# Youtube User Channel Scraper (`scrapedrift/youtube-user-channel-scraper`) Actor 🔎 Scrape and analyze YouTube user channels with YouTube User Channel Scraper! Extract key profile details fast for smarter research, lead gen, and competitive insights. ⚡️ Perfect for creators, marketers & data-driven teams. 🚀 - **URL**: https://apify.com/scrapedrift/youtube-user-channel-scraper.md - **Developed by:** [ScrapeDrift](https://apify.com/scrapedrift) (community) - **Categories:** Lead generation, Social media, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.99 / 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 ### Youtube User Channel Scraper 🎯 If you need consistent YouTube channel metadata (subscribers, videos, views, join date, socials) for outreach or analysis, manually copying data one channel at a time is slow and error-prone. **Youtube User Channel Scraper** pulls YouTube channel details in bulk using channel IDs or channel URLs, so you can move faster with a clean dataset. This youtube channel scraper tool is built for youtube user profile scraper workflows, including youtube channel data scraper and youtube channel URL scraper use cases. It’s a great fit for marketers, data analysts, and researchers who want structured youtube channel metadata scraper output without writing scraping code. In one run, you can process multiple channels in sequence and start exporting results immediately. --- ### See the Data: Sample Output Here's a real record from a single run: ```json { "channelId": "UCyBD3P9YOFWNIMTuDzqeObg", "avatar": "https://example.com/avatar.jpg", "banner": "https://example.com/banner.jpg", "title": "BBC News", "verified": 1, "hasbusinessEmail": 0, "joinDate": "Jan 1, 2006", "country": "United Kingdom", "viewCount": 25400000000, "videoCount": 240000, "subscriberCount": 32000000, "description": "News, analysis and stories from around the world.", "links": [ { "title": "Website", "link": "b-website.com" } ], "indexUrl": "http://www.youtube.com/channel/UCyBD3P9YOFWNIMTuDzqeObg", "channelUrl": "https://www.youtube.com/@BBCNews/about" } ```` | Field | Type | What It Tells You | |---|---|---| | `channelId` | string | The unique YouTube channel identifier for matching and deduping records. | | `avatar` | string | null | The channel profile image URL, useful for previews and reports. | | `banner` | string | null | The channel banner image URL for richer channel cards and exports. | | `title` | string | null | The display name shown for the channel. | | `verified` | number | Whether the channel is marked as verified (returned as `1` or `0`). | | `hasbusinessEmail` | number | Indicates whether the actor detected a business email signal on the channel page (returned as `1` or `0`). | | `joinDate` | string | null | The channel join date as shown by the channel metadata. | | `country` | string | null | The country value extracted from the channel metadata (when available). | | `viewCount` | number | Total view count parsed into a numeric value for ranking and filters. | | `videoCount` | number | Total video count parsed into a numeric value for volume comparisons. | | `subscriberCount` | number | Subscriber count parsed into a numeric value for sizing the channel. | | `description` | string | null | The channel description / about text for context and qualitative review. | | `links` | array | null | A list of channel external links extracted from the channel “links” section. | | `indexUrl` | string | null | A normalized index URL pointing to the channel. | | `channelUrl` | string | null | The final normalized channel URL used for the scrape, typically including the “about” path when applicable. | | `status` | string | Not returned in the dataset schema; failures are handled by not pushing data when metadata can’t be extracted. | 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 { "ids": "UCyBD3P9YOFWNIMTuDzqeObg,UC-1234567890abcdef", "start_urls": [ { "url": "https://www.youtube.com/@BBCNews" }, { "url": "https://www.youtube.com/channel/UCyBD3P9YOFWNIMTuDzqeObg/about" } ] } ``` | Parameter | Required | What It Does | |---|---:|---| | `ids` | ⬜ | A comma-separated list of YouTube Channel IDs (e.g. `UCyBD3P9YOFWNIMTuDzqeObg`). The actor converts each ID into a channel URL and scrapes it. | | `start_urls` | ⬜ | A list of YouTube channel URLs to scrape. The actor processes these first, in the same order they appear in the UI list. | *** ### What It Does Youtube User Channel Scraper fetches YouTube channel details for multiple targets and writes one structured record per successfully extracted channel. #### Scrape channel metadata by ID or URL You can supply a list of YouTube channel URLs or pass channel IDs. The actor normalizes URLs and scrapes channel page metadata, supporting common inputs for a youtube channel URL scraper workflow. #### Output channel metrics as numeric fields Subscriber count, view count, and video count are parsed from the page and returned as numeric values. That makes youtube subscriber count scraper and youtube channel data scraper workflows easier to analyze, sort, and filter. #### Includes key channel context fields The actor extracts channel title, description, join date, and country when those values are available. It also captures `avatar` and `banner` URLs to help with youtube channel metadata scraper reports and enrichment. #### Extracts external links from the channel For channels that publish additional external links, the actor returns them in the `links` array (each with a `title` and `link`). This supports youtube channel about section scraper use cases where you want more than just counts. #### Built for practical batch runs The actor processes inputs in sequence and pushes results to your Apify dataset as it goes. If it can’t fetch or extract metadata for a channel, it logs the issue and continues with the next one, which is helpful for youtube channel list scraper projects. Overall, Youtube User Channel Scraper turns channel pages into structured records you can export and use immediately for outreach, research, and reporting. *** ### Why Youtube User Channel Scraper? There are plenty of ways to pull data from YouTube pages—here’s why Youtube User Channel Scraper stands out. #### Clean, integration-ready channel records The output is already structured with fields for `channelId`, `subscriberCount`, `viewCount`, `videoCount`, `joinDate`, `country`, `description`, and more. That means you can plug the results into your analysis or pipeline without spending time reformatting. #### Designed for bulk channel processing This youtube channel scraper tool is built to handle multiple channel URLs and channel IDs in a single run. It’s a strong fit for teams that need repeatable youtube user profile scraper outputs rather than one-off manual lookups. #### Works with both “about” and standard channel URLs The actor normalizes common channel URL patterns and appends the “about” path when appropriate. That helps keep results consistent for youtube channel about section scraper style workflows. *** ### Real-World Use Cases Here's how different teams put Youtube User Channel Scraper to work: **Influencer Marketing Teams**\ Marketing teams often start with a long list of creators, then narrow it down based on subscriber size, video volume, and engagement proxies like total views. They run this youtube channel metadata scraper on a batch of channel URLs, export the dataset, and build a shortlist faster than manual research. **Sales and Outreach Researchers**\ When outreach depends on channel identity and sizing, researchers need more than just a URL—they need consistent channel metrics and a reliable channel ID to dedupe leads. Youtube User Channel Scraper produces structured subscriberCount and viewCount values to support youtube subscriber count scraper style lead sizing. **Brand Partnerships Analysts**\ For partner scoring, analysts want comparable numeric metrics across many channels. They use the parsed `subscriberCount`, `videoCount`, and `viewCount` from Youtube User Channel Scraper to rank channels and enrich spreadsheets with titles and descriptions. **Community Managers and Audience Analysts**\ Community-focused teams often need to track how channels evolve over time and store channel context for reporting. By capturing joinDate, country, and description in one run, they can maintain a consistent dataset for long-running projects. **Automation Specialists / Data Engineers**\ Automation and data engineering teams can trigger an Apify run, then ingest the dataset into their downstream systems. Since the actor pushes structured JSON records (youtube channel data scraper-ready), it’s easier to wire into repeatable workflows. *** ### 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** — add channel URLs in `start_urls` (processed first) and/or add channel IDs in `ids` (comma-separated). 3. **Keep the run settings default** — this actor manages its own request resilience internally; there are no proxy settings exposed in the input schema. 4. **Start the run** — watch the live log as each channel is processed. 5. **Open the Dataset tab** — results are pushed as the actor extracts metadata successfully. 6. **Export your results** — download the dataset from the dashboard as JSON, CSV, or Excel. The whole setup takes under 5 minutes — results start appearing quickly after launch. *** ### Export & Integration Options Once your data is collected, Youtube User Channel Scraper fits directly into your existing workflow. You can export the dataset from the Apify dashboard as JSON, CSV, or Excel, using the results stored in the dataset tab. For ongoing workflows, you can access results programmatically via the Apify API and push them into your tools. You can also connect the run to automation platforms like Zapier or Make to transfer the extracted youtube channel metadata scraper fields into your CRM or internal systems. If you want the process to run on a cadence, you can schedule the actor to execute automatically from Apify. *** ### Pricing Youtube User Channel 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 often enough for several real test runs. For larger batches or heavier workloads, Apify uses a pay-as-you-go model billed per Actor compute unit (CU). Subscription plans are available on Apify for teams with sustained needs—see the current options on the pricing page. Start free at [apify.com](https://apify.com) — scale up when you need to. *** ### Reliability & Limitations | What We Handle | How | |---|---| | Retries for fetching channel pages | The actor attempts multiple fetches per URL when issues occur. | | Continued progress across multiple inputs | It processes targets and continues even when some channels can’t be extracted. | | Partial results | Records are pushed as channels are successfully scraped and parsed. | | Structured metadata extraction | Output includes consistent fields like `subscriberCount`, `viewCount`, and `videoCount` when available. | Limitations: The actor only works with publicly available channel pages. If channel metadata needed for extraction is missing or inaccessible, that channel may not produce an output record. 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 with usage credits so you can run Youtube User Channel Scraper for real tests before deciding on a paid plan. #### Do I need to log in or create an account on YouTube? No. This actor scrapes YouTube channel details from publicly accessible pages using channel IDs or channel URLs, so you don’t need a user login for the run. #### How accurate is the extracted data? The extracted values come directly from the channel page metadata, then are parsed into the output fields (like numeric counts). If a channel’s public metadata is missing or formatted in an unexpected way, some fields may come back as `null`. #### How many results can I get per run? You can pass multiple channel URLs and/or multiple channel IDs in one run. There is no results-per-run limit in the provided input schema, but your real batch size is constrained by your Apify account and runtime environment. #### How fresh is the data? The data is captured at the moment the actor visits each channel page during your run. For the latest metrics, you’ll want to run the actor closer to the time you need the numbers. #### Is this legal? Does it comply with GDPR / CCPA? Yes for data collection scope in the sense that it targets **publicly available data** on YouTube channel pages. Compliance with GDPR, CCPA, and any applicable regulations is your responsibility when storing, processing, or using the dataset, especially for contact-related workflows. #### Can I export to Google Sheets or Excel? Yes. You can export from the Apify dataset tab as JSON, CSV, or Excel, then import into Google Sheets or your preferred spreadsheet tool. #### Can I schedule this to run automatically? Yes. With Apify, you can schedule actor runs so Youtube User Channel Scraper executes automatically on a cadence you choose. #### Can I access results via the API? Yes. You can retrieve results programmatically using the Apify API, which is useful for integrating youtube channel data scraper outputs into pipelines. #### What happens when the actor encounters an error? When the actor fails to fetch a channel or cannot extract metadata, it logs the error and continues processing the remaining inputs. Successful channels still push their records to the dataset. *** ### Get Help & Use Responsibly Got a question about Youtube User Channel Scraper or a feature you'd like added? Reach out at . We welcome feedback like expanding extracted metadata fields or improving normalization for additional channel URL formats, and we actively maintain this actor. **publicly available data** on YouTube channel pages is used; private accounts, login-gated pages, and password-protected content are not accessed. You’re responsible for complying with GDPR, CCPA, platform ToS, and any applicable regulations. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `ids` (type: `string`): Comma-separated list of YouTube Channel IDs (e.g. UCyBD3P9YOFWNIMTuDzqeObg) ## `start_urls` (type: `array`): List of YouTube channel URLs to scrape. ## Actor input object example ```json { "ids": "UCyBD3P9YOFWNIMTuDzqeObg", "start_urls": [ { "url": "https://www.youtube.com/@BBCNews" } ] } ``` # 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 = { "ids": "UCyBD3P9YOFWNIMTuDzqeObg", "start_urls": [ { "url": "https://www.youtube.com/@BBCNews" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapedrift/youtube-user-channel-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 = { "ids": "UCyBD3P9YOFWNIMTuDzqeObg", "start_urls": [{ "url": "https://www.youtube.com/@BBCNews" }], } # Run the Actor and wait for it to finish run = client.actor("scrapedrift/youtube-user-channel-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 '{ "ids": "UCyBD3P9YOFWNIMTuDzqeObg", "start_urls": [ { "url": "https://www.youtube.com/@BBCNews" } ] }' | apify call scrapedrift/youtube-user-channel-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapedrift/youtube-user-channel-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Youtube User Channel Scraper", "description": "🔎 Scrape and analyze YouTube user channels with YouTube User Channel Scraper! Extract key profile details fast for smarter research, lead gen, and competitive insights. ⚡️ Perfect for creators, marketers & data-driven teams. 🚀", "version": "0.1", "x-build-id": "sleKQi61XYaT3Pwvm" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapedrift~youtube-user-channel-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapedrift-youtube-user-channel-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapedrift~youtube-user-channel-scraper/runs": { "post": { "operationId": "runs-sync-scrapedrift-youtube-user-channel-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapedrift~youtube-user-channel-scraper/run-sync": { "post": { "operationId": "run-sync-scrapedrift-youtube-user-channel-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "ids": { "title": "Channel IDs", "type": "string", "description": "Comma-separated list of YouTube Channel IDs (e.g. UCyBD3P9YOFWNIMTuDzqeObg)" }, "start_urls": { "title": "Start URLs", "type": "array", "description": "List of YouTube channel URLs to scrape.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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 } } } } } } } } } } ```