# YouTube Competitor Analyzer (`hasnainnisar67/youtube-competitor-analyzer`) Actor Compare up to 5 YouTube channels side-by-side. Returns subscriber count, total views, video count, top-viewed videos, latest uploads, oldest uploads, and full video list per channel. Ideal for content strategy, niche research, and SEO benchmarking. - **URL**: https://apify.com/hasnainnisar67/youtube-competitor-analyzer.md - **Developed by:** [Hasnain Nisar](https://apify.com/hasnainnisar67) (community) - **Categories:** Videos - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $0.99 / 1,000 channel analyzeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 Competitor Analyzer - Compare Channels Side-by-Side **Compare up to 5 YouTube channels in a single run.** See subscriber counts, top-performing videos, posting cadence, and average views — perfect for competitor research, influencer due diligence, and content strategy. ### What this YouTube Competitor Analyzer does Pass 1–5 YouTube channel URLs and the actor: 1. Pulls each channel's metadata in parallel (subscribers, total views, video count, description) 2. Extracts the latest N videos from each channel (configurable, default 30) 3. Identifies each channel's **top 3 most-viewed**, **latest 3**, and **oldest 3** videos in the fetched window 4. Returns a single comparison record + per-channel records for easy filtering The output drops straight into Google Sheets, Notion, Airtable, or your BI tool — ready for charts and side-by-side dashboards. ### Why use this YouTube Competitor Analyzer? - **No YouTube Data API key** — the official API caps you at 10,000 units/day - **Up to 5 channels in a single run** — perfect for category benchmarking - **Pre-sorted highlights** — top, latest, oldest delivered ready to chart - **Predictable cost** — analyses complete in 30–60 seconds for 5 channels at 30 videos each - **Resilient input** — accepts handles, channel IDs, custom URLs, or video URLs ### Use cases - **Competitor benchmarking** — compare your channel against 4 rivals in your niche - **Influencer due diligence** — qualify creators before sponsoring or partnering - **Content gap analysis** — see what video formats your competitors crush at - **Niche research** — identify which channels are growing fastest in a category - **Pitch decks & reports** — generate clean comparison tables in minutes ### Input ```json { "channelUrls": [ "https://www.youtube.com/@MrBeast", "https://www.youtube.com/@MarkRober", "https://www.youtube.com/@VeritasiumYT" ], "maxVideos": 30 } ```` | Field | Type | Default | Description | |-------|------|---------|-------------| | `channelUrls` | array of 1-5 strings | required | Channel URLs to compare | | `maxVideos` | integer | 30 | Videos to consider per channel (5–500) | ### Output The first dataset item is the full comparison object: ```json { "channels": [ { "channel_name": "MrBeast", "subscriber_count": 250000000, "view_count": 50000000000, "video_count": 800, "videos_fetched": 30, "top_viewed": [ /* top 3 most-viewed in fetched window */ ], "latest_videos": [ /* most recent 3 uploads */ ], "oldest_videos": [ /* oldest 3 in window — useful for posting-cadence math */ ], "all_videos": [ /* … */ ] }, { /* next channel */ } ] } ``` Each subsequent dataset item is a single-channel record (one per competitor) — the same shape returned by the standalone YouTube Channel Scraper. ### How it works The actor uses [yt-dlp](https://github.com/yt-dlp/yt-dlp) with `extract_flat='in_playlist'` and runs all channel pulls concurrently with `asyncio.gather`. No Playwright, no API tokens, no rate limits. ### Related actors - **YouTube Channel Scraper** — single-channel deep dive - **YouTube Video Info Scraper** — full per-video metadata - **YouTube Downloader** — downloadable MP4 / MP3 URLs ### FAQ **Q: Can I compare more than 5 channels?** The actor caps at 5 to keep runtimes predictable. Run multiple jobs and combine the datasets if you need more. **Q: Is the data live?** Yes — every run hits YouTube fresh. There is no staleness window. **Q: Does it handle very large channels (1M+ videos)?** Set `maxVideos` to whatever window you actually need (e.g. last 100). The actor's runtime scales linearly with this value. # Actor input Schema ## `channelUrls` (type: `array`): Provide between 1 and 5 YouTube channel URLs to analyze in parallel. Accepts /@handle, /channel/UC..., /c/, /user/, or any video URL. ## `maxVideos` (type: `integer`): How many recent videos to consider per channel. ## `proxyConfiguration` (type: `object`): yt-dlp is routed through this proxy. Apify datacenter IPs are aggressively rate-limited by YouTube, so a proxy is required to populate top\_viewed / latest\_videos / oldest\_videos (which need per-video metadata). ## Actor input object example ```json { "channelUrls": [ "https://www.youtube.com/@MrBeast", "https://www.youtube.com/@MarkRober" ], "maxVideos": 30, "proxyConfiguration": { "useApifyProxy": true } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "channelUrls": [ "https://www.youtube.com/@MrBeast", "https://www.youtube.com/@MarkRober" ], "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("hasnainnisar67/youtube-competitor-analyzer").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 = { "channelUrls": [ "https://www.youtube.com/@MrBeast", "https://www.youtube.com/@MarkRober", ], "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("hasnainnisar67/youtube-competitor-analyzer").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 '{ "channelUrls": [ "https://www.youtube.com/@MrBeast", "https://www.youtube.com/@MarkRober" ], "proxyConfiguration": { "useApifyProxy": true } }' | apify call hasnainnisar67/youtube-competitor-analyzer --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=hasnainnisar67/youtube-competitor-analyzer", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Competitor Analyzer", "description": "Compare up to 5 YouTube channels side-by-side. Returns subscriber count, total views, video count, top-viewed videos, latest uploads, oldest uploads, and full video list per channel. Ideal for content strategy, niche research, and SEO benchmarking.", "version": "0.1", "x-build-id": "5NjbCN7AT1MpHPwb1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/hasnainnisar67~youtube-competitor-analyzer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-hasnainnisar67-youtube-competitor-analyzer", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/hasnainnisar67~youtube-competitor-analyzer/runs": { "post": { "operationId": "runs-sync-hasnainnisar67-youtube-competitor-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/hasnainnisar67~youtube-competitor-analyzer/run-sync": { "post": { "operationId": "run-sync-hasnainnisar67-youtube-competitor-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "channelUrls" ], "properties": { "channelUrls": { "title": "Competitor channel URLs (1-5)", "type": "array", "description": "Provide between 1 and 5 YouTube channel URLs to analyze in parallel. Accepts /@handle, /channel/UC..., /c/, /user/, or any video URL.", "items": { "type": "string" } }, "maxVideos": { "title": "Max videos per channel", "minimum": 5, "maximum": 500, "type": "integer", "description": "How many recent videos to consider per channel.", "default": 30 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "yt-dlp is routed through this proxy. Apify datacenter IPs are aggressively rate-limited by YouTube, so a proxy is required to populate top_viewed / latest_videos / oldest_videos (which need per-video metadata).", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```