# TikTok Shop Product Ranking (`datamagnet/tiktok-shop-product-ranking`) Actor Get clean, ranked TikTok Shop product lists for a chosen date, region, and ranking cycle. Easily compare products by sales count or influencer count and export the results for review. - **URL**: https://apify.com/datamagnet/tiktok-shop-product-ranking.md - **Developed by:** [Datamagnet](https://apify.com/datamagnet) (community) - **Categories:** E-commerce, Social media - **Stats:** 3 total users, 1 monthly users, 84.6% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $15.00 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## TikTok Shop Product Ranking Get a clean, easy-to-read list of TikTok Shop products ranked by sales or influencer count for any chosen date and region. ### What it does - Shows ranked TikTok Shop products for the date and region you choose. - Lets you rank by either sales count or influencer count. - Automatically keeps loading more results until it reaches your requested total. - Makes the results simple to review, copy, or export. - Can be narrowed down with optional category filters. ### Use cases - Spot the best-selling TikTok Shop products in a specific market on a given day. - Compare which products are getting the most creator attention versus the most sales. - Research trending categories and product ideas before choosing what to sell or promote. ### Input | Field | Description | Required | Example | |---|---|---:|---| | Date | The ranking date in YYYY-MM-DD format. | Yes | 2025-11-01 | | Region | Region code such as US. | Yes | US | | Max results | Maximum number of ranked products to return. | No | 10 | | Ranking cycle | Choose the ranking period: Daily, Weekly, or Monthly. | Yes | Daily | | Ranking metric | Choose how products are ranked: Sales count or Influencer count. | Yes | Sales count | | Category ID | Optional top-level category filter. | No | 1729649010208641832 | | Category Level 2 ID | Optional second-level category filter. | No | 11 | | Category Level 3 ID | Optional third-level category filter. | No | 111 | ### Output | Field | Description | |---|---| | rank | The product’s position in the ranking list. | | product_name | The product title shown in the ranking. | | product_id | The unique ID for the product. | | category_information | Category IDs for the product, including top-level and subcategories. | | ranking_metric_value | The number used to rank the product, based on your chosen metric. | | date | The ranking date for the results. | | region | The region the ranking was pulled for. | | sales_count | Total sales count for the product. | | influencer_count | Number of influencers associated with the product. | | gmv | Gross merchandise value for the product. | | average_price | Average price of the product. | | currency | Currency code, if available. | | shop_name | Shop name, if available. | | brand_name | Brand name, if available. | | product_url | Product URL, if available. | ### Sample output ```json { "rank": 1, "product_name": "Loaded Tea-At home flavor pack-Powered caffeinated beverage mix-Loaded Tea-Drink-Package-Energy Powder Beverage-55 flavors Caffeine Convenience", "product_id": "1729679758111249333", "category_information": { "category_id": "700437", "category_l2_id": "914824", "category_l3_id": "917512" }, "ranking_metric_value": 262959, "date": "2025-11-01", "region": "US", "sales_count": 262959, "influencer_count": 728, "gmv": 734737.62, "average_price": 3, "currency": null, "shop_name": null, "brand_name": null, "product_url": null } ```` # Actor input Schema ## `date` (type: `string`): The ranking date in YYYY-MM-DD format. ## `region` (type: `string`): Region code such as US. ## `rank_type` (type: `string`): Choose the ranking period: 1 = daily, 2 = weekly, 3 = monthly. ## `category_id` (type: `string`): Optional category filter for the product ranking. ## `max_results` (type: `integer`): Maximum number of ranked products to return. ## `category_l2_id` (type: `string`): Optional second-level category filter for the product ranking. ## `category_l3_id` (type: `string`): Optional third-level category filter for the product ranking. ## `product_rank_field` (type: `string`): Which ranking metric to use: 1 = sales count, 2 = influencer count. ## Actor input object example ```json { "date": "2025-11-01", "region": "US", "rank_type": "1", "category_id": "1729649010208641832", "max_results": 10, "product_rank_field": "1" } ``` # 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 = { "date": "2025-11-01", "region": "US", "rank_type": "1", "max_results": 10, "product_rank_field": "1" }; // Run the Actor and wait for it to finish const run = await client.actor("datamagnet/tiktok-shop-product-ranking").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "date": "2025-11-01", "region": "US", "rank_type": "1", "max_results": 10, "product_rank_field": "1", } # Run the Actor and wait for it to finish run = client.actor("datamagnet/tiktok-shop-product-ranking").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "date": "2025-11-01", "region": "US", "rank_type": "1", "max_results": 10, "product_rank_field": "1" }' | apify call datamagnet/tiktok-shop-product-ranking --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datamagnet/tiktok-shop-product-ranking", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TikTok Shop Product Ranking", "description": "Get clean, ranked TikTok Shop product lists for a chosen date, region, and ranking cycle. Easily compare products by sales count or influencer count and export the results for review.", "version": "0.0", "x-build-id": "MrfbTlwaNF2qVGh0h" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datamagnet~tiktok-shop-product-ranking/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datamagnet-tiktok-shop-product-ranking", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datamagnet~tiktok-shop-product-ranking/runs": { "post": { "operationId": "runs-sync-datamagnet-tiktok-shop-product-ranking", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datamagnet~tiktok-shop-product-ranking/run-sync": { "post": { "operationId": "run-sync-datamagnet-tiktok-shop-product-ranking", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "date", "region" ], "properties": { "date": { "title": "Date", "type": "string", "description": "The ranking date in YYYY-MM-DD format." }, "region": { "title": "Region", "type": "string", "description": "Region code such as US." }, "rank_type": { "title": "Ranking cycle", "enum": [ "1", "2", "3" ], "type": "string", "description": "Choose the ranking period: 1 = daily, 2 = weekly, 3 = monthly." }, "category_id": { "title": "Category ID", "type": "string", "description": "Optional category filter for the product ranking." }, "max_results": { "title": "Max results", "type": "integer", "description": "Maximum number of ranked products to return." }, "category_l2_id": { "title": "Category Level 2 ID", "type": "string", "description": "Optional second-level category filter for the product ranking." }, "category_l3_id": { "title": "Category Level 3 ID", "type": "string", "description": "Optional third-level category filter for the product ranking." }, "product_rank_field": { "title": "Ranking metric", "enum": [ "1", "2" ], "type": "string", "description": "Which ranking metric to use: 1 = sales count, 2 = influencer count." } } }, "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": { 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