# Advertising Marketing Agencies Email Scraper (`solid-scraper/advertising-marketing-agencies-email-scraper`) Actor ๐Ÿ“ง Find verified leads with a powerful Advertising Marketing Agencies email scraper. Target by niche, location & keywords to fuel outreach, campaigns & B2B sales. โšก Faster prospecting, higher response ratesโ€”ideal for agencies & growth teams. ๐Ÿ”Ž๐Ÿš€ - **URL**: https://apify.com/solid-scraper/advertising-marketing-agencies-email-scraper.md - **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 ### Advertising Marketing Agencies Email Scraper ๐Ÿ“ฌ **Advertising Marketing Agencies Email Scraper** automates finding and extracting contact information for advertising and marketing agencies, including emails, phone numbers, and social media profiles, from publicly available web data. If youโ€™re building a **marketing agency email scraper** workflow or looking for a **B2B marketing email scraping tool** to accelerate lead generation, this actor helps you gather targeted agency contact details fasterโ€”saving you hours of manual work and supporting scalable outreach campaigns at the same time. Whether youโ€™re a marketer, researcher, sales team, or data enthusiast, **Advertising Marketing Agencies Email Scraper** makes it easier to discover relevant agency leads and enrich them with emails, phones, and social links for faster prospecting and outreach. --- ### ๐Ÿš€ Why choose Advertising Marketing Agencies Email Scraper? | Feature | Benefit | |---|---| | โœ… **All-in-one agency contact discovery + website scraping** | Extracts emails, phone numbers, and social media profiles for advertising marketing agencies in one run | | โœ… **Reliable extraction with built-in resilience** | Includes retries and fallbacks for smoother scraping across websites | | โœ… **Structured dataset output** | Produces a consistent dataset with business details plus extracted contacts for easy importing | | โœ… **Scale-ready with limits controls** | Lets you target a specific number of businesses with configurable per-location or global limits | | โœ… **Proxy support for stable runs** | Helps reduce IP blocks and rate-limit issues during large-scale scraping | | โœ… **Automation-friendly results** | Pushes each result to Apify dataset immediately so you can monitor and export efficiently | --- ### ๐Ÿ”‘ Key features - ๐Ÿง  **Email + contact enrichment in one workflow**: Extracts `scraped_emails`, `scraped_phones`, and `scraped_social_media` from agency websites - ๐ŸŒ **Website-first extraction for higher relevance**: Uses each business `website` to find contact details tied to the agency itself - ๐Ÿ›ก๏ธ **Proxy support for reliable scraping at scale**: Includes `proxyConfiguration` support to improve stability during bulk runs - ๐Ÿ”„ **Resilience with retry/fallback behavior**: Designed to keep working even when some pages are hard to access - ๐Ÿ“Š **Progress and status fields included**: Outputs `emails_found`, `pages_scraped`, and `scrape_status` so you can assess quality quickly - ๐Ÿ’พ **Real-time dataset saving**: Pushes results as it goes (so you donโ€™t lose progress if a run is interrupted) - ๐ŸŽฏ **Targeted limits for predictable lead volume**: `maxBusinesses` plus `scrapeMaxBusinessesPerLocation` helps you control how many agencies you collect - ๐Ÿ”— **Social media profile links included**: Captures `scraped_social_media` when available --- ### ๐Ÿ“ Input Provide input via an `input.json` file. Example structure: ```json { "googleMapsSearchTerm": "Advertising Marketing Agencies", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ```` #### Input Fields | Field | Required | Description | |---|---|---| | `googleMapsSearchTerm` | Yes | The business type or niche for the email scraper (e.g., `'coffee shops'`, `'dentists'`). Prefilled with `Advertising Marketing Agencies`. | | `googleMapsLocation` | Yes | One or more target geographic locations (e.g., `['Miami, Florida']`). You can provide multiple locations to broaden coverage. | | `maxBusinesses` | No | Target number of businesses to find (1โ€“1000). The scraper stops when this target is reached. Default is `5`. | | `scrapeMaxBusinessesPerLocation` | No | If enabled, the scraper collects up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit. Default is `false`. | | `proxyConfiguration` | No | Proxy settings for scraping. Recommended for large-scale scraping. Default prefill enables `proxy support: true`. | | `proxyConfiguration.proxy support` | No | Set to `true` to enable Apify Proxy (recommended for large batches). | > Note: The actor description says it extracts contact information including emails, phone numbers, and social media profiles. In addition, it can be run with optional email validation via internal flags (not exposed as separate input fields in the schema provided). *** ### ๐Ÿ“ฆ Output After execution, the actor saves each businessโ€™s result to the Apify dataset as JSON. Each dataset row includes business details plus extracted contact fields such as emails, phones, and social media links. ```json [ { "street_address": "123 Example St", "city": "New York", "zip": "10001", "state": "NY", "country_code": "US", "full_address": "123 Example St New York NY 10001 US", "website": "https://example-agency.com", "avg_rating": 4.6, "total_reviews": 120, "name": "Example Advertising Agency", "place_id": "PLACE_ID_VALUE", "phone": "+1 555-0100", "lat": 40.7128, "long": -74.006, "scraped_emails": ["hello@example-agency.com"], "scraped_phones": ["+1 555-0101"], "scraped_social_media": ["https://www.linkedin.com/company/example-agency/"], "emails_found": 1, "pages_scraped": 3, "scrape_status": "success", "email_found": "hello@example-agency.com" } ] ``` #### Output Fields | Field | Type | Description | |---|---|---| | `name` | string | Business name | | `website` | string | Business website (used as the basis for website scraping) | | `phone` | string | Phone number associated with the business listing | | `full_address` | string | Full formatted address string | | `city` | string | City name | | `state` | string | State/region | | `zip` | string | ZIP/postal code | | `country_code` | string | Country code | | `scraped_emails` | array | Array of extracted email addresses from the business website | | `scraped_phones` | array | Array of extracted phone numbers from the business website | | `scraped_social_media` | array | Array of extracted social media profile links from the business website | | `emails_found` | number | Count of emails found on the website | | `pages_scraped` | number | Number of processed URLs/pages during website scraping | | `avg_rating` | number | Average rating value from the business listing | | `total_reviews` | number | Total reviews value from the business listing | | `lat` | number | Latitude from the business listing | | `long` | number | Longitude from the business listing | | `place_id` | string | Listing place identifier | | `scrape_status` | string | Status of website scraping (for example `success`, `failed`, `no_website`, or `error`) | | `email_found` | string | When at least one email is found, each dataset row is flattened and includes the specific email in `email_found` | | `scrape_error` | string | Error message when `scrape_status` indicates failure or error | **Export note:** You can export the Apify dataset results to JSON/CSV from the dataset tab for analysis and CRM import. *** ### ๐Ÿงญ How to use Advertising Marketing Agencies Email Scraper (via Apify Console) 1. **Open Apify Console**\ Log in at https://console.apify.com and go to the **Actors** section. 2. **Find the actor**\ Search for **Advertising Marketing Agencies Email Scraper** and open its actor page. 3. **Configure INPUT**\ In the **INPUT** section, set: `googleMapsSearchTerm` (defaults to `Advertising Marketing Agencies`) and `googleMapsLocation` (one or more locations).\ Optionally set `maxBusinesses`, `scrapeMaxBusinessesPerLocation`, and `proxyConfiguration`. 4. **Set proxy settings (recommended for scale)**\ If you plan to scrape many agencies or multiple locations, use the **Proxy configuration** options (including `proxy support`). 5. **Run the actor**\ Click **Run** to start. While it runs, watch the logs to see progress and extraction status (including when businesses have no website or when scraping fails for a domain). 6. **Review dataset output**\ When the run finishes, open the **OUTPUT** tab and view the dataset named **Business Contact Data** / view **Businesses with Contact Information**. 7. **Export your results**\ Export the dataset to JSON or CSV for outreach lists, data analysis, or pipeline ingestion. No coding requiredโ€”get accurate agency email and contact data in minutes with **Advertising Marketing Agencies Email Scraper**. ๐Ÿš€ *** ### โš™๏ธ Advanced features & SEO optimization - ๐Ÿ“Œ **Keyword-targeted agency lead collection**: Engineered to excel at *agency client lead list scraper* and *email finder for advertising agencies* style workflows using your selected search term and locations - ๐Ÿงฉ **Smart per-location vs global limits**: Use `scrapeMaxBusinessesPerLocation` to control whether each location gets up to `maxBusinesses` results or whether you keep a single combined cap - ๐ŸŒ **Complete lead enrichment**: Works as an *email database scraper for agencies* by combining business listing data (address, rating) with website-based contacts (emails, phones, social links) - ๐Ÿ’พ **Immediate dataset saving**: Designed to push results promptly so you can monitor progress and reduce rework risk when running large campaigns - ๐Ÿ›ก๏ธ **Proxy-ready scraping**: Built with `proxyConfiguration` in mind to support reliable extraction at scale for targeted prospect email scraping *** ### ๐Ÿ’ก Best use cases - ๐Ÿ“ˆ **Marketing team lead generation**: Build a **cold email list building tool** for outreach by collecting agency emails plus phones and social links in one workflow - ๐Ÿงช **Market research analyst**: Quantify advertising and marketing agencies presence by region using `city`, `state`, `avg_rating`, and `total_reviews` alongside contact details - ๐Ÿ“จ **Sales prospecting**: Create a **sales prospecting email scraping** dataset to feed sequences faster with verified structure (emails + `email_found` per row) - ๐ŸŽฏ **Digital marketing lead extraction**: Use it as a *digital marketing leads email extractor* to enrich campaigns with agency contact channels and social profiles - ๐Ÿงฐ **CRM + pipeline automation**: Import results into CRM using consistent fields like `website`, `full_address`, `scraped_emails`, and `scrape_status` - ๐Ÿงพ **Agency partnership sourcing**: Find prospective partners by scraping agency contacts and building an *agency client lead list scraper* dataset for BD teams - ๐Ÿ•ต๏ธ **Data enrichment for outreach**: Improve your prospecting list quality by combining listing details with website-derived contacts (emails, phones, social media) *** ### ๐Ÿ”ง Technical specifications - **Supported Input Formats** - โœ… JSON input with `googleMapsSearchTerm`, `googleMapsLocation`, and optional limits/proxy settings (per the schema) - **Proxy Support** - โœ… Yes via `proxyConfiguration` (including `proxy support`) - **Retry Mechanism** - โœ… Yes (actor is designed with resilience and fallback behavior during website scraping) - **Dataset Structure** - โœ… Apify dataset view outputs the fields configured under **Business Contact Data**, including: `name`, `website`, `phone`, `full_address`, `city`, `state`, `zip`, `country_code`, `scraped_emails`, `scraped_phones`, `scraped_social_media`, `emails_found`, `pages_scraped`, `avg_rating`, `total_reviews`, `lat`, `long`, `place_id`, `scrape_status` - **Flattening behavior** - โœ… When emails are found, the actor pushes one row per `email_found` (and removes `scraped_emails` / `_detailed_emails` from that flattened row) - **Limit controls** - โœ… Uses `maxBusinesses` to stop after reaching the target - โœ… `scrapeMaxBusinessesPerLocation` controls whether the limit is per location or global *** ### โ“ FAQ #### Can I use this for a specific marketing niche beyond advertising marketing agencies? Yes. You can set `googleMapsSearchTerm` to a niche or business type you want, while keeping `googleMapsLocation` for your target geography. This works well for scenarios like a *marketing contact email extractor* for other agency categories too. #### How do the limits workโ€”whatโ€™s the difference between `maxBusinesses` and `scrapeMaxBusinessesPerLocation`? `maxBusinesses` sets the target number of businesses to find (1โ€“1000). If `scrapeMaxBusinessesPerLocation` is `true`, youโ€™ll collect up to `maxBusinesses` results per location. If itโ€™s `false`, all locations share a single combined cap up to the total limit. #### Will I always get emails in the dataset? No. The dataset includes `scraped_emails`, and `emails_found` indicates how many emails were found for that business. Businesses can also have `scrape_status` values like `no_website`, `failed`, or `error` depending on what happened during website scraping. #### What contact fields can I expect besides email? The actor extracts and outputs `scraped_phones` and `scraped_social_media` in addition to `scraped_emails`, along with website and basic business listing data such as `avg_rating`, `total_reviews`, `full_address`, and `place_id`. #### Does the actor support proxies? Yes. Use `proxyConfiguration` and (optionally) `proxyConfiguration.proxy support` to improve reliability during large-scale scraping. #### Do I need to write code to use Advertising Marketing Agencies Email Scraper? No. You can run it directly in Apify Console by filling out the `INPUT` fields and then exporting from the dataset output. #### How should I use the exported data for outreach? Treat the output as lead-contact discovery data. The dataset includes `email_found` per row when emails are present, which makes it easy to build outreach lists. Always ensure your outreach practices comply with applicable privacy laws and platform policies. #### Is it legal and compliant to scrape publicly available contact info? โœ… The actor is intended to scrape **publicly accessible sources**. However, legal compliance (including GDPR/CCPA), consent requirements, and anti-spam regulations are your responsibility. Use the data responsibly and ethically. *** ### ๐Ÿค Support & feature requests Have questions about **Advertising Marketing Agencies Email Scraper** or want improvements (for example CSV-friendly formatting, additional enrichment fields, or export options)? ๐Ÿ’ก Send a feature request by contacting us at . ๐Ÿ“ง For support or feedback, email . Your feedback directly shapes the roadmap for this **advertising marketing agencies email scraper** experience. *** ### *Advertising Marketing Agencies Email Scraper* โ€” build targeted agency email lists faster ๐Ÿš€ If you want the most comprehensive, SEO-optimized way to collect agency contact data for lead generation, **Advertising Marketing Agencies Email Scraper** is built to help you move from research to outreach at scale. *** ### Disclaimer This tool accesses **publicly accessible sources**. It does not access private profiles, authenticated data, password-protected pages, or any other restricted content. You are responsible for ensuring your use complies with applicable laws (including GDPR and CCPA where relevant), spam regulations, and the target websitesโ€™ terms of service. For data removal requests, contact . Use this actor responsibly, ethically, and for legitimate purposes only. # Actor input Schema ## `googleMapsSearchTerm` (type: `string`): Enter the business type or niche for email scraper (e.g., 'coffee shops', 'dentists'). ## `googleMapsLocation` (type: `array`): Target geographic location for the email scraper (e.g., 'Miami, Florida'). ## `maxBusinesses` (type: `integer`): Target number of businesses to find (1-1000). The scraper will stop when this target is reached. ## `scrapeMaxBusinessesPerLocation` (type: `boolean`): If enabled, the scraper will collect up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit. ## `proxyConfiguration` (type: `object`): Proxy settings for scraping. Recommended for large-scale scraping. ## Actor input object example ```json { "googleMapsSearchTerm": "Advertising Marketing Agencies", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "googleMapsSearchTerm": "Advertising Marketing Agencies", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/advertising-marketing-agencies-email-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "googleMapsSearchTerm": "Advertising Marketing Agencies", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/advertising-marketing-agencies-email-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "googleMapsSearchTerm": "Advertising Marketing Agencies", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }' | apify call solid-scraper/advertising-marketing-agencies-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solid-scraper/advertising-marketing-agencies-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Advertising Marketing Agencies Email Scraper", "description": "๐Ÿ“ง Find verified leads with a powerful Advertising Marketing Agencies email scraper. Target by niche, location & keywords to fuel outreach, campaigns & B2B sales. โšก Faster prospecting, higher response ratesโ€”ideal for agencies & growth teams. ๐Ÿ”Ž๐Ÿš€", "version": "1.0", "x-build-id": "f79H0PwCtyGMRk5Kr" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~advertising-marketing-agencies-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-advertising-marketing-agencies-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~advertising-marketing-agencies-email-scraper/runs": { "post": { "operationId": "runs-sync-solid-scraper-advertising-marketing-agencies-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~advertising-marketing-agencies-email-scraper/run-sync": { "post": { "operationId": "run-sync-solid-scraper-advertising-marketing-agencies-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "googleMapsLocation", "googleMapsSearchTerm" ], "properties": { "googleMapsSearchTerm": { "title": "Search Term", "type": "string", "description": "Enter the business type or niche for email scraper (e.g., 'coffee shops', 'dentists').", "default": "Advertising Marketing Agencies" }, "googleMapsLocation": { "title": "Location", "type": "array", "description": "Target geographic location for the email scraper (e.g., 'Miami, Florida').", "default": [ "New York" ], "items": { "type": "string" } }, "maxBusinesses": { "title": "Maximum Businesses With Emails", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Target number of businesses to find (1-1000). The scraper will stop when this target is reached.", "default": 5 }, "scrapeMaxBusinessesPerLocation": { "title": "Scrape Max Businesses Per Location", "type": "boolean", "description": "If enabled, the scraper will collect up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit.", "default": false }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for scraping. Recommended for large-scale scraping." } } }, "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 } } } } } } } } } } ```