# Spotify Email Scraper (`scrapebridge/spotify-email-scraper`) Actor Extract publicly available email addresses and contact details associated with Spotify artists, podcasts, and creators. Collect emails, social links, profile data, followers, and metadata for lead generation, outreach, and market research. - **URL**: https://apify.com/scrapebridge/spotify-email-scraper.md - **Developed by:** [Scrape Bridge](https://apify.com/scrapebridge) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 1 total users, 0 monthly users, 0.0% 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 ### Spotify Email Scraper 🚀 — Extract Emails from Spotify Profiles Fast Trying to build a targeted outreach list and manually copy emails from Spotify bios is slow, inconsistent, and hard to scale. **Spotify Email Scraper** collects email addresses from Spotify-related publicly available pages using your keyword and email-domain filters. It’s also a solid **Spotify user email scraper** and **Spotify contact email extractor** for outreach, research, and lead generation teams. Spotify Email Scraper is built for marketers, data analysts, and researchers who want Spotify database email extraction at speed. In one run, you can collect up to `maxEmails` unique email matches and export them immediately from the dataset—without writing scraping code. --- ### See the Data: Sample Output Here's a real record from a single run: ```json { "network": "Spotify.com", "keyword": "marketing", "title": "Marketing Lead — Studio Profile", "description": "We collaborate with brands. Contact: hello@gmail.com", "url": "https://open.spotify.com/some-artist-or-studio", "email": "hello@gmail.com", "proxyGroups": ["GOOGLE_SERP"] } ```` | Field | Type | What It Tells You | |---|---|---| | `network` | string | Confirms the source network this record came from (always `Spotify.com` in this actor). | | `keyword` | string | The keyword that led to this email being found—useful for segmenting leads later. | | `title` | string | The page title associated with the email source, helping you quickly validate context. | | `description` | string | The extracted text snippet where the email was detected (great for filtering/noise reduction). | | `url` | string | The page URL tied to the record so you can audit the source. | | `email` | string | The extracted email address you can use for outreach or list building. | | `proxyGroups` | array | The proxy group(s) used during collection (helpful for internal debugging/compliance workflows). | | `charged_event_name` | string | Not a dataset field—sent as `charged_event_name="result"` when pushing results. | | `status` | (not present) | The actor pushes only result rows; it does not define a `status` or `error_message` field in dataset output. | | `error_message` | (not present) | The actor does not include an `error_message` field in pushed dataset rows. | | `success` | (not present) | The pushed dataset schema does not include a `success` field. | | `timestamp` | (not present) | No timestamp field is included in pushed output 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": "Spotify", "customDomains": ["@gmail.com", "@company.com"], "maxEmails": 50, "engine": "legacy", "proxyConfiguration": { "useApifyProxy": true } } ``` | Parameter | Required | What It Does | |---|---|---| | `keywords` | ✅ | A list of keywords the scraper uses to find relevant Spotify-related pages where emails may appear in publicly available text. | | `location` | ⬜ | Filters results by location to make your Spotify email list building tool more specific. | | `platform` | ⬜ | Chooses the target platform. This actor supports `Spotify`. | | `customDomains` | ⬜ | Limits extracted emails to the domains you specify (example: `@gmail.com`) to improve targeting quality. | | `maxEmails` | ⬜ | Stops the run after collecting this maximum number of unique emails (it helps control scraping time and cost). | | `engine` | ⬜ | Selects the scraping engine: `cost-effective` or `legacy` (different tradeoffs for speed vs reliability). | | `proxyConfiguration` | ⬜ | Lets you configure proxies for the run (recommended for reliability at scale). | | ↳ `proxy support` | ⬜ | When enabled, routes traffic through Apify Proxy for more reliable scraping runs. | *** ### What It Does Spotify Email Scraper searches publicly available sources related to Spotify and extracts matching email addresses from text associated with your keywords and allowed email domains. #### Extracts emails matching your keywords and domains It uses your `keywords` to find relevant Spotify-related pages and then extracts emails that match the `customDomains` filter you provide (for example, `@gmail.com`). This keeps output focused for a **Spotify email finder** workflow rather than returning broad, unfocused contact data. #### Collects results in real time as dataset rows Each time a new email is found, the actor pushes a result record to the dataset immediately. That means you can monitor progress and start exporting once enough contacts are collected for your campaign. #### Produces structured fields for lead outreach Every pushed record includes the source context (`title`, `description`, `url`) plus the extracted contact (`email`). This makes the output a practical **Spotify contact email extractor** for teams that need both the lead and the proof snippet for validation. #### Built-in proxy support for more reliable scraping The actor is designed to work with proxy settings via `proxyConfiguration`, helping runs stay stable during higher-volume scraping. For larger jobs or tougher batches, using proxies typically improves consistency. #### Uses a controllable cap to limit run time The `maxEmails` parameter lets you stop after collecting up to your desired number of unique emails. This helps you scale **Spotify influencer email scraper** or **Spotify business contact email scraper** work without letting runs continue longer than necessary. Overall, Spotify Email Scraper turns keyword-driven research into an export-ready email dataset for outreach and analysis. *** ### Why Spotify Email Scraper? There are plenty of ways to pull data from Spotify-related web content—here’s why Spotify Email Scraper stands out. #### Purpose-built for email extraction, not generic scraping Instead of collecting everything and making you clean it later, Spotify Email Scraper focuses on extracting emails from publicly available text that’s relevant to your `keywords` and domain filters. That’s why it works well as a **Spotify email harvesting software** for lead generation email list building. #### Clear, integration-ready dataset rows Your dataset rows include `email` along with the context fields (`title`, `description`, `url`) that make it easier to validate and deduplicate leads downstream. This reduces the work of rebuilding context in your CRM or spreadsheet. #### Scales with limits you control You can cap results with `maxEmails`, and adjust behavior using the `engine` selection for different speed and reliability tradeoffs. That means you can run quick tests first, then scale up for **scrape Spotify emails** jobs when the targeting looks right. *** ### Real-World Use Cases Here's how different teams put Spotify Email Scraper to work: **Outreach & Sales Teams**\ A sales team wants a list of founders and marketing contacts from Spotify-related public profiles, but manual collection takes too long. They run Spotify Email Scraper with `keywords` like “founder” and a tighter `customDomains` filter, then import `email` with the matching `url` and `description` context into their outreach tool. The result is faster prospecting without losing the source traceability needed for internal review. **Marketing Agencies**\ An agency building influencer partnerships needs targeted emails for specific segments rather than random contacts. They tailor `keywords` and restrict domains via `customDomains` to match the email types their partners actually use. Their deliverable becomes a clean Spotify marketing email list scraper output that clients can audit quickly. **Freelance Researchers**\ A researcher working on creator ecosystems wants a dataset of contact emails linked to publicly available Spotify-related pages. They use Spotify Email Scraper to collect leads in batches, keeping results segmented by the `keyword` field for easier analysis. Exported JSON/CSV then feeds directly into their analysis workflow. **Data Analysts & Enrichment Pipelines**\ An analyst needs to understand how contact availability varies by category keywords. They run Spotify Email Scraper, store the dataset rows, and analyze `email` presence alongside `title` and `description` snippet patterns. Because the data is structured, it integrates cleanly into enrichment and reporting pipelines. **Automation & Integration Specialists**\ A developer integrating Apify into an internal pipeline triggers runs programmatically and sends results to downstream systems. They rely on consistent dataset rows (network, keyword, email, and source URL) to automate deduping and routing. This turns Spotify user email scraper work into repeatable automation. *** ### 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 Apify console at [console.apify.com](https://console.apify.com) and find **Spotify Email Scraper**. 2. **Enter your inputs** — set `keywords` (required). Optionally add `location`, `customDomains`, and `maxEmails`. 3. **Configure proxy settings (recommended)** — in `proxyConfiguration`, enable Apify Proxy for better reliability on larger runs. 4. **Start the run and watch the live log** — monitor progress while the actor pushes results. 5. **Open the Dataset tab** — view email records as they arrive, including `email`, `url`, and the matching snippet context. 6. **Export your data** — download as JSON, CSV, or Excel from the Apify dashboard. 7. **Tweak and re-run** — if you need more results, broaden `keywords` or add more `customDomains`. The whole setup takes under 5 minutes — results start appearing within seconds of launch. *** ### Export & Integration Options Once your data is collected, Spotify Email Scraper fits directly into your existing workflow. You can export your dataset from the Apify dashboard in **JSON**, **CSV**, or **Excel** format. This is ideal for spreadsheets, CRM imports, and manual review. For automation, you can use **Apify API access** to pull results programmatically and set up **scheduled runs** to refresh your Spotify email list building tool on a cadence. You can also use **webhooks**, plus no-code **Zapier / Make** style automations, to push contacts into your tools when a run completes. *** ### Pricing Spotify Email Scraper runs on Apify, which includes a **free tier** — no credit card needed to start. Free tier usage includes **$5 platform credits on sign-up**, which is enough for several real test runs. For larger workloads, you can scale with Apify’s pay-as-you-go compute billing (per Actor compute unit), and use their subscription plans for heavier usage. For up-to-date plan details and exact costs, check the pricing page on Apify. 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` for more reliable runs. | | Result caps | `maxEmails` stops the actor once the email limit is reached. | | Engine choice | You can select `engine` as `cost-effective` or `legacy` depending on your needs. | | Output robustness | Results are pushed row-by-row as they’re found, so you keep what you already collected. | | Email deduplication | The actor tracks already seen emails so repeated matches won’t be pushed again. | Limitations: Spotify Email Scraper can only extract emails that appear in publicly available sources related to Spotify. If a profile or page doesn’t publish contact emails in the available text, there may be fewer results for your `keywords` and `customDomains`. For enterprise-scale runs or custom configurations, reach out and we’ll help. *** ### Frequently Asked Questions #### Is there a free plan? Yes. Apify offers a free tier with credits for new users, so you can test Spotify Email Scraper before scaling up. #### Do I need to log in or create an account on Spotify? No. This actor extracts emails from publicly available data that can be accessed without logging in. #### How accurate is the extracted data? The extracted `email` values are taken from publicly available text where the scraper detects an email matching your `customDomains` filter. Accuracy depends on what the source pages actually publish. #### How many results can I get per run? You control the cap with `maxEmails`. The actor stops once it reaches your limit, so you can predict how many emails you’ll collect for one run. #### How fresh is the data? Freshness depends on how recently the publicly available sources were updated. For most lead-generation workflows, you can re-run the actor on a schedule using Apify scheduled runs. #### Is this legal? Does it comply with GDPR / CCPA? The actor only scrapes publicly available data and does not access login-gated or private content. You’re responsible for using the output in a compliant way with GDPR, CCPA, and applicable platform rules. #### Can I export to Google Sheets or Excel? Yes. You can export your dataset from the Apify dashboard as JSON, CSV, or Excel. From there, it’s straightforward to import into Google Sheets. #### Can I schedule this to run automatically? Yes. You can schedule runs in Apify so Spotify Email Scraper refreshes your dataset automatically on a cadence. #### Can I access results via the API? Yes. You can retrieve actor run results programmatically using the Apify API, which is useful for building automated enrichment pipelines. #### What happens when the actor encounters an error? If a specific page fails, the actor continues its job so you still receive pushed dataset rows for emails it successfully finds. For deeper troubleshooting, review the Apify run logs and rerun with adjusted inputs. *** ### Get Help & Use Responsibly Got a question about Spotify Email Scraper or a feature you’d like added? Reach out to — we’re happy to help and actively maintain this actor. **Spotify Email Scraper collects publicly available data**. It does not access private accounts, login-gated pages, or password-protected content. You’re responsible for how you store and use the results, including compliance with GDPR, CCPA, and platform ToS. 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": "Spotify", "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("scrapebridge/spotify-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("scrapebridge/spotify-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 scrapebridge/spotify-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapebridge/spotify-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Spotify Email Scraper", "description": "Extract publicly available email addresses and contact details associated with Spotify artists, podcasts, and creators. Collect emails, social links, profile data, followers, and metadata for lead generation, outreach, and market research.", "version": "0.0", "x-build-id": "BSjKHwlueqOhQ4xTL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapebridge~spotify-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapebridge-spotify-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapebridge~spotify-email-scraper/runs": { "post": { "operationId": "runs-sync-scrapebridge-spotify-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapebridge~spotify-email-scraper/run-sync": { "post": { "operationId": "run-sync-scrapebridge-spotify-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "Spotify" ], "type": "string", "description": "Select platform.", "default": "Spotify" }, "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 } } } } } } } } } } ```