Key Metrics
Understanding the metrics that matter for checkout optimization
Last updated: 2025-01-16
Understanding your key metrics is essential for optimizing checkout performance. This guide explains what each metric measures, why it matters, and how to improve it.
Revenue Metrics
Total Revenue
The total value of all completed orders in the selected period.
{
"metric": "total_revenue",
"definition": "Sum of all order totals (after discounts, before shipping/tax)",
"calculation": "SUM(order_subtotal) for completed orders",
"good_for": "Overall business health",
"benchmark": "Varies by industry"
}CheckoutOS-Attributed Revenue
Revenue directly attributable to CheckoutOS features:
- Upsell product revenue
- Bundle discounts saved (vs buying separately)
- Incremental revenue from checkout extensions
{
"metric": "checkoutos_revenue",
"definition": "Revenue from products added via CheckoutOS features",
"includes": [
"Post-purchase upsell revenue",
"Bundle product revenue",
"Subscription conversion value"
],
"excludes": [
"Original cart items",
"Non-CheckoutOS upsells"
]
}Revenue Per Visitor (RPV)
Average revenue generated per checkout visitor. A key metric for A/B testing.
{
"metric": "revenue_per_visitor",
"calculation": "Total Revenue / Total Checkout Visitors",
"example": {
"total_revenue": 127450,
"visitors": 15420,
"rpv": 8.27
},
"why_it_matters": "Accounts for both conversion rate and AOV changes"
}Order Metrics
Average Order Value (AOV)
The average value of completed orders. CheckoutOS focuses on increasing AOV through upsells, bundles, and subscription conversions.
{
"metric": "average_order_value",
"calculation": "Total Revenue / Number of Orders",
"variants": {
"baseline_aov": "Orders without CheckoutOS features",
"enhanced_aov": "Orders with CheckoutOS features",
"aov_lift": "(Enhanced - Baseline) / Baseline * 100"
},
"example": {
"baseline": 78.20,
"enhanced": 94.50,
"lift": "20.8%"
}
}AOV Lift Target
Most stores see 15-30% AOV lift from CheckoutOS. If your lift is below 15%, review your upsell offers and targeting rules.
Order Count
Total number of completed orders. While CheckoutOS focuses on AOV, some features (like checkout extensions) can also improve order completion rate.
Conversion Metrics
Checkout Conversion Rate
Percentage of checkout visitors who complete their order.
{
"metric": "checkout_conversion_rate",
"calculation": "Completed Orders / Checkout Started * 100",
"benchmarks": {
"poor": "< 45%",
"average": "45-55%",
"good": "55-65%",
"excellent": "> 65%"
}
}Upsell Acceptance Rate
Percentage of customers who accept an upsell offer when shown.
{
"metric": "upsell_acceptance_rate",
"calculation": "Upsells Accepted / Upsells Shown * 100",
"benchmarks": {
"poor": "< 10%",
"average": "10-15%",
"good": "15-25%",
"excellent": "> 25%"
},
"factors": [
"Offer relevance",
"Discount attractiveness",
"Product fit",
"Timing"
]
}Bundle Attachment Rate
Percentage of orders that include a bundle offer.
{
"metric": "bundle_attachment_rate",
"calculation": "Orders with Bundles / Total Orders * 100",
"benchmarks": {
"average": "5-10%",
"good": "10-20%",
"excellent": "> 20%"
}
}Engagement Metrics
Offers Shown
Number of times CheckoutOS features were displayed to customers:
- Upsell offers presented
- Bundle suggestions displayed
- Checkout extensions rendered
Click-Through Rate (CTR)
Percentage of customers who interact with CheckoutOS features.
{
"engagement_metrics": {
"upsell_ctr": {
"definition": "Clicks on upsell 'Add' button / Views",
"good": "> 20%"
},
"bundle_ctr": {
"definition": "Bundle builder interactions / Views",
"good": "> 15%"
},
"extension_ctr": {
"definition": "Clicks on extension elements / Views",
"good": "Varies by extension"
}
}
}Customer Metrics
New vs Returning
Compare CheckoutOS performance across customer types:
- New customers — First-time buyers
- Returning customers — Previous purchasers
Returning customers typically have higher acceptance rates — use this data to adjust targeting.
Customer Lifetime Value Impact
Track how CheckoutOS affects long-term customer value:
- Subscription conversion rate
- Repeat purchase rate for upsell customers
- Average orders per customer
Setting Metric Goals
Goal Setting
- Start with benchmarks — Use industry averages as baselines
- Set realistic targets — 10-20% improvement is significant
- Track trends, not snapshots — Week-over-week matters more
- Focus on leading indicators — CTR predicts acceptance rate
Related Topics
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