Data-Driven Decision Making

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# Customer Segmentation
Segment A: High value, recent — reward loyalty
Segment B: High value, lapsed — re-engagement
Segment C: Low value, recent — upsell
Segment D: Low value, lapsed — low priority

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kpis = {
    "Traffic": {"current": 50000, "target": 60000, "unit": "visitors"},
    "Conversion": {"current": 3.2, "target": 4.0, "unit": "%"},
    "Revenue": {"current": 125000, "target": 150000, "unit": "$"},
    "CAC": {"current": 45, "target": 35, "unit": "$", "lower_better": True},
    "LTV": {"current": 280, "target": 350, "unit": "$"},
}

print("Marketing KPIs Dashboard:")
print(f"{'Metric':14} {'Current':>10} {'Target':>10} {'Progress':>10}")
print("-" * 50)

for name, data in kpis.items():
    lower = data.get("lower_better", False)
    if lower:
        progress = min(100, round(data["target"] / max(data["current"], 1) * 100))
    else:
        progress = min(100, round(data["current"] / data["target"] * 100))
    symbol = "$" if data["unit"] == "$" else ""
    print(f"{name:14} {symbol}{data[\"current\"]:>9} {symbol}{data[\"target\"]:>9} {progress:>9}%")