How to build PayPal payment dashboards in Metabase

PayPal processes your payments, refunds, and payouts across the web and marketplaces. Metabase is where you turn that transaction activity into shared dashboards for volume, net revenue, refunds, and disputes. Because Metabase reads from SQL databases, the reliable way to connect them is a small pipeline: sync PayPal into a database or warehouse on a schedule, then point Metabase at it. This guide walks through that path end to end — including a free option with no paid connector.

How do you connect PayPal to Metabase?

Metabase connects to SQL databases and warehouses — not to SaaS APIs directly, and there's no native PayPal connector. So connecting PayPal to Metabase means one thing: run a small pipeline that copies PayPal data into a database on a schedule, then connect Metabase to that database. Once the data lands, the models, metrics, and SQL later in this guide all work.

The good news: this doesn't require a paid tool. Use a managed connector if you want zero maintenance, or a free, code-based sync you host yourself — both are covered in Build the pipeline below, and in more depth in our guide to building a data pipeline.

What can you analyze from PayPal data in Metabase?

• Processed volume — gross volume and transaction count
• Net revenue — what lands after PayPal fees and refunds
• Refunds and disputes — refund rate, chargebacks, and win/loss
• Payment mix — by type, country, and currency
• Fees — cost of processing as a share of volume
• Payouts — settlement and withdrawals over time

Which PayPal dashboards should you build in Metabase?

How do you build the PayPal → Metabase pipeline?

For dashboards that need history and reliability, land PayPal data in a database first, then connect Metabase to that database.

Connector options

• Transaction Search API (free, first-party) — pull transaction history with fees and status into your own pipeline.
• Downloadable reports (free, CSV) — settlement and activity reports for periodic loads when an API pipeline is overkill.
• Airbyte — has a PayPal Transaction source for scheduled syncs. Free if you self-host the open-source version; paid on Airbyte Cloud.

Notes

• Land raw tables first, then build clean models on top.
• PayPal is multi-currency — convert to a single reporting currency or split by currency.
• Separate fees, refunds, and holds so net revenue is accurate.
• Transaction events can arrive as several rows (sale, fee, refund) — model a clean one-row-per-transaction view.

Can you generate a PayPal dashboard with AI?

Yes — and once PayPal data is synced into a database, this is the fastest way to a strong first draft. First give an AI assistant a way to read your Metabase schema and create questions and dashboards, then paste the prompt below. It builds the dashboard from your database tables and tells the agent to skip metrics the schema can't support instead of faking them.

Two ways to let an assistant query and build in Metabase

Both connect to a Metabase instance that's already pointed at your synced database — the pipeline above moves the data; these just let the assistant read and write Metabase. Pick whichever fits your setup:

Set up the Metabase MCP server

Enable it under Admin → AI → MCP, then point your client at the endpoint:

# Metabase built-in MCP (replace with your instance URL)
claude mcp add --transport http metabase https://your-metabase.example.com/api/metabase-mcp

{
  "mcpServers": {
    "metabase": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://your-metabase.example.com/api/metabase-mcp"]
    }
  }
}

Clients with native remote support can use a "url" field instead of the mcp-remote bridge. Confirm the current endpoint in the Metabase MCP docs.

Set up the Metabase CLI

Install it globally, then authenticate once (the binary is mb):

# Install the CLI (the binary is `mb`)
npm install -g @metabase/cli

# Authenticate once — opens your browser on Metabase v62+, or use an API key
mb auth login --url https://your-metabase.example.com
mb auth status

On Metabase v62+ mb auth login opens your browser; older servers fall back to an API key. A terminal-based assistant can then inspect your schema (mb db schemas, mb table get --include fields) and create content (mb card create, mb dashboard create) against the synced tables.

Prompt: build the PayPal Payments Overview dashboard

With MCP or the CLI connected, paste this into your assistant to generate the dashboard:

Create a polished Metabase dashboard for PayPal payments analytics using the
available PayPal tables in this database.

Goal: Help founders and finance leaders understand processed volume, net revenue
after fees, refunds, disputes/chargebacks, and payment mix from PayPal data.

First, inspect the schema and identify the available PayPal tables (often a
transactions export from the Transaction Search / Reporting API). Do not assume
exact table names. Map the raw data into these analytical concepts where
possible: Transactions, Orders/Payments, Captures, Refunds, Disputes, Fees, and
Payouts.

Important:
- Build the dashboard from durable database/warehouse tables (Transaction
  Search / Reporting API or a managed connector).
- Separate gross processed volume from net revenue (after PayPal fees and
  refunds).
- Compute payment/capture success rate on a consistent denominator.
- Show refunds and disputes as their own lines; don't silently net them into
  volume.
- Report in a single reporting currency; PayPal is multi-currency, so convert
  with a documented rate or split by currency.
- Do not claim Metabase connects natively to PayPal unless that is explicitly
  true in this environment.

Dashboard title: PayPal Payments Overview

Sections:
1. Executive summary (KPI cards): Processed volume; Net revenue; Fees %; Refund
   rate; Dispute rate; Average transaction value.
2. Volume & net revenue: Volume by day; Gross vs. net; Average transaction value.
3. Refunds & disputes: Refund rate; Disputes/chargebacks by month; Win/loss rate.
4. Payments mix: Volume by payment type, country, and currency; Capture success
   rate.
5. Fees & payouts: Fees as a share of volume; Payouts over time; Net settlement.

Filters: Payment type, Country, Currency, Date range.

Before finalizing, create or recommend reusable Metabase models:
modeled_paypal_transactions, modeled_paypal_refunds, and modeled_paypal_disputes.

Output: Build the dashboard if you have permission; otherwise provide the exact
questions, SQL, model definitions, and layout. Include caveats for any metric
that cannot be calculated from the available schema. Reconcile totals against
PayPal reports. Keep it practical, dense, and executive-readable. Avoid vanity
metrics.

How should you model PayPal data in Metabase?

Core tables

Modeling advice

• Build one clean modeled_paypal_transactions view: one row per transaction with gross, fee, and net.
• Convert all amounts to a single reporting currency in a model layer.
• Link refunds and disputes to their original transaction to net them.
• Define success rate on a consistent denominator (comparable transaction types).
• Reconcile modeled totals against PayPal's settlement reports.

Which PayPal metrics should you track in Metabase?

What SQL powers PayPal dashboards in Metabase?

These assume the modeled tables above (PostgreSQL dialect, amounts in minor units). Adjust identifiers to match your schema.

SELECT
  date_trunc('day', transaction_date)                 AS day,
  COUNT(*)                                            AS transactions,
  ROUND(SUM(amount) / 100.0, 2)                       AS gross_volume,
  ROUND(SUM(fee_amount) / 100.0, 2)                   AS fees,
  ROUND(SUM(amount - fee_amount) / 100.0, 2)          AS net_volume
FROM paypal_transactions
WHERE status = 'completed'
  AND transaction_date >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY 1
ORDER BY 1;

SELECT
  date_trunc('month', transaction_date)               AS month,
  COUNT(*) FILTER (WHERE txn_type = 'sale')           AS sales,
  COUNT(*) FILTER (WHERE txn_type = 'refund')         AS refunds,
  ROUND(100.0 * COUNT(*) FILTER (WHERE txn_type = 'refund')
    / NULLIF(COUNT(*) FILTER (WHERE txn_type = 'sale'), 0), 2)
    AS refund_rate_pct
FROM paypal_transactions
GROUP BY 1
ORDER BY 1;

SELECT
  date_trunc('month', opened_at)                      AS month,
  COUNT(*)                                            AS disputes,
  COUNT(*) FILTER (WHERE outcome = 'won')             AS won,
  ROUND(100.0 * COUNT(*) FILTER (WHERE outcome = 'won')
    / NULLIF(COUNT(*), 0), 1)                         AS win_rate_pct
FROM paypal_disputes
GROUP BY 1
ORDER BY 1;

What are common mistakes when analyzing PayPal in Metabase?

Related

Related analytics

Related metrics

Related integrations

FAQ