Reporting
Reporting in NaafiPay is built around three principles: every report is filterable, every report can be exported as CSV or PDF, and every report can be scheduled to land in your inbox automatically. This page covers the four reports you will use most often — Payments, Subscriptions, Payouts, and Refunds — and explains how to combine filters to answer specific business questions like “how much did we collect from bKash last Friday after 6 PM?”.
Payments report
The Payments report is the master ledger of every payment attempt across every rail. Filter by date range, status (completed, pending, failed, cancelled), gateway, customer, amount range, or custom metadata key. The view shows gross, fee, and net amounts, plus a one-click link to the underlying invoice and customer.
Subscriptions report
The Subscriptions report shows your active recurring revenue with cohort analysis, churn rate by plan, and lifetime value per customer. You can drill into any subscription to see the renewal history, payment method, and dunning attempts.
Payouts report
The Payouts report lists deposits reported by your bank, MFS or payment provider, with a downloadable CSV showing each related payment record. This is the report your accountant will ask for at the end of every month.
Refunds report
The Refunds report tracks every refund processed, including the original payment, the reason code, who approved it, and the customer-facing status. Useful for compliance review and for spotting refund fraud patterns.
Custom segments
Save a filtered view as a named segment so you can return to it with one click. Common examples:
- Failed payments in the last 7 days — useful for support follow-ups
- High-value customers — payments above BDT 50,000
- One specific marketing campaign — filter by
metadata.campaign_id - Weekend revenue — filter by day of week
API access
Every report is also available through the GET /api/public/v1/payments, GET /api/subscriptions, and GET /api/payouts endpoints, which accept the same filter parameters. Build your own BI dashboard or pipe the data into a warehouse with a nightly cron job.