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Platform · Bol

Bol Data Scraping Services

Where the winning offer is chosen on delivery promise as much as on price, so the offer list is the dataset rather than a supporting detail.

Bol data scraping is the automated collection of publicly visible Bol data with the full offer list per product — every seller, their price and their individual delivery promise — and the Netherlands and Belgium storefronts kept separate throughout.

On most marketplaces the cheapest offer wins the page. On Bol the delivery promise is weighted heavily enough that a more expensive offer routinely holds the default position, which makes a price-only dataset actively misleading.

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

bol_offers.jsonl LIVE FEED
{"product_id":"92002* redacted","storefront":"nl", "offer_id":"of_1* redacted","offer_count":7, "seller_type":"bol_own","seller_name":"Bol", "price":42.99, "delivery_promise":"tomorrow", "is_default_offer":true} {"product_id":"92002* redacted","storefront":"nl", "offer_id":"of_4* redacted", "seller_type":"partner","seller_name":"Example Trading BV", "price":38.50, "delivery_promise":"5-7 days", "is_default_offer":false} {"product_id":"92002* redacted","storefront":"be", "price":44.95, "delivery_promise":"2-3 days","is_default_offer":true}
3 of 2,660,400 product-offer rowsfull offer list retained · storefront mandatory · schema v2.8

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Bol or its owners. Bol 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
amazon
D2C + Marketplace
NYKAA
D2C + Marketplace
Walmart
FMCG Marketplace
udaan
Food Delivery
Uber Eats
Quick Commerce
blinkit
Taxi Aggregator
Uber
E-Commerce
Tmall
Bol at a glance

How we handle Bol specifically

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

Platform
Bol, Netherlands and Belgium storefronts
Primary structure
Offer list per product, not one price per product
Delivery promise
Captured per seller offer, not per product
Storefronts
NL and BE kept separate on every record
Sellers
Bol's own stock separated from partner sellers
Default offer
Which offer held the page, tracked over time
Refresh
Daily standard; sub-daily on promotional weeks
Region
Netherlands and Belgium
Platform specifics

What makes Bol data different from other marketplaces

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

Delivery promise decides the page, so it belongs on every offer

Bol weights delivery speed heavily in which offer is presented by default. An offer priced above another can hold the page because it can deliver tomorrow.

  • A dataset capturing only the cheapest offer reports a price that is not the one most shoppers are shown.
  • A dataset capturing only the default offer misses that a cheaper option exists a click away.
  • A dataset without delivery promise per offer cannot explain why the default offer is not the cheapest, which is the question a client actually has.

We capture the full offer list with price and delivery promise on each row, plus is_default_offer. That combination is what makes it possible to see whether a competitor is winning the page on price or on logistics — and those call for entirely different responses.

Netherlands and Belgium are two markets on one brand

Bol serves both countries, and price, assortment, delivery promise and VAT treatment can all differ between them.

storefront is mandatory on every record. Blending the two produces a dataset that is wrong for both and that shifts whenever the mix of observed pages changes.

For clients selling into Benelux this split is usually the point rather than a technicality: the same product can be competitively priced in one country and not in the other, and a blended figure hides exactly that.

Bol competes with its own partner sellers, on the same page

Bol sells its own stock and hosts partner sellers on the same product pages. The two are commercially different in a way a single price column cannot express.

Bol's own price is the retailer's decision and what a supplier negotiates against. A partner's price is an independent third party, and for a brand it is a channel-integrity question.

We capture seller_type and the seller name on every offer. For brand clients, the most common finding is a partner seller holding the default position on their own product at a price that undercuts the agreed one — visible only when every offer is captured rather than one per product.

Which offer holds the page is a series worth keeping

Default-offer ownership changes, and the changes are informative. A seller who takes the page after a small price move, or who holds it despite being more expensive, is telling you how the selection is weighted.

Because is_default_offer is on every offer row at every capture, buy-box ownership becomes a time series rather than a snapshot. Tracked across a category it shows which sellers are structurally advantaged on delivery and which are simply buying position on price.

That series cannot be reconstructed later from a dataset that stored one price per product, which is why the offer-list structure has to be chosen at the start.

Scope

What we collect on Bol, 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

  • The full offer list per product, not one price per product
  • Price and delivery promise on every offer row
  • is_default_offer, making buy-box ownership a time series
  • seller_type separating Bol's own stock from partner sellers
  • Seller name where displayed
  • storefront mandatory: NL and BE never blended
  • VAT basis as displayed per storefront
  • Delivery cost and any free-delivery threshold as displayed
  • Product identifier and EAN retained together
  • Rating, review count and review velocity
  • Search rank on a fixed query set with sponsored placements flagged

❌ What we do not, and why

  • Customer identities or any personal data
  • Anything behind a login, including membership delivery benefits tied to an account
  • Seller cost, margin or fee data, which is not publicly visible
  • The platform's offer-selection logic; we record the outcome, not the algorithm
  • Inferred sales volume presented as fact
  • Full review text at scale; structured attributes and counts instead

Core Bol fields

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

Field What it is on this platform
product_id / ean Platform identifier and EAN, retained together
storefront nl or be — mandatory, never blended
offer_id The specific offer, since a product has several
seller_type / seller_name Bol's own stock or a partner seller
price Price for this offer specifically
delivery_promise The promise on this offer, which is why it may hold the page
delivery_cost / free_delivery_threshold As displayed for this offer
is_default_offer Whether this offer held the page at capture time
vat_basis How VAT is shown in this storefront
offer_count How many offers the product carried at capture
captured_at Timestamp at minute precision
Use cases

What teams do with Bol data

Understanding why you are not winning the page

Price and delivery promise on every offer show whether a competitor holds the default position on price or on logistics, which require completely different responses.

Partner-seller channel integrity

Every offer captured, not one per product, surfaces partner sellers holding the default position on your products below the agreed price.

Buy-box ownership over time

is_default_offer on every offer row at every capture turns page ownership into a series that cannot be reconstructed retrospectively.

Netherlands versus Belgium positioning

Storefront on every record shows where the same product is competitively priced in one country and not the other, which a blended figure hides.

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

Send us a Bol 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 inside two business days
  • 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.

Bol is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Bol 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 Bol-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

Bol data scraping: frequently asked questions

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

Because on Bol the winning offer is frequently not the cheapest. Delivery promise is weighted heavily enough that a more expensive offer can hold the page.

Capturing only the default offer reports a price that ignores cheaper options a click away; capturing only the cheapest reports a price most shoppers are not shown. Both together, with delivery promise on each, answer the question a client actually has.

Yes, and storefront is mandatory on every record. Price, assortment, delivery promise and VAT treatment can all differ between them.

For clients selling into Benelux this split is usually the point: a product can be competitively priced in one country and not the other, and a blended figure conceals exactly that.

We record the outcome and the inputs visible on the page — price, delivery promise, seller type — not the platform's selection logic, which is not public.

In practice the visible inputs explain most cases. Where they do not, we say so rather than inventing a mechanism.

Yes, on every offer. Bol's own price is the retailer's decision and what a supplier negotiates against; a partner's price is an independent third party's.

For brand clients the most common finding is a partner holding the default position on their own product below the agreed price, which is invisible in any dataset storing one price per product.

No, and this is worth deciding early. Default-offer ownership is only recoverable if every offer was stored at every capture from the start.

A dataset that stored one price per product cannot be turned into an offer-level history afterwards, so the structure has to be chosen before collection begins rather than when the question comes up.

See real Bol 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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Our web scraping expertise is relied on by 4,000+ global enterprises including Zomato, Tata Consumer, Subway, and Expedia — helping them turn web data into growth.

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