REMA 1000 Scraper - Danish Grocery Products & Prices

What does REMA 1000 Scraper do?

REMA 1000 Scraper extracts structured product data from rema1000.dk — including current shelf price and campaign flags, per-unit comparison pricing, bottle-deposit (pant) breakout, department taxonomy, product labels (organic, store-brand, …), temperature-zone flags, and multi-resolution product images. It supports keyword search and controllable result limits, so you can run the same query consistently over time.

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Key features

• 🛍️ Shopping-basket monitor — paste your weekly shopping list as productIds (or productUrls — URLs straight from your browser) and combine with Incremental Mode to get rows back only when something changes: price drop, campaign start, deposit change, or the SKU getting delisted. Weekly tracking of a 20-item basket runs around a cent per check.
• 🥗 Search by ingredient — find products by what they contain, not just their name. The store's own search indexes product titles and categories but not ingredients, so a search for "pistacie" misses chocolate, ice cream, and granola bars that contain pistachios. The ingredientFilter input lets you substring-match on the ingredient list — pass a single term ("pistacie") or an array of terms that must all appear (["pistacie", "hasselnød"] for products containing both). Useful for allergen tracking, premium-ingredient discovery, and preservative audits.
• 🔍 Keyword search — search the catalog with query ("mælk", "økologisk", "pasta", brand names …) — matches across product names, descriptions, and category terms. Pair with Incremental Mode to monitor every product that matches a query, even as new SKUs enter the catalog.
• 💰 Current price + tilbud with discount % — every product row carries the active shelf price plus isCampaign / isAdvertised flags, priceValidFrom / priceValidUntil, a priceOverMaxQuantity value when the chain caps the campaign at N units per customer, and a precomputed discountPercent field that ranks tilbud by % off the regular price (Bearnaise on tilbud reads discountPercent: 61.5, Tuborg 6-pak 31.5, etc.). Sort the dataset by discount-desc to surface the week's deepest cuts directly.
• 🥗 Ingredients + structured nutrition — every product row carries the full ingredients text (allergens already stripped of inline HTML markup) plus a structured nutrition[] array — name/value pairs for energy, fat, saturated fat, carbs, sugars, fibre, protein, salt — pulled straight from the compliance-grade source the chain itself publishes. No regex over marketing prose.
• 🏭 EU GPSR manufacturer + recall signal — manufacturer block on every product: name, full address, country code, website, and securityAlert (non-null when the SKU is under active recall / safety warning). Required by EU GPSR regulation since 13 Dec 2024 — surfaced ready-made for compliance audits, recall monitoring, and supplier intelligence.
• 🏷️ Structured unit size + brand — unitSize, unitMeasure, and brand parsed from the shelf-label string — so "1 LTR. / REMA 1000" becomes 1 + ltr + REMA 1000 as separate fields. No regex on the subtitle. 14 unit tokens recognized across the full catalog (gr / ml / stk / cl / ltr / kg / par / mtr / pk / sæt / bakke / bdt / pose / rl) at 100% parse rate.
• ♻️ Incremental mode — daily runs emit only products whose price, campaign flag, or validity window changed since the prior run — the rest stay UNCHANGED and are filtered out by default. Perfect for price-tracking apps and tilbud-alert pipelines. Saves 80–95% on recurring monitoring.
• 🔔 Notifications — Telegram, Slack, Discord, WhatsApp Cloud API, generic webhook — out of the box. Pair with incremental + notifyOnlyChanges for "new tilbud" alerts the moment campaigns drop, without polling the flyer.
• 📦 Compact mode — drop the heavy fields (ingredients text, full nutrition table, image variants, manufacturer block, label objects, price history) and keep shopping essentials: identity, current price, per-unit price, campaign flags + discount %, parsed unit size + brand, and basket line totals. Cuts each row by ~77% — ideal for AI agents, MCP servers, and LLM context windows where allergen text is noise.

What data can you extract from rema1000.dk?

Each result includes Core listing fields (productId, name, subtitle, unitSize, unitMeasure, brand, ingredients, and nutrition, and more) and detail fields when enrichment is enabled (description). In standard mode, all fields are always present — unavailable data points are returned as null, never omitted. In compact mode, only core fields are returned.

Input

The main inputs are a search keyword and a result limit. Additional filters and options are available in the input schema.

Key parameters:

• productIds — Track a specific list of products by REMA product ID (e.g. [100004, 60214]). Combine with Incremental Mode to monitor your weekly shopping basket — only get rows back when something changes (price, campaign, delisting). When using Incremental Mode you MUST also set 🔑 State Key (e.g. "my-rema-basket") so multiple baskets don't share state. (default: [])
• productUrls — Same as productIds but accepts full rema1000.dk product URLs — paste straight from your browser. URLs are merged with productIds. (default: [])
• quantities — Optional per-product counts for basket mode. Two accepted forms: • Object map: {"200313": 12, "21464": 6} (compact, preferred for the Console editor) • Array of pairs: [{"id": 200313, "qty": 12}, {"id": 21464, "qty": 6}] (useful from Make / n8n / Zapier flows) Drives subtotal, pant, and max-quantity (over-cap) campaign math. Default qty=1 per product when omitted. Ignored outside basket mode. (default: {})
• query — Keyword search across the REMA catalog (e.g. "mælk", "økologisk", "pasta"). Searches product names, brands, and category terms (NOT ingredients — use ingredientFilter for that). Mutually exclusive with productIds — if both are set, productIds wins.
• sortBy — Optional ordering of the dataset rows before push. Default is source-emit order (department + page for browse, search-relevance for search, basket-input order for basket). Null / missing values always sink to the bottom regardless of direction.
• ingredientFilter — Case-insensitive substring filter on the ingredient list. Accepts a single ingredient ("pistacie") or a JSON array of terms that ALL must appear (["pistacie", "hasselnød"] finds products containing both). Useful for finding products with a specific ingredient that isn't in the product name — REMA's search doesn't index ingredients, so this filter runs over fetched results. Narrow your scope with query or productIds first to keep cost down. Only meaningful in basket and search modes.
• departmentIds — Limit scraping to specific departments. Leave empty to scrape all 15 departments. IDs: 10 Brød, 20 Frugt & grønt, 30 Kød/fisk/fjerkræ, 40 Køl, 50 Frost, 60 Mejeri, 70 Ost, 80 Kolonial, 90 Drikkevarer, 100 Husholdning, 110 Baby, 120 Pleje, 130 Slik, 140 Kiosk, 160 Nemt & hurtigt. (default: [])
• campaignsOnly — Only emit products currently on campaign (tilbud) or in the advertised flyer. (default: false)
• maxResults — Maximum total products (0 = unlimited; full catalog ≈ 3,900). (default: 200)
• compact — Drop heavy fields (ingredients text, full nutrition table, image variants, manufacturer block, label objects, price history) and keep only shopping essentials: identity, current price, per-unit price, campaign flags + discount %, basket line totals, lifecycle. Cuts each row from ~2,850 chars to ~650 (77% smaller) — ideal for AI agents, MCP servers, and LLM context windows where you don't need allergen text. Same dataset row count, same billing — just smaller payloads. (default: false)
• incrementalMode — Compare against previous run state — emit only NEW / UPDATED / EXPIRED products (price changes, new SKUs, delistings). In Basket mode you MUST also set stateKey. In Search / Browse modes stateKey auto-generates from the scope dimensions. (default: false)
• stateKey — Stable identifier for incremental tracking. In Basket mode this is REQUIRED — choose a name like "my-rema-basket" so multiple baskets don't share state. In Search / Browse mode it auto-generates from your query / departments if left empty.
• ...and 15 more parameters

Input examples

Weekly basket with quantities — 10 products, tilbud + pant — Tracks a realistic 10-product weekly shop with per-item quantities. The mix includes two tilbud-with-pant items (Tuborg 6-pak), two tilbud-without-pant items (Bearnaise, kyllingelår), two normal-with-pant items (Icetea, Ribena), and four normal items. Combined with incrementalMode: true, only price changes / new campaigns / delistings get pushed.

→ 10 dataset rows (one per product, with quantity, lineSubtotal, lineDeposit, lineSavings, lineTotal populated on each). Run status message + weekly-shopping-summary KV record carry the basket roll-up: products 10 · units 24 · subtotal 330.03 + pant 22.50 = total 352.53 DKK · saving 123.30 DKK on 8 tilbud-units.

{
  "productIds": [
    "200313",
    "110032",
    "250055",
    "10914",
    "21464",
    "100004",
    "100028",
    "100042",
    "11046",
    "100065"
  ],
  "quantities": {
    "10914": 6,
    "11046": 1,
    "21464": 3,
    "100004": 1,
    "100028": 2,
    "100042": 2,
    "100065": 1,
    "110032": 4,
    "200313": 2,
    "250055": 2
  },
  "incrementalMode": true,
  "stateKey": "weekly-shopping",
  "notifyOnlyChanges": true
}

Basic search — Keyword-driven search with a result cap.

→ Full payload per result — all standard fields populated where the source provides them.

{
  "query": "mælk",
  "maxResults": 50
}

Incremental tracking — Only emit products that changed since the previous run with this stateKey.

→ First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set emitUnchanged: true to include unchanged records as well.

{
  "query": "mælk",
  "maxResults": 200,
  "incrementalMode": true,
  "stateKey": "mælk-tracker"
}

Compact output for AI agents — Return only core fields for AI-agent and MCP workflows.

→ Small payload with the most important fields — ideal for piping into LLMs without token overhead.

{
  "query": "mælk",
  "maxResults": 50,
  "compact": true
}

Output

Each run produces a dataset of structured product records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example product record

{
  "productId": 110032,
  "name": "BEARNAISE SAUCE",
  "subtitle": "66 GR. / KNORR",
  "unitSize": 66,
  "unitMeasure": "gr",
  "brand": "KNORR",
  "description": "BEARNAISE SAUCE KNORR\n\nVarenummer: 110032",
  "ingredients": "Stivelse (kartoffel-/potet- og risstivelse), vegetabilske olier/oljer (solsikke- og majsolie/olje), salt, MÆLKEPROTEIN/MELKEPROTEIN, HVEDEMEL/HVETEMEL, løg/løk¹, gær-/gjærekstrakt, MÆLKESUKKER/MELKESU...",
  "nutrition": [
    {
      "name": "Energi",
      "value": "562 KJ / 135 kcal",
      "sort": 1
    },
    {
      "name": "Fedt",
      "value": "11",
      "sort": 2
    },
    {
      "name": "Heraf mættede fedtsyrer",
      "value": "2,6",
      "sort": 3
    },
    {
      "name": "Kulhydrat",
      "value": "6,2",
      "sort": 4
    },
    {
      "name": "Heraf sukkerarter",
      "value": "3,9",
      "sort": 5
    },
    {
      "name": "Kostfibre",
      "value": "< 0,5",
      "sort": 6
    },
    {
      "name": "Protein",
      "value": "3,1",
      "sort": 7
    },
    {
      "name": "Salt",
      "value": "0,64",
      "sort": 8
    }
  ],
  "barcodes": [
    "8710604750950"
  ],
  "countryOfOrigin": "",
  "categoryId": 5243030,
  "categoryName": "Saucer & nem mad",
  "manufacturer": null,
  "warnings": [],
  "itemDisclaimer": null,
  "url": "https://shop.rema1000.dk/varer/110032",
  "portalUrl": "https://shop.rema1000.dk/varer/110032",
  "source": "rema1000.dk",
  "departmentId": 80,
  "departmentName": "Kolonial",
  "price": 10,
  "currency": "DKK",
  "isCampaign": true,
  "isAdvertised": true,
  "priceValidFrom": null,
  "priceValidUntil": "2026-05-16",
  "deposit": null,
  "compareUnit": "kg",
  "comparePrice": 151.52,
  "maxQuantity": 6,
  "priceOverMaxQuantity": 25.95,
  "priceHistory": [
    {
      "price": 10,
      "isCampaign": true,
      "isAdvertised": true,
      "startingAt": null,
      "endingAt": "2026-05-16",
      "deposit": null,
      "compareUnit": "kg",
      "comparePrice": 151.52,
      "maxQuantity": 6,
      "priceOverMaxQuantity": 25.95
    }
  ],
  "imageUrl": "https://rema-product-images.digital.rema1000.dk/110032/1-medium-nDPWJ6gK9W.webp",
  "images": [
    {
      "small": "https://rema-product-images.digital.rema1000.dk/110032/1-small-nDPWJ6gK9W.webp",
      "medium": "https://rema-product-images.digital.rema1000.dk/110032/1-medium-nDPWJ6gK9W.webp",
      "large": "https://rema-product-images.digital.rema1000.dk/110032/1-large-nDPWJ6gK9W.webp"
    }
  ],
  "labels": [
    {
      "id": null,
      "name": "on_discount",
      "image": null
    },
    {
      "id": null,
      "name": "avisvare",
      "image": null
    },
    {
      "id": null,
      "name": "discount",
      "image": null
    }
  ],
  "ageLimit": null,
  "hazardStatements": [],
  "temperatureZone": null,
  "isSelfScale": false,
  "isWeightItem": false,
  "isBatchItem": false,
  "isAvailableInAllStores": true,
  "scrapedAt": "2026-05-15T17:31:16.660Z",
  "contentHash": "681a8282c50048793ab21c355da5c1e639407764e1ae00e6fb090e7a89f002c7",
  "changeType": null,
  "firstSeenAt": null,
  "lastSeenAt": null,
  "expiredAt": null,
  "isRepost": false,
  "repostOfId": null,
  "repostDetectedAt": null,
  "discountPercent": 61.5,
  "quantity": null,
  "lineSubtotal": null,
  "lineDeposit": null,
  "lineSavings": null,
  "lineTotal": null
}

Incremental fields

When incremental: true, each record also carries:

• changeType — one of NEW, UPDATED, UNCHANGED, REAPPEARED, EXPIRED. Default output covers NEW / UPDATED / REAPPEARED; set emitUnchanged: true or emitExpired: true to opt into the others.
• firstSeenAt, lastSeenAt — ISO-8601 timestamps tracking the listing across runs.

How to scrape rema1000.dk

1. Go to REMA 1000 Scraper in Apify Console.
2. Enter a search keyword.
3. Set maxResults to control how many results you need.
4. Click Start and wait for the run to finish.
5. Export the dataset as JSON, CSV, or Excel.

Use cases

• Extract product data from rema1000.dk for market research and competitive analysis.
• Track pricing trends across regions and categories over time.
• Monitor new and changed listings on scheduled runs without processing the full dataset every time.
• Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
• Export clean, structured data to dashboards, spreadsheets, or data warehouses.

How much does it cost to scrape rema1000.dk?

REMA 1000 Scraper uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

• Run start: $0.01 per run
• Per result: $0.004 per product record

Example costs:

• 10 results: $0.05
• 100 results: $0.41
• 500 results: $2.01

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 250 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.

Churn rate	Full re-scrape run cost	Incremental run cost	Savings vs full re-scrape	Monthly cost after baseline
5% — stable niche query	$1.01	$0.06	$0.95 (94%)	$1.80
15% — moderate broad query	$1.01	$0.16	$0.85 (84%)	$4.80
30% — high-volume aggregator	$1.01	$0.31	$0.70 (69%)	$9.30

Full re-scrape monthly cost at daily polling: $30.30. First month with incremental costs $2.75 / $5.65 / $10.00 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

Platform usage (compute and proxies) is billed separately by Apify based on actual consumption. Incremental runs consume less on result processing, though fixed per-run overhead stays the same.

FAQ

How many results can I get from rema1000.dk?

The number of results depends on the search query and available listings on rema1000.dk. Use the maxResults parameter to control how many results are returned per run.

Does REMA 1000 Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

Can I integrate REMA 1000 Scraper with other apps?

Yes. REMA 1000 Scraper works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use REMA 1000 Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use REMA 1000 Scraper through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use compact mode and descriptionMaxLength to keep payloads manageable for LLM context windows.

Is it legal to scrape rema1000.dk?

This actor extracts publicly available data from rema1000.dk. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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3. Click Start — export results as JSON, CSV, or Excel

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