# Realtor Lead Finder — Instagram (`gocreative.ai/realtor-lead-finder`) Actor Find Instagram-active real estate agents from any hashtag set. Returns pre-filtered, quality-scored leads — real agents only. Each row: handle, name, followers, bio, email-from-bio, business category, engagement %. Ready for cold DM outreach, CRM import, and recruiting. - **URL**: https://apify.com/gocreative.ai/realtor-lead-finder.md - **Developed by:** [GoCreative AI](https://apify.com/gocreative.ai) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $12.00 / 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 ## Realtor Lead Finder — Instagram Find **real, active real estate agents and brokers** on Instagram from any hashtag set. We do the boring work — hashtag scrape, quality filter, profile enrichment, deduplication, and email extraction — and hand you a clean lead list ready to drop into your CRM. ### What you get back Each row is one realtor, with these fields: | Field | Example | |---|---| | `username` | `michellerealtyone` | | `full_name` | `Michelle Sanchez` | | `followers` | `12450` | | `following` | `983` | | `posts` | `412` | | `biography` | `Top 1% Realtor at @kw_signature. DM me to buy or sell 🏡` | | `email` | `michelle@kwsignature.com` *(extracted from bio if present)* | | `external_url` | `https://kwsignature.com/michelle` | | `is_business` | `true` | | `business_category` | `Real Estate Agent` | | `verified` | `false` | | `engagement_pct` | `4.32` *(top-post likes / followers)* | | `found_via_hashtag` | `realestateagent` | | `profile_url` | `https://www.instagram.com/michellerealtyone/` | | `profile_pic` | `https://…` | ### What we **don't** return (already filtered out) - Coaches, mentors, consultants - Marketing agencies, podcasters, influencers (unless real estate is their actual job) - Loan officers, mortgage brokers, title companies, attorneys, accountants - Home stagers, decorators, contractors, photographers - Generic spam (`buy_now`, `freegift`, etc.) - Usernames longer than 30 chars (typically businesses, not individuals) You get **real estate agents only** — the people who actually list, sell, and rep buyers. ### Inputs ```json { "hashtags": [ "realestateagent", "realtorlife", "realtorsofinstagram" ], "maxResults": 100, "minFollowers": 500, "requireEmailInBio": false, "engagementMinPct": 0 } ```` | Input | Description | |---|---| | `hashtags` | List of Instagram hashtags to source from (no `#`) | | `maxResults` | Hard cap on returned leads (after filtering) | | `minFollowers` | Drop accounts under this follower count | | `requireEmailInBio` | Strict: only return leads whose bio has an email address | | `engagementMinPct` | Drop accounts below this engagement % (top-post-likes ÷ followers) | ### Use cases - **Cold DM / cold email outreach** — Instantly, Apollo, lemlist, GoHighLevel - **Recruiting** for brokerages - **AI lead enrichment** before adding to CRM - **Market intelligence** — who's posting where, growing fastest ### How we compare The generic Apify Instagram scrapers return everyone who used a hashtag — coaches, brands, randoms. You then spend hours cleaning the CSV. This actor is the cleaning, baked in. ### Pricing Pay-per-result. See the Pricing tab for current rate. *** Issues, requests, or want a new niche scraped? Open an issue on the actor page. # Actor input Schema ## `hashtags` (type: `array`): Instagram hashtags to search (without #). Defaults target real-estate agents specifically. ## `maxResults` (type: `integer`): Total number of quality leads to return after filtering. Increase = more posts scraped upstream = higher Apify cost. ## `minFollowers` (type: `integer`): Skip accounts below this follower count. Useful for filtering out very new agents. ## `requireEmailInBio` (type: `boolean`): Strict filter: only include accounts whose bio contains an email address. ## `engagementMinPct` (type: `number`): Skip accounts whose avg-likes/follower ratio is below this %. Set to 0 to disable. ## Actor input object example ```json { "hashtags": [ "realestateagent", "realtorlife", "realtorsofinstagram" ], "maxResults": 100, "minFollowers": 0, "requireEmailInBio": false, "engagementMinPct": 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 = { "hashtags": [ "realestateagent", "realtorlife", "realtorsofinstagram" ] }; // Run the Actor and wait for it to finish const run = await client.actor("gocreative.ai/realtor-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 = { "hashtags": [ "realestateagent", "realtorlife", "realtorsofinstagram", ] } # Run the Actor and wait for it to finish run = client.actor("gocreative.ai/realtor-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 '{ "hashtags": [ "realestateagent", "realtorlife", "realtorsofinstagram" ] }' | apify call gocreative.ai/realtor-lead-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=gocreative.ai/realtor-lead-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Realtor Lead Finder — Instagram", "description": "Find Instagram-active real estate agents from any hashtag set. Returns pre-filtered, quality-scored leads — real agents only. Each row: handle, name, followers, bio, email-from-bio, business category, engagement %. Ready for cold DM outreach, CRM import, and recruiting.", "version": "0.1", "x-build-id": "8nBAoyhF6s6bME9W0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/gocreative.ai~realtor-lead-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-gocreative.ai-realtor-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/gocreative.ai~realtor-lead-finder/runs": { "post": { "operationId": "runs-sync-gocreative.ai-realtor-lead-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/gocreative.ai~realtor-lead-finder/run-sync": { "post": { "operationId": "run-sync-gocreative.ai-realtor-lead-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "hashtags" ], "properties": { "hashtags": { "title": "Hashtags", "type": "array", "description": "Instagram hashtags to search (without #). Defaults target real-estate agents specifically.", "default": [ "realestateagent", "realtorlife", "realtorsofinstagram", "realestatebroker", "licensedagent" ], "items": { "type": "string" } }, "maxResults": { "title": "Max leads to return", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Total number of quality leads to return after filtering. Increase = more posts scraped upstream = higher Apify cost.", "default": 100 }, "minFollowers": { "title": "Minimum follower count", "minimum": 0, "type": "integer", "description": "Skip accounts below this follower count. Useful for filtering out very new agents.", "default": 0 }, "requireEmailInBio": { "title": "Only return leads with email in bio", "type": "boolean", "description": "Strict filter: only include accounts whose bio contains an email address.", "default": false }, "engagementMinPct": { "title": "Minimum engagement rate (%)", "minimum": 0, "maximum": 100, "type": "number", "description": "Skip accounts whose avg-likes/follower ratio is below this %. Set to 0 to disable.", "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 } } } } } } } } } } ```