A/B Testing Experiments

📊 A/B testing analysis of key user flows in an e-commerce platform.
Includes four experiments with statistical validation and actionable insights.
Results are visualized in an interactive Tableau dashboard.

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📁 Repository Structure

This repository contains PDF reports of four A/B testing experiments focused on optimizing different steps of the user purchase journey:

1. Begin Checkout Test
   📌 Hypothesis: Enlarging the checkout button will increase the begin_checkout rate without reducing completed purchases.
   🎯 Goal: +5% begin_checkout, no negative impact on sessions with orders.

2. Mobile One-Click Order Test
   📌 Hypothesis: Simplifying checkout to a one-click flow on mobile will boost purchases without reducing new account creation.
   🎯 Goal: +15% add_payment_info, maintain new account creation rate.

3. Product Recommendations Test
   📌 Hypothesis: Showing only one recommended item (based on user history) will increase add_to_cart conversion.
   🎯 Goal: +5% add_to_cart rate.

4. Payment Information Test
   📌 Hypothesis: Introducing Google Pay and Apple Pay will increase add_payment_info and begin_checkout metrics.
   🎯 Goal: +2% in both add_payment_info/session and begin_checkout/session.

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📈 Dashboard

Explore the interactive Tableau dashboard with all test results here.