⚡️ A/B Testing

A/B testing is a controlled experiment where you compare two versions to see which performs better.

At its core: change one thing → measure the impact.

Core idea:
Same users, different variants, measurable outcome.

Where it is used:

📊 Product feature launches
🛒 Conversion optimization
📧 Email marketing
🌐 UI/UX decisions
📱 Growth experiments

It's purpose is to make decisions based on real user behavior instead of opinions.

Simple flow:
1️⃣ Split users randomly
2️⃣ Show version A and B
3️⃣ Measure key metric
4️⃣ Pick the winner

Things to know:

🎯 Needs enough sample size
⚖️ Randomization is critical
⏳ Stop only after statistical significance
🚫 Testing too many changes at once breaks results

✅ A/B testing = scientific method for product decisions.