# Yelp Leads Scraper - Business Email & Phone (`oriented_wallpaper/yelp-leads-scraper`) Actor Scrape Yelp businesses by category + location into a contactable lead list — emails from each business site, phone, website, address, rating & reviews, a 0-100 lead score, dedupe, and optional AI cold openers. Export CSV/JSON. - **URL**: https://apify.com/oriented\_wallpaper/yelp-leads-scraper.md - **Developed by:** [Flash Scrape](https://apify.com/oriented_wallpaper) (community) - **Categories:** Lead generation, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 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 ## Yelp Email Scraper - Business Leads, Phone & Reviews **Yelp email scraper** that turns any Yelp category + location into a contactable list of **local business leads** — complete with emails, phones, websites, ratings, and reviews. Search something like *"dentists in Austin, TX"* and get back a clean, scored, ready-to-contact spreadsheet of businesses, not a raw listing dump. Unlike Yelp itself (which almost never shows an email), this **Yelp scraper** visits each business's own website to find the real email address — so the leads you export are actually reachable. Built for cold outreach, agencies, B2B sales prospecting, and anyone building a local-business lead list. --- ### How to scrape Yelp for leads You don't need an API key, a Yelp login, or any code. Three steps: 1. Enter one or more **search terms** (e.g. `coffee shops`, `plumbers`, `med spas`). 2. Enter one or more **locations** (e.g. `Austin, TX`, `Miami, FL`). Every term is searched in every location. 3. Set your filters and `maxItems`, then run. The actor pulls matching Yelp businesses, visits each business website to enrich emails and social links, removes duplicates, scores every lead 0–100, and pushes a clean dataset you can export to CSV, JSON, or Excel — best leads first. - **Find local business emails on Yelp** — visits each website's home / contact / about pages to pull the real email (Yelp rarely exposes one itself). - **Get phone, website & address for every business** — the core contact fields you need to reach out. - **Filter Yelp leads by rating & review count** — keep only established, well-rated businesses. - **Export only contactable leads** — drop businesses with no website or no email so you don't pay for dead rows. - **Rank leads automatically** — a 0–100 lead score sorts the best prospects to the top. - **Write AI cold-email openers** — an optional one-line personalized icebreaker per lead. --- ### What data you get One row per business, scored and sorted best-first. Field names below match the dataset schema exactly. | Field | Description | |---|---| | `lead_score` | 0–100 score from email + phone + website + rating + review volume. | | `name` | Business name. | | `category` | Yelp category (e.g. `Coffee & Tea`). | | `phone` | Business phone number. | | `email` | Email found on the business website. | | `email_status` | `found` or `missing`. | | `website` | Business website URL. | | `address` | Full street address. | | `city` | City. | | `rating` | Star rating (1–5). | | `reviews` | Number of reviews. | | `icebreaker` | Optional AI-written cold-email opener. | | `yelp_url` | Link back to the Yelp listing. | #### JSON output sample ```json { "lead_score": 90, "name": "Joe's Coffee House", "category": "Coffee & Tea", "phone": "+1 512-555-0199", "email": "hello@joescoffee.com", "email_status": "found", "website": "https://joescoffee.com", "address": "123 Congress Ave, Austin, TX 78701", "city": "Austin", "rating": 4.5, "reviews": 312, "icebreaker": "Loved that your cold brew keeps a 4.5 across 300+ reviews in Austin…", "yelp_url": "https://www.yelp.com/biz/joes-coffee-house-austin" } ```` Results also render as a sortable table on the Output tab and export to CSV / JSON / Excel. *** ### Filters & options (input) Provide search terms + locations, then tune what gets delivered. You're only charged for leads that survive your filters. | Field | What it does | |---|---| | `searchTerms` | Categories / keywords to scrape, one per line — e.g. `plumbers`, `dentists`. | | `locations` | Cities / areas, one per line — e.g. `Denver, CO`. Each term is searched in each location. | | `maxItems` | Max businesses to scrape across all searches (default 50). | | `minRating` | Keep only businesses at or above this star rating (0 = off). | | `minReviews` | Keep only businesses with at least this many reviews (0 = off). | | `onlyWithWebsite` | Drop businesses with no website. | | `onlyWithEmail` | Drop businesses where no email was found — best for cold email. | | `enrichEmails` | Visit each business website to extract emails + socials (default on, no key needed). | | `writeOpeners` | Add an AI cold-opener per lead — needs your own AI key. | | `llmProvider` / `llmApiKey` / `llmModel` | Pick OpenAI or Anthropic and supply your key for the openers. | Example input: ```json { "searchTerms": ["restaurants", "coffee shops"], "locations": ["Austin, TX", "Portland, OR"], "maxItems": 50, "minRating": 4, "minReviews": 25, "onlyWithWebsite": true, "onlyWithEmail": true, "enrichEmails": true, "writeOpeners": false } ``` *** ### Use with AI agents & automation This **Yelp lead scraper** plugs straight into your stack. Call it from the Apify **MCP** server so AI agents (Claude, ChatGPT, Cursor) can pull leads on demand, or wire the dataset into **Make**, **n8n**, or **Zapier** to push new leads into your CRM the moment a run finishes. Sync the output to **Google Sheets** for a live, shareable lead list — no engineering required. *** ### Pricing Pay per result on top of Apify platform usage — you're only charged for leads delivered **after** filtering, so tightening `minRating`, `minReviews`, `onlyWithWebsite`, or `onlyWithEmail` directly lowers your cost. The optional AI openers run on **your own** OpenAI/Anthropic key, billed by that provider. See the actor's pricing tab for current rates. *** ### Other Flash Scrape scrapers Building leads from more than one source? The rest of the suite shares the same clean, scored output format: - [Google Maps Leads Opener](https://apify.com/oriented_wallpaper/google-maps-leads-opener) — Google Maps business leads - [BBB + Yellow Pages Leads Scraper](https://apify.com/oriented_wallpaper/bbb-yellowpages-leads-scraper) — BBB + Yellow Pages leads - [Instagram Leads Scraper](https://apify.com/oriented_wallpaper/instagram-leads-scraper) — Instagram profile leads - [TikTok Leads Scraper](https://apify.com/oriented_wallpaper/tiktok-leads-scraper) — TikTok creator leads - [YouTube Leads Scraper](https://apify.com/oriented_wallpaper/youtube-leads-scraper) — YouTube creator leads - [Smart Scraper by Example](https://apify.com/oriented_wallpaper/smart-scraper-by-example) — no-code web scraper *** ### FAQ **Is it legal to scrape Yelp?** This actor collects **public** business listing data — the same information any visitor can see. That's generally fine for legitimate prospecting, but you're responsible for how you use it: follow Yelp's terms and anti-spam laws like CAN-SPAM and GDPR in any outreach you send. **Do I need an API key?** No. The Yelp scraping and email enrichment work without any key. The only place a key is needed is the optional AI cold-openers, where you supply your own OpenAI or Anthropic key — it's used once per run and never stored. **Will every business have an email?** No. Yelp itself rarely lists an email, so emails are pulled from each business's own website. Businesses with no site, or no email on it, show `email_status: missing`. Turn on `onlyWithEmail` to keep just the contactable leads. **How many results can I get?** Set `maxItems` up to 1000 businesses per run across all your search terms and locations. Add more terms or locations and run again to scale further. **Can I export to CSV / Google Sheets?** Yes. Every run exports to CSV, JSON, or Excel from the dataset, and you can sync results to Google Sheets automatically via Make, n8n, Zapier, or the Apify API. **Can I scrape multiple cities at once?** Yes. Add several locations and several search terms — each term is searched in each location, then deduped into a single scored list. # Actor input Schema ## `searchTerms` (type: `array`): Business categories / keywords to scrape — one per line. e.g. 'coffee shops', 'dentists', 'plumbers'. ## `locations` (type: `array`): Cities / areas to search in — one per line. e.g. 'Austin, TX', 'Miami, FL'. Each search term is searched in each location. ## `maxItems` (type: `integer`): Maximum number of Yelp businesses to scrape across all search terms. ## `minRating` (type: `integer`): Keep only businesses with at least this star rating, 1-5 (0 = no filter). ## `minReviews` (type: `integer`): Keep only businesses with at least this many reviews (0 = no filter). A proxy for established, real businesses. ## `onlyWithWebsite` (type: `boolean`): Drop businesses with no website (you can't enrich an email without one). ## `onlyWithEmail` (type: `boolean`): Drop businesses where no email could be found. Best for cold-email campaigns. ## `enrichEmails` (type: `boolean`): Visit each business website (home + /contact + /about) to extract emails and social links. Higher email fill-rate. No key needed. ## `writeOpeners` (type: `boolean`): Generate a personalized one-sentence outreach opener for each lead. Requires your OpenAI/Anthropic key below. ## `llmProvider` (type: `string`): Which model writes the openers. ## `llmApiKey` (type: `string`): Your own OpenAI or Anthropic API key. Used only to write the openers; never stored. ## `llmModel` (type: `string`): Override the default model (gpt-4o-mini for OpenAI, claude-haiku-4-5-20251001 for Anthropic). ## `minScore` (type: `integer`): Keep only leads scoring at or above this value, 0-100 (0 = no filter). Pay only for your best A/B leads. ## Actor input object example ```json { "searchTerms": [ "dentists", "med spas" ], "locations": [ "Miami, FL", "New York, NY" ], "maxItems": 50, "minRating": 0, "minReviews": 0, "onlyWithWebsite": false, "onlyWithEmail": false, "enrichEmails": true, "writeOpeners": false, "llmProvider": "openai", "minScore": 0 } ``` # 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 = { "searchTerms": [ "coffee shops" ], "locations": [ "Austin, TX" ] }; // Run the Actor and wait for it to finish const run = await client.actor("oriented_wallpaper/yelp-leads-scraper").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 = { "searchTerms": ["coffee shops"], "locations": ["Austin, TX"], } # Run the Actor and wait for it to finish run = client.actor("oriented_wallpaper/yelp-leads-scraper").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 '{ "searchTerms": [ "coffee shops" ], "locations": [ "Austin, TX" ] }' | apify call oriented_wallpaper/yelp-leads-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=oriented_wallpaper/yelp-leads-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Yelp Leads Scraper - Business Email & Phone", "description": "Scrape Yelp businesses by category + location into a contactable lead list — emails from each business site, phone, website, address, rating & reviews, a 0-100 lead score, dedupe, and optional AI cold openers. Export CSV/JSON.", "version": "0.1", "x-build-id": "Aef2ZwQgY8Tu9P3DW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/oriented_wallpaper~yelp-leads-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-oriented_wallpaper-yelp-leads-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/oriented_wallpaper~yelp-leads-scraper/runs": { "post": { "operationId": "runs-sync-oriented_wallpaper-yelp-leads-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/oriented_wallpaper~yelp-leads-scraper/run-sync": { "post": { "operationId": "run-sync-oriented_wallpaper-yelp-leads-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchTerms": { "title": "Search terms (what)", "type": "array", "description": "Business categories / keywords to scrape — one per line. e.g. 'coffee shops', 'dentists', 'plumbers'.", "items": { "type": "string" } }, "locations": { "title": "Locations (where)", "type": "array", "description": "Cities / areas to search in — one per line. e.g. 'Austin, TX', 'Miami, FL'. Each search term is searched in each location.", "items": { "type": "string" } }, "maxItems": { "title": "Max businesses", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of Yelp businesses to scrape across all search terms.", "default": 50 }, "minRating": { "title": "Minimum rating", "minimum": 0, "maximum": 5, "type": "integer", "description": "Keep only businesses with at least this star rating, 1-5 (0 = no filter).", "default": 0 }, "minReviews": { "title": "Minimum reviews", "minimum": 0, "type": "integer", "description": "Keep only businesses with at least this many reviews (0 = no filter). A proxy for established, real businesses.", "default": 0 }, "onlyWithWebsite": { "title": "Only businesses with a website", "type": "boolean", "description": "Drop businesses with no website (you can't enrich an email without one).", "default": false }, "onlyWithEmail": { "title": "Only businesses with an email", "type": "boolean", "description": "Drop businesses where no email could be found. Best for cold-email campaigns.", "default": false }, "enrichEmails": { "title": "Find emails on the business website", "type": "boolean", "description": "Visit each business website (home + /contact + /about) to extract emails and social links. Higher email fill-rate. No key needed.", "default": true }, "writeOpeners": { "title": "Write an AI cold-opener per lead", "type": "boolean", "description": "Generate a personalized one-sentence outreach opener for each lead. Requires your OpenAI/Anthropic key below.", "default": false }, "llmProvider": { "title": "AI provider (for openers)", "enum": [ "openai", "anthropic" ], "type": "string", "description": "Which model writes the openers.", "default": "openai" }, "llmApiKey": { "title": "AI API key (for openers)", "type": "string", "description": "Your own OpenAI or Anthropic API key. Used only to write the openers; never stored." }, "llmModel": { "title": "AI model (optional)", "type": "string", "description": "Override the default model (gpt-4o-mini for OpenAI, claude-haiku-4-5-20251001 for Anthropic)." }, "minScore": { "title": "Minimum lead score", "minimum": 0, "maximum": 100, "type": "integer", "description": "Keep only leads scoring at or above this value, 0-100 (0 = no filter). Pay only for your best A/B leads.", "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 } } } } } } } } } } ```