Conversion Rate Optimization (CRO) increases the percentage of visitors who take desired actions.
CRO Process
- Analyze current data
- Identify drop-off points
- Hypothesize improvements
- A/B test changes
- Implement winners
Conversion Rate Optimization (CRO) increases the percentage of visitors who take desired actions.
# Conversion Rate CR = (Conversions / Visitors) × 100 # A/B Testing Variant A: 500 visitors, 25 conversions = 5% Variant B: 500 visitors, 35 conversions = 7% Lift: (7-5)/5 × 100 = 40% improvement
def conversion_metrics(visitors, conversions, revenue): conv_rate = (conversions / visitors * 100) if visitors else 0 avg_order = (revenue / conversions) if conversions else 0 revenue_per_visitor = (revenue / visitors) if visitors else 0 return { "conversion_rate": f"{conv_rate:.2f}%", "avg_order_value": f"${avg_order:.2f}", "revenue_per_visitor": f"${revenue_per_visitor:.2f}", "annual_projection": f"${revenue_per_visitor * visitors * 365:,.0f}" } m = conversion_metrics(visitors=5000, conversions=150, revenue=12000) print("CRO Metrics:") for k, v in m.items(): print(f" {k:22}: {v}")
What is A/B testing?
Testing two versions of a page/element to see which performs better. Only one variable changes at a time.
What is a conversion?
A conversion is when a visitor completes a desired action (purchase, signup, etc).
Define hypothesis, create variants, split traffic 50/50, run for statistical significance (usually 2-4 weeks), analyze results, implement winner.