# YouTube Sponsorship & Brand Deal Tracker (`seemuapps/youtube-sponsorship-tracker`) Actor Scan a YouTube channel's recent videos and extract every sponsor, brand deal, affiliate link, and promo code from the descriptions. - **URL**: https://apify.com/seemuapps/youtube-sponsorship-tracker.md - **Developed by:** [Andrew](https://apify.com/seemuapps) (community) - **Categories:** Videos, Lead generation, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $12.00 / 1,000 sponsor / brand deal detecteds 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 Sponsorship & Brand Deal Tracker Find out which brands pay any YouTube creator. Scan a channel's recent videos and extract every sponsor, brand deal, affiliate link, and promo code straight from the video descriptions — no login required. ### What you get One row per detected sponsor signal (video × brand), with: - **brandDomain** and **brandNameGuess** — the company behind each link or shout-out - **link** and **resolvedLink** — the raw URL, plus the real destination when a shortener (bit.ly, geni.us, amzn.to, lmg.gg, linktr.ee…) is followed - **linkType** — `affiliate`, `utm`, `direct`, or `social`, so you can separate paid placements from a creator's own socials - **promoCodes** and **discount** — extracted discount codes (e.g. `SAVE20`) and offers (e.g. `15% off`) - **matchedPhrase** — the exact sponsor wording detected, like "Thanks Wispr Flow for sponsoring" or "brought to you by…" - **signalTypes** — which detectors fired for the row (`link`, `affiliate`, `utm`, `promo-code`, `sponsor-phrase`) - Full video context: channelId, channelTitle, videoId, videoUrl, videoTitle, publishedAt - Export to JSON, CSV, or Google Sheets directly from the Apify console ### Use cases - **Competitor and market research** — see which brands sponsor creators in your niche and how often - **Influencer vetting** — verify a creator's real brand partnerships before you sign a deal - **Affiliate and partnership intelligence** — discover active affiliate programs and promo codes across a channel - **Lead generation** — build a list of brands already investing in creator marketing - **Media monitoring** — track a creator's sponsors over time ### How to use 1. Enter a **Channel** — an `@handle` (e.g. `@mkbhd`), a channel URL (`youtube.com/@handle`, `/channel/UC…`, `/c/Name`, `/user/Name`), or a raw `UC…` channel ID. Or paste explicit **Video URLs** to scan specific videos instead. 2. Set **Max Videos** — how many of the channel's most-recent uploads to scan (default 30, up to 200). 3. Leave **Resolve Short Links** on to follow link shorteners and reveal the real brand behind each link. 4. Run the actor — results appear in the **Dataset** tab. Videos that contain no detectable sponsor signals still emit one row (with `brandDomain` empty and an empty `signalTypes`) so you can confirm the video was scanned. ### Output format Each dataset record: ```json { "channelId": "UCXuqSBlHAE6Xw-yeJA0Tunw", "channelTitle": "Linus Tech Tips", "videoId": "bNpmB1heEF0", "videoUrl": "https://www.youtube.com/watch?v=bNpmB1heEF0", "videoTitle": "Linux is Easy, right?", "publishedAt": "2026-05-28T18:48:55Z", "brandDomain": "wisprflow.ai", "brandNameGuess": "Wisprflow", "link": "https://ref.wisprflow.ai/ltt", "resolvedLink": null, "linkType": "direct", "promoCodes": ["LTT"], "discount": null, "matchedPhrase": "Thanks Wispr Flow for sponsoring", "signalTypes": ["link", "promo-code", "sponsor-phrase"] } ```` # Actor input Schema ## `channelInput` (type: `string`): A YouTube channel to scan: an @handle, a channel URL (youtube.com/@handle, /channel/UC..., /c/Name, /user/Name), or a raw UC channel id. Leave empty if you supply Video URLs instead. ## `videoUrls` (type: `array`): Optional explicit list of YouTube video URLs (or video IDs) to scan instead of a whole channel. If provided, the channel field is ignored. ## `maxVideos` (type: `integer`): How many of the channel's most-recent videos to scan for sponsor signals (1-200). Ignored when Video URLs are supplied. ## `resolveShortLinks` (type: `boolean`): Follow link shorteners (bit.ly, geni.us, amzn.to, etc.) to reveal the real destination brand domain. Slightly slower but gives cleaner brand attribution. ## Actor input object example ```json { "channelInput": "@mkbhd", "maxVideos": 30, "resolveShortLinks": true } ``` # Actor output Schema ## `results` (type: `string`): One record per (video, detected brand). Fields: channelId, channelTitle, videoId, videoUrl, videoTitle, publishedAt, brandDomain, brandNameGuess, link, resolvedLink, linkType (affiliate|utm|direct|social), promoCodes, discount, matchedPhrase, signalTypes. Videos with no sponsor signals emit a single row with brandDomain=null and signalTypes=\[]. # 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 = { "channelInput": "@mkbhd" }; // Run the Actor and wait for it to finish const run = await client.actor("seemuapps/youtube-sponsorship-tracker").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 = { "channelInput": "@mkbhd" } # Run the Actor and wait for it to finish run = client.actor("seemuapps/youtube-sponsorship-tracker").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 '{ "channelInput": "@mkbhd" }' | apify call seemuapps/youtube-sponsorship-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seemuapps/youtube-sponsorship-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Sponsorship & Brand Deal Tracker", "description": "Scan a YouTube channel's recent videos and extract every sponsor, brand deal, affiliate link, and promo code from the descriptions.", "version": "1.0", "x-build-id": "if2tr9huJm4bAfCMu" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seemuapps~youtube-sponsorship-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seemuapps-youtube-sponsorship-tracker", "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/seemuapps~youtube-sponsorship-tracker/runs": { "post": { "operationId": "runs-sync-seemuapps-youtube-sponsorship-tracker", "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/seemuapps~youtube-sponsorship-tracker/run-sync": { "post": { "operationId": "run-sync-seemuapps-youtube-sponsorship-tracker", "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": { "channelInput": { "title": "Channel", "type": "string", "description": "A YouTube channel to scan: an @handle, a channel URL (youtube.com/@handle, /channel/UC..., /c/Name, /user/Name), or a raw UC channel id. Leave empty if you supply Video URLs instead." }, "videoUrls": { "title": "Video URLs", "type": "array", "description": "Optional explicit list of YouTube video URLs (or video IDs) to scan instead of a whole channel. If provided, the channel field is ignored.", "items": { "type": "string" } }, "maxVideos": { "title": "Max Videos", "minimum": 1, "maximum": 200, "type": "integer", "description": "How many of the channel's most-recent videos to scan for sponsor signals (1-200). Ignored when Video URLs are supplied.", "default": 30 }, "resolveShortLinks": { "title": "Resolve Short Links", "type": "boolean", "description": "Follow link shorteners (bit.ly, geni.us, amzn.to, etc.) to reveal the real destination brand domain. Slightly slower but gives cleaner brand attribution.", "default": 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 } } } } } } } } } } ```