> ## Documentation Index > Fetch the complete documentation index at: https://www.bitnob.dev/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > Bitnob API requests authenticate with an `X-Auth-Client` API key header against https://api.bitnob.com. > Always use the sandbox environment for testing. Never put live API keys in sample code. > Money amounts are integers in the smallest unit of the currency (satoshis for BTC, cents for fiat). Never use floats. > Every state-changing request takes a client-supplied `reference` and must be treated as idempotent on retry. > Quotes expire. Re-quote rather than reusing a stale quote id. # Module 16: Metrics and KPIs for card products > The metrics that describe a healthy card product, across engagement, spend, and operations. ## Learning objectives * Know the key metrics that define a healthy card product * Understand what to track for user engagement, spend behavior, and operational health * Learn how to combine transactional and behavioral KPIs * Use data to identify product gaps, fraud, revenue leakage, or growth opportunities * Know how to report success internally and to stakeholders ## Why metrics are critical for card products Virtual cards touch infrastructure, user behavior, and financial outcomes, which means they expose more data and risk than most product features. If you aren’t measuring: * How people are using their cards * What’s working and what’s failing * Where your fees and float are going * Which user segments are active Then you’re flying blind, and you won’t be able to grow or defend the product. ## Foundational KPI categories | Category | Examples | | - | - | | Adoption & Issuance | Cards created, users with active cards, issuance success rate | | Usage & Engagement | Number of transactions, frequency of spend, card retention | | Monetization & Revenue | Top-up volume,FX margins, fee revenue, card lifetime value | | Risk & Fraud | Decline rate, chargeback rate, refund volume, suspicious patterns | | Operational Health | Refund time, webhook success rate, failed top-up volume | ### 1. Adoption & issuance These metrics tell you how many users are creating and activating cards, and whether issuance is smooth. | Metric | Why It Matters | | - | - | | Cards issued per user | Are users creating multiple cards? Too few? Too many? | | Card activation rate | % of issued cards that received at least one transaction | | Issuance success rate | Are cards failing at creation? What’s causing it? | | Time to first top-up | How fast are users funding and using their cards? | Segment by source (wallet users vs. promo users), geography, or plan type. ### 2. Usage & engagement You’re not just measuring functionality. You’re measuring value. | Metric | Why It Matters | | - | - | | Transactions per active card per month | Low = dead cards, high = engaged users | | Average top-up amount | Indicates trust and card role (small spends vs. core spending) | | Time to first spend | Shorter = good UX, trust, and onboarding | | Spend per MCC or merchant | Are users paying for subscriptions, ads, services? | | Card churn rate | % of cards not used again after first transaction | These help you decide where to invest in features, UI improvements, or education. ### 3. Monetization & revenue Revenue doesn’t only come from usage volume. It comes from spend mix, FX exposure, and behavior patterns. | Metric | Why It Matters | | - | - | | FX margin per transaction | What are you earning from currency conversion? | | Average fee per user | Sum of card creation, top-up, cross-border, and usage-based fees | | Monthly card LTV | Total revenue generated per card over time | | Cross-border revenue vs. cost | Are international transactions profitable? | | Float margin (if any) | Difference between float usage and issuance cost | Be honest with yourself: if usage is high but revenue is low, your business model needs to evolve. ### 4. Risk & fraud metrics These protect your platform, partners, and users. | Metric | Why It Matters | | - | - | | Decline rate | High = poor UX or fraud attempts | | Auto-termination rate | Are your fraud rules working or misfiring? | | Refund volume as % of spend | Too high = merchant risk, refund farming | | Chargeback rate | Network compliance issue if too high (>1%) | | High-velocity users flagged | Prevent multi-account or automation abuse | You must measure not only who spends, but how and why they stop. ### 5. Operational KPIs These track performance of your integration and user experience. | Metric | Why It Matters | | - | - | | Webhook success rate | Are you receiving and handling events reliably? | | Average refund time | Delay here causes support friction | | Failed top-ups | Are users hitting balance, FX, or card status issues? | | Support tickets per 1000 users | Are users confused or confident? | | Card lifecycle delay (issue → fund → spend) | Shorter = better UX and onboarding | ## Advanced metrics for strategic teams Once your product is growing, add: * Revenue per MCC or merchant type * Top-up conversion rate: % of users who top-up after card issuance * Cost per issued card (including support and fraud losses) * Break-even point per card: at what point does each card become profitable * Cards per account type or pricing tier: detect usage-value gaps ## Recap * A virtual card product without metrics is unscalable and unaccountable * Measure more than transactions: measure behavior, timing, margin, and retention * Build dashboards for product, ops, and finance that surface the *why*, not just the *what* * Use metrics to improve onboarding, user education, risk, and monetization * Your card metrics should tie back to business KPIs: activation, trust, and margin This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.