Get Orders History

Get Orders History

curl --request GET \
  --url 'https://api.example.com/{{orders_api_base_url}}/orders/history/'

const options = {method: 'GET'};

fetch('https://api.example.com/{{orders_api_base_url}}/orders/history/', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.example.com/{{orders_api_base_url}}/orders/history/",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/{{orders_api_base_url}}/orders/history/"

	req, _ := http.NewRequest("GET", url, nil)

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

require 'uri'
require 'net/http'

url = URI("https://api.example.com/{{orders_api_base_url}}/orders/history/")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Get.new(url)

response = http.request(request)
puts response.read_body

{
  "period_summary": {
    "date_from": "<string>",
    "date_to": "<string>",
    "total_orders": 123,
    "total_revenue": "<string>",
    "average_order_value": "<string>",
    "completion_rate": 123,
    "cancellation_rate": 123
  },
  "time_series_data": [
    {
      "period": "<string>",
      "orders_count": 123,
      "revenue": "<string>",
      "average_order_value": "<string>",
      "completion_rate": 123,
      "peak_hour": "<string>"
    }
  ],
  "partner_performance": {
    "UberEats": {},
    "DoorDash": {},
    "GrubHub": {},
    "LulaDirect": {}
  },
  "analytics": {
    "growth_trends": {},
    "seasonal_patterns": {},
    "performance_indicators": {},
    "recommendations": [
      {}
    ]
  },
  "comparison": {
    "previous_period": {},
    "growth_metrics": {},
    "trend_analysis": "<string>"
  }
}

GET

{orders_api_base_url}

orders

history

Get Orders History

curl --request GET \
  --url 'https://api.example.com/{{orders_api_base_url}}/orders/history/'

const options = {method: 'GET'};

fetch('https://api.example.com/{{orders_api_base_url}}/orders/history/', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.example.com/{{orders_api_base_url}}/orders/history/",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/{{orders_api_base_url}}/orders/history/"

	req, _ := http.NewRequest("GET", url, nil)

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

require 'uri'
require 'net/http'

url = URI("https://api.example.com/{{orders_api_base_url}}/orders/history/")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Get.new(url)

response = http.request(request)
puts response.read_body

{
  "period_summary": {
    "date_from": "<string>",
    "date_to": "<string>",
    "total_orders": 123,
    "total_revenue": "<string>",
    "average_order_value": "<string>",
    "completion_rate": 123,
    "cancellation_rate": 123
  },
  "time_series_data": [
    {
      "period": "<string>",
      "orders_count": 123,
      "revenue": "<string>",
      "average_order_value": "<string>",
      "completion_rate": 123,
      "peak_hour": "<string>"
    }
  ],
  "partner_performance": {
    "UberEats": {},
    "DoorDash": {},
    "GrubHub": {},
    "LulaDirect": {}
  },
  "analytics": {
    "growth_trends": {},
    "seasonal_patterns": {},
    "performance_indicators": {},
    "recommendations": [
      {}
    ]
  },
  "comparison": {
    "previous_period": {},
    "growth_metrics": {},
    "trend_analysis": "<string>"
  }
}

This endpoint provides access to comprehensive historical order data with powerful analytics capabilities. Ideal for business intelligence, performance reporting, trend analysis, and strategic planning.

This endpoint includes advanced analytics features like trend calculations, performance metrics, and comparative analysis across different time periods.

Query Parameters

string

required

The unique identifier of the store whose order history you want to retrieve

string

required

Start date for historical data retrieval (ISO 8601 format: YYYY-MM-DDTHH:mm:ssZ)

string

required

End date for historical data retrieval (ISO 8601 format: YYYY-MM-DDTHH:mm:ssZ)

string

default:"daily"

Data aggregation level: “hourly”, “daily”, “weekly”, “monthly”

boolean

default:"true"

Whether to include advanced analytics and performance metrics

boolean

default:"false"

Include comparison with the previous equivalent period

string

Filter by specific delivery platform for focused analysis

boolean

default:"false"

Include detailed item-level analytics in the response

Response

object

High-level summary for the requested time period

Show Period Summary

string

Start date of the period

string

End date of the period

integer

Total number of orders

string

Total revenue generated

string

Average order value

number

Percentage of orders completed successfully

number

Percentage of orders canceled

array

Data points broken down by the specified granularity

Show Time Series Point

string

Time period identifier

integer

Number of orders in this period

string

Revenue for this period

string

Average order value for this period

number

Completion rate for this period

string

Busiest hour in this period (if granularity allows)

object

Performance breakdown by delivery platform

Show Partner Performance

object

Performance metrics for UberEats orders

object

Performance metrics for DoorDash orders

object

Performance metrics for GrubHub orders

object

Performance metrics for LulaDirect orders

object

Advanced analytics and insights (when include_analytics=true)

Show Analytics Details

object

Order volume and revenue growth trends

object

Identified seasonal patterns and recommendations

object

Key performance indicators and benchmarks

array

AI-generated insights and recommendations for improvement

object

Comparison with previous period (when compare_period=true)

Show Period Comparison

object

Summary of the previous equivalent period

object

Growth percentages and changes

string

Analysis of trends between periods

Response Example

{
  "period_summary": {
    "date_from": "2024-01-01T00:00:00Z",
    "date_to": "2024-01-31T23:59:59Z",
    "total_orders": 1247,
    "total_revenue": "64,859.75",
    "average_order_value": "52.03",
    "completion_rate": 94.5,
    "cancellation_rate": 3.2
  },
  "time_series_data": [
    {
      "period": "2024-01-01",
      "orders_count": 45,
      "revenue": "2,341.25",
      "average_order_value": "52.03",
      "completion_rate": 96.0,
      "peak_hour": "19:00"
    },
    {
      "period": "2024-01-02",
      "orders_count": 38,
      "revenue": "1,977.50",
      "average_order_value": "52.04",
      "completion_rate": 95.0,
      "peak_hour": "18:30"
    }
  ],
  "partner_performance": {
    "UberEats": {
      "total_orders": 485,
      "total_revenue": "25,243.80",
      "average_order_value": "52.05",
      "completion_rate": 95.2,
      "average_prep_time": "18.5 minutes"
    },
    "DoorDash": {
      "total_orders": 412,
      "total_revenue": "21,424.20",
      "average_order_value": "52.01",
      "completion_rate": 94.8,
      "average_prep_time": "17.2 minutes"
    },
    "GrubHub": {
      "total_orders": 245,
      "total_revenue": "12,745.50",
      "average_order_value": "52.02",
      "completion_rate": 93.5,
      "average_prep_time": "19.8 minutes"
    },
    "LulaDirect": {
      "total_orders": 105,
      "total_revenue": "5,446.25",
      "average_order_value": "51.87",
      "completion_rate": 96.8,
      "average_prep_time": "15.3 minutes"
    }
  },
  "analytics": {
    "growth_trends": {
      "monthly_growth": "+12.5%",
      "revenue_trend": "increasing",
      "order_volume_trend": "stable_growth"
    },
    "seasonal_patterns": {
      "peak_days": ["Friday", "Saturday", "Sunday"],
      "peak_hours": ["17:00-21:00"],
      "seasonal_recommendations": "Consider extended hours on weekends"
    },
    "performance_indicators": {
      "efficiency_score": 87.5,
      "customer_satisfaction_proxy": 94.5,
      "revenue_per_hour": "$425.30"
    },
    "recommendations": [
      "Consider promoting during Tuesday-Thursday slow periods",
      "UberEats partnership showing strongest performance",
      "Weekend capacity could be increased to capture more demand"
    ]
  },
  "comparison": {
    "previous_period": {
      "total_orders": 1098,
      "total_revenue": "57,241.50",
      "average_order_value": "52.14"
    },
    "growth_metrics": {
      "order_growth": "+13.6%",
      "revenue_growth": "+13.3%",
      "avg_order_value_change": "-0.2%"
    },
    "trend_analysis": "Strong growth in order volume and revenue with stable order values, indicating successful customer acquisition and retention"
  }
}

Granularity Examples

Hourly Analysis (for operational optimization)

GET {{orders_api_base_url}}/orders/history/?store_id=449235c1-3d04-4519-998b-40d2a621e5e0&date_from=2024-01-15T00:00:00Z&date_to=2024-01-15T23:59:59Z&granularity=hourly

Weekly Trends (for strategic planning)

GET {{orders_api_base_url}}/orders/history/?store_id=449235c1-3d04-4519-998b-40d2a621e5e0&date_from=2024-01-01T00:00:00Z&date_to=2024-03-31T23:59:59Z&granularity=weekly&compare_period=true

Monthly Performance Review

GET {{orders_api_base_url}}/orders/history/?store_id=449235c1-3d04-4519-998b-40d2a621e5e0&date_from=2024-01-01T00:00:00Z&date_to=2024-12-31T23:59:59Z&granularity=monthly&include_analytics=true

Business Intelligence: Use the analytics data to identify growth opportunities, optimize operations, and make data-driven decisions about staffing, inventory, and marketing.

Data Freshness: Historical data is updated in near real-time. For the most current hour’s data, allow 15-30 minutes for complete processing.

Large Datasets: When requesting large date ranges with hourly granularity, responses may be substantial. Consider using daily or weekly granularity for broad analysis.

Use Cases

Business Intelligence Applications

Revenue Analysis

Monthly/quarterly revenue trends
Platform performance comparison
Seasonal revenue patterns

Operational Optimization

Identify peak hours for staffing
Optimize kitchen capacity planning
Improve order completion rates

Strategic Planning

Market penetration analysis
Growth opportunity identification
Partnership performance evaluation

Performance Monitoring

KPI tracking and benchmarking
Efficiency improvement initiatives
Customer satisfaction analysis

API Documentation - Legacy

API Documentation - Latest

Query Parameters

Response

Response Example

Use Cases

​Query Parameters

​Response

​Response Example

​Use Cases

Query Parameters

Response

Response Example

Use Cases