# Law Firm Lead Finder (`george.the.developer/law-firm-lead-finder`) Actor Find law firms in any city with verified contacts, validated emails, and lead scores. Built for legal marketing agencies and legal tech companies. - **URL**: https://apify.com/george.the.developer/law-firm-lead-finder.md - **Developed by:** [George Kioko](https://apify.com/george.the.developer) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Law Firm Lead Finder - Legal Marketing Intelligence Find, enrich, and score law firm leads from Google Maps. Built for legal marketing agencies who need verified contact data and qualified lead lists for attorney clients. ### What it does 1. **Scrapes Google Maps** for law firms matching your search query 2. **Enriches each firm** with website data, emails, and social profiles 3. **Validates emails** to ensure deliverability 4. **Scores and ranks leads** using a legal-vertical scoring algorithm tuned for law firms ### Why this exists Law firms are high-value clients ($5K-$50K+ retainers) but hard to reach. Generic lead scrapers miss the nuances: lawyers get fewer reviews, websites signal credibility more than most verticals, and practice area matters for targeting. This tool is built specifically for legal marketing. ### Input examples ```json { "searchQuery": "personal injury lawyers in Houston TX", "maxResults": 50, "enrichWebsites": true, "validateEmails": true, "minRating": 3.5 } ```` More search queries that work well: - `"family law attorneys Phoenix"` - `"criminal defense lawyers New York"` - `"immigration lawyers Los Angeles"` - `"estate planning attorneys Chicago"` - `"DUI lawyers Atlanta"` ### Output fields | Field | Description | |-------|-------------| | `rank` | Position in scored results (1 = best lead) | | `leadScore` | 0-100 quality score tuned for legal vertical | | `firmName` | Law firm name | | `vertical` | Always `"legal"` | | `category` | Google Maps category | | `address` | Full street address | | `phone` | Phone number | | `website` | Firm website URL | | `rating` | Google Maps rating | | `reviewCount` | Number of Google reviews | | `emails` | Array of found emails with validation status | | `socialProfiles` | LinkedIn, Facebook, Twitter, etc. | | `enrichment` | Raw website enrichment data | | `aiAnalysis` | AI-powered sales intelligence (optional) | ### Scoring algorithm (legal-tuned) | Signal | Points | Why | |--------|--------|-----| | Has website | +20 | Lawyers without websites are not marketing-ready | | Has phone | +15 | Direct contact channel | | Has email | +20 | Primary outreach channel | | Email validated | +10 | Deliverable = actionable | | Rating >= 4.0 | +15 | Reputation signals quality firm | | Rating >= 4.5 | +5 bonus | Top-tier firm | | Reviews > 20 | +10 | Active practice (low bar for legal) | | Reviews > 50 | +5 bonus | Well-established firm | | Social profiles | +5 | Marketing-aware firm | ### Pricing **$39 per search** (pay-per-event). Each search scrapes, enriches, validates, and scores up to your `maxResults` limit. ### Who this is for - Legal marketing agencies - Law firm SEO companies - Attorney lead generation services - Legal tech sales teams - Court reporting services prospecting for clients ### Architecture ```mermaid graph TD A[Search Query] --> B[Google Maps Scraper] B --> C[Website Enricher] C --> D[Email Validator] D --> E[Legal Lead Scorer] E --> F[Ranked Lead List] F --> G[Optional: AI Analysis] ``` # Actor input Schema ## `searchQuery` (type: `string`): What to search on Google Maps. Include location for best results. ## `maxResults` (type: `integer`): Maximum number of businesses to scrape from Google Maps. ## `enrichWebsites` (type: `boolean`): Enrich each business with website contact data, social profiles, and technologies. ## `validateEmails` (type: `boolean`): Validate all discovered email addresses for deliverability. ## `minRating` (type: `number`): Only include businesses with this rating or higher. Set to 0 to include all. ## Actor input object example ```json { "searchQuery": "personal injury lawyers in Houston TX", "maxResults": 20, "enrichWebsites": true, "validateEmails": true, "minRating": 0 } ``` # 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 = { "searchQuery": "personal injury lawyers in Houston TX" }; // Run the Actor and wait for it to finish const run = await client.actor("george.the.developer/law-firm-lead-finder").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 = { "searchQuery": "personal injury lawyers in Houston TX" } # Run the Actor and wait for it to finish run = client.actor("george.the.developer/law-firm-lead-finder").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 '{ "searchQuery": "personal injury lawyers in Houston TX" }' | apify call george.the.developer/law-firm-lead-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=george.the.developer/law-firm-lead-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Law Firm Lead Finder", "description": "Find law firms in any city with verified contacts, validated emails, and lead scores. Built for legal marketing agencies and legal tech companies.", "version": "1.0", "x-build-id": "Ad0LXNrZA6SlRmL0k" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/george.the.developer~law-firm-lead-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-george.the.developer-law-firm-lead-finder", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/george.the.developer~law-firm-lead-finder/runs": { "post": { "operationId": "runs-sync-george.the.developer-law-firm-lead-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/george.the.developer~law-firm-lead-finder/run-sync": { "post": { "operationId": "run-sync-george.the.developer-law-firm-lead-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchQuery" ], "properties": { "searchQuery": { "title": "Search Query", "type": "string", "description": "What to search on Google Maps. Include location for best results." }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of businesses to scrape from Google Maps.", "default": 20 }, "enrichWebsites": { "title": "Enrich Websites", "type": "boolean", "description": "Enrich each business with website contact data, social profiles, and technologies.", "default": true }, "validateEmails": { "title": "Validate Emails", "type": "boolean", "description": "Validate all discovered email addresses for deliverability.", "default": true }, "minRating": { "title": "Minimum Rating", "minimum": 0, "maximum": 5, "type": "number", "description": "Only include businesses with this rating or higher. Set to 0 to include all.", "default": 0 } } }, "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 } } } } } } } } } } ```