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Platform · Cdiscount

Cdiscount Data Scraping Services

Where French regulation puts two extra fields on the page that almost no dataset collects.

Cdiscount data scraping is the automated collection of publicly visible Cdiscount data for France — with the repairability index and eco-participation fee captured as published regulatory fields, retail stock separated from marketplace offers, and instalment payment options recorded alongside price.

France requires a repairability score on many electronics and an environmental contribution to be displayed. Both are on the page, both are structured, and almost nobody collects them — which makes them the most under-used competitive fields in French ecommerce.

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

cdiscount_regulatory.jsonl LIVE FEED
{"cdiscount_product_id":"cd-771204", "offer_source":"cdiscount_retail", "is_default_offer":true, "price":289.99, "repairability_index":8.1, "eco_participation_fee":1.80, "regulatory_field_missing":false, "instalments_available":true, "instalment_count":4, "sale_period":"none", "brand_type":"third_party"} {"cdiscount_product_id":"cd-771204", "offer_source":"marketplace", "seller_name":"Example Distribution", "price":274.00, "repairability_index":6.4, "regulatory_field_conflict":true, "note":"same product, two sellers, different declared score"}
2 of 1,884,100 offer rowsrepairability captured on 84.2% of eligible · schema v2.1

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

Our Data Powers
B2C Marketplace
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Taxi Aggregator
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Cdiscount at a glance

How we handle Cdiscount specifically

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

Platform
Cdiscount retail stock plus marketplace offers in France
Regulatory fields
Repairability index and eco-participation fee, both legally displayed
Why unusual
Structured, comparable, mandated — and rarely in any dataset
Offer split
Cdiscount-sold separated from marketplace seller offers
Payment
Instalment options captured as their own field
Own brand
Own-brand and exclusive brands via maintained mappings
Refresh
Daily standard; sub-daily during French sale periods
Region
France
Platform specifics

What makes French ecommerce data different

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

Two mandated fields nobody collects

French regulation requires certain product categories to display a repairability score and an environmental contribution amount. Both appear on the product page as structured values.

Repairability index

  • It is a numeric score on a published scale, so it is directly comparable across products and retailers.
  • It is a purchase factor in categories where French consumers are increasingly repair-conscious.
  • It is a competitive signal for brands: your score against a rival's is a fact, not an opinion.
  • It is a compliance field, so absence where it should be present is itself an observation.

Eco-participation fee

An environmental contribution amount, displayed separately from the headline price on applicable categories. It is part of what the customer pays and it varies by product weight and category.

We capture repairability_index, eco_participation_fee and regulatory_field_missing where a category should carry one and does not. We do not verify either figure — both are published by the seller under a regulatory scheme, and validating them would require the underlying assessment. We capture what was published, with a date.

For anyone selling electronics or furniture into France, the repairability score is the cheapest competitive intelligence available and it is sitting unused on every product page.

Retail and marketplace offers price independently

Cdiscount sells its own inventory alongside marketplace sellers, and both appear on the same product page.

  • Cdiscount-sold offers are the retailer's pricing decision, which for a brand is a buying-relationship question.
  • Marketplace offers come from third parties setting their own prices, which is a channel-control question.
  • Regulatory fields can differ between offers on the same product, since they are seller-declared under the scheme.
  • Grey stock concentrates on the marketplace side, as everywhere with a marketplace layer.

We capture offer_source plus seller identity, and the full offer set rather than only the shown price. Where two offers on one product declare different repairability scores, that discrepancy is worth surfacing rather than picking one — so we deliver it per offer with a regulatory_field_conflict flag.

Instalment payment is a French purchase mechanic

Paying in several instalments is common in French ecommerce, and availability differs by offer and by price band. As in Germany with invoice payment, this affects conversion independently of price.

  • Instalment availability is a merchandising decision, so changes in it are competitive activity price monitoring cannot see.
  • The number of instalments differs, and more instalments on the same price is a better offer to a cash-flow-sensitive buyer.
  • It differs between retail and marketplace offers, compounding with the offer split.

We capture instalments_available and instalment_count as separate fields. As on Otto and Mercado Libre, we do not compute a single effective price from them: whether terms matter depends on your buyer, and that judgement is yours.

French sale periods are also regulated in timing, which makes promotional depth unusually clean to measure here — the base price is observable outside the window. We record sale_period as context so those windows stay separable.

Scope

What we collect on Cdiscount, 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

  • Repairability index as published, per offer
  • Eco-participation fee as published, separate from headline price
  • A flag where a category should carry a regulatory field and does not
  • A conflict flag where two offers on one product declare different scores
  • Offer source separating Cdiscount-sold from marketplace, with seller identity
  • Instalment availability and count as separate fields
  • Regulated sale period recorded as context
  • Own-brand and exclusive brand classification via maintained mappings
  • Ratings and review text without reviewer profiles

❌ What we do not, and why

  • Verification of a repairability score or eco-participation amount
  • A single effective price computed from instalment terms
  • Seller portal or any credentialed Cdiscount system
  • Sales volumes or seller economics
  • Reviewer names, profiles or review histories

Core Cdiscount fields

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

Field What it is on this platform
cdiscount_product_id Platform product identifier, the join key
offer_source / seller_name cdiscount_retail or marketplace, with seller identity
price / was_price Price and previous price
repairability_index Published repairability score for this offer
eco_participation_fee Published environmental contribution, separate from price
regulatory_field_missing Set where a category should carry a field and does not
regulatory_field_conflict Set where offers on one product declare different scores
instalments_available / instalment_count Instalment availability and number offered
sale_period Which regulated sale window, if any, the observation falls within
brand_type own_brand, cdiscount_exclusive or third_party
is_default_offer Whether this is the offer shown by default
Use cases

What teams do with Cdiscount data

Repairability benchmarking for electronics brands

Published repairability scores are collected per offer, giving a directly comparable competitive metric that is mandated, structured and almost never in a dataset.

Total-cost comparison including environmental fees

Eco-participation fees are captured separately from headline price, so the amount a French customer actually pays is computable rather than understated.

Regulatory field compliance monitoring

Missing and conflicting regulatory fields are flagged, surfacing offers where a mandated score is absent or where two sellers on one product disagree.

Payment-terms-aware competitive analysis

Instalment availability and count are captured alongside price, identifying competitors competing on terms rather than on headline price.

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

Send us a Cdiscount 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.

Cdiscount is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Cdiscount 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 ecommerce data scraping covers, and a Cdiscount-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

Cdiscount data scraping: frequently asked questions

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

A numeric score on a published scale that French regulation requires on certain electronics. Because it is mandated, structured and on a common scale, it is directly comparable across products and retailers.

For a brand selling electronics into France it is the cheapest competitive intelligence available, and it is sitting unused on every product page. Almost no dataset collects it.

No. It is published by the seller under a regulatory scheme, and validating it would require the underlying assessment rather than the displayed number.

We capture what was published with a date, and flag where a category should carry a score and does not, or where two offers on one product declare different ones. That discrepancy is worth surfacing rather than resolved by us picking one.

Because it is part of what the customer pays and it is displayed separately from the headline price, varying by product weight and category.

A price comparison using headline price alone understates the French cost. Keeping the fee as its own field lets you build the total on whichever basis your analysis needs.

Because they are different pricing authorities, and here they can also declare different regulatory fields on the same product since those are seller-declared under the scheme.

We deliver both offer types with seller identity and flag regulatory conflicts rather than picking a value.

Yes, as context on records collected within them. Sale timing is regulated in France, which is unusually convenient: base price is observable outside the window, so promotional depth is cleanly measurable.

Without the context field, a price index across a sale period shows a market-wide drop that is a scheduled regulated event.

We quote individually. Drivers are category scope, whether full offer sets are needed, whether regulatory fields are required across the catalogue, and refresh frequency.

One scoping call, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

See real Cdiscount 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.

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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