Platform · Idealo

Idealo Data Scraping Services

A comparison engine sells nothing, so the record here is a merchant offer rather than a product.

Idealo data scraping is the automated collection of publicly visible price comparison engine data — where the unit of record is the merchant offer, not the product, with merchant identity, total price including shipping, paid placement separated from organic ranking, and offer-set composition per product.

Every other platform page here is about a retailer or a marketplace. A comparison engine is neither: it holds no stock and sets no prices. That changes the shape of the data completely.

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Free pilot on your own Idealo list, returned in 24 hours. No card, no trial clock — and you keep the sample data either way.

idealo_offers.jsonl LIVE FEED

{"product_key":"aw-idl-771204", "match_confidence":0.94, "market":"DE", "merchant_name":"Example Elektronik", "merchant_rating":4.6, "item_price":189.00, "shipping_cost":0.00, "total_price":189.00, "rank_position":1, "placement_type":"organic", "delivery_time_quoted":"2-3 days", "offer_count":41, "merchant_entered_at":"2026-06-02"} {"product_key":"aw-idl-771204", "merchant_name":"Unknown Handel", "item_price":172.00, "shipping_cost":24.90, "total_price":196.90, "placement_type":"undetermined", "note":"lower item price, higher total — MAP check on item price"}

2 of 8,204,880 merchant-offer rowsplacement undetermined on 12.4% · schema v1.8

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Idealo or its owners. Idealo and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

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Idealo at a glance

How we handle Idealo specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Platform: Idealo across its European markets
Unit of record: The merchant offer, not the product
Why that matters: The engine sells nothing, so there is no platform price to collect
Placement: Paid placement separated from organic ranking where distinguishable
Total price: Item plus shipping, since ranking often uses total
Merchants: Merchant identity on every offer, which is the analytical unit
Refresh: Daily standard; sub-daily on priority categories
Region: Germany and other European markets

Platform specifics

What makes comparison engine data different from retailer data

These are the reasons a Idealo dataset needs its own handling rather than a shared retail schema.

The offer is the record, and the merchant is the entity

On a retailer, the product has a price. On a marketplace, the listing has offers from sellers. On a comparison engine there is no platform price at all — the engine aggregates offers from independent merchants and ranks them.

What follows

Every row is merchant-plus-product, and a product with forty merchants produces forty rows.
Merchant identity is the analytical unit. Which merchants list you, at what price, in what rank position.
There is no buy box to win, but rank position matters commercially in the same way.
Offer set composition is a signal. Merchants entering and leaving a product's offer set is competitive activity.

We deliver one record per merchant offer with merchant_name, rank_position, item price, shipping and total. For a brand, this is the cleanest available view of who is selling their product across an entire market, and it is a materially different question from what any single retailer's data answers.

Paid placement has to be separated from organic rank

Comparison engines carry paid placement alongside organic ranking. Treating a paid position as an organic one overstates a merchant's competitive strength considerably.

A merchant at position one via paid placement is not outcompeting on price.
Organic rank usually reflects total price, so it is a genuine competitiveness signal.
Paid density varies by category, so a category with heavy paid placement needs different interpretation.
Paid share over time shows where merchants are buying visibility rather than earning it.

We capture placement_type as paid, organic or undetermined, and rank_position within each. Where paid and organic cannot be distinguished from public markup, we set undetermined rather than guessing — and we report the undetermined share per category so you know how much of a ranking analysis rests on it.

Total price is the ranking basis, so shipping is not optional

Comparison engines commonly rank on total price rather than item price, because that is what shoppers compare. A dataset holding item price alone cannot explain the ranking it is looking at.

Shipping varies by merchant, and a merchant with a low item price and high shipping ranks worse than its item price suggests.
Free-shipping thresholds change the total at basket level, which single-item comparison cannot capture.
Delivery time is displayed and is a genuine trade-off alongside total price.

We capture item price, shipping cost and total_price separately, plus quoted delivery time. Total is the field that explains rank; item price is the field a brand's MAP policy usually references. Both are needed and they answer different questions, which is exactly why we do not deliver only one.

Scope

What we collect on Idealo, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

One record per merchant offer, with merchant identity on every row
Item price, shipping cost and total price as separate fields
Rank position, with paid and organic placement separated where distinguishable
An undetermined placement value where public markup does not allow the distinction, with its share reported
Quoted delivery time per merchant offer
Offer set composition per product, with merchants entering and leaving tracked
Product identity matched across merchant listings with confidence
Market on every record across covered European storefronts
Merchant rating where displayed

❌ What we do not, and why

A single platform price, since the engine sets none
Guessed paid-versus-organic classification where markup does not support it
Merchant back-office or any credentialed system
Click, conversion or spend data, none of which is published
Reviewer names, profiles or review histories

Core Idealo fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
product_key / match_confidence	Cross-merchant product identity with confidence
merchant_name / merchant_rating	Merchant identity and rating where displayed
item_price / shipping_cost / total_price	The three price fields, kept separate
rank_position	Position within the offer list
placement_type	paid, organic or undetermined
placement_undetermined_share	Per-category share where the distinction could not be made
delivery_time_quoted	Quoted delivery time for this merchant offer
offer_count	How many merchant offers the product carries
merchant_entered_at / merchant_left_at	When a merchant joined or left this product's offer set
market	Storefront country, mandatory on every record
free_shipping_threshold	Threshold that removes shipping cost, where displayed

Use cases

What teams do with Idealo data

Market-wide reseller visibility for brands

One record per merchant offer gives the cleanest available view of who sells your product across a whole market, which no single retailer's data can provide.

MAP monitoring at market scale

Item price per merchant with identity supports minimum advertised price monitoring across every merchant listing a product, not just the ones you know about.

Ranking analysis that accounts for paid placement

Placement type separates bought visibility from earned position, so a merchant at rank one via paid placement is not read as outcompeting on price.

Total-cost competitiveness

Item price, shipping and total are held separately, so the field explaining rank and the field a MAP policy references are both available.

The 24-hour sample — run on your sources, not ours

Send us a Idealo item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

Idealo is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Idealo data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what pricing & product data covers, and a Idealo-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

Idealo data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

Because a comparison engine holds no stock and sets no prices — it aggregates offers from independent merchants and ranks them. There is no platform price to collect.

So a product with forty merchants produces forty rows, and merchant identity is the analytical unit. For a brand, this is the cleanest view of who sells their product across a whole market.

Where public markup allows it, yes. Where it does not, we set placement_type to undetermined rather than guessing, and report the undetermined share per category.

That share matters: it tells you how much of a ranking analysis rests on an unresolved classification. Guessing would produce a clean-looking field that quietly overstates or understates merchant competitiveness.

Because they answer different questions. Total price usually explains the ranking, since engines commonly rank on what shoppers compare. Item price is what a brand's MAP policy typically references.

Delivering only one leaves you unable to answer half the questions. Shipping also varies by merchant, so a low item price with high shipping ranks worse than the item price suggests.

Different, not better. Retailer collection gives you depth on that retailer — availability, variants, promotional mechanics. A comparison engine gives you breadth: every merchant listing a product, in one place.

For MAP and reseller monitoring, breadth usually wins. For assortment and availability analysis, retailer collection wins. Many clients run both.

Yes, with entered and left dates per product offer set. Merchants entering a product's offer set is competitive activity, and a merchant appearing that you have not authorised is exactly what brand protection is looking for.

It requires continuous collection to be meaningful; a monthly snapshot shows composition but not movement.

We quote individually. The distinctive driver is offer volume: because every merchant offer is a row, a product with many merchants multiplies volume well beyond retailer collection.

A defined product set sits at the lighter end; broad category coverage across markets sits considerably higher. One scoping call, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

See real Idealo data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

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