Platform · Flink

Flink Data Scraping

Q: What if the platform only shows a combined price?

We flag deposit_separable: false and do not estimate the split. Deposit amounts vary by container type and an estimate would put a derived number in a field that looks observed.

Q: What does Flink collection cost?

We quote individually. Drivers are addresses times SKUs times observations per day, with the address panel design as the biggest lever. One scoping call, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

One of the few European rapid-grocery operators still standing, and a market where the deposit on a bottle is its own field.

Flink data scraping collects product listings, zone-level pricing, fee structures and availability across Flink's German and European operations. Two things shape the work: delivery-zone granularity rather than city, and Pfand — the German deposit on beverage containers, which is a separate amount from the shelf price and must not be folded into it.

European rapid grocery consolidated heavily. Flink is one of the operators that came through it, which makes it the practical benchmark for the category in Germany.

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flink_2026-08-25.jsonl LIVE FEED

{"sku":"EX-4471","city":"Berlin", "address_id":"BER-MITTE-014","hub_id":"hub-221", "price":4.99,"currency":"EUR", "deposit_amount":1.50,"deposit_type":"einweg_6x", "deposit_separable":true, "pack_size":330,"pack_unit":"ml","unit_count":6, "price_per_unit":2.52,"unit_basis":"per litre, excl deposit", "grundpreis_displayed":2.52,"grundpreis_matches":true, "note":"4.99 + 1.50 Pfand is NOT a 6.49 product"} {"sku":"EX-8812", "price_per_unit":1.98,"grundpreis_displayed":2.31, "grundpreis_matches":false, "note":"computed and displayed disagree — usually a listing error worth flagging"} {"sku":"EX-9902","address_id":"BER-EDGE-031", "serviceable":false, "caution":"outside hub radius — catchments cut across postcodes"}

3 of 1,884,220 sku-address rows · addresses: 260Pfand separate from shelf price · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Flink or its owners. Flink 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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Flink at a glance

How we handle Flink specifically

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

Platform: Flink — rapid grocery, Germany and selected European markets
Granularity: Delivery zone, not city. Hub catchments do not follow postal areas
The German specific: Pfand deposits are separate from shelf price. Never folded in
Consequence: A price comparison that ignores Pfand is wrong on every beverage line
Fees: Delivery fee and minimum order value as separate fields
Availability: Zone serviceability distinct from item stock
Language: German product names retained; no translation into the record
Refresh: Daily standard; sub-daily where promotional intensity is the question

Platform specifics

What is specific to Flink and to German grocery

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

Pfand is a separate amount and it breaks naive comparisons

Germany operates a mandatory deposit on most beverage containers. It is displayed separately from the shelf price and it is refundable on return, so it is not part of the product's cost in the way a price is.

A six-pack at €4.99 plus €1.50 Pfand is not a €6.49 product.
Deposit amounts differ by container type — single-use, reusable, glass, crate — so it is not a flat adjustment.
Comparing a German beverage price to a non-deposit market without separating it produces a systematic error on the whole category.

We capture price and deposit_amount as separate fields with deposit_type, and never combine them into a single figure. Where a platform displays only a combined figure we flag deposit_separable: false rather than estimating the split.

This is the same discipline applied to taxes and gratuities on cruise fares, and to fees on delivery platforms: a component that varies independently belongs in its own field.

Zones, not cities, and hub catchments that cut across postcodes

Flink serves from urban hubs with delivery radii. Those radii cut across postal boundaries, so a postcode-level view is wrong in both directions — part of a postcode is served and part is not, and two nearby addresses can be served by different hubs with different assortments.

Address-level observation using a designed panel, not postcode centroids.
Serviceability recorded as its own state, distinct from an item being out of stock.
Hub identity captured where exposed, so assortment differences are attributable.

The panel design is the main scoping decision and the main cost driver. We agree it against the catchment types that matter — dense inner-city, student districts, suburban edge — rather than sweeping a city exhaustively.

German product naming and unit pricing

German grocery convention requires unit pricing (Grundpreis) on shelf, and it is usually present in listings. That is helpful, and it is also worth checking rather than trusting.

We parse pack size and unit ourselves and compute unit price on a stated basis, rather than only taking the displayed Grundpreis.
Where our computed value and the displayed one disagree, we deliver both and flag it, since a discrepancy is usually a listing error worth knowing about.
Multipacks and crates need unit count separated from pack size, which is where most parsers fail on beverage lines.

Names

German product names are retained exactly as published. We do not machine-translate into the name field — a translated name becomes indistinguishable from an original within weeks, and product matching against your own catalogue starts failing silently.

Scope

What we collect on Flink, 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

Zone-level price, with the address panel design stated
Pfand deposit amount and type as separate fields from shelf price
deposit_separable flag where a platform shows only a combined figure
Serviceability as a distinct state from out of stock
Delivery fee and minimum order value as separate fields
Pack size and unit parsed by us, alongside the displayed Grundpreis
Discrepancy flagged where computed and displayed unit price disagree
German product names retained exactly as published
Hub identity where the platform exposes it

❌ What we do not, and why

A shelf price with Pfand folded into it
A deposit split estimated where the platform shows only a combined figure
Machine translation written into the product name field
Sales, order volumes or hub throughput
Customer, rider or order data

Core Flink fields

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

Field	What it is on this platform
sku / product_key	Your identifier and our matched identity
address_id / zone / city / country	Panel point and geography
hub_id	Where exposed, so assortment differences are attributable
price / currency	Shelf price, without deposit
deposit_amount / deposit_type / deposit_separable	Pfand as its own fields
serviceable / in_stock	Two distinct states
delivery_fee / min_order_value	Fee structure, separate from item price
pack_size / pack_unit / unit_count	Parsed by us
price_per_unit / unit_basis	Computed, with the basis named
grundpreis_displayed / grundpreis_matches	The displayed unit price and whether it agrees with ours
observed_at	Timestamp

Use cases

What teams do with Flink data

German rapid-grocery price benchmarking

Zone-level pricing with Pfand separated, so beverage comparisons are correct rather than systematically inflated by a refundable deposit.

Cross-market European comparison

Deposit kept out of the shelf price, so a German price is comparable to a non-deposit market without a category-wide error.

Assortment by catchment type

Hub-level range across inner-city, student and suburban-edge panels, showing what each catchment is actually offered.

Listing accuracy monitoring

Our computed unit price against the displayed Grundpreis, with disagreements flagged — a discrepancy is usually a listing error a retailer wants to know about.

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

Send us a Flink 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.

Flink is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Flink 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 quick commerce data covers, and a Flink-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

Flink data scraping: frequently asked questions

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

Because it is a refundable deposit, not part of the product's cost. A six-pack at €4.99 plus €1.50 Pfand is not a €6.49 product, and deposit amounts differ by container type so it is not a flat adjustment.

Folding it in produces a systematic error across the entire beverage category, and it makes German prices incomparable to non-deposit markets.

We flag deposit_separable: false and do not estimate the split. Deposit amounts vary by container type and an estimate would put a derived number in a field that looks observed.

Because hub delivery radii cut across postal boundaries. Part of a postcode is served and part is not, and two nearby addresses can be served by different hubs with different assortments.

We use a designed address panel agreed against the catchment types that matter to you.

Both. We parse pack size and unit ourselves and compute unit price on a stated basis, and we also capture the displayed Grundpreis.

Where they disagree we deliver both and flag it, because a discrepancy is usually a listing error rather than a parsing failure — and for a retailer that is a finding worth having.

Not into the name field. A translated name becomes indistinguishable from an original within weeks, and matching against your own catalogue starts failing silently.

Translation is available as a separate field with the engine and date recorded.

We quote individually. Drivers are addresses times SKUs times observations per day, with the address panel design as the biggest lever.

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

See real Flink 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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