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FE&R Quick Start Guide: Introduction

Welcome to the Quick Start Guide for Feature Experimentation & Rollout (FE&R)!

Whether you are a Product Manager aiming to drive business impact through smarter, safer releases, or a Developer looking to implement robust feature flags and experimentation in your codebase, this guide is designed to get you up and running quickly and confidently.

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What is FE&R?

FE&R is AB Tasty’s unified platform for feature experimentation, progressive rollout, and server-side testing. It empowers teams to test new features, business logic, and user experiences across web and mobile, before scaling to your entire user base. With FE&R, you can launch, measure, and iterate on product changes with minimal risk and maximum business value.

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Who is this guide for?

  • Product Managers: Learn how to define experiments, set business KPIs, and monitor the impact of new features, without relying solely on technical teams.

  • Developers: Get step-by-step instructions to integrate FE&R SDKs, implement feature flags, and track events for robust experimentation and safe rollouts.

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What’s Next? Your FE&R Onboarding Journey

To make your onboarding as smooth as possible, we’ve broken down the process into clear, actionable steps. Follow the stepper below to see where you are and what’s coming next:

1

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Access and setup

  • Get access to the FE&R platform and invite your team.

  • Set up user roles and permissions.

2

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Define Your First experiment

  • Identify a feature or business logic to test.

  • Set clear KPIs and success metrics.

3

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SDK integration

  • Install and configure the SDK for your stack (React, iOS, Android, etc.).

  • Select IDs and user context for targeting.

4

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Create Flags and Variations

  • Product Managers: Use the dashboard to define flags, variations, and targeting rules.

  • Developers: Implement flags in your codebase.

5

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Event Tracking & KPI Setup

6

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Launch & Monitor

  • Soft launch your experiment, monitor results, and progressively roll out to more users.

  • Analyze results and iterate based on insights.

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