Failed payments drain revenue and weaken the customer experience. They trigger abandonment, extra support workload, and chargebacks that add cost. The most reliable way to cut failure rates is to track the right e-commerce KPIs and use them to spot patterns. You will see where the checkout process slows, which decline codes dominate, and how retry logic performs. This article sets out the important KPIs and metrics and shows how to apply them in an e-commerce business.
You cannot fix what you cannot see. E-commerce KPIs give you a shared language for performance benchmarking, early issue detection, and strategy choices that scale. When you measure authorisation quality, checkout latency, and decline reasons, you can improve conversion rate, protect customer satisfaction, and control fraud losses.
Personalised experiences link to higher conversion. Statista reports that 63% of professionals saw a conversion rate gain from personalisation. That strengthens the case for measuring conversion rate alongside sales KPIs to validate what changes actually work.
Fraud costs keep rising, which makes tracking payment success rate and chargeback rate more important. Industry estimates reported losses of about USD 44.3 billion in 2024 and a forecast of over USD 100 billion by 2029.
Recurring payments face higher risk than one-off orders. Industry data suggests global authorisation declines average around 17%, and subscription or recurring payments can reach up to 30%. That is a clear signal to monitor retries and dunning flows separately from first-time purchases.
Customer loyalty is also at stake. 62% of customers do not return after a single failed transaction. Keep this in mind when setting response targets and incident priorities.
KPI |
Definition |
Why it matters |
Formula |
Benchmark |
Authorisation rate |
Share of authorisation attempts approved by issuers |
Indicates issuer acceptance health by market and method |
Approved authorisations ÷ authorisation attempts |
Domestic cards often 85–95%. Cross-border lower. Track by BIN and time of day |
Payment success rate |
Share of payment attempts that reach successful capture |
Combines gateway, risk checks, and issuer outcomes into one revenue KPI |
Successful captures ÷ payment attempts |
Aim for ≥ 90% on one-off domestic card payments where risk is low |
Decline code breakdown |
Mix of decline reasons from issuers and risk systems |
Shows where to act: insufficient funds vs. do not honour vs. authentication failures |
% by decline reason over a period |
Top three reasons should explain ≥ 70% of declines; each gets an action plan |
Checkout error rate |
Share of checkout starts that fail due to a technical or validation error |
Catches bugs, broken fields, and tokenisation errors that harm conversion |
Error-flagged checkouts ÷ checkout starts |
Keep under 1–2% and investigate spikes within the hour |
Checkout latency |
Median time from pay click to final response |
Long waits cause drop-offs and duplicate clicks |
Median response time in seconds |
Keep end-to-end under 5 seconds. Page load under 3 seconds, payment response under 2 seconds |
Retry recovery rate |
Share of soft-declined payments recovered by retries or updated credentials |
Measures revenue you win back from transient issues |
Recovered payments from soft declines ÷ initial soft-decline attempts |
20–40% on soft declines with structured retries and updated credentials |
Refund and chargeback rate |
Share of successful payments later refunded or disputed |
Indicates product fit, service quality, or fraud exposure |
(Refunds or chargebacks) ÷ successful payments |
Chargebacks well under 1%. Watch friendly fraud and reason codes |
Conversion rate (CR) |
Share of sessions that become orders |
Connects traffic, UX, and payment acceptance |
Orders ÷ sessions reaching checkout |
Varies by vertical. Track by device and traffic source |
Average order value (AOV) |
Average basket value of completed orders |
Helps judge revenue impact of recovery actions |
Gross revenue ÷ number of orders |
Track by channel and campaign; pair with conversion rate |
Customer lifetime value (CLV) |
Value a customer brings over time |
Links payment health to long-term value and churn rate |
AOV × purchase frequency × average lifespan |
Use gross and margin-adjusted variants for decisions |
Look at results by country, currency, BIN, issuer, scheme, payment method, device, browser, and time of day. Separate one-off purchases from recurring billing so you can see where involuntary churn rises.
If you handle high volumes, use APIs to feed a lightweight dashboard. Use APIs to feed data into a simple dashboard and set up alerts for red flags—like authorisation rates suddenly dropping, checkout pages loading too slowly, or a specific error code spiking.
Make sure forms are short, mobile-friendly, and have built-in error checks. Features like autofill and address suggestions make the process faster and cut down on mistakes. Research shows that smoother mobile checkouts lead to fewer errors and more completed purchases.
Route transactions by market, issuer, and method to improve approval quality. Keep credentials current with account updater services. Treat recurring payments as a separate stream and design a retry ladder that varies the day, time, and amount within sensible limits. Use domestic processing for cross‑border traffic where possible.
Keep forms short and mobile-friendly. Use clear field validation and straightforward error copy. Add address autocomplete to reduce input mistakes. Make the checkout process resilient to weak networks and cache key assets so pages load quickly.
For soft declines, space retries in line with issuer behaviour and cap the count to protect experience. For subscriptions, pair retries with account updater and a short reminder before renewal. Track retry recovery rate as a first‑class KPI and compare ladders by cohort.
Use risk scoring to focus step‑up checks where risk is high. Apply strong customer authentication when liability shift or issuer preference requires it. Watch chargeback rate and refund rate together, read top reason codes, and tune rules by market and method.
Aim for quick, consistent responses and keep end‑to‑end latency under five seconds. Prioritise incidents on the payment step. Add clear on‑page guidance when a payment fails and offer simple recovery options such as one‑click retry links or saved payment methods.
Lowering failed payments comes down to clarity and consistency. When you track the right metrics and act on what they tell you, problems stop slipping through the cracks. Authorisation rates, checkout performance, and recovery data are signals that show you exactly where to make changes for smoother payments and a better customer experience.
Antom helps make that process easier. With tools like Revenue Booster, Combined Payment, and real-time dashboards, you can monitor, adapt, and optimise your payment flow without adding extra complexity. And because Antom supports multiple regions and over 300 payment methods, you can give your customers a frictionless experience no matter where they are.