Get top 10 data usage apps

Tool Name: airdroid_business_get_top_10_data_usage_apps

Risk Level: 🟢 Low Risk

Execution Mode: ⚡ Synchronous

Category: Reports & Analytics

Quick Start (Copy & Use)

In one sentence: Get the Top 10 apps by data consumption within a specified date range

What you need: StartDate (start date), EndDate (end date)

Success criteria: StatusCode=200 and ErrorMessage="" and HasData="Data available"

What to do next: Analyze app data consumption based on the FlowTopAppList, or combine with Get Top 10 Apps by Usage Duration to compare usage duration

Minimal request example:

{
  "StartDate": "2026-01-01",
  "EndDate": "2026-01-31"
}

Minimal response example:

{
  "FlowTopAppList": [
    {
      "pkg_id": "com.tencent.mm",
      "app_name": "WeChat",
      "icon_url": "https://cdn.example.com/wechat.png",
      "total_count": "976.56",
      "wifi_count": "488.28",
      "mobile_count": "488.28"
    }
  ],
  "HasData": "Data available",
  "StatusCode": 200,
  "ErrorMessage": ""
}

Recipes (Common Recipes)

Recipe 1: Query All Devices Top Data Usage Apps for the Last 30 Days

Scenario: Quick overview of app data consumption

{
  "StartDate": "2026-01-05",
  "EndDate": "2026-02-03",
  "OrderBy": 1
}

Recipe 2: Filter Data Usage by Group

Scenario: View app data consumption for a specific group only

{
  "StartDate": "2026-01-01",
  "EndDate": "2026-01-31",
  "GroupIds": [100],
  "OrderBy": 1
}

GroupIds can be obtained via the Get a Group ID by Group Name tool

Recipe 3: Only Count Mobile Data Usage

Scenario: Analyze apps with the highest mobile data consumption

{
  "StartDate": "2026-01-01",
  "EndDate": "2026-01-31",
  "OrderBy": 3
}

Recipe 4: Only Count WiFi Data Usage

Scenario: Analyze apps with the highest WiFi data consumption

{
  "StartDate": "2026-01-01",
  "EndDate": "2026-01-31",
  "OrderBy": 2
}

1. Overview

1.1 Description

Get the Top 10 apps ranked by data consumption within a specified date range, with support for group filtering and data type sorting.

1.2 When to Use

• Data cost control: Identify apps consuming the most data
• Bandwidth optimization: Find apps that need data throttling
• Policy development: Develop usage policies based on app data consumption
• Anomaly detection: Discover apps with abnormal data consumption

1.3 Execution Mode & Response

This is a synchronous operation that returns results immediately upon invocation.

• Return value: FlowTopAppList array containing Top 10 app data usage
• Data scope: Returns Top 10 apps by data consumption (sorted descending)

1.4 Prerequisites

1.5 Prerequisite Tools

2. Inputs

2.1 Parameter List

2.2 Parameter Details

`StartDate`

• Type: string
• Format: YYYY-MM-DD (e.g., 2026-01-01)
• Constraints: Cannot be a future date

`EndDate`

• Type: string
• Format: YYYY-MM-DD (e.g., 2026-03-31)
• Constraints:
  • Cannot be earlier than StartDate
  • Cannot be a future date
  • Date range with StartDate cannot exceed 90 days

`GroupIds`

• Type: number-array
• How to obtain: Via the Get a Group ID by Group Name tool
• Example:

  [100, 101]

`OrderBy`

• Type: number
• Options:

2.3 Parameter Combination Logic

• GroupIds and OrderBy are independent filter/sort conditions
• Date range StartDate to EndDate must be valid and not exceed 90 days

3. Outputs

3.1 Response Examples

Success response:

{
  "FlowTopAppList": [
    {
      "pkg_id": "com.tencent.mm",
      "app_name": "WeChat",
      "icon_url": "https://cdn.example.com/wechat.png",
      "total_count": "976.56",
      "wifi_count": "762.94",
      "mobile_count": "213.63"
    },
    {
      "pkg_id": "com.alibaba.android.rimet",
      "app_name": "DingTalk",
      "icon_url": "https://cdn.example.com/dingtalk.png",
      "total_count": "488.28",
      "wifi_count": "381.47",
      "mobile_count": "106.81"
    }
  ],
  "HasData": "Data available",
  "StatusCode": 200,
  "ErrorMessage": ""
}

No data response:

{
  "FlowTopAppList": [],
  "HasData": "No data available",
  "StatusCode": 200,
  "ErrorMessage": ""
}

Error response:

{
  "FlowTopAppList": [],
  "HasData": "No data available",
  "StatusCode": -1,
  "ErrorMessage": "Invalid start_date. Must be a non-empty string."
}

3.2 Field Descriptions

3.3 Data Unit Notes

Important: total_count, wifi_count, and mobile_count are all in MB (megabytes).

Field notes:

• total_count: Total data = WiFi data + Mobile data
• wifi_count: WiFi network data usage
• mobile_count: Mobile (cellular) network data usage

4. Examples

4.1 Basic Example: Query Last 30 Days App Data Usage Rankings

Request parameters:

{
  "StartDate": "2026-01-05",
  "EndDate": "2026-02-03"
}

Response:

{
  "FlowTopAppList": [
    {
      "pkg_id": "com.tencent.mm",
      "app_name": "WeChat",
      "icon_url": "https://cdn.example.com/wechat.png",
      "total_count": "1953.12",
      "wifi_count": "1525.88",
      "mobile_count": "427.25"
    }
  ],
  "HasData": "Data available",
  "StatusCode": 200,
  "ErrorMessage": ""
}

4.2 Advanced Example: Filter by Group for Mobile Data Only

Request parameters:

{
  "StartDate": "2026-01-01",
  "EndDate": "2026-01-31",
  "GroupIds": [100],
  "OrderBy": 3
}

4.3 Error Example: Empty Date

Request parameters:

{
  "StartDate": "",
  "EndDate": "2026-01-31"
}

Response:

{
  "FlowTopAppList": [],
  "HasData": "No data available",
  "StatusCode": -1,
  "ErrorMessage": "Invalid start_date. Must be a non-empty string."
}

5. Error Handling

5.1 AB Three-Layer Error Codes

5.2 Common Errors

5.3 Agent Self-Healing Decision Table

6. Best Practices

6.1 Performance Optimization

• Set reasonable date ranges: Smaller date ranges mean faster queries
• Use group filtering: If only interested in specific groups, setting GroupIds reduces data volume
• Choose data type as needed: Use OrderBy=3 when only interested in mobile data usage

6.2 Security Notes

🟢 Read operation: No special security requirements

6.3 Data Interpretation Tips

• All data values are in MB (string type); convert to numbers for calculations
• HasData="No data available" means no data, possibly because:
  • Filter conditions are too strict
  • Devices have not reported data usage
  • No data usage records within the date range
• wifi_count + mobile_count should equal total_count

7. Related Tools

7.1 Prerequisite Tools

7.2 Follow-up Tools

7.3 Similar Tools Comparison

8. Tool Chains

8.1 App Data vs Usage Duration Comparison Pattern

Scenario: Analyze the relationship between app data consumption and usage duration

Tool chain:

Get Top 10 Data Usage Apps → Get Top 10 Apps by Usage Duration → Comparative analysis

Steps:

1. Call Get Top 10 Data Usage Apps to get the Top 10 data usage apps
2. Use the same date parameters to call Get Top 10 Apps by Usage Duration for Top 10 by usage duration
3. Comparative analysis: High data + low duration = data-intensive apps; High duration + low data = lightweight apps

8.2 Group Data Usage Analysis Pattern

Scenario: Compare app data consumption across different groups

Tool chain:

Get a Group ID by Group Name (Group A) → Get Top 10 Data Usage Apps →
Get a Group ID by Group Name (Group B) → Get Top 10 Data Usage Apps → Comparative analysis

Steps:

1. Get Group A's GroupId and query Top data usage apps
2. Get Group B's GroupId and query Top data usage apps
3. Compare app data consumption differences between the two groups

8.3 WiFi vs Mobile Data Comparison Pattern

Scenario: Analyze app data consumption across different network types

Tool chain:

Get Top 10 Data Usage Apps (OrderBy=2) → Get Top 10 Data Usage Apps (OrderBy=3) → Comparative analysis

Steps:

1. Call this tool with OrderBy=2 to get WiFi data usage Top apps
2. Call this tool with OrderBy=3 to get mobile data usage Top apps
3. Compare and analyze app data consumption patterns across different networks