# Instagram Lookalike Search (`dataovercoffee/instagram-lookalike-search`) Actor 🔮 Lookalike Instagram creators + 🍰 search engagement stats from 150M+ influencers. - **URL**: https://apify.com/dataovercoffee/instagram-lookalike-search.md - **Developed by:** [Data Over Coffee](https://apify.com/dataovercoffee) (community) - **Categories:** Social media, Lead generation - **Stats:** 15 total users, 5 monthly users, 100.0% runs succeeded, 3 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $200.00 / 1,000 creators 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 ### 🔍 Find Instagram Creators by Content + Audience, Not Hashtags Give it 1-10 creators you already love. Our creator **search engine** scans **150M+ Instagram creators** and returns the ones that make similar content **for a similar audience**, matched by what they actually post. Ranked, filtered, and ready to export, usually in a few minutes. ### 🧠 What Makes It Different Most "similar creator" tools match the topic and stop there. You get accounts on the same subject, but reaching a different audience in a different market. A lookalike is only useful if it reaches *your* people, so this goes further: - **It targets your audience, not just your topic.** Every match is a creator whose audience mirrors your seed's, so the creators you get actually reach the people you're trying to reach, not just people who post about the same thing. - **Audience + geo targeting is automatic.** No filters to tune, no manual setup — it's built into the matching engine. Every result already fits your seed's audience and market out of the box. - **Emails included.** Public business emails come back **in the results**, ready for outreach. No separate email-scraper step. ### ⚙️ How It Works 1. **Give us 1-10 seed creators.** Paste the Instagram handles you already like. 2. **We find the closest matches** across 150M+ creators by what they actually publish: content, not hashtags or self-declared category. 3. **We match the audience automatically.** Every result reaches the same kind of audience as your seeds, with no manual targeting needed. 4. **We score and rank** every match 0-1 by how closely it fits. 5. **We apply your optional filters** (followers, engagement, email, exclusions). 6. **You get a ranked list** with full metadata and emails. Runs resume safely. Interrupt and restart, and it skips creators it already delivered and never bills you twice. ### 💡 Use Cases | Who | Problem | How | |---|---|---| | Brand marketer | Sponsored one creator, need 200 more like them | Seed the creator, get audience-matched lookalikes with engagement | | Agency | A creator dropped out, need a fast replacement | Seed the dropped creator, turn on `only_has_email` | | Ecommerce / DTC | Need 50 micro-creators under 20k for UGC | Seed known micro-creators, set `max_followers` | | Sales / outreach | Need creators with real contact info | Seed your best partners, turn on `only_has_email`, emails come back in the data | | Niche research | Is my shortlist actually the best out there? | Seed a few, see who else exists in the same niche and market | ### ⚡ How To Use It 1. Paste **`seed_usernames`** (1-10 Instagram handles, e.g. `["natgeo"]`). 2. Set **`limit`** (default 100, up to 5,000). 3. Optional: filter by followers, avg likes/comments, post count, or email; exclude creators you already have. 4. Run, then download results as CSV / JSON / Excel. No country setting to pick — geo and audience targeting are built into the matching engine, so every result already fits your seed's market. ### 💰 Pricing - **$0.20 per result.** Pay only for the creators you get back. - Up to **5,000 results** per search. - Apify free tier includes **$5 of usage**. ### 🏆 Tips - **Multiple seeds = a sharper niche.** One seed is broad; three seeds in the same niche return creators similar to *all* of them at once. - **Keep seeds in one niche.** Mixed-niche seeds dilute the match, so run a separate search per niche. - **Geo targeting is automatic.** There's no country filter to set — the audience-matching engine already targets your seed's market, so every result reaches the right audience out of the box. - **Filter by engagement, not just followers.** Avg likes/comments tell you who's actually watched. - **Dedup across runs.** Paste up to 500,000 handles into `exclude_usernames` so you're never charged for a creator twice. Need more than one run's worth? Use your best results as new seeds and keep going. ### 📦 What You Get One row per creator: handle, numeric user ID, full name, bio, profile URL, external link, followers, post count, avg likes, avg comments, country, public emails, verified / private flags, category, and a match score (0-1). ### ❓ FAQ #### How is this different from Instagram's "suggested" accounts? Suggested accounts are based on who *you* follow. This searches 150M+ creators for ones similar to a seed *you* choose, matched by content **and** audience, with filters and up to 5,000 ranked results. #### How do I find creators similar to a competitor? Paste the competitor's handle(s) as seeds. Add your own top creators as seeds too and the overlap tightens to exactly your niche and market. #### Does it return email addresses? Yes. Public business emails come back in the `emails` field. Turn on `only_has_email` to return only creators that have one. No separate scraper needed. #### I got fewer results than my limit, is something wrong? No. We drop inactive, spammy, and off-audience creators before returning results, and your filters narrow further. If the niche is small or filters are tight, fewer creators pass, which is the filter working. Need more? Use your best results as new seeds and run again, pasting prior results into `exclude_usernames`. #### Can I target a specific country? You don't need to — geo and audience targeting are automatic, built into the matching engine. Every result already reaches your seed's market, so there's no country filter to tune. (Each creator's inferred country still comes back in the data for reference.) #### Need help? Email support@dataovercoffee.com with your Run ID, or open an issue on the actor's page. # Actor input Schema ## `seed_usernames` (type: `array`): Instagram usernames to find lookalikes for. Provide 1-10 handles (e.g. hormozi). More seeds = more precise results; creators common to several seeds rank highest. ## `limit` (type: `integer`): Maximum number of lookalike creators to return. The actual count is capped at whichever is lower: this value, or what your "Maximum cost per run" allows. ## `min_followers` (type: `integer`): Only include creators with at least this many followers. ## `max_followers` (type: `integer`): Only include creators with at most this many followers. ## `min_avg_likes` (type: `integer`): Minimum average likes per post. ## `max_avg_likes` (type: `integer`): Maximum average likes per post. ## `min_avg_comments` (type: `integer`): Minimum average comments per post. ## `max_avg_comments` (type: `integer`): Maximum average comments per post. ## `min_post_count` (type: `integer`): Only include creators with at least this many posts. ## `max_post_count` (type: `integer`): Only include creators with at most this many posts. ## `only_has_email` (type: `boolean`): Only include creators with a public email (in bio or extracted). Great for outreach. ## `exclude_usernames` (type: `array`): Usernames to exclude from results — e.g. creators you already have from previous runs. Up to 500,000. ## Actor input object example ```json { "seed_usernames": [ "hormozi" ], "limit": 100, "only_has_email": false } ```` # Actor output Schema ## `lookalikes` (type: `string`): Dataset of Instagram creators similar to the seeds, ranked by lookalike score. # 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 = { "seed_usernames": [ "hormozi" ], "limit": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("dataovercoffee/instagram-lookalike-search").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 = { "seed_usernames": ["hormozi"], "limit": 100, } # Run the Actor and wait for it to finish run = client.actor("dataovercoffee/instagram-lookalike-search").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 '{ "seed_usernames": [ "hormozi" ], "limit": 100 }' | apify call dataovercoffee/instagram-lookalike-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dataovercoffee/instagram-lookalike-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Lookalike Search", "description": "🔮 Lookalike Instagram creators + 🍰 search engagement stats from 150M+ influencers.", "version": "1.0", "x-build-id": "dPadGudG4tRgaSQBk" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dataovercoffee~instagram-lookalike-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dataovercoffee-instagram-lookalike-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dataovercoffee~instagram-lookalike-search/runs": { "post": { "operationId": "runs-sync-dataovercoffee-instagram-lookalike-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dataovercoffee~instagram-lookalike-search/run-sync": { "post": { "operationId": "run-sync-dataovercoffee-instagram-lookalike-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "seed_usernames" ], "properties": { "seed_usernames": { "title": "Seed creators (usernames)", "type": "array", "description": "Instagram usernames to find lookalikes for. Provide 1-10 handles (e.g. hormozi). More seeds = more precise results; creators common to several seeds rank highest.", "items": { "type": "string" } }, "limit": { "title": "Max results", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of lookalike creators to return. The actual count is capped at whichever is lower: this value, or what your \"Maximum cost per run\" allows.", "default": 100 }, "min_followers": { "title": "Min followers", "minimum": 1000, "type": "integer", "description": "Only include creators with at least this many followers." }, "max_followers": { "title": "Max followers", "minimum": 1000, "type": "integer", "description": "Only include creators with at most this many followers." }, "min_avg_likes": { "title": "Min avg likes", "type": "integer", "description": "Minimum average likes per post." }, "max_avg_likes": { "title": "Max avg likes", "type": "integer", "description": "Maximum average likes per post." }, "min_avg_comments": { "title": "Min avg comments", "type": "integer", "description": "Minimum average comments per post." }, "max_avg_comments": { "title": "Max avg comments", "type": "integer", "description": "Maximum average comments per post." }, "min_post_count": { "title": "Min posts", "type": "integer", "description": "Only include creators with at least this many posts." }, "max_post_count": { "title": "Max posts", "type": "integer", "description": "Only include creators with at most this many posts." }, "only_has_email": { "title": "Has public email only", "type": "boolean", "description": "Only include creators with a public email (in bio or extracted). Great for outreach.", "default": false }, "exclude_usernames": { "title": "Exclude usernames", "maxItems": 500000, "type": "array", "description": "Usernames to exclude from results — e.g. creators you already have from previous runs. Up to 500,000.", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```