# Trivago Email Scraper (`scraper-engine/trivago-email-scraper`) Actor

Trivago Email Scraper extracts publicly available hotel email addresses from Trivago listings. Build targeted contact lists by city or property type. Ideal for travel marketers, agencies, and B2B suppliers running hotel outreach campaigns.

- **URL**: https://apify.com/scraper-engine/trivago-email-scraper.md
- **Developed by:** [Scraper Engine](https://apify.com/scraper-engine) (community)
- **Categories:** Lead generation, Automation, Travel
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$19.99/month + usage

To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors

## What's an Apify Actor?

Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).


# README

### **Social Media** Email Scraper 📱

The Trivago Email Scraper allows users to **extract** valuable **contact** information from hotel listings on Trivago. This includes email addresses, phone numbers, and other essential details for communication purposes.

The tool is designed to provide structured and organized **data** that can be used for marketing, outreach, or **data**base creation. By automating the **extract**ion process, users can save time and ensure accuracy in their **data** collection efforts.

The scraper is capable of handling large-scale **data** **extract**ion tasks while maintaining compliance with legal and ethical standards. It is suitable for businesses of all sizes looking to leverage Trivago's extensive hotel directory for their operations.

The **extract**ed **data** is presented in a clean format, ready for immediate use or further processing.

Trivago Email Scraper is designed to extract contact information from hotel listings on Trivago efficiently and accurately. It is a powerful tool for businesses looking to streamline communication with hotels and hospitality providers.

Using the Trivago Email Scraper, you can automate the process of gathering emails, saving time and reducing manual effort. This tool is ideal for those in the travel industry seeking reliable data extraction solutions.

With advanced scraping capabilities, the Trivago Email Scraper ensures high-quality results while adhering to legal and ethical guidelines. It simplifies the process of collecting contact details from hotel websites.

### Support and feedback

- **Bug reports**: Open a ticket in the repository Issues section
- **Custom features**: Contact our enterprise support team
  *Email: dev.scraperengine@gmail.com *
### Extractable Data Table 📊
| Data Type | Description |
| --- | --- |
| Email Addresses | Extract verified email addresses from Trivago hotel listings. |
| Phone Numbers | Retrieve contact phone numbers provided by hotels on Trivago. |
| Hotel Names | Collect the names of hotels listed on Trivago for identification purposes. |
| Hotel Locations | Extract location details such as city and country for each hotel. |
| Website URLs | Gather official website links of hotels listed on Trivago. |
| Ratings and Reviews | Scrape ratings and reviews associated with hotels on Trivago. |
| Pricing Information | Extract pricing details for hotel listings on Trivago. |
| Amenities | Retrieve information about amenities provided by hotels listed on Trivago. |

### Key Features of **Social Media** Email Scraper

Here are the **standout features** that make the **Social Media** Email Scraper a **top-tier tool** for **marketers**, **agencies**, and **researchers**:

- ⭐ **Automated** extraction of emails and contact details from Trivago hotel listings
- ⭐ User-friendly interface requiring minimal technical expertise
- ⭐ Supports large-scale data extraction for extensive hotel directories
- ⭐ Provides structured and organized data ready for immediate use
- ⭐ Ensures compliance with legal and ethical standards during data scraping
- ⭐ Offers high accuracy and reliability in extracting relevant information
- ⭐ Includes filtering options to target specific hotel categories or locations
- ⭐ Compatible with various file formats for exporting extracted data
- ⭐ **Regular** updates to adapt to Trivagos website changes
- ⭐ **Fast** processing speeds for efficient data collection

### How to use **Social Media** Email Scraper 🚀

Follow this **simple, step-by-step guide** to start extracting **Social Media** emails today:

1. ✅ Install the Trivago Email Scraper software on your device
2. ✅ Open the application and **log in** using your credentials
3. ✅ Enter the URL of the Trivago page you wish to scrape data from
4. ✅ **Select** the data types you want to extract such as emails or phone numbers
5. ✅ Apply filters to narrow down the search to specific hotels or locations if needed
6. ✅ **Start** the scraping process and monitor progress through the interface
7. ✅ **Review** the extracted data once the process is complete
8. ✅ **Export** the data to your preferred file format for further use

### Use Cases 🎯

Marketing Campaigns
🎯 Extract hotel email addresses for targeted marketing campaigns
🎯 Build a contact database for email outreach

Business Development
🎯 Gather contact information for partnership opportunities
🎯 **Identify** potential clients in the hospitality industry

Competitor Analysis
🎯 **Analyze** hotel pricing and amenities for competitive insights
🎯 **Study** ratings and reviews to understand market trends

Data Aggregation
🎯 Create a centralized database of hotel contact details
🎯 Organize structured data for research or analytics

### Why choose us? 💎

The Trivago Email Scraper stands out as a **reliable** and efficient tool for extracting contact information from Trivago hotel listings. Our software is designed to simplify the data collection process, saving you time and effort while ensuring accuracy.

With **advanced** features and a **user-friendly** interface, the scraper caters to businesses of all sizes, from startups to established enterprises. We prioritize compliance with legal and ethical standards, ensuring that your data extraction activities remain within the bounds of the law.

Our tool is **regular**ly updated to adapt to changes in Trivago's website structure, maintaining its effectiveness over time. Whether you are conducting marketing campaigns, building a contact database, or analyzing industry trends, the Trivago Email Scraper provides the functionality you need.

By choosing our solution, you gain access to a powerful tool that delivers high-quality results and supports your business objectives.

### **Social Media** Email Scraper Scalability 📈

The Trivago Email Scraper is designed to handle data extraction tasks of varying scales, making it suitable for both small and large businesses. Whether you need to scrape data from a few hotel listings or thousands, the tool offers consistent performance and reliability.

Its **advanced** algorithms ensure fast processing speeds, even when handling **extensive** datasets. The scraper's scalability allows users to extract data from multiple pages or categories on Trivago without compromising accuracy.

Additionally, it includes features to filter and target specific data points, enabling **efficient** and focused data collection. By leveraging the Trivago Email Scraper, businesses can scale their operations and adapt to growing data needs with ease.

### **Social Media** Email Scraper Legal Guidelines ⚖️

**Yes**—scraping **Social Media** is **legal** as long as you follow **ethical** and **compliant** practices. The **Social Media** Email Scraper extracts only **publicly available** information from **public** **Social Media** profiles, making it **safe** and **compliant** for **research**, **marketing**, and **analysis**.

#### Legal & Ethical Guidelines
⚖️ **Ensure** compliance with Trivagos terms of service when using the scraper
⚖️ **Do not** use extracted data for illegal or unethical purposes
⚖️ **Obtain** consent before contacting individuals using scraped email addresses
⚖️ **Avoid** scraping data that is explicitly restricted by Trivago
⚖️ **Use** the scraper responsibly to prevent overloading Trivagos servers
⚖️ Regularly review legal regulations regarding data scraping in your region
⚖️ **Do not** sell or distribute scraped data without proper authorization
⚖️ Respect privacy laws and guidelines when handling extracted information

### Input Parameters 🧩
📦 Example Input (JSON)
```json
{
  "keywords": ["Trivago Email Scraper"],
  "country": "Global",
  "maxEmailNumbers": 20,
  "platform": "Social Media",
  "engine": "legacy"
}
````

### Input Table

| Data Type | Description |
| --- | --- |
| keywords | Keywords to find relevant profiles |
| country | Country setting (Global) |
| maxEmailNumbers | Maximum emails to collect (default 20) |
| platform | Platform to scrape (Social Media) |
| engine | Engine type (legacy) |
| proxyConfiguration | Optional proxy settings |

### Output Format 📤

📝 Example Output (JSON)

```json
[
  {
    "network": "Social Media",
    "keyword": "Trivago Email Scraper",
    "title": "Google's Single-Benefit Marketing Strategy for Chrome ...",
    "description": "✓For years, once we created a Gmail account, we couldn't change the username (the part before @ gmail.com ). ... Grand Rapids Marketing Co. Read more",
    "url": "https://www.linkedin.com/posts/phill-agnew_heres-how-google-marketed-chrome-browser-activity-7404878510214914048-dLxI",
    "email": "before@gmail.com"
  }
]
```

### Output Table

| Data Type | Description |
| --- | --- |
| network | Identifies Social Media as the source |
| keyword | Keyword that triggered the result (Trivago Email Scraper) |
| title | Profile title or username |
| description | Public bio snippet with contact info |
| url | Direct Social Media profile link |
| email | Extracted email address |

### FAQ ❓

#### What is the Trivago **Email Scraper**?

The Trivago Email Scraper is a tool designed to extract contact information from hotel listings on Trivago.

#### What data can I **extract** using the Trivago **Email Scraper**?

You can extract email addresses, phone numbers, hotel names, locations, website URLs, ratings, reviews, pricing, and amenities.

#### Is the Trivago **Email Scraper** **legal** to use?

**Yes**, it is legal to use as long as you comply with Trivago's terms of service and relevant data privacy laws.

#### Do I need technical expertise to use the Trivago **Email Scraper**?

**No**, the tool is **user-friendly** and requires minimal technical knowledge.

#### Can I filter data during the scraping process?

**Yes**, the scraper includes **filtering** options to target specific hotels or locations.

#### How do I **export** the **extract**ed data?

You can export the data in various file formats, such as **CSV** or Excel.

#### Does the scraper work with large datasets?

**Yes**, the Trivago Email Scraper is designed to handle large-scale data extraction tasks efficiently.

#### Is the scraper updated regularly?

**Yes**, the tool is updated to adapt to changes in Trivago's website structure.

#### Can I use the scraper for marketing purposes?

**Yes**, you can use the extracted data for marketing campaigns, provided you comply with legal guidelines.

#### What happens if Trivago changes its website layout?

The scraper is regularly updated to ensure compatibility with changes in Trivago's website layout.

#### Does the scraper support multiple languages?

**Yes**, it can extract data from Trivago listings in various languages.

#### Can I scrape data from **specific** hotel categories?

**Yes**, you can apply filters to target specific hotel categories during the scraping process.

#### Is the **extract**ed data accurate?

**Yes**, the scraper is designed to provide high accuracy in extracting relevant information.

#### How fast is the data **extract**ion process?

The Trivago Email Scraper offers fast processing speeds for efficient data collection.

#### Can I contact hotels using the scraped data?

**Yes**, but ensure you obtain consent and comply with privacy laws before contacting hotels.

# Actor input Schema

## `keywords` (type: `array`):

List of keywords to search for on Trivago (e.g., \['marketing', 'founder', 'business']). The actor will search Google for Trivago profiles/posts containing these keywords and extract email addresses.

## `platform` (type: `string`):

Select platform.

## `location` (type: `string`):

Optional: Add location to search query (e.g., 'London', 'New York'). Leave empty to search globally.

## `emailDomains` (type: `array`):

Optional: Filter results to only include emails from specific domains (e.g., \['@gmail.com', '@outlook.com']). Leave empty to collect all email domains.

## `maxEmails` (type: `integer`):

Maximum number of emails to collect per keyword (default: 20).

## `engine` (type: `string`):

Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive.

## `proxyConfiguration` (type: `object`):

Choose which proxies to use. By default, no proxy is used. If Google rejects or blocks the request, the actor will automatically fallback to datacenter proxy, then residential proxy with 3 retries.

## Actor input object example

```json
{
  "keywords": [
    "marketing"
  ],
  "platform": "Trivago",
  "location": "",
  "emailDomains": [
    "@gmail.com"
  ],
  "maxEmails": 20,
  "engine": "legacy",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "keywords": [
        "marketing"
    ],
    "emailDomains": [
        "@gmail.com"
    ],
    "proxyConfiguration": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("scraper-engine/trivago-email-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "keywords": ["marketing"],
    "emailDomains": ["@gmail.com"],
    "proxyConfiguration": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("scraper-engine/trivago-email-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "keywords": [
    "marketing"
  ],
  "emailDomains": [
    "@gmail.com"
  ],
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}' |
apify call scraper-engine/trivago-email-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=scraper-engine/trivago-email-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Trivago Email Scraper",
        "description": "Trivago Email Scraper extracts publicly available hotel email addresses from Trivago listings. Build targeted contact lists by city or property type. Ideal for travel marketers, agencies, and B2B suppliers running hotel outreach campaigns.",
        "version": "0.1",
        "x-build-id": "ihhJtY6d123Fodpfu"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/scraper-engine~trivago-email-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-scraper-engine-trivago-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/scraper-engine~trivago-email-scraper/runs": {
            "post": {
                "operationId": "runs-sync-scraper-engine-trivago-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK",
                        "content": {
                            "application/json": {
                                "schema": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/scraper-engine~trivago-email-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-scraper-engine-trivago-email-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "required": [
                    "keywords"
                ],
                "properties": {
                    "keywords": {
                        "title": "Keywords",
                        "type": "array",
                        "description": "List of keywords to search for on Trivago (e.g., ['marketing', 'founder', 'business']). The actor will search Google for Trivago profiles/posts containing these keywords and extract email addresses.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "platform": {
                        "title": "Platform",
                        "enum": [
                            "Trivago"
                        ],
                        "type": "string",
                        "description": "Select platform.",
                        "default": "Trivago"
                    },
                    "location": {
                        "title": "Location Filter",
                        "type": "string",
                        "description": "Optional: Add location to search query (e.g., 'London', 'New York'). Leave empty to search globally.",
                        "default": ""
                    },
                    "emailDomains": {
                        "title": "Email Domains Filter",
                        "type": "array",
                        "description": "Optional: Filter results to only include emails from specific domains (e.g., ['@gmail.com', '@outlook.com']). Leave empty to collect all email domains.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "maxEmails": {
                        "title": "Maximum Emails per Keyword",
                        "minimum": 1,
                        "maximum": 5000,
                        "type": "integer",
                        "description": "Maximum number of emails to collect per keyword (default: 20).",
                        "default": 20
                    },
                    "engine": {
                        "title": "Engine",
                        "enum": [
                            "legacy"
                        ],
                        "type": "string",
                        "description": "Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.",
                        "default": "legacy"
                    },
                    "proxyConfiguration": {
                        "title": "Proxy Configuration",
                        "type": "object",
                        "description": "Choose which proxies to use. By default, no proxy is used. If Google rejects or blocks the request, the actor will automatically fallback to datacenter proxy, then residential proxy with 3 retries."
                    }
                }
            },
            "runsResponseSchema": {
                "type": "object",
                "properties": {
                    "data": {
                        "type": "object",
                        "properties": {
                            "id": {
                                "type": "string"
                            },
                            "actId": {
                                "type": "string"
                            },
                            "userId": {
                                "type": "string"
                            },
                            "startedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "finishedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "status": {
                                "type": "string",
                                "example": "READY"
                            },
                            "meta": {
                                "type": "object",
                                "properties": {
                                    "origin": {
                                        "type": "string",
                                        "example": "API"
                                    },
                                    "userAgent": {
                                        "type": "string"
                                    }
                                }
                            },
                            "stats": {
                                "type": "object",
                                "properties": {
                                    "inputBodyLen": {
                                        "type": "integer",
                                        "example": 2000
                                    },
                                    "rebootCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "restartCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "resurrectCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "computeUnits": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "options": {
                                "type": "object",
                                "properties": {
                                    "build": {
                                        "type": "string",
                                        "example": "latest"
                                    },
                                    "timeoutSecs": {
                                        "type": "integer",
                                        "example": 300
                                    },
                                    "memoryMbytes": {
                                        "type": "integer",
                                        "example": 1024
                                    },
                                    "diskMbytes": {
                                        "type": "integer",
                                        "example": 2048
                                    }
                                }
                            },
                            "buildId": {
                                "type": "string"
                            },
                            "defaultKeyValueStoreId": {
                                "type": "string"
                            },
                            "defaultDatasetId": {
                                "type": "string"
                            },
                            "defaultRequestQueueId": {
                                "type": "string"
                            },
                            "buildNumber": {
                                "type": "string",
                                "example": "1.0.0"
                            },
                            "containerUrl": {
                                "type": "string"
                            },
                            "usage": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "integer",
                                        "example": 1
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "usageTotalUsd": {
                                "type": "number",
                                "example": 0.00005
                            },
                            "usageUsd": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "number",
                                        "example": 0.00005
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```