# Hiring Signal Leads (`chromy_conviction/hiring-signal-leads`) Actor Find companies actively hiring for roles that indicate buying intent, then return ranked B2B lead records with proof jobs and suggested buyer titles. - **URL**: https://apify.com/chromy\_conviction/hiring-signal-leads.md - **Developed by:** [Scott McClaren](https://apify.com/chromy_conviction) (community) - **Categories:** Lead generation, Jobs, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $250.00 / 1,000 qualified company leads This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Hiring Signal Leads Apify Actor that turns public ATS job postings into ranked B2B lead records. Customer input: - target hiring roles or keywords - location filters - a signal preset such as sales tools, AI infrastructure, healthcare staffing, or field operations - max leads Output: - company name and website - hiring intensity score - matching open roles - proof job links - likely business need - suggested buyer titles - ATS sources ### How It Works The Actor calls an upstream job-data Actor, defaults to `jobo.world/ats-jobs-api`, then converts raw job rows into company-level hiring-signal leads. Default upstream pricing observed on Apify: `jobo.world/ats-jobs-api` lists `from $1.30 / 1,000 jobs`. Set customer pricing with enough margin to cover upstream job volume. ### Local Test ```powershell npm install npm test ```` ### Run On Apify Use `sample-input.json` as the first run input. The Actor needs `APIFY_TOKEN` in the Apify runtime so it can call the upstream job-data Actor. ### Suggested Store Positioning **Hiring Signal Leads** Find companies actively hiring for roles that indicate buying intent. Enter target roles and locations; get ranked company leads with proof job links, hiring intensity, likely business need, and suggested buyer titles. ### Suggested Pricing Use pay-per-event or paid Actor pricing in Apify Console. Practical starting point: - charge by company lead returned - start around `$0.25` to `$0.75` per qualified company lead - keep `maxJobsToAnalyze` bounded so upstream cost does not outrun revenue Example economics: - upstream cost: about `$1.30` per 1,000 jobs with ATS Jobs API - 1,000 analyzed jobs produce 50 to 200 leads depending on query - charging `$0.25` per lead produces `$12.50` to `$50` revenue before Apify/platform fees ### Product Boundary This is not a people/contact-email scraper. It returns company-level hiring signals with proof jobs. Customers can use the output to enrich contacts in Apollo, Clay, HubSpot, Salesforce, or another workflow. # Actor input Schema ## `queries` (type: `array`): Job titles or hiring signals to search for. Examples: SDR, Account Executive, Revenue Operations, AI Engineer. ## `locations` (type: `array`): Optional cities, regions, or countries. ## `signalPreset` (type: `string`): Used to choose inferred need and suggested buyer titles. ## `whatYouSell` (type: `string`): Optional one-line description used in output context. ## `maxLeads` (type: `integer`): Maximum number of ranked company lead records to return. ## `maxJobsToAnalyze` (type: `integer`): Upper bound on upstream job records to fetch and score. ## `postedAfter` (type: `string`): Relative or ISO date supported by the upstream ATS Jobs API. Examples: 30 days ago, 2026-01-01T00:00:00Z. ## `strictTitleMatch` (type: `boolean`): When true, upstream search and local scoring focus on job titles instead of descriptions. ## `sources` (type: `array`): Optional ATS source filter. Leave empty for broadest coverage. ## `includeCompanyDetails` (type: `boolean`): Ask upstream job provider for enriched company details when available. This can increase upstream cost/time. ## `upstreamActorId` (type: `string`): Default uses ATS Jobs API. Advanced users can swap in a compatible job-data Actor. ## `upstreamInputOverride` (type: `object`): Optional raw fields merged into the upstream Actor input. ## `sampleJobs` (type: `array`): Optional direct job records for testing without an upstream Actor. ## Actor input object example ```json { "queries": [ "Sales Development Representative", "Account Executive", "Revenue Operations" ], "locations": [ "United States" ], "signalPreset": "sales_tools", "whatYouSell": "", "maxLeads": 100, "maxJobsToAnalyze": 1000, "postedAfter": "30 days ago", "strictTitleMatch": true, "sources": [], "includeCompanyDetails": false, "upstreamActorId": "jobo.world/ats-jobs-api", "upstreamInputOverride": {}, "sampleJobs": [] } ``` # Actor output Schema ## `qualifiedLeads` (type: `string`): No description ## `proofJobs` (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 = { "queries": [ "Sales Development Representative", "Account Executive", "Revenue Operations" ], "locations": [ "United States" ] }; // Run the Actor and wait for it to finish const run = await client.actor("chromy_conviction/hiring-signal-leads").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 = { "queries": [ "Sales Development Representative", "Account Executive", "Revenue Operations", ], "locations": ["United States"], } # Run the Actor and wait for it to finish run = client.actor("chromy_conviction/hiring-signal-leads").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 '{ "queries": [ "Sales Development Representative", "Account Executive", "Revenue Operations" ], "locations": [ "United States" ] }' | apify call chromy_conviction/hiring-signal-leads --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=chromy_conviction/hiring-signal-leads", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hiring Signal Leads", "description": "Find companies actively hiring for roles that indicate buying intent, then return ranked B2B lead records with proof jobs and suggested buyer titles.", "version": "1.0", "x-build-id": "XZfWzjcuvhP6pZ1NP" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/chromy_conviction~hiring-signal-leads/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-chromy_conviction-hiring-signal-leads", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/chromy_conviction~hiring-signal-leads/runs": { "post": { "operationId": "runs-sync-chromy_conviction-hiring-signal-leads", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/chromy_conviction~hiring-signal-leads/run-sync": { "post": { "operationId": "run-sync-chromy_conviction-hiring-signal-leads", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "queries" ], "properties": { "queries": { "title": "Target roles or keywords", "type": "array", "description": "Job titles or hiring signals to search for. Examples: SDR, Account Executive, Revenue Operations, AI Engineer.", "items": { "type": "string" } }, "locations": { "title": "Locations", "type": "array", "description": "Optional cities, regions, or countries.", "items": { "type": "string" } }, "signalPreset": { "title": "Signal preset", "enum": [ "sales_tools", "ai_infra", "healthcare_staffing", "field_ops", "custom" ], "type": "string", "description": "Used to choose inferred need and suggested buyer titles.", "default": "sales_tools" }, "whatYouSell": { "title": "What the customer sells", "type": "string", "description": "Optional one-line description used in output context.", "default": "" }, "maxLeads": { "title": "Max company leads", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of ranked company lead records to return.", "default": 100 }, "maxJobsToAnalyze": { "title": "Max jobs to analyze", "minimum": 10, "maximum": 10000, "type": "integer", "description": "Upper bound on upstream job records to fetch and score.", "default": 1000 }, "postedAfter": { "title": "Posted after", "type": "string", "description": "Relative or ISO date supported by the upstream ATS Jobs API. Examples: 30 days ago, 2026-01-01T00:00:00Z.", "default": "30 days ago" }, "strictTitleMatch": { "title": "Strict title matching", "type": "boolean", "description": "When true, upstream search and local scoring focus on job titles instead of descriptions.", "default": true }, "sources": { "title": "ATS sources", "type": "array", "description": "Optional ATS source filter. Leave empty for broadest coverage.", "default": [], "items": { "type": "string" } }, "includeCompanyDetails": { "title": "Include company details", "type": "boolean", "description": "Ask upstream job provider for enriched company details when available. This can increase upstream cost/time.", "default": false }, "upstreamActorId": { "title": "Upstream job-data Actor", "type": "string", "description": "Default uses ATS Jobs API. Advanced users can swap in a compatible job-data Actor.", "default": "jobo.world/ats-jobs-api" }, "upstreamInputOverride": { "title": "Upstream input override", "type": "object", "description": "Optional raw fields merged into the upstream Actor input.", "default": {} }, "sampleJobs": { "title": "Sample/local jobs", "type": "array", "description": "Optional direct job records for testing without an upstream Actor.", "default": [] } } }, "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 } } } } } } } } } } ```