# TikTok & Instagram Creator Stats - Engagement Rate & Grade (`seemuapps/tiktok-instagram-creator-stats`) Actor Check followers, engagement rate, average likes, posting cadence, and an engagement grade for any TikTok or Instagram creator in bulk. - **URL**: https://apify.com/seemuapps/tiktok-instagram-creator-stats.md - **Developed by:** [Andrew](https://apify.com/seemuapps) (community) - **Categories:** Social media, Lead generation, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 1,000 creator profile analyzeds 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## TikTok & Instagram Creator Stats - Engagement Rate & Grade Check any creator's real engagement in seconds — followers, engagement rate, average likes, posting cadence, and a simple A–D engagement grade — for TikTok and Instagram profiles in bulk. No login or cookies required. ### What you get - **Profile stats**: followers, following, post count, verification status, bio, and avatar - **Engagement rate** — computed from the creator's actual performance, benchmarked against their audience size - **Engagement grade (A–D)** — instantly compare creators of any size on a level playing field - **Average likes and comments** per post (Instagram: sampled from recent posts; TikTok: lifetime average) - **Posting cadence**: posts per week and date of the most recent post (Instagram) - **Follower ratio** (followers ÷ following) — a quick bot/spam signal - Analyze up to 100 mixed TikTok + Instagram profiles per run - Export to JSON, CSV, or Google Sheets directly from the Apify console ### Use cases - **Influencer vetting** — verify a creator's engagement is real before paying for a collaboration - **Campaign shortlisting** — batch-compare hundreds of candidate creators and rank by grade - **Competitor analysis** — track how competing brands' accounts actually perform - **Agency reporting** — refresh client and prospect stats on a schedule - **Lead scoring** — enrich creator lists with follower counts and engagement quality ### How to use 1. Paste profiles into **Profiles** — full URLs (`https://www.tiktok.com/@user`, `https://www.instagram.com/user`) or `tiktok:username` / `instagram:username`, mixed freely 2. (Optional) Adjust **Instagram sample size** — how many recent posts to average (default 12) 3. Run the actor — one record per profile appears in the **Dataset** tab ### Output format Each dataset record: ```json { "platform": "tiktok", "username": "creator", "profileUrl": "https://www.tiktok.com/@creator", "fullName": "Creator Name", "verified": true, "followers": 394100, "following": 93, "postsCount": 252, "totalLikes": 13900000, "engagementRatePct": 14.0, "engagementBasis": "lifetime_average", "avgLikes": 55158, "avgComments": null, "postsPerWeek": null, "followerRatio": 4237.6, "grade": "A", "gradeLabel": "Excellent engagement" } ```` Instagram records also include `avgComments`, `postsPerWeek`, and `lastPostAt`, with the engagement rate computed from a sample of recent posts (`engagementBasis: "recent_posts_sample"`). ### How the grade works The engagement rate is benchmarked against the creator's follower band — a 5,000-follower account is expected to have a much higher rate than a 5M-follower account. Rates above the band's "excellent" threshold earn an **A**, down to **D** for rates well below the norm for that audience size. ### Notes - Private Instagram profiles return profile stats only (no engagement metrics). - One result = one analyzed profile. Invalid entries are skipped and not charged. # Actor input Schema ## `profiles` (type: `array`): Creator profiles to analyze — mix TikTok and Instagram freely. Accepts full profile URLs (https://www.tiktok.com/@user, https://www.instagram.com/user) or 'tiktok:username' / 'instagram:username'. Maximum 100 per run. ## `igSampleSize` (type: `integer`): How many recent Instagram posts to sample when computing the engagement rate (1–36). More posts = more accurate but slower. ## Actor input object example ```json { "profiles": [ "https://www.tiktok.com/@tiktok", "instagram:natgeo" ], "igSampleSize": 12 } ``` # Actor output Schema ## `results` (type: `string`): One record per profile: platform, username, followers, following, posts, engagement rate, average likes/comments, posting cadence, and engagement grade. # 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 = { "profiles": [ "https://www.tiktok.com/@tiktok", "instagram:natgeo" ] }; // Run the Actor and wait for it to finish const run = await client.actor("seemuapps/tiktok-instagram-creator-stats").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 = { "profiles": [ "https://www.tiktok.com/@tiktok", "instagram:natgeo", ] } # Run the Actor and wait for it to finish run = client.actor("seemuapps/tiktok-instagram-creator-stats").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 '{ "profiles": [ "https://www.tiktok.com/@tiktok", "instagram:natgeo" ] }' | apify call seemuapps/tiktok-instagram-creator-stats --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seemuapps/tiktok-instagram-creator-stats", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TikTok & Instagram Creator Stats - Engagement Rate & Grade", "description": "Check followers, engagement rate, average likes, posting cadence, and an engagement grade for any TikTok or Instagram creator in bulk.", "version": "1.0", "x-build-id": "58LKpxGJ4alp9hYSq" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seemuapps~tiktok-instagram-creator-stats/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seemuapps-tiktok-instagram-creator-stats", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seemuapps~tiktok-instagram-creator-stats/runs": { "post": { "operationId": "runs-sync-seemuapps-tiktok-instagram-creator-stats", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seemuapps~tiktok-instagram-creator-stats/run-sync": { "post": { "operationId": "run-sync-seemuapps-tiktok-instagram-creator-stats", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "profiles" ], "properties": { "profiles": { "title": "Profiles", "type": "array", "description": "Creator profiles to analyze — mix TikTok and Instagram freely. Accepts full profile URLs (https://www.tiktok.com/@user, https://www.instagram.com/user) or 'tiktok:username' / 'instagram:username'. Maximum 100 per run.", "items": { "type": "string" } }, "igSampleSize": { "title": "Instagram sample size", "minimum": 1, "maximum": 36, "type": "integer", "description": "How many recent Instagram posts to sample when computing the engagement rate (1–36). More posts = more accurate but slower.", "default": 12 } } }, "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 } } } } } } } } } } ```