# Instagram B2b Email Scraper (`scraperoka/instagram-b2b-email-scraper`) Actor 🏢 Email Scraper for B2B extracts verified contacts from target websites & profiles—names, roles, and emails—fast & accurate. 🚀 Perfect for lead gen, sales outreach, and market research. 📈 Get ready to scale. - **URL**: https://apify.com/scraperoka/instagram-b2b-email-scraper.md - **Developed by:** [Scraperoka](https://apify.com/scraperoka) (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 $0.01 / 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 ### Instagram B2b Email Scraper 📬 **Instagram B2b Email Scraper** helps you extract professional business email addresses from Instagram profiles for B2B lead generation. If you’re looking for an **Instagram email scraper B2B** or an **Instagram lead email extractor** that turns publicly available profile signals into an outreach-ready list, this tool is built for you—without manual profile hunting. Whether you’re a marketer, recruiter, data analyst, or researcher, you can use **Instagram contact email finder** workflows to quickly collect emails tied to relevant keywords and a target region, then move to outreach at scale. --- ### 🚀 Why choose Instagram B2b Email Scraper? | Feature | Benefit | |---|---| | ✅ **All-in-one email discovery** | Extracts business emails across the selected Instagram content sources (All, Profiles, Posts, or Reels) | | ✅ **Reliability-focused engine modes** | Supports different scraping engine options for balancing speed and reliability | | ✅ **Email quota control** | Limits collection using `maxEmails` to manage time and operational costs | | ✅ **Structured dataset output** | Saves results with consistent fields for easier filtering, enrichment, and export | | ✅ **Scales for bulk lead building** | Designed to gather large email lists by running keyword + country campaigns | | ✅ **Ready for data pipelines** | Output can be exported to tools you already use (JSON/CSV from the Apify dataset) | --- ### 🔑 Key features - 🧠 **B2B-focused email extraction**: Targets business contact emails associated with Instagram profiles using configured keyword intent - 🔎 **Keyword-driven prospecting**: Use one or more `keywords` to find relevant business profiles (e.g. “fitness”, “gym”, “workout”) - 🌍 **Country targeting**: Restrict results using a selected `country` for more relevant B2B Instagram email leads - 🧾 **Multiple content source options**: Choose `scrapeFrom` = All, Profiles, Posts, or Reels for coverage across content types - 🛡️ **Resilience and fallback behavior**: Includes retries/fallback logic and controlled concurrency for more consistent outcomes - 📊 **Clean, structured results**: Dataset fields include the profile context plus `email`, `email_domain`, and `email_type` - 💾 **Direct dataset saving**: Results are stored into the Apify dataset as records with consistent schema - ⏱️ **Quota-based stopping**: Uses `maxEmails` as an upper limit so you can run smaller or larger campaigns intentionally --- ### 📝 Input Provide input via an `input.json` file. Example structure: ```json { "keywords": [ "fitness", "gym", "workout" ], "country": "United States", "scrapeFrom": "All", "engine": "legacy", "maxEmails": 20 } ```` #### Input Fields | Field | Required | Description | |---|---:|---| | `keywords` | ✅ | One or more search terms to target business profiles on Instagram. | | `country` | ✅ | The geographic region to focus your B2B lead search (e.g. “United States”, “United Kingdom”, etc.). | | `scrapeFrom` | ✅ | Choose where to extract emails from: `All`, `Profiles`, `Posts`, or `Reels`. Use `All` for the most comprehensive coverage. | | `engine` | ❌ | Select extraction method. `cost-effective` (Fast Mode) focuses on residential proxies with concurrent async requests; `legacy` (Legacy Mode) uses a classic approach and may take more time and cost. Default is `legacy`. | | `maxEmails` | ✅ | Set the maximum number of business emails to extract (minimum 1, maximum 10000). This controls run size, time, and operational cost. | *** ### 📦 Output The actor saves each result into the Apify dataset in JSON format with consistent fields for downstream analysis and export. Example record: ```json { "keyword": "fitness", "title": "Profile Title", "url": "https://www.instagram.com/example/", "description": "Profile Description", "email": "contact@example.com", "email_domain": "example.com", "email_type": "Classification", "scrape_from": "Content Source", "country": "Target Region" } ``` #### Output Fields | Field | Type | Description | |---|---|---| | `keyword` | string | The search term that led to this result (your B2B campaign keyword) | | `title` | string | Profile title | | `url` | string | Profile URL | | `description` | string | Profile description text | | `email` | string | Business email address found | | `email_domain` | string | The email domain extracted from `email` | | `email_type` | string | Classification of the extracted email (as labeled by the actor) | | `scrape_from` | string | Which content source type was used for extraction (`All`, `Profiles`, `Posts`, or `Reels`) | | `country` | string | Target region used for the campaign | Note: The dataset is organized as a table view (“Business Email Results”) inside Apify for easy browsing and export to JSON/CSV. *** ### 🚀 How to use Instagram B2b Email Scraper (via Apify Console) 1. **Open Apify Console**\ Log in at https://console.apify.com and go to the **Actors** tab. 2. **Find the actor**\ Search for **Instagram B2b Email Scraper** and open its actor page. 3. **Configure INPUT**\ In the **INPUT** section, fill out: `keywords` (array of terms), `country`, `scrapeFrom`, and `maxEmails`.\ Optionally set `engine` to control the scraping engine mode. 4. **Set your scope (recommended)**\ Use `scrapeFrom = All` for broader coverage, or limit to `Profiles`, `Posts`, or `Reels` to narrow results.\ Set `maxEmails` to control how many emails you want returned (e.g. 20 for a quick test run). 5. **Run the actor**\ Click **Run**. Watch the logs for progress and any retry/fallback events. 6. **Review results in the dataset**\ After completion, open the **OUTPUT** tab and open the dataset titled **Business Email Results**. 7. **Export your data**\ Export the dataset to JSON or CSV and use it in your lead pipeline, CRM, spreadsheets, or outreach workflows. No coding required—get Instagram outreach email lists in minutes with **Instagram lead email extractor** style results. *** ### 🧩 Advanced features & SEO optimization - ⚡ **Engine modes for different priorities**: Instagram business email scraping can be run in `legacy` or `cost-effective` extraction engine modes depending on your desired speed vs reliability balance - 🔁 **Retries and fallback logic**: Includes retries and fallback behavior to improve consistency when encountering blocks or empty results during crawling - 🧠 **Keyword + region targeting**: Engineered for bulk Instagram email leads by combining your `keywords` with `country` focus for more relevant contact discovery - 🧾 **Output designed for enrichment**: With fields like `email_domain` and `email_type`, it’s easier to filter, validate, and route leads in downstream systems - 🌐 **Content-source coverage**: Uses `scrapeFrom` to control whether you want emails from profiles only, posts only, reels only, or across all content types *** ### 🎯 Best use cases - 📈 **B2B outreach teams building lead lists**: Quickly assemble an Instagram outreach email list by extracting emails tied to relevant business niches - 🧑‍💼 **Agencies qualifying influencer and brand prospects**: Use Instagram influencer email scraper results to find business contacts by keyword and region - 🔍 **Market researchers mapping company contact channels**: Compare which business email domains appear across Instagram business profiles by country - 🧠 **Recruiters and staffing teams**: Gather business contact emails from relevant employer keywords (useful for targeted recruiting outreach) - 🛠️ **CRM and sales automation workflows**: Feed structured results fields like `email_domain`, `email_type`, and `url` into your pipeline - 📊 **Data analysts doing enrichment at scale**: Analyze email distribution and profile metadata for B2B Instagram email collection projects - ✉️ **Content collaboration outreach**: Find business emails for collaborations and inquiries using Instagram company email scraper style results *** ### 🔧 Technical specifications - **Supported Input Formats** ✅ - `keywords` (array of strings) - `country` (string from the allowed list) - `scrapeFrom` (`All`, `Profiles`, `Posts`, `Reels`) - `engine` (`cost-effective`, `legacy`) - `maxEmails` (integer, 1–10000) - **Proxy Support** ✅ - Supports built-in proxy support tailored to the selected scraping engine mode for more reliable scraping. - **Retry Mechanism** ✅ - Includes retries and fallbacks to improve resilience when requests fail or yield empty results. - **Dataset Structure** ✅ - Dataset fields: `keyword`, `title`, `url`, `description`, `email`, `email_domain`, `email_type`, `scrape_from`, `country` - **Rate Limits & Performance** ⚠️ - Performance varies with your chosen `maxEmails`, the size of your keyword set, and run conditions. - **Limitations** ⚠️ - Results depend on what is publicly available and discoverable from Instagram profiles and the selected content types. *** ### ❓ FAQ #### ✅ Does this scrape private Instagram profiles or authenticated content? No. Instagram B2b Email Scraper is designed to extract from **publicly available sources** and does not access private profiles or password-protected content. #### ✅ What email types does the dataset return? The dataset includes `email_type`, which contains the actor’s classification label for the extracted email, along with the extracted `email` and `email_domain`. #### ✅ How do I control how many emails I get? Use the `maxEmails` input. It sets the maximum number of business emails to extract and helps you control runtime. #### ✅ Can I scrape only certain Instagram content types? Yes. Set `scrapeFrom` to `Profiles`, `Posts`, or `Reels`. If you want the broadest coverage, use `All`. #### ✅ Can I run keyword campaigns for multiple niches at once? Yes. Provide multiple values in the `keywords` array to generate B2B Instagram email leads across different business niches. #### ✅ Is an API or coding required? No. You can run it directly from Apify Console and export the dataset to JSON/CSV. If you integrate into automation, you can still use the dataset output in your pipeline. #### ❌ Will I always get emails for every profile? No. The tool extracts emails only when business contact emails are present in the publicly available content it processes. #### 💬 How can I request data removal? For data removal requests, contact . *** ### 🤝 Support & feature requests Want to improve Instagram B2b Email Scraper or request enhancements for Instagram email scraper B2B workflows? - 💡 **Feature Requests**: Share ideas like additional export formats, better filtering options, or CRM-ready field mappings. - 📧 **Contact**: Email Your feedback helps shape the roadmap for better Instagram outreach email list generation. *** *Instagram B2b Email Scraper is a most comprehensive, SEO-optimized way to collect B2B contact emails from Instagram at scale.*\ *Run smart keyword + country campaigns and save time on manual prospecting.* *** ### Disclaimer **This tool accesses publicly accessible sources only.** It does not access private profiles, authenticated data, or password-protected pages. It’s your responsibility to comply with applicable laws and regulations (including GDPR/CCPA where relevant), email/spam rules, and Instagram/platform terms while using the output. For data removal requests, contact . Please use Instagram B2b Email Scraper responsibly, ethically, and for legitimate purposes only. # Actor input Schema ## `keywords` (type: `array`): Define one or more search terms to target business profiles on Instagram. ## `country` (type: `string`): Select the geographic region to focus your B2B lead search. ## `scrapeFrom` (type: `string`): Select content type to extract business emails from — All, Posts, Reels, or Profiles. ## `engine` (type: `string`): Select extraction method. 🚀 Optimized Mode: Leverages residential proxies with concurrent async requests for rapid, cost-efficient scraping. 🔧 Traditional Mode: Utilizes GOOGLE\_SERP proxy with classic selectors - higher reliability but increased time and cost. ## `maxEmails` (type: `integer`): Set the maximum number of business emails to extract. ## Actor input object example ```json { "keywords": [ "fitness", "gym", "workout" ], "country": "United States", "scrapeFrom": "All", "engine": "legacy", "maxEmails": 20 } ``` # 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 = { "keywords": [ "fitness", "gym", "workout" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scraperoka/instagram-b2b-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": [ "fitness", "gym", "workout", ] } # Run the Actor and wait for it to finish run = client.actor("scraperoka/instagram-b2b-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": [ "fitness", "gym", "workout" ] }' | apify call scraperoka/instagram-b2b-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraperoka/instagram-b2b-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram B2b Email Scraper", "description": "🏢 Email Scraper for B2B extracts verified contacts from target websites & profiles—names, roles, and emails—fast & accurate. 🚀 Perfect for lead gen, sales outreach, and market research. 📈 Get ready to scale.", "version": "1.0", "x-build-id": "JM0D3yOd4mYG2BEVw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraperoka~instagram-b2b-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraperoka-instagram-b2b-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraperoka~instagram-b2b-email-scraper/runs": { "post": { "operationId": "runs-sync-scraperoka-instagram-b2b-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraperoka~instagram-b2b-email-scraper/run-sync": { "post": { "operationId": "run-sync-scraperoka-instagram-b2b-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "country", "scrapeFrom", "maxEmails" ], "properties": { "keywords": { "title": "Search Keywords", "type": "array", "description": "Define one or more search terms to target business profiles on Instagram.", "items": { "type": "string" } }, "country": { "title": "Target Country", "enum": [ "United States", "United Kingdom", "Canada", "Australia", "Germany", "France", "India", "Japan", "Brazil", "Italy", "Spain", "Netherlands", "Sweden", "Norway", "Denmark", "Finland", "Poland", "Czech Republic", "Hungary", "Romania", "Bulgaria", "Croatia", "Slovenia", "Slovakia", "Estonia", "Latvia", "Lithuania", "Portugal", "Greece", "Cyprus", "Malta", "Luxembourg", "Ireland", "Belgium", "Austria", "Switzerland", "Liechtenstein", "Iceland", "South Korea", "China", "Mexico", "Argentina", "Chile", "Colombia", "Peru", "Venezuela", "Ecuador", "Uruguay", "Paraguay", "Bolivia", "Guyana", "Suriname", "French Guiana", "Falkland Islands (Malvinas)", "South Georgia and the South Sandwich Islands", "Bonaire, Sint Eustatius and Saba", "Curaçao", "Aruba", "Sint Maarten (Dutch part)", "Turks and Caicos Islands", "British Virgin Islands", "Anguilla", "Montserrat", "Antigua and Barbuda", "Barbados", "Dominica", "Grenada", "Saint Kitts and Nevis", "Saint Lucia", "Saint Vincent and the Grenadines", "Trinidad and Tobago", "Jamaica", "Bahamas", "Belize", "Costa Rica", "Guatemala", "Honduras", "Nicaragua", "Panama", "El Salvador", "Cuba", "Dominican Republic", "Haiti", "Puerto Rico", "U.S. Virgin Islands", "American Samoa", "Guam", "Northern Mariana Islands", "Saudi Arabia", "United Arab Emirates", "Bahrain", "Iraq", "Iran, Islamic Republic of", "Israel", "Jordan", "Kuwait", "Lebanon", "Oman", "Qatar", "Syrian Arab Republic", "Yemen", "Afghanistan", "Bangladesh", "Bhutan", "Maldives", "Nepal", "Pakistan", "Sri Lanka", "Myanmar", "Cambodia", "Lao People's Democratic Republic", "Thailand", "Viet Nam", "Malaysia", "Singapore", "Brunei Darussalam", "Philippines", "Indonesia", "Timor-Leste", "Papua New Guinea", "Fiji", "New Zealand", "Solomon Islands", "Vanuatu", "New Caledonia", "French Polynesia", "Wallis and Futuna", "Samoa", "Tonga", "Tuvalu", "Kiribati", "Nauru", "Federated States of Micronesia", "Marshall Islands", "Palau", "Cook Islands", "Niue", "Tokelau" ], "type": "string", "description": "Select the geographic region to focus your B2B lead search.", "default": "United States" }, "scrapeFrom": { "title": "Email Source", "enum": [ "All", "Profiles", "Posts", "Reels" ], "type": "string", "description": "Select content type to extract business emails from — All, Posts, Reels, or Profiles.", "default": "All" }, "engine": { "title": "Scraping Engine", "enum": [ "cost-effective", "legacy" ], "type": "string", "description": "Select extraction method. 🚀 Optimized Mode: Leverages residential proxies with concurrent async requests for rapid, cost-efficient scraping. 🔧 Traditional Mode: Utilizes GOOGLE_SERP proxy with classic selectors - higher reliability but increased time and cost.", "default": "legacy" }, "maxEmails": { "title": "Email Quota", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Set the maximum number of business emails to extract.", "default": 20 } } }, "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 } } } } } } } } } } ```