Documentation · Getting Started

Quick Start Guide

Get your first growth experiment running in under 5 minutes. This guide walks you through everything you need to start testing hypotheses and driving measurable growth.

💡 Tip: Complete the onboarding wizard first - it configures AI features to match your business context, making all suggestions more relevant from day one.

What You'll Learn

In this quick start guide, you'll learn how to set up your GrowthLab account, navigate the platform, and launch your first experiment using our AI tools.

Step 1: Create Your Account

Begin your growth experimentation journey by signing up and completing our intelligent onboarding process:

  1. Sign up at the signup page
  2. Complete the onboarding wizard by providing information about your business, growth objectives, and key performance metrics
  3. Review AI-generated experiments tailored to your specific context - we'll automatically suggest 3–5 high-potential experiments based on your goals

The onboarding process takes approximately 3–5 minutes and helps our AI understand your unique business needs.

Step 2: Navigate Your Dashboard

Your GrowthLab dashboard is organized into three core sections designed for maximum efficiency:

Experiment Board Visualize your entire pipeline across three stages, Drafted, Running, and Captured, with a drag-and-drop interface that keeps your team aligned. Each card leads with its title and one ICE priority cue plus its test method and a grounding marker, so you can scan the board fast. The full ICE / ROTI / AAA scorecard lives in the experiment detail view and the Database table.

The experiment database with ICE, ROTI, and AAA scores and status

Analytics Dashboard Track key performance indicators including experiment velocity, win rates, pipeline health, and activation progress. Monitor the ROI of your experimentation program with real-time insights.

Learnings Library Build institutional knowledge by capturing insights from completed experiments. Our AI Learning Synthesis engine identifies patterns across your learnings to surface meta-insights and inform future hypothesis development.

Step 3: Launch Your First Experiment

Create a structured, data-driven experiment in minutes:

  1. Click "New Experiment" to add one manually, or use "Generate next batch" to have the AI draft a batch from a goal you set
  2. Define your hypothesis using the structured If/Then/Because format - or let the AI Hypothesis Refiner improve it for you
  3. Run the AI Metric Validator to ensure your chosen metric is appropriate and get sample size guidance
  4. Assign ICE scores (or use Smart ICE Editor with AI suggestions) to prioritize effectively
  5. Launch the Execution Wizard to get a step-by-step implementation plan, draft copy, and pre-launch checklist

⚠️ Warning: Don't skip the hypothesis structure step. Vague hypotheses lead to ambiguous results that can't inform future decisions.

Step 4: Track & Learn

As your experiment runs:

Next Steps

Now that you've created your first experiment, dive deeper into best practices:

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