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GET
/
api
/
analytics
/
:eventId
curl -X GET https://api.gatepass.io/api/analytics/clx1234567890 \
  -H "Authorization: Bearer YOUR_TOKEN"

{
  "totalRevenue": 125500.00,
  "ticketsSold": 1247,
  "totalTickets": 1500,
  "salesByDay": [
    {
      "date": "2024-05-01",
      "sales": 45
    },
    {
      "date": "2024-05-02",
      "sales": 78
    },
    {
      "date": "2024-05-03",
      "sales": 120
    },
    {
      "date": "2024-05-04",
      "sales": 156
    }
  ],
  "salesByTier": [
    {
      "name": "VIP",
      "sold": 98,
      "total": 100
    },
    {
      "name": "Premium",
      "sold": 234,
      "total": 300
    },
    {
      "name": "General",
      "sold": 915,
      "total": 1100
    }
  ],
  "attendance": {
    "checkIns": 1089,
    "noShows": 158,
    "checkInRate": 87.3,
    "hourlyBreakdown": [
      {
        "hour": "10:00",
        "checkIns": 45
      },
      {
        "hour": "11:00",
        "checkIns": 123
      },
      {
        "hour": "12:00",
        "checkIns": 234
      },
      {
        "hour": "13:00",
        "checkIns": 189
      },
      {
        "hour": "14:00",
        "checkIns": 267
      },
      {
        "hour": "15:00",
        "checkIns": 156
      },
      {
        "hour": "16:00",
        "checkIns": 75
      }
    ],
    "peakHours": [
      {
        "hour": "14:00",
        "count": 267
      },
      {
        "hour": "12:00",
        "count": 234
      },
      {
        "hour": "13:00",
        "count": 189
      },
      {
        "hour": "15:00",
        "count": 156
      }
    ]
  },
  "geography": {
    "cities": [
      {
        "city": "Lagos",
        "count": 567,
        "percentage": 45.5
      },
      {
        "city": "Abuja",
        "count": 234,
        "percentage": 18.8
      },
      {
        "city": "Port Harcourt",
        "count": 156,
        "percentage": 12.5
      },
      {
        "city": "Ibadan",
        "count": 123,
        "percentage": 9.9
      },
      {
        "city": "Kano",
        "count": 89,
        "percentage": 7.1
      }
    ],
    "countries": [
      {
        "country": "Nigeria",
        "count": 1098,
        "percentage": 88.0
      },
      {
        "country": "Ghana",
        "count": 78,
        "percentage": 6.3
      },
      {
        "country": "Kenya",
        "count": 45,
        "percentage": 3.6
      },
      {
        "country": "South Africa",
        "count": 26,
        "percentage": 2.1
      }
    ]
  }
}

Documentation Index

Fetch the complete documentation index at: https://mintlify.com/GoodnessFx/GatePass/llms.txt

Use this file to discover all available pages before exploring further.

Retrieve detailed analytics for an event, including sales data, attendance metrics, geographic distribution, and time-based patterns. Available to event organizers only.

​
Authentication

​
Authorization
string
required
Bearer token for authentication (organizer role required)

​
Path Parameters

​
eventId
string
required
The unique identifier of the event

​
Response

​
totalRevenue
number
Total revenue from ticket sales
​
ticketsSold
number
Total number of tickets sold
​
totalTickets
number
Total event capacity
​
salesByDay
array
Daily sales breakdown
​
salesByTier
array
Ticket sales by tier
​
attendance
object
Attendance and check-in metrics
​
geography
object
Geographic distribution of ticket buyers
curl -X GET https://api.gatepass.io/api/analytics/clx1234567890 \
  -H "Authorization: Bearer YOUR_TOKEN"

{
  "totalRevenue": 125500.00,
  "ticketsSold": 1247,
  "totalTickets": 1500,
  "salesByDay": [
    {
      "date": "2024-05-01",
      "sales": 45
    },
    {
      "date": "2024-05-02",
      "sales": 78
    },
    {
      "date": "2024-05-03",
      "sales": 120
    },
    {
      "date": "2024-05-04",
      "sales": 156
    }
  ],
  "salesByTier": [
    {
      "name": "VIP",
      "sold": 98,
      "total": 100
    },
    {
      "name": "Premium",
      "sold": 234,
      "total": 300
    },
    {
      "name": "General",
      "sold": 915,
      "total": 1100
    }
  ],
  "attendance": {
    "checkIns": 1089,
    "noShows": 158,
    "checkInRate": 87.3,
    "hourlyBreakdown": [
      {
        "hour": "10:00",
        "checkIns": 45
      },
      {
        "hour": "11:00",
        "checkIns": 123
      },
      {
        "hour": "12:00",
        "checkIns": 234
      },
      {
        "hour": "13:00",
        "checkIns": 189
      },
      {
        "hour": "14:00",
        "checkIns": 267
      },
      {
        "hour": "15:00",
        "checkIns": 156
      },
      {
        "hour": "16:00",
        "checkIns": 75
      }
    ],
    "peakHours": [
      {
        "hour": "14:00",
        "count": 267
      },
      {
        "hour": "12:00",
        "count": 234
      },
      {
        "hour": "13:00",
        "count": 189
      },
      {
        "hour": "15:00",
        "count": 156
      }
    ]
  },
  "geography": {
    "cities": [
      {
        "city": "Lagos",
        "count": 567,
        "percentage": 45.5
      },
      {
        "city": "Abuja",
        "count": 234,
        "percentage": 18.8
      },
      {
        "city": "Port Harcourt",
        "count": 156,
        "percentage": 12.5
      },
      {
        "city": "Ibadan",
        "count": 123,
        "percentage": 9.9
      },
      {
        "city": "Kano",
        "count": 89,
        "percentage": 7.1
      }
    ],
    "countries": [
      {
        "country": "Nigeria",
        "count": 1098,
        "percentage": 88.0
      },
      {
        "country": "Ghana",
        "count": 78,
        "percentage": 6.3
      },
      {
        "country": "Kenya",
        "count": 45,
        "percentage": 3.6
      },
      {
        "country": "South Africa",
        "count": 26,
        "percentage": 2.1
      }
    ]
  }
}

​
Access Control

Only the event organizer (creator) can access analytics for their events. Attempting to view analytics for events created by other users will result in a 403 Forbidden error.

​
Use Cases

​
Sales Performance

Track daily sales trends to identify:
  • Peak sales periods
  • Impact of marketing campaigns
  • Last-minute ticket purchases
  • Tier popularity

​
Attendance Optimization

Use attendance data to:
  • Plan staff allocation during peak hours
  • Identify optimal check-in start times
  • Reduce wait times at entry
  • Predict no-show rates

​
Geographic Insights

Understand your audience to:
  • Target marketing in high-performing regions
  • Plan future event locations
  • Arrange transportation and accommodations
  • Tailor content to regional preferences
Analytics are updated in real-time as tickets are sold and attendees check in. Refresh the data during your event to monitor live attendance.

​
EventAnalytics Model

Analytics data is also stored in the EventAnalytics table with daily snapshots:
  • ticketsSold: Cumulative tickets sold
  • revenue: Total revenue
  • uniqueBuyers: Number of unique customers
  • checkIns: Total check-ins
  • checkInRate: Attendance percentage
  • noShows: Tickets purchased but not used
  • topCountries: JSON array of country data
  • topCities: JSON array of city data
  • hourlyBreakdown: JSON array of time-based patterns

​
Chart-Ready Data

All response arrays are formatted for direct use with charting libraries: 
// Line chart: Sales over time
const salesChart = {
  labels: analytics.salesByDay.map(d => d.date),
  data: analytics.salesByDay.map(d => d.sales)
};

// Bar chart: Check-ins by hour
const attendanceChart = {
  labels: analytics.attendance.hourlyBreakdown.map(h => h.hour),
  data: analytics.attendance.hourlyBreakdown.map(h => h.checkIns)
};

// Pie chart: Sales by tier
const tierChart = {
  labels: analytics.salesByTier.map(t => t.name),
  data: analytics.salesByTier.map(t => t.sold)
};

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