before committing to a full release. This is fundamentally different from A/B testing, which measures the impact of variants. A phased rollout measures whether a change is safe and effective enough to ship to everyone.
For PMs, the biggest benefit is risk containment. If a redesigned checkout flow increases cart abandonment, catching that at 10% affects 10% of your revenue. Catching it at 100% is a crisis. Stripe phases every change to its payment processing pipeline because even a 0.1% increase in payment failures can affect millions of dollars in transaction volume.
Phased rollouts also give PMs data to make the case for or against a feature. Instead of debating hypothetically whether a change will "feel right" to users, the PM can point to actual metrics from the 10% cohort: "Support tickets are flat, NPS is up 3 points, and day-7 retention improved by 1.2%. Let us go to 50%."
How It Works in Practice
Internal (dogfooding) -- Release to your own team first. Catch obvious bugs, gather initial UX feedback, and ensure the feature works in production. Duration: 2-5 days. Criteria: no crashes, no data loss, team members can complete core workflows.
Private beta (50-200 users) -- Invite a selected group of real users. Choose users who represent your target audience and are willing to provide feedback. Duration: 1-2 weeks. Criteria: no critical bugs, task completion rates match or exceed the existing experience.
Limited rollout (5-10%) -- Enable the feature for a small random sample of production users via feature flags. Duration: 1-2 weeks. Monitor: error rates, latency, support ticket volume, key engagement metrics, and retention. Criteria: all metrics within 5% of baseline.
Expanded rollout (25-50%) -- If limited rollout metrics are healthy, expand. At this scale, you start to see the impact on aggregate business metrics. Duration: 1 week. Monitor: revenue metrics, funnel conversion, support volume. Criteria: no statistically significant regression in any business metric.
General availability (100%) -- Full rollout. Remove the feature flag (or keep it as a kill switch). Communicate the change through release notes, in-app messaging, or email. Continue monitoring for 1-2 weeks post-launch.
Common Pitfalls
No clear criteria for advancing between phases. Without pre-defined go/no-go metrics, the team debates subjectively whether to proceed. Set specific thresholds before starting: "We advance if error rate stays below 0.5% and retention is within 2% of baseline."
Phases that are too short. Running each phase for only 24 hours misses weekly usage patterns. A feature that performs well on Tuesday might degrade Saturday checkout traffic. Run each phase long enough to see full usage cycles.
Selecting biased cohorts. Rolling out to power users first can mask problems that affect casual users. Ensure your phased cohorts are representative of your full user base in terms of geography, usage frequency, and account type.
Treating the rollout as one-directional. Phased rollouts must include the option to pause or roll back. If metrics degrade at 25%, roll back to 10% and investigate. Teams that only know how to go forward eventually ship a problem to 100% of users.
Related Concepts
Canary Release is a specific implementation of phased rollout focused on infrastructure-level validation, typically at 1-5% of traffic.
Feature Flag is the mechanism most teams use to control which users see the new feature during each phase of the rollout.
Release Management is the broader process that a phased rollout fits into, covering planning, coordination, and post-release monitoring.Explore More PM Terms
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