Test variants at scale
Store experiment splits in config, not code
Define experiment variants and traffic splits in Replane. Product teams adjust percentages without engineering involvement.
Before & after Replane
See how teams transform their workflow
Without Replane
Hardcoded experiment logic
Traffic splits are buried in code. Changing percentages requires a deploy.
Inconsistent user experience
Users see different variants on page refresh or across devices.
Slow iteration cycles
Product teams wait for engineering to adjust splits. Experiments take weeks to tune.
No real-time adjustments
Can't scale winners or pause losers quickly. Losing money while waiting for deploys.
With Replane
Config-driven experiments
Define variants and percentages in Replane. Change splits without touching code.
Consistent hashing
Users always see the same variant across sessions, devices, and page reloads.
Self-service for product
Product teams adjust experiments directly. No engineering bottleneck.
Instant traffic shifts
Scale winners to 100% or pause losers immediately. Changes apply in milliseconds.
Data-driven decisions
Run experiments without engineering overhead
Consistent Assignment
Same variant across sessions for each user
Instant Traffic Shifts
Changes propagate in under a second
No Deploys
Adjust experiment splits without code
Unlimited Variants
Test as many variants as you need
Three simple steps
Get up and running in minutes, not hours
Define variants
Create an experiment config with variant names and traffic percentages. No code changes required.
Assign consistently
Use our built-in hashing to ensure users see the same variant across sessions and devices.
Adjust in real-time
Shift traffic between variants instantly. Scale winners, pause losers—no deploy needed.
Why teams choose Replane
Built for developers who value speed, reliability, and control
Consistent assignment
Built-in hashing ensures users see the same variant across sessions, devices, and page reloads.
Real-time traffic shifts
Adjust variant percentages instantly. No code changes, no deploys, no waiting.
Track everything
Full audit log of all changes. Know exactly when traffic splits changed for accurate analysis.
Works with your stack
Official SDKs for all major languages and frameworks
1import { Replane } from '@replanejs/sdk'23interface Configs {4 'checkout-experiment': 'control' | 'variant_a' | 'variant_b'5}67const replane = new Replane<Configs>()89await replane.connect({10 baseUrl: 'https://replane.example.com',11 sdkKey: process.env.REPLANE_SDK_KEY12})1314// Get variant for user (consistent across sessions)15const variant = replane.get('checkout-experiment', {16 context: { userId: user.id }17})1819switch (variant) {20 case 'control':21 return renderClassicCheckout()22 case 'variant_a':23 return renderStreamlinedCheckout()24 case 'variant_b':25 return renderOneClickCheckout()26}2728// Track conversion for analytics29analytics.track('checkout_started', {30 experiment: 'checkout-experiment',31 variant,32 userId: user.id33})
Questions about A/B Testing
Common questions and answers
Replane uses consistent hashing based on your context properties (like userId). The same user always gets the same variant, even across different sessions or devices. The hash is deterministic and stable.
Yes! Each experiment is a separate config. You can run as many concurrent experiments as you need. Just make sure to track which experiments each user is exposed to for accurate analysis.
Replane focuses on experiment assignment, not analytics. Track experiment exposure events in your analytics tool (Mixpanel, Amplitude, etc.) and analyze results there. This separation of concerns gives you maximum flexibility.
Changes propagate instantly via SSE. New users get assigned based on updated percentages. Existing users may get reassigned if their hash bucket changes—this is expected behavior when adjusting splits.
Yes! Use override rules to target specific segments. For example, show variant_a only to premium users, or exclude certain regions from an experiment entirely.
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