# Dripshop Seller Intelligence & Analytics (`scraper-tools/dripshop-seller-intelligence-analytics`) Actor Extract seller analytics and reputation metrics from Dripshop sellers. Analyse followers, lifetime sales, ratings, activity scores, box breaks, and estimated revenue to identify top sellers and market opportunities. - **URL**: https://apify.com/scraper-tools/dripshop-seller-intelligence-analytics.md - **Developed by:** [Scraper Tools Labs](https://apify.com/scraper-tools) (community) - **Categories:** E-commerce, Automation, Agents - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Dripshop Seller Intelligence Analyse Dripshop sellers and extract structured intelligence including reputation, activity, reviews, and box break analytics. This Actor collects seller data and calculates advanced seller metrics useful for marketplace research, competitor monitoring, and reseller analytics. --- ## Features ### Seller Profile Data Extracts structured seller information including: - Seller ID - Seller slug - Seller name - Seller followers - Seller lifetime sales - Seller rating - Seller stream count - Seller description - Seller location and store type --- ### Review Analytics Calculates seller reputation metrics including: - Review count - Reviews analysed - Average review rating - Positive review ratio - Negative review ratio --- ### Box Break Analytics Analyses current active box breaks including: - Active break count - Average break price - Sell-through rate - Inventory utilisation --- ### Advanced Computed Metrics The actor calculates seller intelligence metrics such as: - Seller activity score - Seller reputation score - Seller tier classification - Seller demand score - Seller growth score - Estimated monthly break revenue - Estimated platform commission - Estimated platform fees - Estimated monthly profit estimate These metrics help identify high-performing sellers and potential marketplace opportunities. --- ## Input Example input: ```json { "sellers": ["Rockets_Revenge"], "includeReviews": true, "maxReviewsPerSeller": 50, "includeBoxBreaks": true } ```` ### Parameters | Field | Type | Description | |------|------|-------------| | sellers | array | List of Dripshop seller slugs | | includeReviews | boolean | Fetch seller reviews | | maxReviewsPerSeller | integer | Maximum number of reviews to analyse | | includeBoxBreaks | boolean | Fetch active box breaks | *** ## Example Output ```json { "sellerSlug": "Rockets_Revenge", "sellerFollowers": 1599, "sellerLifetimeSales": 28450, "sellerRating": 4.9, "sellerActivityScore": 51, "sellerReputationScore": 61, "sellerTier": "Bronze" } ``` Results include both raw seller data and computed marketplace intelligence metrics. *** ## Use Cases #### Marketplace Intelligence Track seller activity and identify top-performing sellers. #### Reseller Research Discover profitable sellers and high-demand streams. #### Competitor Monitoring Analyse seller growth, reputation trends, and engagement. #### Automated Data Pipelines Export data into analytics tools or data warehouses. *** ## Running the Actor ### Apify Console 1. Open the Actor 2. Click **Run** 3. Enter seller slugs 4. Download results from the dataset Results can be exported in: - JSON - CSV - Excel - XML *** ### API Example Run the actor: POST https://api.apify.com/v2/acts/YOUR\_ACTOR\_ID/runs Fetch results: GET https://api.apify.com/v2/datasets/DATASET\_ID/items *** ## Limits Default safe limits: - Max sellers per run: 50 - Max reviews per seller: 100 - Box breaks per seller: 10 These limits help prevent excessive API load. *** ## Roadmap Planned improvements: - Incremental monitoring - Historical seller analytics - Proxy support - Scheduling examples - Webhook integrations - Seller comparison analytics *** ## Disclaimer This Actor is an independent data extraction tool and is not affiliated with Dripshop. ## Actor input object example ```json {} ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("scraper-tools/dripshop-seller-intelligence-analytics").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 = {} # Run the Actor and wait for it to finish run = client.actor("scraper-tools/dripshop-seller-intelligence-analytics").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 '{}' | apify call scraper-tools/dripshop-seller-intelligence-analytics --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraper-tools/dripshop-seller-intelligence-analytics", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Dripshop Seller Intelligence & Analytics", "description": "Extract seller analytics and reputation metrics from Dripshop sellers. Analyse followers, lifetime sales, ratings, activity scores, box breaks, and estimated revenue to identify top sellers and market opportunities.", "version": "0.0", "x-build-id": "gjDu4I0woNxqhEuNr" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraper-tools~dripshop-seller-intelligence-analytics/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraper-tools-dripshop-seller-intelligence-analytics", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraper-tools~dripshop-seller-intelligence-analytics/runs": { "post": { "operationId": "runs-sync-scraper-tools-dripshop-seller-intelligence-analytics", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraper-tools~dripshop-seller-intelligence-analytics/run-sync": { "post": { "operationId": "run-sync-scraper-tools-dripshop-seller-intelligence-analytics", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": {} }, "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 } } } } } } } } } } ```