# Imerco Scraper — Danish Kitchen, Home & Tableware Products (`studio-amba/imerco-scraper`) Actor Scrape products, prices, ratings, and availability from Imerco.dk. Denmark's leading kitchen, home & tableware retailer. Supports search, category browsing, and full catalog via sitemap. - **URL**: https://apify.com/studio-amba/imerco-scraper.md - **Developed by:** [Studio Amba](https://apify.com/studio-amba) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## Imerco Scraper Scrapes kitchenware, tableware, and home accessories from imerco.dk -- Denmark's specialist retailer for brands like Royal Copenhagen, Georg Jensen, and Stelton. ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `searchQuery` | String | No | Search in Danish (e.g., "stegepande", "vinglas") | | `categoryUrl` | String | No | Imerco category URL | | `maxResults` | Integer | No | Max products (default: 100) | | `proxyConfiguration` | Object | No | Proxy config | Without input, the scraper fetches the product sitemap and scrapes from there. ### Output | Field | Type | Example | |-------|------|---------| | `name` | String | `"Royal Copenhagen Bla Mega Tallerken 27 cm"` | | `brand` | String | `"Royal Copenhagen"` | | `price` | Number | `399.00` | | `originalPrice` | Number | `499.00` | | `currency` | String | `"DKK"` | | `ean` | String | `"5705140252788"` | | `sku` | String | `"2382027"` | | `inStock` | Boolean | `true` | | `rating` | Number | `4.5` | | `reviewCount` | Number | `23` | | `imageUrl` | String | Product image | | `description` | String | Product description | | `specs` | Object | `{"Farve": "Bla", "Materiale": "Porcelaen"}` | | `category` | String | `"Tallerkener"` | | `categories` | Array | Breadcrumb categories | ### Extraction method Product data comes from JSON-LD embedded in each product page. Breadcrumb categories are extracted from a separate BreadcrumbList JSON-LD block. Original (was) prices are read from HTML elements since they're not in the structured data. Imerco product URLs use `?id=NNNNN` query parameters. The sitemap at `/sitemap/products` contains all product URLs. ### Cost About **$0.25 per 1,000 products**. ### Notes - Danish site, prices in DKK - Search uses `/soeg?q=...` - The `__NEXT_DATA__` script is checked as a fallback for product link discovery on listing pages ### Why use Imerco Scraper - **Price monitoring** — Track prices, stock, and promotions across Imerco at scale - **Competitive intelligence** — Compare your catalog against Imerco pricing and assortment - **Market research** — Analyze category trends, new arrivals, and rating distributions - **Lead generation** — Build product datasets for affiliate sites, comparison tools, or feeds - **No login or cookies required** — Authenticated access not needed; works out of the box ### How to use Imerco Scraper 1. Open the **Input** tab and provide a search query, category URL, or product list 2. Adjust optional filters such as `maxResults` or proxy settings 3. Click **Start** and wait for the run to complete 4. Download results from the **Output** tab in JSON, CSV, Excel, XML, or HTML 5. Schedule recurring runs from the **Schedule** tab if you need ongoing data ### How to scrape Imerco data This Actor automates the process of extracting structured product data from Imerco. You can run it directly from the Apify console, the Apify API, or any of the official SDKs (JavaScript, Python). The scraper handles pagination, retries, and rate limiting so you can focus on the data, not the plumbing. Typical workflows: - **One-off export**: paste a category URL or keyword, set `maxResults`, and run - **Scheduled monitoring**: set a daily cron in the Schedule tab to track prices over time - **Programmatic integration**: trigger runs from your backend via the Apify API and pull the dataset when finished - **Webhook automation**: receive a callback the moment a run completes and pipe the results into Zapier, Make, n8n, BigQuery, or Google Sheets ### Tips for best results - **Start small** — run with `maxResults: 10` before launching large jobs - **Use proxies** — residential proxies reduce blocking on protected sites - **Throttle on big jobs** — keep `maxConcurrency` modest (5–10) for stability - **Schedule runs** — daily runs are usually enough for price monitoring - **Inspect the dataset schema** — the Storage tab shows the full output structure ### FAQ and support **Is it legal to scrape Imerco?** This Actor extracts publicly available data. Always review the website's Terms of Service before scraping at scale, and respect rate limits. **Why am I getting fewer results than expected?** Some categories have hidden pagination or load more on scroll. Increase `maxResults` and verify your filters. **Can I extract data for a single product?** Yes — provide the full product URL in `startUrls` and the scraper will return one item. **The site blocks me — what should I do?** Enable Apify residential proxies in the input. Datacenter IPs are blocked by many e-commerce sites. For issues, feature requests, or bug reports, open a ticket in the Issues tab on the Actor page or contact support@apify.com. We monitor every actor and ship fixes quickly when sites change. # Actor input Schema ## `searchQuery` (type: `string`): Search for products by keyword (e.g., 'gryde', 'glas', 'royal copenhagen'). Uses imerco.dk search. ## `categoryUrl` (type: `string`): An Imerco category page URL to scrape. Example: https://www.imerco.dk/koekkenudstyr/gryder-og-stegepander/gryder. If empty and no search query, scrapes from product sitemap. ## `maxResults` (type: `integer`): Maximum number of products to return. ## `proxyConfiguration` (type: `object`): Proxy settings. Recommended for large runs to avoid rate limiting. ## Actor input object example ```json { "searchQuery": "gryde", "maxResults": 100 } ```` # 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 = { "searchQuery": "gryde" }; // Run the Actor and wait for it to finish const run = await client.actor("studio-amba/imerco-scraper").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 = { "searchQuery": "gryde" } # Run the Actor and wait for it to finish run = client.actor("studio-amba/imerco-scraper").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 '{ "searchQuery": "gryde" }' | apify call studio-amba/imerco-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=studio-amba/imerco-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Imerco Scraper — Danish Kitchen, Home & Tableware Products", "description": "Scrape products, prices, ratings, and availability from Imerco.dk. Denmark's leading kitchen, home & tableware retailer. Supports search, category browsing, and full catalog via sitemap.", "version": "0.1", "x-build-id": "WlwFFTDCcvgSrNwgy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/studio-amba~imerco-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-studio-amba-imerco-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/studio-amba~imerco-scraper/runs": { "post": { "operationId": "runs-sync-studio-amba-imerco-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/studio-amba~imerco-scraper/run-sync": { "post": { "operationId": "run-sync-studio-amba-imerco-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQuery": { "title": "Search Query", "type": "string", "description": "Search for products by keyword (e.g., 'gryde', 'glas', 'royal copenhagen'). Uses imerco.dk search." }, "categoryUrl": { "title": "Category URL", "type": "string", "description": "An Imerco category page URL to scrape. Example: https://www.imerco.dk/koekkenudstyr/gryder-og-stegepander/gryder. If empty and no search query, scrapes from product sitemap." }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 50000, "type": "integer", "description": "Maximum number of products to return.", "default": 100 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings. Recommended for large runs to avoid rate limiting." } } }, "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 } } } } } } } } } } ```