# Zoominfo Data Catalog Extractor (`getdataforme/zoominfo-data-catalog-extractor`) Actor The Zoominfo Data Catalog Extractor is an Apify tool for scraping detailed data from Zoominfo's catalog, including job postings, contacts, and financial reports.... - **URL**: https://apify.com/getdataforme/zoominfo-data-catalog-extractor.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 50.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 1,000 results 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 --- ## Zoominfo Data Catalog Extractor ### Introduction The **Zoominfo Data Catalog Extractor** is a powerful tool designed to scrape and extract detailed data from the Zoominfo Data Catalog. This Apify Actor enables users to access comprehensive datasets on job postings, contact information, earnings reports, and more, providing valuable insights for business intelligence, market research, and competitive analysis. ### Features - **Comprehensive Data Extraction**: Extracts a wide range of data including job postings, contacts, and financial filings. - **High-Quality Data**: Ensures reliable and accurate datasets with verified sources. - **Customizable Limits**: Allows users to set item limits for tailored data extraction needs. - **Global Coverage**: Accesses global datasets spanning multiple industries and regions. - **User-Friendly Configuration**: Simple setup with intuitive input parameters. ### Input Parameters | Parameter | Type | Required | Description | Example | |-------------|---------|----------|-----------------------------------------------------------------------------|-------------------------------------------| | `Urls` | array | Yes | The URLs for the spider to scrape. | `["https://example.com/data"]` | | `item_limit`| integer | No | Maximum items to scrape per actor run. Set to 0 for no limit. | `10` | ### Example Usage #### Input JSON ```json { "Urls": [ "https://cws-zoominfo-assets.zoominfo.com/data-page/data-platform-standalone.html" ], "item_limit": 10 } ```` #### Output JSON ```json [ { "zi_idx": "1", "zi_open": "1", "name": "Contact", "badge": "Core", "tagline": "Person-level intelligence at scale", "field_count": "26 fields", "description": "Professional profiles for 500M+ people — verified emails, mobile phones, direct dials, job titles, management level, and accuracy scores.", "coverage": "Global", "table_name": "PRD_DATA_SERVICES_AND_SOLUTIONS.PRD_DATACUBES.PERSON_DATACUBE_TABLE", "key_fields": [ "ZoomInfo Contact ID", "First / Last Name", "Job Title", "Job Function", "Management Level", "Direct Phone", "Mobile Phone", "Email Address", "Contact Accuracy Score", "Contact Accuracy Grade", "LinkedIn URL", "Notice Provided Date", "ZoomInfo Company ID" ], "use_cases": [ "Contact enrichment", "Outbound sequencing", "ABM targeting", "Persona modeling" ], "raw_text": "Contact Core Person-level intelligence at scale 26 fields Professional profiles for 500M+ people — verified emails, mobile phones, direct dials, job titles, management level, and accuracy scores. Coverage: Global PRD_DATA_SERVICES_AND_SOLUTIONS.PRD_DATACUBES.PERSON_DATACUBE_TABLE KEY FIELDS ZoomInfo Contact ID First / Last Name Job Title Job Function Management Level Direct Phone Mobile Phone Email Address Contact Accuracy Score Contact Accuracy Grade LinkedIn URL Notice Provided Date ZoomInfo Company ID USE CASES Contact enrichment Outbound sequencing ABM targeting Persona modeling", "actor_id": "izl78f7JjDYOQbS3b", "run_id": "vxBOnZuoGfWbzSpei" }, { "zi_idx": "2", "zi_open": "1", "name": "Job Postings", "badge": "Core", "tagline": "Hiring activity across 281M job postings worldwide", "field_count": "32 fields", "description": "Aggregated job posting data sourced from PredictLeads — 281M+ records spanning 6.5 years of history. Includes job title, department, management level, salary, contract type, and open/closed status, all linkable to ZoomInfo company records.", "coverage": "Global (2019–present)", "table_name": "yazi-prd-zany-zebra.zdp_gtm_store.v_latest_job_post_global", "key_fields": [ "Job Title", "Company Name", "Website Domain", "ZI Company ID", "Description", "Categories", "Departments", "Job Functions", "Management Level", "Contract Type", "Salary", "Address", "First Seen", "Last Seen", "Job Post Closed" ], "use_cases": [ "Hiring signal prospecting", "ICP role targeting", "Competitive talent tracking", "GTM trigger campaigns" ], "raw_text": "Job Postings Core Hiring activity across 281M job postings worldwide 32 fields Aggregated job posting data sourced from PredictLeads — 281M+ records spanning 6.5 years of history. Includes job title, department, management level, salary, contract type, and open/closed status, all linkable to ZoomInfo company records. Coverage: Global (2019–present) yazi-prd-zany-zebra.zdp_gtm_store.v_latest_job_post_global KEY FIELDS Job Title Company Name Website Domain ZI Company ID Description Categories Departments Job Functions Management Level Contract Type Salary Address First Seen Last Seen Job Post Closed USE CASES Hiring signal prospecting ICP role targeting Competitive talent tracking GTM trigger campaigns", "actor_id": "izl78f7JjDYOQbS3b", "run_id": "vxBOnZuoGfWbzSpei" }, { "zi_idx": "3", "zi_open": "1", "name": "Earnings & Public Filings", "badge": "Core", "tagline": "Turn public earnings events into sales intelligence", "field_count": "41 fields", "description": "Full transcripts and metadata for 250K+ earnings calls, presentations, and investor events sourced from Aiera. Covers earnings calls (13.5%), earnings releases (25%), presentations (53%), special situations, and investor meetings — with 100% ZoomInfo company match rate.", "coverage": "United States — Public Companies (2022–present)", "table_name": "PRD_DATA_SERVICES_AND_SOLUTIONS.PRD_DATACUBES.EARNINGS_CUBE_TABLE", "key_fields": [ "ZoomInfo Company ID", "Company Name", "Ticker", "Bloomberg Ticker", "Event Type", "Event Date", "Fiscal Year", "Fiscal Quarter", "Consolidated Transcript", "Transcript Audio URL", "Public URL", "Status" ], "use_cases": [ "Executive briefings", "Account planning", "Competitive research", "Trigger-based outreach" ], "raw_text": "Earnings & Public Filings Core Turn public earnings events into sales intelligence 41 fields Full transcripts and metadata for 250K+ earnings calls, presentations, and investor events sourced from Aiera. Covers earnings calls (13.5%), earnings releases (25%), presentations (53%), special situations, and investor meetings — with 100% ZoomInfo company match rate. United States — Public Companies (2022–present) PRD_DATA_SERVICES_AND_SOLUTIONS.PRD_DATACUBES.EARNINGS_CUBE_TABLE KEY FIELDS ZoomInfo Company ID Company Name Ticker Bloomberg Ticker Event Type Event Date Fiscal Year Fiscal Quarter Consolidated Transcript Transcript Audio URL Public URL Status USE CASES Executive briefings Account planning Competitive research Trigger-based outreach", "actor_id": "izl78f7JjDYOQbS3b", "run_id": "vxBOnZuoGfWbzSpei" } ] ``` ### Use Cases - **Market Research and Analysis**: Gain insights into market trends and competitor strategies. - **Competitive Intelligence**: Monitor competitors' job postings, financial reports, and contact information. - **Price Monitoring**: Track pricing changes across industries for strategic decision-making. - **Content Aggregation**: Aggregate data for content creation and marketing purposes. - **Academic Research**: Utilize datasets for academic studies and publications. - **Business Automation**: Automate data collection processes to enhance operational efficiency. ### Installation and Usage 1. Search for "Zoominfo Data Catalog Extractor" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters as needed. 4. Click "Start" to begin extraction. 5. Monitor progress in the log. 6. Export results in your preferred format (JSON, CSV, Excel). ### Output Format The output data is structured with key fields such as `zi_idx`, `name`, `badge`, `tagline`, `field_count`, `description`, `coverage`, `table_name`, `key_fields`, `use_cases`, and `raw_text`. Each entry provides comprehensive details about the extracted dataset, including its purpose, coverage, and potential use cases. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: [Get Data For Me](https://getdataforme.com/contact/) We're here to help you get the most out of this Actor! # Actor input Schema ## `Urls` (type: `array`): The urls for the spider. ## `item_limit` (type: `integer`): Maximum items to scrape per actor run. Set to 0 for no limit. ## Actor input object example ```json { "Urls": [ "https://cws-zoominfo-assets.zoominfo.com/data-page/data-platform-standalone.html" ], "item_limit": 10 } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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("getdataforme/zoominfo-data-catalog-extractor").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 = {} # Run the Actor and wait for it to finish run = client.actor("getdataforme/zoominfo-data-catalog-extractor").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 '{}' | apify call getdataforme/zoominfo-data-catalog-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/zoominfo-data-catalog-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Zoominfo Data Catalog Extractor", "description": "The Zoominfo Data Catalog Extractor is an Apify tool for scraping detailed data from Zoominfo's catalog, including job postings, contacts, and financial reports....", "version": "0.0", "x-build-id": "6XVdFWhkK9mhpD4hK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~zoominfo-data-catalog-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-zoominfo-data-catalog-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~zoominfo-data-catalog-extractor/runs": { "post": { "operationId": "runs-sync-getdataforme-zoominfo-data-catalog-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~zoominfo-data-catalog-extractor/run-sync": { "post": { "operationId": "run-sync-getdataforme-zoominfo-data-catalog-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "default": [ "https://cws-zoominfo-assets.zoominfo.com/data-page/data-platform-standalone.html" ], "items": { "type": "string" } }, "item_limit": { "title": "Item limit", "minimum": 0, "type": "integer", "description": "Maximum items to scrape per actor run. Set to 0 for no limit.", "default": 10 } } }, "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 } } } } } } } } } } ```