# Decision Maker Search (`companyenrich/decision-maker-search`) Actor Find decision makers with CompanyEnrich people search filters and cursor pagination. - **URL**: https://apify.com/companyenrich/decision-maker-search.md - **Developed by:** [companyenrich](https://apify.com/companyenrich) (community) - **Categories:** Agents, Lead generation - **Stats:** 2 total users, 1 monthly users, 80.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $500.00 / 1,000 decision-maker-searches 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 ### What does CompanyEnrich Decision Maker Search do? **CompanyEnrich Decision Maker Search** finds professional profiles for sales, recruiting, and GTM workflows. It uses cursor-based pagination, so you can continue beyond page-based limits while saving one dataset row per decision maker. The Actor is built for users who want CompanyEnrich people data through Apify schedules, datasets, webhooks, integrations, and no-code automations. Users run the Actor with decision maker search filters only. ### Why use CompanyEnrich Decision Maker Search? Use this Actor for sales prospecting, recruiting research, CRM enrichment, account-based workflows, and GTM operations that need people filtered by title, company domain, seniority, department, country, or company criteria. CompanyEnrich is an API-first B2B data platform for platforms, AI agents, RevOps teams, and GTM workflows. Its people data supports professional profile search across titles, companies, seniority, departments, and company filters. ### How to use CompanyEnrich Decision Maker Search 1. Open the Actor in Apify Console. 2. Add people filters such as `positionQuery`, `domains`, `countries`, `seniority`, or `department`. 3. Optionally paste a previous `nextCursor` into `cursor` to continue a search. 4. Click **Start**. 5. Download results from the default dataset as JSON, CSV, Excel, HTML, or through the Apify API. Each run returns one fixed page of up to 10 decision makers. The page size is not configurable. To get more results, use the `nextCursor` from the dataset or summary as the `cursor` in the next run. ### Input | Field | Type | Description | | ------------------- | ------------ | ----------------------------------------------------------------------------------- | | `query` | string | Optional decision maker search query. | | `positionQuery` | string array | Search terms for current job title, such as `sales` or `founder`. | | `domains` | string array | Company domains to find decision makers for. Up to 100 domains. | | `countries` | string array | Optional ISO 2-letter country codes. | | `seniority` | string array | Optional seniority filters such as `c-suite`, `vp`, `director`, or `manager`. | | `department` | string array | Optional department slugs such as `sales`, `marketing`, or `engineering-technical`. | | `cursor` | string | Optional starting cursor from a previous run. | | `companyFilter` | object | Advanced CompanyEnrich company lookup filter. | | `exclude` | object | Advanced people exclusion filters. | | `additionalFilters` | object | Advanced JSON filters passed directly to the API. | | `failOnError` | boolean | If enabled, the run fails after pushing an error row when the API call fails. | Example input: ```json { "positionQuery": ["sales"], "domains": ["apple.com"], "seniority": ["director", "vp"] } ```` ### Output The Actor writes one item per decision maker to the default dataset. You can download the dataset in JSON, CSV, Excel, HTML, or access it through the Apify API. Example dataset item: ```json { "status": "success", "rank": 1, "name": "Jane Doe", "position": "VP Sales", "seniority": "vp", "department": "sales", "linkedinUrl": "https://www.linkedin.com/in/example", "country": "United States", "currentCompanyName": "Apple", "currentCompanyDomain": "apple.com", "nextCursor": "eyJwYWdlIjoyfQ", "creditCost": 50, "person": { "id": 123, "name": "Jane Doe" } } ``` The default key-value store also contains an `OUTPUT` summary record with result counts, fixed page size, cursor metadata, and pagination totals. ### Pricing and usage This Actor uses Apify pay-per-event pricing. Each run requests one fixed page of up to 10 decision makers, so `person-profile` events are charged for that fixed page when pay-per-event pricing is active. CompanyEnrich documents `POST /people/search/scroll` as costing 2 credits per person returned, with 2 credits minimum if no results are found. ### Tips and advanced options - Use company `domains` when you need people from specific accounts. - Use `positionQuery`, `seniority`, and `department` together for more targeted searches. - Store `nextCursor` from the dataset or summary to continue the search with the next fixed 10-result page. - Use `exclude` to remove unwanted titles, countries, domains, seniorities, or departments. - Use Apify schedules, webhooks, integrations, and API access to connect people results to downstream workflows. ### FAQ, disclaimers, and support **Does this Actor scrape websites?**\ No. It calls the CompanyEnrich REST API and stores the API response in Apify datasets. **Where can I get help?**\ Use the Actor Issues tab in Apify Console for bugs, field requests, or integration questions. Learn more about CompanyEnrich at https://companyenrich.com. # Actor input Schema ## `query` (type: `string`): Optional search query for decision makers. ## `positionQuery` (type: `array`): Search queries to apply to a decision maker's current job title. ## `domains` (type: `array`): Company domains to find decision makers for. CompanyEnrich allows up to 100 domains. ## `countries` (type: `array`): Optional ISO 2-letter country codes to filter by. ## `seniority` (type: `array`): Optional seniority filters. ## `department` (type: `array`): Optional department slugs such as sales, marketing, engineering-technical, information-technology, finance, operations, or human-resources. ## `cursor` (type: `string`): Optional cursor from a previous run. Leave empty to start from the first page. ## `atCurrentCompanyAfter` (type: `string`): Only include people who joined their current company after this UTC date or date-time. ## `atCurrentCompanyBefore` (type: `string`): Only include people who joined their current company before this UTC date or date-time. ## `atCurrentPositionAfter` (type: `string`): Only include people who started their current position after this UTC date or date-time. ## `atCurrentPositionBefore` (type: `string`): Only include people who started their current position before this UTC date or date-time. ## `companyFilter` (type: `object`): Advanced CompanyEnrich company lookup filter for people search, matching the API's CompanyLookupInput schema. ## `exclude` (type: `object`): Advanced decision maker exclusion filters, such as excluded domains, countries, seniority, department, or positionQuery. ## `additionalFilters` (type: `object`): Advanced JSON filters passed directly to CompanyEnrich Decision Maker Search. ## `requestTimeoutSecs` (type: `integer`): Maximum time to wait for each CompanyEnrich API request. ## `maxRetries` (type: `integer`): Retry count for transient network failures, 429 responses, and 5xx responses. ## `failOnError` (type: `boolean`): When enabled, the Actor pushes an error row to the dataset and then fails the run if CompanyEnrich returns an error. ## Actor input object example ```json { "positionQuery": [ "sales" ], "domains": [ "apple.com" ], "countries": [], "seniority": [], "department": [], "companyFilter": {}, "exclude": {}, "additionalFilters": {}, "requestTimeoutSecs": 30, "maxRetries": 2, "failOnError": true } ``` # Actor output Schema ## `dataset` (type: `string`): No description ## `summary` (type: `string`): No description # 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 = { "positionQuery": [ "sales" ], "domains": [ "apple.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("companyenrich/decision-maker-search").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 = { "positionQuery": ["sales"], "domains": ["apple.com"], } # Run the Actor and wait for it to finish run = client.actor("companyenrich/decision-maker-search").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 '{ "positionQuery": [ "sales" ], "domains": [ "apple.com" ] }' | apify call companyenrich/decision-maker-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=companyenrich/decision-maker-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Decision Maker Search", "description": "Find decision makers with CompanyEnrich people search filters and cursor pagination.", "version": "0.1", "x-build-id": "Z7F14x8b2WeoA7tGG" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/companyenrich~decision-maker-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-companyenrich-decision-maker-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/companyenrich~decision-maker-search/runs": { "post": { "operationId": "runs-sync-companyenrich-decision-maker-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/companyenrich~decision-maker-search/run-sync": { "post": { "operationId": "run-sync-companyenrich-decision-maker-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "query": { "title": "Decision maker query", "type": "string", "description": "Optional search query for decision makers." }, "positionQuery": { "title": "Position queries", "type": "array", "description": "Search queries to apply to a decision maker's current job title.", "items": { "type": "string" }, "default": [ "sales" ] }, "domains": { "title": "Company domains", "type": "array", "description": "Company domains to find decision makers for. CompanyEnrich allows up to 100 domains.", "items": { "type": "string" }, "default": [ "apple.com" ] }, "countries": { "title": "Countries", "type": "array", "description": "Optional ISO 2-letter country codes to filter by.", "items": { "type": "string" }, "default": [] }, "seniority": { "title": "Seniority", "type": "array", "description": "Optional seniority filters.", "items": { "type": "string", "enum": [ "owner", "founder", "c-suite", "partner", "vp", "head", "director", "manager", "senior", "entry", "intern" ] }, "default": [] }, "department": { "title": "Department", "type": "array", "description": "Optional department slugs such as sales, marketing, engineering-technical, information-technology, finance, operations, or human-resources.", "items": { "type": "string" }, "default": [] }, "cursor": { "title": "Starting cursor", "type": "string", "description": "Optional cursor from a previous run. Leave empty to start from the first page." }, "atCurrentCompanyAfter": { "title": "At current company after", "type": "string", "description": "Only include people who joined their current company after this UTC date or date-time." }, "atCurrentCompanyBefore": { "title": "At current company before", "type": "string", "description": "Only include people who joined their current company before this UTC date or date-time." }, "atCurrentPositionAfter": { "title": "At current position after", "type": "string", "description": "Only include people who started their current position after this UTC date or date-time." }, "atCurrentPositionBefore": { "title": "At current position before", "type": "string", "description": "Only include people who started their current position before this UTC date or date-time." }, "companyFilter": { "title": "Company filter", "type": "object", "description": "Advanced CompanyEnrich company lookup filter for people search, matching the API's CompanyLookupInput schema.", "default": {} }, "exclude": { "title": "Exclude filters", "type": "object", "description": "Advanced decision maker exclusion filters, such as excluded domains, countries, seniority, department, or positionQuery.", "default": {} }, "additionalFilters": { "title": "Additional filters", "type": "object", "description": "Advanced JSON filters passed directly to CompanyEnrich Decision Maker Search.", "default": {} }, "requestTimeoutSecs": { "title": "Request timeout seconds", "minimum": 1, "type": "integer", "description": "Maximum time to wait for each CompanyEnrich API request.", "default": 30 }, "maxRetries": { "title": "Max retries", "minimum": 0, "type": "integer", "description": "Retry count for transient network failures, 429 responses, and 5xx responses.", "default": 2 }, "failOnError": { "title": "Fail run on API errors", "type": "boolean", "description": "When enabled, the Actor pushes an error row to the dataset and then fails the run if CompanyEnrich returns an error.", "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 } } } } } } } } } } ```