# Podcast Sponsor Evidence Report Scraper (`taroyamada/podcast-sponsor-evidence-report-scraper`) Actor Find public podcast sponsor evidence from RSS feeds, show pages, and Apple search terms, then generate source-linked research exports. - **URL**: https://apify.com/taroyamada/podcast-sponsor-evidence-report-scraper.md - **Developed by:** [åĪŠéƒŽ åąąį”°](https://apify.com/taroyamada) (community) - **Categories:** Business, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $15.00 / 1,000 podcast enriched shows 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 ## Podcast Sponsor Evidence Report Scraper Podcast agencies and sponsorship researchers use this actor to scan public RSS feeds, show pages, and Apple search terms. Input podcast RSS feeds, public show URLs, or search terms. Get source-linked sponsor evidence rows, publisher links, and reviewable research export rows. ### Store Quickstart 1. Start with the first input example below using `dryRun=false`. 2. Keep `emitUnchanged=false` so repeated no-change runs emit zero rows and zero charges. 3. Review `billingEventName` before scheduling recurring runs. ### Input Examples ```json { "rssFeedUrls": [ "https://feeds.npr.org/510289/podcast.xml" ], "showUrls": [], "searchTerms": [ "business podcast sponsorship research" ], "maxEpisodesPerFeed": 8, "emitResearchExport": true, "emitUnchanged": false, "dryRun": false } ```` ```json { "rssFeedUrls": [ "https://feeds.npr.org/510289/podcast.xml" ], "showUrls": [], "searchTerms": [ "ecommerce podcast" ], "maxEpisodesPerFeed": 8, "emitResearchExport": true, "emitUnchanged": false, "dryRun": false } ``` ```json { "rssFeedUrls": [ "https://feeds.npr.org/510289/podcast.xml" ], "showUrls": [], "searchTerms": [ "business podcast sponsorship research" ], "maxEpisodesPerFeed": 8, "emitResearchExport": false, "emitUnchanged": false, "dryRun": false } ``` ### Sample Output See `docs/sample-output.json` for a complete sample. ### Output Fields Every row includes: - `billingEventName` for PAY\_PER\_EVENT charging - `sourceName`, `sourceUrl`, `retrievedAt`, and `sourceMethod` - `authorizationBasis` - `limitations` and `prohibitedInterpretations` ### Pricing Phase 8.10 target pricing uses tiered PAY\_PER\_EVENT events: - `podcast-enriched-show`: $0.015 per source-linked public show row without sponsor evidence - `podcast-sponsor-evidence`: $0.25 per source-linked sponsor evidence row - `podcast-research-export`: $7.00 per generated research export row No-change runs must emit zero default dataset rows and zero billable events by default. ### Compliance Guardrails - Use public RSS, public show pages, and public podcast search surfaces. - Use sponsor evidence only for source-linked research and human review. - Keep sponsor evidence source-linked and reviewable. ### See Also - `apple-podcast-scraper` for Apple Podcasts show metadata. - `apple-podcast-chart-tracker` for chart movement workflows. - `apple-podcast-reviews-monitor` for listener review workflows. # Actor input Schema ## `rssFeedUrls` (type: `array`): Public podcast RSS feed URLs to inspect. ## `showUrls` (type: `array`): Public podcast show or publisher pages to inspect. ## `searchTerms` (type: `array`): Optional Apple iTunes Search API terms for feed discovery. ## `maxEpisodesPerFeed` (type: `integer`): Maximum RSS episode items to inspect per feed. ## `emitResearchExport` (type: `boolean`): Emit one sponsorship research export row when evidence rows are found. ## `emitUnchanged` (type: `boolean`): When false, previously seen evidence is suppressed. ## `dryRun` (type: `boolean`): When true, emit sample rows locally without external live calls or billing. ## Actor input object example ```json { "rssFeedUrls": [ "https://feeds.npr.org/510289/podcast.xml" ], "showUrls": [], "searchTerms": [ "business podcast sponsorship research" ], "maxEpisodesPerFeed": 8, "emitResearchExport": true, "emitUnchanged": false, "dryRun": 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("taroyamada/podcast-sponsor-evidence-report-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`ðŸ’ū 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 = {} # Run the Actor and wait for it to finish run = client.actor("taroyamada/podcast-sponsor-evidence-report-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("ðŸ’ū 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 '{}' | apify call taroyamada/podcast-sponsor-evidence-report-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=taroyamada/podcast-sponsor-evidence-report-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Podcast Sponsor Evidence Report Scraper", "description": "Find public podcast sponsor evidence from RSS feeds, show pages, and Apple search terms, then generate source-linked research exports.", "version": "0.1", "x-build-id": "dIBTOBtV3aeiPn4Im" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/taroyamada~podcast-sponsor-evidence-report-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-taroyamada-podcast-sponsor-evidence-report-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/taroyamada~podcast-sponsor-evidence-report-scraper/runs": { "post": { "operationId": "runs-sync-taroyamada-podcast-sponsor-evidence-report-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/taroyamada~podcast-sponsor-evidence-report-scraper/run-sync": { "post": { "operationId": "run-sync-taroyamada-podcast-sponsor-evidence-report-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "rssFeedUrls": { "title": "RSS feed URLs", "type": "array", "description": "Public podcast RSS feed URLs to inspect.", "items": { "type": "string" }, "default": [ "https://feeds.npr.org/510289/podcast.xml" ] }, "showUrls": { "title": "Show URLs", "type": "array", "description": "Public podcast show or publisher pages to inspect.", "items": { "type": "string" }, "default": [] }, "searchTerms": { "title": "Apple Podcast search terms", "type": "array", "description": "Optional Apple iTunes Search API terms for feed discovery.", "items": { "type": "string" }, "default": [ "business podcast sponsorship research" ] }, "maxEpisodesPerFeed": { "title": "Max episodes per feed", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum RSS episode items to inspect per feed.", "default": 8 }, "emitResearchExport": { "title": "Emit research export", "type": "boolean", "description": "Emit one sponsorship research export row when evidence rows are found.", "default": true }, "emitUnchanged": { "title": "Emit unchanged rows", "type": "boolean", "description": "When false, previously seen evidence is suppressed.", "default": false }, "dryRun": { "title": "Dry run", "type": "boolean", "description": "When true, emit sample rows locally without external live calls or billing.", "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 } } } } } } } } } } ```