Analytics

What You Can Analyze

Prahsys offers four types of analytics to help you understand different aspects of your payment operations:

Payment Analytics - Track payment volume, success rates, revenue trends, and payment methods
Customer Analytics - Monitor customer acquisition, retention, and activity patterns
Transaction Analytics - Analyze transaction types, operation patterns, and success rates
Payout Analytics - Understand settlement timing, fee structures, and payout amounts

How Analytics Work

All analytics endpoints share a common set of powerful features that give you flexibility in how you query and group your data.

Time Periods

You can specify time periods in two ways:

Relative Periods - Use the forLast parameter to query recent time periods:

# Last 30 days
curl "https://api.prahsys.com/n1/organization/Z70B874W63DW/analytics/payments?forLast=30d" \
  -H "Authorization: Bearer YOUR_API_KEY"

Available values for forLast:

1h - Last hour
24h - Last 24 hours
7d - Last 7 days
30d - Last 30 days
3mo - Last 3 months
6mo - Last 6 months
1y - Last year

Absolute Periods - Use periodStart and periodEnd parameters to specify exact date ranges:

# Specific date range (January 2025)
curl "https://api.prahsys.com/n1/organization/Z70B874W63DW/analytics/payments?periodStart=2025-01-01T00:00:00Z&periodEnd=2025-01-31T23:59:59Z" \
  -H "Authorization: Bearer YOUR_API_KEY"

📘
You cannot use both forLast and periodStart/periodEnd in the same query. Choose one approach based on your needs.

Intervals and Grouping

The interval parameter controls how your data is grouped over time. This is essential for creating time-series charts and understanding trends.

Available intervals:

hour - Group by hour (best for short time periods like 1-24 hours)
day - Group by day (default, ideal for 7-30 days)
week - Group by week (good for 3-6 months)
month - Group by month (ideal for 6-12 months)
year - Group by year (for multi-year analysis)

# Daily breakdown for the last 30 days
curl "https://api.prahsys.com/n1/organization/Z70B874W63DW/analytics/payments?forLast=30d&interval=day" \
  -H "Authorization: Bearer YOUR_API_KEY"

# Monthly breakdown for the last year
curl "https://api.prahsys.com/n1/organization/Z70B874W63DW/analytics/payments?forLast=1y&interval=month" \
  -H "Authorization: Bearer YOUR_API_KEY"

Timezone Handling

By default, all analytics use UTC timezone. You can specify a different timezone using the timezone parameter to ensure intervals align with your business hours.

# Group by day in Phoenix timezone
curl "https://api.prahsys.com/n1/organization/Z70B874W63DW/analytics/payments?forLast=30d&interval=day&timezone=America/Phoenix" \
  -H "Authorization: Bearer YOUR_API_KEY"

Supported timezone formats:

IANA timezone identifiers: America/Phoenix, America/Los_Angeles, America/New_York, Europe/London, etc.
Common abbreviations: MST, MDT, PST, PDT, EST, EDT, etc.

❗️
Important
The timezone affects how intervals are calculated.
For example, with interval=day&timezone=America/Phoenix, data is grouped by Phoenix days (midnight to midnight Phoenix time), not UTC days.

Response Structure

All analytics endpoints return data in a consistent format, making it easy to work with different analytics types using the same code patterns.

Common Response Format

Every analytics response is wrapped in a standard API response:

{
  "success": true,
  "statusCode": 200,
  "offset": null,
  "limit": null,
  "data": {
    // Analytics data here
  }
}

Analytics Data Structure

Within the data object, all analytics responses follow this pattern:

{
  "periodStart": "2025-11-28T00:00:00.000000Z",
  "periodEnd": "2025-12-05T00:00:00.000000Z",
  "timezone": "UTC",

  // Period-level aggregate metrics
  "totalMetric1": 1234,
  "totalMetric2": 5678,

  // Interval configuration
  "interval": "day",

  // Per-interval breakdown
  "intervals": [
    {
      "intervalStart": "2025-11-28T00:00:00.000000Z",
      "intervalEnd": "2025-11-29T00:00:00.000000Z",
      "totalMetric1": 176,
      "totalMetric2": 811
    },
    {
      "intervalStart": "2025-11-29T00:00:00.000000Z",
      "intervalEnd": "2025-11-30T00:00:00.000000Z",
      "totalMetric1": 182,
      "totalMetric2": 824
    }
    // ... more intervals
  ]
}

Period-Level vs Interval-Level Data

Period-Level Data - The top-level metrics represent aggregates for the entire time period you queried. Use these for summary cards, totals, and overall statistics.

Interval-Level Data - The intervals array breaks down the same metrics into smaller time chunks based on your interval parameter. Use these for:

Time-series charts and graphs
Identifying trends over time
Spotting anomalies or patterns
Creating detailed timeline visualizations

Understanding the Intervals Array

Each object in the intervals array contains:

intervalStart - The beginning of this time interval (ISO 8601 timestamp)
intervalEnd - The end of this time interval (ISO 8601 timestamp)
All the same metrics as the period-level data, but only for this specific interval

Empty Intervals: If there's no activity during a particular interval, Prahsys automatically includes that interval with zero values. This ensures you have complete time-series data without gaps, making it easier to create charts and visualizations.

Example with an empty interval:

{
  "intervalStart": "2025-11-30T00:00:00.000000Z",
  "intervalEnd": "2025-12-01T00:00:00.000000Z",
  "numPaymentsCreated": 0,
  "numPaymentsProcessed": 0,
  "totalCapturedAmount": 0,
  "totalRefundedAmount": 0
  // ... all other metrics set to 0 or null
}

Charting with Intervals: The intervals array is designed to be used directly with charting libraries:

// Example: Creating a revenue chart
const chartData = response.data.intervals.map(interval => ({
  date: new Date(interval.intervalStart),
  revenue: interval.totalNetCapturedAmount
}));

// Now use chartData with your preferred charting library