# GTM Signals Aggregator (`mambalabs/gtm-signals-aggregator`) Actor Combines GTM hiring signals and tech stack detection into one flat Clay-ready row with a composite signal score. - **URL**: https://apify.com/mambalabs/gtm-signals-aggregator.md - **Developed by:** [Mamba Labs](https://apify.com/mambalabs) (community) - **Categories:** Lead generation, Automation, MCP servers - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $120.00 / 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 ## GTM Signals Aggregator One call. Both GTM signals. Hiring intent plus tech stack in a single flat row. This actor takes a company domain, runs [GTM Hiring Signal Scraper](https://apify.com/mambalabs/gtm-hiring-signal-scraper) and [GTM Tech Stack Signal Scraper](https://apify.com/mambalabs/gtm-tech-stack-signal-scraper) in parallel, merges both outputs into one flat Clay-ready row, and adds a composite signal score with a plain-English summary. --- ### Who should use this **Use this actor if you want both signals in one call.** - Only need hiring signals? Use [GTM Hiring Signal Scraper](https://apify.com/mambalabs/gtm-hiring-signal-scraper) at $0.07/result. - Only need tech stack detection? Use [GTM Tech Stack Signal Scraper](https://apify.com/mambalabs/gtm-tech-stack-signal-scraper) at $0.07/result. - Want both in one row with a composite score? That is what this actor does. --- ### The math Running both actors separately costs $0.07 + $0.07 = $0.14 per company. This actor runs both in parallel and returns a single merged row at $0.12 per company. That is a 14% saving, plus you get a composite signal score and a plain-English summary field on top. --- ### Input | Field | Type | Required | Notes | |---|---|---|---| | `company_domain` | String | Yes | Bare domain, e.g. stripe.com. Strips https://, www., and trailing paths automatically. | | `include_summary` | Boolean | No | Include a plain-English gtm_signal_summary field. Default: true. | Example input: ```json { "company_domain": "hubspot.com", "include_summary": true } ```` *** ### Output One flat row per domain. All 28 fields present in every result. Null over missing keys. No nested objects. #### Composite fields (added by this actor) | Field | Type | Description | |---|---|---| | `company_domain` | String | Echoed from input | | `composite_signal` | String | high / medium / low | | `gtm_signal_summary` | String | Plain-English 1-2 sentence summary of combined signals. Omitted if include\_summary is false. | **Composite signal logic:** - high: GTM hiring detected AND CRM or sequencer detected - medium: GTM hiring OR tooling detected, but not both - low: No signals on either side #### Hiring signal fields (from GTM Hiring Signal Scraper) | Field | Type | Description | |---|---|---| | `gtm_hiring_signal` | Boolean | True if any GTM role detected | | `signal_strength` | String | high / medium / low | | `gtm_role_count` | Integer | Number of GTM roles detected | | `top_gtm_role` | String | Highest-tier role found | | `gtm_roles_detected` | String | Comma-separated matched roles | | `most_recent_posting_date` | String | ISO date of most recent GTM posting | | `ats_platform` | String | greenhouse / lever / ashby / none | | `career_page_url` | String | Direct link to career page | #### Tech stack fields (from GTM Tech Stack Signal Scraper) | Field | Type | Description | |---|---|---| | `crm_detected` | String | hubspot / salesforce / pipedrive / zoho / none | | `seq_tool_detected` | String | outreach / salesloft / apollo / instantly / lemlist / reply / none | | `uses_hubspot` | Boolean | | | `uses_salesforce` | Boolean | | | `uses_clay` | Boolean | | | `uses_apollo` | Boolean | | | `uses_outreach` | Boolean | | | `uses_gong` | Boolean | | | `uses_zoominfo` | Boolean | | | `uses_drift` | Boolean | | | `uses_intercom` | Boolean | | | `marketing_automation_detected` | String | marketo / pardot / hubspot / eloqua / none | | `gtm_tool_count` | Integer | Count of detected GTM tools | | `tech_stack_signal` | String | high / medium / low | #### Run metadata | Field | Type | Description | |---|---|---| | `actor1_error` | Boolean | True if hiring signal scraper failed. Tech stack fields still populated. | | `actor2_error` | Boolean | True if tech stack scraper failed. Hiring signal fields still populated. | | `run_date` | String | ISO timestamp of run | *** ### Sample output ```json { "company_domain": "hubspot.com", "composite_signal": "high", "gtm_signal_summary": "Actively hiring GTM roles and running Salesforce. Strong buying signal.", "gtm_hiring_signal": true, "signal_strength": "high", "gtm_role_count": 5, "top_gtm_role": "VP Sales", "ats_platform": "greenhouse", "crm_detected": "salesforce", "seq_tool_detected": "outreach", "uses_hubspot": false, "uses_salesforce": true, "uses_outreach": true, "tech_stack_signal": "high", "actor1_error": false, "actor2_error": false, "run_date": "2026-04-07T12:05:41.000Z" } ``` *** ### Clay integration Add this actor as an HTTP request enrichment column in any Clay table. 1. In your Clay table, add a column: Add Enrichment > HTTP API. 2. Set Method to POST. 3. URL: `https://api.apify.com/v2/acts/mambalabs~gtm-signals-aggregator/run-sync-get-dataset-items?token=YOUR_TOKEN` 4. Body: ```json { "company_domain": "{{domain}}" } ``` 5. Map output fields to columns using dot notation, e.g. `{{response.composite_signal}}`. Each row costs $0.12 and returns all 28 fields. No prompt engineering. No Claygent credit burn. Compare: a Claygent column researching tech stack burns 3-5 credits per row ($0.015-0.025 on Clay's standard plan) and requires a custom prompt. This actor returns structured, consistent output at $0.07 per signal type with zero prompt work. *** ### Pricing $0.12 per company. Pay per result, no subscription. | Option | Cost per company | |---|---| | GTM Hiring Signal Scraper only | $0.07 | | GTM Tech Stack Signal Scraper only | $0.07 | | Both run separately | $0.14 | | GTM Signals Aggregator (this actor) | $0.12 | | Saving | 14% | BuiltWith charges $295/month for tech stack data. This actor runs at $0.12 per company for both hiring and tech stack signals combined, with no subscription required. *** ### Known limitations - Hiring signal detection covers Greenhouse, Lever, and Ashby ATS platforms only. Companies using Workday, iCIMS, or other platforms return no hiring data. - Tech stack detection reads public-facing scripts and network calls. Tools loaded server-side or behind auth walls may not appear. - If one sub-actor fails, the other's fields still populate. Check `actor1_error` and `actor2_error` flags if any fields are null. - Each run calls both sub-actors via the Apify API. Sub-actor cold start times can affect total run duration. Typical runs complete in 30-60 seconds. *** ### Related actors - [GTM Hiring Signal Scraper](https://apify.com/mambalabs/gtm-hiring-signal-scraper) - Greenhouse, Lever, and Ashby scraper. $0.07/result. - [GTM Tech Stack Signal Scraper](https://apify.com/mambalabs/gtm-tech-stack-signal-scraper) - CRM and sequencer detection from a domain. $0.07/result. *** Built by [Mamba Labs](https://apify.com/mambalabs). # Actor input Schema ## `company_domain` (type: `string`): Bare domain to analyze, e.g. stripe.com ## `include_summary` (type: `boolean`): Include a plain-English gtm\_signal\_summary field in the output. Default true. ## Actor input object example ```json { "company_domain": "", "include_summary": true } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("mambalabs/gtm-signals-aggregator").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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("mambalabs/gtm-signals-aggregator").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 mambalabs/gtm-signals-aggregator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=mambalabs/gtm-signals-aggregator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GTM Signals Aggregator", "description": "Combines GTM hiring signals and tech stack detection into one flat Clay-ready row with a composite signal score.", "version": "0.1", "x-build-id": "hz8Ue6RJwUTC8DUSF" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mambalabs~gtm-signals-aggregator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mambalabs-gtm-signals-aggregator", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/mambalabs~gtm-signals-aggregator/runs": { "post": { "operationId": "runs-sync-mambalabs-gtm-signals-aggregator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/mambalabs~gtm-signals-aggregator/run-sync": { "post": { "operationId": "run-sync-mambalabs-gtm-signals-aggregator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "company_domain": { "title": "Company Domain", "type": "string", "description": "Bare domain to analyze, e.g. stripe.com", "default": "" }, "include_summary": { "title": "Include GTM Signal Summary", "type": "boolean", "description": "Include a plain-English gtm_signal_summary field in the output. Default true.", "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 } } } } } } } } } } ```