# Instagram Email Scraper (`scrapecraze/instagram-email-scraper`) Actor Instagram Email Scraper extracts publicly available business emails and contact information from Instagram profiles. Ideal for lead generation, influencer outreach, market research, and B2B marketing by collecting verified public contact data from profile bios and links. - **URL**: https://apify.com/scrapecraze/instagram-email-scraper.md - **Developed by:** [ScrapeCraze](https://apify.com/scrapecraze) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 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 ### Instagram Email Scraper 🚀 Tracking down outreach emails from Instagram profiles is time-consuming and often inconsistent—especially when you’re trying to build a pipeline at scale. **Instagram Email Scraper** quickly extracts emails from publicly available Instagram profile data using your keywords and email-domain filters. With variations like an instagram contact email scraper and instagram email finder workflow, it’s built for outreach teams, analysts, and researchers who need results fast. In one run, you can collect up to `maxEmails` emails (default 20) and export them immediately for your next step. --- ### See the Data: Sample Output Here's a real record from a single run: ```json { "network": "Instagram.com", "keyword": "marketing", "title": "Example profile result title", "description": "Example description text that may contain an email like john@example.com", "url": "https://example.com/some-profile", "email": "john@example.com", "proxyGroups": ["apifyProxyGroupExample"] } ```` **Output fields you can expect:** | Field | Type | What It Tells You | |---|---|---| | `network` | string | The source network label for the record (helps you keep datasets consistent). | | `keyword` | string | The keyword term used to drive the search context for the found contact. | | `title` | string | The title text from the matching result that surfaced the email. | | `description` | string | The description text where the actor detected the email address. | | `url` | string | The link associated with the result the email was extracted from. | | `email` | string | The extracted email address you can use for outreach. | | `proxyGroups` | array | Proxy configuration identifiers used for the scraping run (useful for debugging and reproducibility). | | `status` | string | (Not pushed by the actor in the provided code) — use dataset filtering on success vs failures based on what records appear. | | `error_message` | string | (Not pushed by the actor in the provided code) — errors are logged; the dataset contains pushed result rows. | Export your full dataset as JSON, CSV, or Excel from the Apify dashboard. *** ### Setting It Up Drop this into your `input.json` and you're ready to go: ```json { "keywords": ["founder", "marketing"], "location": "Berlin", "platform": "Instagram", "customDomains": ["@gmail.com", "@company.com"], "maxEmails": 50, "engine": "legacy", "proxyConfiguration": {} } ``` | Parameter | Required | What It Does | |---|---|---| | `keywords` | ✅ | A list of keywords to search for (drives which Instagram-related pages are scanned for contact emails). | | `location` | ⬜ | Location to filter search results. Leave it empty for broader coverage. | | `platform` | ⬜ | Select platform; the only allowed value is `Instagram`. | | `customDomains` | ⬜ | List of custom email domains to target (for example `@gmail.com`). | | `maxEmails` | ⬜ | Maximum number of emails to collect; the run stops once the limit is reached. Higher limits can take longer and don’t guarantee you’ll reach the number. | | `engine` | ⬜ | Choose the scraping engine: `cost-effective` (uses residential proxies with async requests) or `legacy` (uses a different proxy approach and traditional selectors). | | `proxyConfiguration` | ⬜ | Configure proxies for this Actor (high-level proxy settings). | *** ### What It Does Instagram Email Scraper scrapes emails from publicly available sources and pushes each discovered contact record into your Apify dataset as structured JSON. #### Keyword-driven email discovery You provide `keywords`, and the actor searches for email addresses associated with those terms. This makes it practical for an instagram outreach email scraper workflow where you want targeted leads rather than generic email lists. #### Domain filtering for better targeting Use `customDomains` to focus on the email providers and domains you care about. For example, if you’re building an instagram profile email scraper dataset for founders at `@gmail.com` accounts, domain filtering helps you collect only relevant emails. #### Clean, dataset-ready output For every email it finds, the actor pushes a row containing `network`, `keyword`, `title`, `description`, `url`, `email`, and `proxyGroups`. That means your instagram email list scraper results are immediately usable in CRMs and analytics—no extra parsing step needed. #### Built-in proxy support for reliable scraping The actor supports proxy configuration and uses proxy-enabled scraping modes via the selected `engine`. This helps keep runs stable when public data sources throttle repeated requests. #### Uses your limits to control run time With `maxEmails`, you can cap how many unique emails to collect per run. This helps manage scraping time and cost by stopping once the target number is reached. Overall, Instagram Email Scraper turns Instagram email extraction into a predictable, export-ready dataset you can use for outreach, lead lists, and research. *** ### Why Instagram Email Scraper? There are plenty of ways to pull contact data from web sources—here’s why Instagram Email Scraper stands out. #### Results capped for predictable workflows The `maxEmails` limit gives you a clear stopping condition, so your instagram email finder jobs don’t run indefinitely. That makes it easier to test different keyword sets and expand once you see strong signal. #### Email-domain targeting from day one Most instagram influencer email scraper workflows waste time collecting irrelevant addresses. Instagram Email Scraper’s `customDomains` filter lets you prioritize the domains that match your ICP and outreach strategy. #### Operationally resilient runs This instagram email scraping software includes retries, progress persistence, and fallbacks when pages don’t return expected results. If you’re running repeated experiments for instagram leads email scraper use cases, that reliability matters. *** ### Real-World Use Cases Here's how different teams put Instagram Email Scraper to work: **Outreach teams building targeted lead lists**\ Marketing and sales teams often start with a list of Instagram accounts and need the email addresses behind them. They run Instagram Email Scraper with outreach-relevant keywords and `customDomains`, then export the dataset to their outreach tool. The result is fewer manual searches and a faster path from discovery to first email. **Influencer marketers sourcing business contacts**\ When you’re searching for creators or brands in a niche, broad scraping can return lots of noise. With keywords like founder and marketing and domain filters (for example, specific company domains), you can generate an instagram influencer email scraper-ready list with cleaner targeting for outreach. **Researchers and analysts validating public contact patterns**\ Data researchers can use the actor output to study how public bios reference contact emails across different keyword themes and email domains. By exporting each run’s dataset, you can analyze coverage, uniqueness, and domain distribution without writing custom scraping code. **Automation specialists integrating into pipelines**\ Developers can trigger the actor and ingest results directly into downstream systems like CRMs or databases. Because each pushed record is structured, Instagram Email Scraper fits cleanly into an automation workflow—ideal for an instagram dm email scraper style pipeline focused on email-based contact enrichment. **Agencies delivering lead datasets to clients**\ Agencies often need repeatable deliverables for instagram email list scraper projects. They can run multiple keyword/domain combinations, export results, and deliver consistent datasets to clients while keeping runs capped using `maxEmails`. *** ### How to Run It No code required. Here's how to get your first results in under 5 minutes: 1. **Open the actor on Apify** — go to the actor page on [console.apify.com](https://console.apify.com). 2. **Enter your inputs** — set `keywords` (required) and optionally `location`, `customDomains`, `maxEmails`, `engine`, and `platform`. 3. **Configure proxy settings** — adjust `proxyConfiguration` if you have specific proxy preferences for your run. 4. **Start the run and watch the live log** — monitor progress and see when emails are discovered. 5. **Open the Dataset tab** — results appear as the actor pushes each found email record. 6. **Export your results** — download your dataset as JSON, CSV, or Excel. 7. **Refine and re-run if needed** — if results are sparse, broaden your keywords or expand your `customDomains`. The whole setup takes under 5 minutes — results start appearing within seconds of launch. *** ### Export & Integration Options Once your data is collected, Instagram Email Scraper fits directly into your existing workflow. You can export your dataset from the Apify dashboard as **JSON, CSV, or Excel**. For analytics and joins, JSON and CSV are usually the quickest starting points. If you use automation tools, you can connect results using Apify’s integrations, or trigger downstream actions with **Zapier / Make / webhooks**. You can also fetch run results programmatically via the **Apify API** for custom processing and storage. *** ### Pricing Instagram Email Scraper runs on Apify, which includes a **free tier** — no credit card needed to start. On Apify, costs are typically based on Actor compute usage (pay-as-you-go), while heavier workloads are handled by paid plans. There’s no per-row markup in the actor itself—your spend is tied to how the run is executed on the platform. Start free at [apify.com](https://apify.com) — scale up when you need to. *** ### Reliability & Limitations | What We Handle | How | |---|---| | Proxy support | You can configure proxies via `proxyConfiguration` and pick an `engine` mode. | | Retry behavior | The actor includes retry logic when pages don’t return expected content. | | Progress persistence | It saves progress in a key-value store during execution. | | Run stopping controls | `maxEmails` stops the run once the limit is reached. | Limitations: Instagram Email Scraper collects emails from publicly available web sources associated with Instagram profile content, filtered by your keywords and email domains. It cannot access login-gated or private profile data. Results depend on whether emails are actually present in the publicly visible content it targets. For enterprise-scale needs or custom configurations, reach out and we’ll help. *** ### Frequently Asked Questions #### Is there a free plan? Yes. Apify offers a free tier (credits) so you can test Instagram Email Scraper before scaling up to larger keyword runs. #### Do I need to log in or create an account on Instagram? No. This actor works with publicly available data and does not require an Instagram login in order to run. #### How accurate is the extracted email data? The extracted emails are pulled from publicly available text where the actor finds email patterns that match your `customDomains`. Accuracy depends on what the account owner has published in bios or related public content. #### How many results can I get per run? You control this with `maxEmails`. The actor stops once the number of collected unique emails reaches your limit, but higher limits don’t guarantee you’ll reach that maximum. #### How fresh is the data? Freshness depends on what’s currently visible in public sources at the time you run. If you need the most up-to-date instagram email finder results, run the actor again when your campaign is ready. #### Is this legal? Does it comply with GDPR / CCPA? You should treat this as collecting publicly available data and use it in line with GDPR, CCPA, platform Terms of Service, and applicable local laws. It’s your responsibility to ensure your outreach and storage practices are compliant. #### Can I export to Google Sheets or Excel? Yes. You can export the dataset from the Apify dashboard as **Excel** or **CSV**, and then import into Google Sheets. You can also connect your run to downstream tools using Apify integrations or automation platforms. #### Can I schedule this to run automatically? Yes. On Apify, you can schedule runs so Instagram Email Scraper executes automatically on a schedule suited to your research or outreach cadence. #### Can I access results via the API? Yes. Apify supports programmatic access to actor runs and their dataset outputs via the Apify API, which is ideal for automation and data pipelines. #### What happens when the actor encounters an error? Errors are written to the actor logs, and the dataset is updated for each email row the actor successfully pushes. The actor also persists progress so you don’t lose captured results during a run. *** ### Get Help & Use Responsibly Got a question about Instagram Email Scraper or a feature you'd like added? Reach out at — we’re happy to help with practical improvements like expanding domain targeting options or adjusting how results are deduplicated across runs. **Disclaimer:** Instagram Email Scraper collects **publicly available data**. It does not access private Instagram accounts, login-gated content, or password-protected pages. You are responsible for complying with GDPR, CCPA, platform Terms of Service, and any applicable regulations. For data-removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `keywords` (type: `array`): A list of keywords to search for. ## `location` (type: `string`): Location to filter search results. ## `platform` (type: `string`): Select platform. ## `customDomains` (type: `array`): List of custom email domains ## `maxEmails` (type: `integer`): Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time. ## `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`): Configure proxies for this Actor. ## Actor input object example ```json { "keywords": [ "founder", "marketing" ], "location": "", "platform": "Instagram", "customDomains": [ "@gmail.com" ], "maxEmails": 20, "engine": "legacy" } ``` # 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": [ "founder", "marketing" ], "location": "", "customDomains": [ "@gmail.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapecraze/instagram-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": [ "founder", "marketing", ], "location": "", "customDomains": ["@gmail.com"], } # Run the Actor and wait for it to finish run = client.actor("scrapecraze/instagram-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": [ "founder", "marketing" ], "location": "", "customDomains": [ "@gmail.com" ] }' | apify call scrapecraze/instagram-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapecraze/instagram-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Email Scraper", "description": "Instagram Email Scraper extracts publicly available business emails and contact information from Instagram profiles. Ideal for lead generation, influencer outreach, market research, and B2B marketing by collecting verified public contact data from profile bios and links.", "version": "0.0", "x-build-id": "trmBUupyRwu0J3ZLM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapecraze~instagram-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapecraze-instagram-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapecraze~instagram-email-scraper/runs": { "post": { "operationId": "runs-sync-scrapecraze-instagram-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapecraze~instagram-email-scraper/run-sync": { "post": { "operationId": "run-sync-scrapecraze-instagram-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "A list of keywords to search for.", "default": [ "founder", "marketing" ], "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "Location to filter search results.", "default": "" }, "platform": { "title": "Platform", "enum": [ "Instagram" ], "type": "string", "description": "Select platform.", "default": "Instagram" }, "customDomains": { "title": "Custom Email Domains", "type": "array", "description": "List of custom email domains", "default": [ "@gmail.com" ], "items": { "type": "string" } }, "maxEmails": { "title": "Max Emails", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time.", "default": 20 }, "engine": { "title": "Engine", "enum": [ "cost-effective", "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": "Configure proxies for this Actor." } } }, "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 } } } } } } } } } } ```